Convergence of GDP per capita in EU25 - DiVA...

DEPARTMENT OF ECONOMICS Uppsala University Masterrsquos thesis Fall 2006

Convergence of GDP per capita in EU25

Does it happen and how can it be explained

Author Martin Nybom

Supervisor Christian Nilsson Abstract

The EU25 Member Statesrsquo GDP per capita levels converged in 1994-2005 Convergence

occurred at an average speed of approximately 15 percent per year In the first part of this

paper unconditional convergence is analyzed by looking at both β- and σ-convergence and the

performances of the catch-up economies are compared discussed and related to the

convergence definition In a second stage the catch-up performances are analyzed in relation

to theory of economic integration Substantial increases in labor productivity explain a great

deal of the catch-up for poorer economies such as the Baltic states while increases in

employment have been relatively more important for the less poorer economies such as Spain

Portugal and Slovenia Labor productivity is further elaborated and it is found that both FDIs

and internal savings have been consistently higher for the catch-up economies than the non-

catching-up economies FDIs are also assumed to have indirect effects such as promoting

incorporation of technology

Key words Convergence catch-up EU25 the European Union Economic integration

2

Table of contents 1 Introduction 4 2 Are the countries of the enlarged EU converging6

21 How to measure convergence 7 22 Evidence of convergence ndash estimation of β 8 23 Evidence of convergence ndash changes in σ 10

3 Are some catching up faster than others11 31 An expanded β-model 11 32 The estimation results 12 33 A descriptive approach 13

4 What is economic integration and how can it be explained14 41 The neo-classical concepts of growth and economic integration 14 42 Integration through internal accumulation of capital 17 43 Integration through capital mobility 18 44 Integration through migration 20 45 Integration through trade 22 46 Summing up integration mechanisms causing convergence 23

5 Explaining catch-up performances 24 51 Productivity and investments ndash decisive for convergence 24 52 Internal savings foreign investments or technology 25 52 Human capital and technology 28 53 Employment and demographic change ndash integration through migration 29 54 Degree of openness ndash integration through trade 31 55 Summing up what explains catch-up performances in Europe 33

6 Conclusions35 References 36 Appendices 38

3

1 Introduction

Real convergence the process by which poorer economies over the phase of time catch up on

richer ones in terms of income or output has in empirical studies been shown to be far from

automatic Barro and Sala-i-Martin (1991) have found convincing evidence of convergence in

per capita incomes between US states but on the other hand also found that divergence

rather than convergence seems to be the norm when comparing countries on a global level

(1995 chapter 12) Further studies have reinforced the idea that the convergence concept is

conditioned on some level of homogeneity between the compared economies (eg Fagerberg

and Verspagen 1996 Tondl 1999)

This notion is related to whether a set of crucial theoretical assumptions hold and if the

production functions across the economies are of similar form Islam (1995) has by using a

panel data approach and controlling for cross-sectional fixed effects shown that there can be

convergence however to different steady states Hence one can separate between catch-up

when controlling for different production functions (conditional convergence) and

unconditional catch-up (absolute convergence) Islam and his followers have shown that

conditional convergence is more common than absolute convergence

The European Union which is the region of interest in this paper is first of all a political

project with the fundamental purpose to prevent war in Europe However this project has

since the beginning been carried out by the means of economic integration This is to

understand as the process in which national markets for goods services capital and labor

merge to form larger regional markets The enlarged economic area enables more efficient

allocations of resources such as the factors of production A properly functioning reallocation

process fosters convergence in prices as well as returns to capital and labor which in turn is

expected to give rise to convergence of GDP per capita Thus convergence theory and theory

of economic integration are closely related and to some extent teach us the same things

mainly because of their direct derivation from neo-classical growth theory

4

This paper focuses on economic integration and absolute convergence in Europe 1994-2005

Most empirical studies have found significant absolute convergence for the area of EU151

(see eg Hlouskova and Wagner 2002) while studies of a wider Europe (eg including the

Balkans the ex-Soviet Republics etc) or the whole world at best find conditional

convergence and on occasion also divergence In this paper the area of interest will be the

enlarged EU (hereinafter EU252) - an area more heterogeneous than EU15 but probably more

homogeneous than a wider Europe or the whole world The fall of the iron curtain and the

course towards EU enlargement are events that most likely have initiated large scale

integration processes resembling the idea outlined above Since economic integration and real

convergence can be seen as two sides of the same coin both concepts will be treated here

Convergence theory is applied in the first step in order to estimate if and at which rate

absolute convergence has taken place in the EU25 Theory of economic integration will be

used in a second step in order to look at the mechanisms causing convergence

The focus will solely be on absolute convergence in per capita GDP Thus I will not control

for different steady states Evidence of absolute convergence is of greater relevance for policy

making and can easier be linked to the discussion based on the integration concept Absolute

convergence in per capita GDP will be estimated by looking at β- and σ-convergence two

measures introduced by Barro and Sala-i-Martin (1992) Since the definition of absolute

convergence states that the lower the initial GDP level is the faster the country is expected to

grow I will differentiate between catch-up economies3 to see if this has been the case In a

closing analysis there will be an attempt to explain catch-up performances by relating growth

rates to integration mechanisms such as trade investments and migration

The following section includes a brief outlining of the convergence concept and the methods

which will be applied to test for absolute convergence Further assessments of absolute

convergence will be provided and the performances of the catch-up countries will be

compared In section 4 the mechanisms of economic integration are presented Based on the

fundamentals of growth theory and theory of economic integration section 5 analyzes likely

1 The European Union before the eastward enlargement in 2004 but after the accession of Austria Finland and Sweden in 1995 consisted of 15 Member States and is referred to as EU15 2 The EU after the eastward enlargement in 2004 but before the accession of Bulgaria and Romania in 2007 consisted of 25 countries and is referred to as EU25 3 The 11 member states with per capita GDPs below the average of EU25 ie Czech Republic Estonia Greece Hungary Latvia Lithuania Poland Portugal Slovak Republic Slovenia and Spain (Cyprus and Malta are actually also below the EU-average but are excluded from the analysis)

5

explanatory factors that may account for the catch-up performances Within a theoretical

framework the catch-up performances found in section 3 are compared and analyzed Finally

I conclude and give suggestions on further possible research topics

2 Are the countries of the enlarged EU converging

Convergence in per capita levels of GDP and income has been a popular research topic since

the early 1990s The empirical evidence found up until now follow a couple of seemingly

consistent patterns Firstly convergence in general and particularly absolute convergence

appears to be highly dependent on how similar the studied economies are Studies only

including economies with large industrial and service sectors show more significant

convergence than studies which also include economies that are more dependent on eg

agriculture and tourism (see Fagerberg and Verspagen 1996) Trade barriers between the

studied economies as well as considerable political and judicial asymmetries also seem to

hamper convergence The fastest convergence has thus been estimated within more

homogenous economic areas with low internal barriers of trade such as among the US states

or the countries of EU124 and EU15 (see Barro and Sala-i-Martin 1992 1995 Tondl 1999

Kaitala 2004)

Although convergence seems to be conditioned on a certain degree of homogeneity it is

difficult to separate the importance of eg trade barriers and what sectors the economy is

based on This due to the fact that these two factors usually correspond strongly with each

other Economic regions with similar economies often have lower barriers of trade and vice

versa Another factor worth mentioning is if and how the business cycle affects convergence

Since many estimations of convergence (including the one in this paper) are based on rather

short time periods the impact of business cycles on the convergence process could be crucial

McGranahan (2003) has studied this relationship for regions in the US and found a positive

correlation between inter-regional inequality and the expansion of the economy Divergence

in incomes was the norm during the upswing of the 1980s while the economic decline in the

early 1990s was associated with convergence However since this paperrsquos period of focus did

not see any remarkable booms or busts this aspect will not be analyzed in detail

4 EU12 includes the 12 Member States up until the accession of Austria Finland and Sweden in 1995

6

21 How to measure convergence

A frequently used and well documented method when looking at absolute convergence within

a region of economies is to estimate so called β-convergence (Barro and Sala-i-Martin 1992)

This measure is obtained by the means of a straightforward econometric model in which

growth in per capita GDP is explained by the per capita GDP level in the preceding period

Barro and Sala-i-Martin originally estimated the β-coefficient on a cross-section of countries

with the starting GDP per capita level as regressor although followers within the field of

study have shown that it can be performed using panel data as well (see eg Islam 1996) The

panel approach is useful among other things because it generates more degrees of freedom

than the cross-section approach Because of these advantages this is the approach that will be

applied in this paper The equation to estimate is of the following form

iititit yyy εβα ++=minus minusminus 11 logloglog where t = 1 2hellip T and i = 1 2hellip n (21)

and the dependent variable since it is the first difference of a logarithmic scale is an

approximation of the annual growth rate in percent Another clear-cut method to use when

one wants to study convergence is to follow the development of the dispersion of per capita

GDP levels within the region of interest So called σ-convergence takes place if the dispersion

within the region decreases over time (Barro and Sala-i-Martin 1992) The dispersion in per

capita GDP between countries can be calculated in different ways but two convenient

measures are the coefficient of variance c and the standard deviation of the log GDP per

capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)

These two measures c and v do not seem to differ much at first glance and one expects to

find similar information Yet it has been shown that they in some situations can give rise to

conflicting results above all when the dispersion between the observed countries is large

(Dalgaard and Vastrup 2001) In this case the measures will differ since they put a different

7

weight to how far from the average observations are located The two measures have as an

example given contradictory estimates of global convergence from 1960 and onwards The

countries that were among the poorest in 1960 have not converged towards mean while the

countries above the poorest group have converged quite rapidly The result will in this case

depend on how you weight the countries with respect to their deviation from the mean

22 Evidence of convergence ndash estimation of β

Using the three measures of convergence outlined above a brief picture of whether absolute

convergence has taken place will now to be provided The observed period stretches from

1994 until 2005 and all but three of the EU25 countries are included The three small member

states Cyprus Malta and Luxembourg were for different reasons excluded from the analysis

As regards Cyprus and Malta the main reason was insufficient GDP data (comparable data

was only available from 1998 and onwards) Further these two Mediterranean economies

with dominant tourism and farming sectors can also not be expected to have much in common

with the other member states in terms of level and shape of production functions

Luxembourg is typically removed from analyses like these because of its economyrsquos

distinctive character In particular the per capita approach is because of the massive inward

commuting to Luxemburg meaningless to compare with that of the other member states

As the eight accession countries of Central and Eastern Europe went through rough transition

in the early 1990s with slumping production levels and fleeing populations the estimation

period was restricted to 1994-2005 although seemingly reliable data from around 1991 exist

for most them Latvia had for example a negative change in real GDP of about 31 percent in

1992 In Lithuania it fell by about 19 percent the same year In 1994 their respective

economies were about half the size of the estimated pre-transition levels Although the

transition itself as well as effects and counter-effects from it might have played an important

role also in the development after 1994 this choice of starting point seems to be consistent

with some sort of normalization in these economies Included data for the Western European

economies was also restricted to the period 1994-2005 in order to keep the panel balanced

Thus one has to keep in mind that the estimates do not account for the most intensive

transition period for the CEECs5 which most certainly affects the results6

5 CEECs refers to the eight rsquoCentral and Eastern European countriesrsquo of the EU ie the catch-up economies included in this paper less Greece Portugal and Spain

8

Table 1

Least square β-estimation dependent variable is itit yy 1 loglog minusminus

Coefficient value Standard error t-Statistic α 01757 00157 111711

β -01537 00017 -90545

R2 of model is 02562 Source data Eurostat (2006)

The results received from the estimation of the β-coefficient are shown in table 1 and indicate

that significant convergence in terms of per capita GDP has taken place in the region over the

studied time period The β-coefficient is estimated to -0015 corresponding to an annual

speed of convergence of about 15 percent7 This means that a member state on average

decreases the gap to the average level of per capita GDP in EU25 with 15 percent per year A

practical method of symbolizing what this means is to apply the half-life measure8 ie the

time necessary for an economy given an estimated convergence speed to close half of the

gap separating it from the average Assuming that the estimated convergence speed will be

consistent over the future it will take an economy 48 years to close half of the gap separating

it from the average A scatter plot and regression line showing the relationship between yearly

change in GDP per capita and the GDP per capita level the year before is graphed below

6 The data which this paper is based upon is exclusively collected from Eurostat (2006 see link in references) the EU statistics institution The GDP-data is in real terms (1995 Euros) Data on capital formation FDI trade etc are all in 1995 Euros Population labor force etc are measured at mid-year (first of July) in order to get more unbiased estimates when using the per capita measures 7 The speed of convergence is found by solving for λ in the equation β = eλt-1 where t in this case equals 1 8 The half-life measure is defined by ( ) ( )βτ +minus= 1ln2ln

9

Figure 1

Annual growth vs starting level

-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105

GDP per capita the year before (logs)

Cha

nge

in G

DP

per c

apita

(log

s)

Source data Eurostat (2006)

23 Evidence of convergence ndash changes in σ

The two measures of dispersion indicate that the dispersion in per capita GDP among the

studied economies has gradually fallen over time The trend in dispersion when using the

coefficient of variance c as well as the standard deviation of the log GDP per capita v are

presented in appendix 1 and shown graphically in figure 2 If the coefficient of variation is

applied the dispersion fell however only marginally (from 055 to 054 ie by about 2

percent) When using the v-measure the fall in dispersion was more significant Over the

period it changed from 099 to 084 a decrease of about 18 percent That the latter measure

gives a more significant proof of convergence is probably related to the fact that it puts

greater weight to observations with a large deviation from the mean (eg the Baltic states) and

that these economies have converged faster relative the ones closer to the mean

10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc

v is the standard deviation of per capita GDPs in logs (equation 23) and c is the coefficient

of variance (eq 22)


3 Are some catching up faster than others

31 An expanded β-model

The original equation used to estimate theβ -coefficient was of the following form


By expanding this model with dummy variables groupings of catch-up-economies can be

analyzed with respect to their catch-up performance Three groups of Member States (MS)

were formed based on their initial gaps in per capita GDP to the EU-average (see figure 3 in

section 33) which also coincide rather strongly with geographical location The groups are

(1) the Baltic MS (Estonia Latvia and Lithuania) (2) CEE4 ie the Central and Eastern

European MS (Poland Czech Republic Slovak Republic and Hungary) and (3) SE4 ie the

poorer than average MS of Southern Europe (Slovenia Greece Spain and Portugal)

The definition of absolute convergence states that poorer economies are suppose to grow at a

faster rate than richer ones however the yearly gap reduction in percent is expected to be

equal among the economies A necessary condition for absolute convergence is that the

poorer a country is at an initial stage the faster it should grow By assigning dummies for

11

these three groups and leaving the others as reference possible fixed growth effects for these

three groups can be distinguished In doing so the dummies will make variations in the size

of the intercept possible thus indicating whether a group of countries is converging faster or

slower than a reference point Thus the dummy coefficients in the model below indicate the

groupsrsquo deviation from the intercept of the reference group

iSSCCBBitRitit DDDyyy εαααβα +++++=minus minusminus 11 logloglog (32)

where t = 1 2hellip T and i = 1 2 hellip n

and takes on the value one for the Baltic member states is one for the CEE4 and

is one for the SE4 The intercept of the reference group

BD CD SD

Rα indicates a ldquocorerdquo growth rate

and the dummy coefficients are the three groupsrsquo respective fixed deviation from this

intercept

32 The estimation results

The estimation of the equation outlined above gives results indicating that the Baltic group

has a somewhat higher speed of convergence relative the reference group The coefficients for

the other two groups are negative indicating a lower intercept and a lower speed of

convergence relative the reference group The fixed deviations are all insignificant at a five

percent significance level Thus a hypothesis stating that all the groups converge towards the

mean with equal speeds would not be rejected The group SE4 has a negative deviation from

the reference intercept which at the ten percent level would be weakly significant

Table 2

Least square estimation with group dummies dependent variable itit yy 1 loglog minusminus

Coefficient value Standard error t-Statistic

Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407


Summing up the speeds of convergence for the three groups are at a conventional five

percent level neither significantly higher nor significantly lower than the reference grouprsquos

Yet the results do give a weak indication of faster convergence for the Baltic group than the

other two groups Of these two SE4 seems to converge marginally slower than CEE4

although the difference is small Below there will be a brief description of the growth

performances of the catch-up economies included in the three groups

33 A descriptive approach

Figure 3 below shows the total per capita GDP growth over the time period for the 11

countries below the average of EU259 The Baltic economies all doubled their per capita GDP

(Estonia was the most impressive with a growth close to 130 percent) The economies of

CEE4 grew by around 50 to 60 percent with the Czech Republic as a negative deviator The

economies of SE4 grew by around 40 percent with Slovenia deviating positively All of the

11 catch-up economies grew faster than the average of EU25 which had a positive change of

less than 13 percent between 1994 and 2005 Thus all 11 catch-up economies answered to the

theoretical expectations and actually caught-up and closed the gap to the average The

definition of absolute convergence said that the growth should be higher the lower the initial

level of GDP per capita From the figure below this more or less seems to have been the case

9 The average is weighted with respect to the sizes of the countries Thus a positive change in Germany affects the average more than an equal change in eg Sweden

13

Figure 3

Per capita GDP growth vs initial level

020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent

Period growth (1995-2005)Level in 1994 ( of EU-25)


4 What is economic integration and how can it be explained

When talking about economic integration one has to distinguish between real and monetary

integration (Baldwin and Wyplosz 2006) The former concerns real variables such as level of

output and allocation of production factors while the latter concerns the integration of

monetary systems and currencies eg the introduction of the Euro This paper focuses

exclusively on integration in real terms Further integration can take place at both macro and

micro levels States can force integration through macroeconomic decisions regarding trade

agreements and currency unions but at least as important for the integration process is the

behavior of firms and individuals Tools from microeconomic theory will be the basis of the

theoretical framework that is to be presented below

41 The neo-classical concepts of growth and economic integration

A set of integration mechanisms which can function as driving forces behind convergence in

GDP levels will be presented below They are (1) internal accumulation of capital (ie

savings) (2) cross-border capital mobility (3) cross-border labor migration and (4) trade

They will be briefly illustrated with Edgeworth boxes and linked to how they affect per capita

GDP The mechanisms are derived from the neo-classical growth models presented by

14

Ramsey (1928) Solow (1956) and Koopmans (1965) and the standard production function of

the form

αα minus= 1

tttt LKAY with 10 ltltα (41)

where output Y for an exogenously given level of technology A depends on capital K and

labor L In the original model the savings rate is assumed to be exogenous and constant

Although K generally has been restricted to physical capital one may also think of it in a

broader sense comprising of physical capital and human capital (Mankiw Romer and Weil

1992) The main characteristics of this production function are constant returns to scale (since

the coefficients sum to 1) and diminishing marginal products of the production factors K and

L Hence imagining given levels of technology labor and savings rate additional capital

yields decreasing rates of return and growth rates This implies a steady state where capital

per worker k and output per worker y are constant

( kfy = )

)

(42)

The steady state output y is above all determined by the exogenously given level of

technology A which all economies are supposed to have free access to The assumption of

equal access to available technology or fast technological dispersion can be regarded as valid

for highly open economies with similar levels of education This may be expected for

advanced economies in general eg Western Europe but a critical issue is whether it can be

expanded to include the CEECs as well In the analysis section there will be a discussion of

how technological dispersion can function as a factor behind convergence but for the time

being the term indicating level of technology A is dropped Expression (41) can be rewritten

as

( LKfY = (43)

By dividing by total population N we get the following expression for per capita output

y = ( )NL

LLKf

NY

times= (44)

15

Thus output per capita depends on output per hour of labor (labor productivity) and hours of

labor to total population The latter can be further elaborated in order to take into account the

number of economically active (ie size of the labor force) and the size of the working age

population so that (44) becomes

( )N

WAWALF

LFL

LLKfy timestimestimes=

(45)

where LF is the size of the labor force and WA working age population GDP per capita now

depends on labor productivity hours of labor per economically active LLF the participation

rate LFWA and the size of the working age population to total population In order to

conveniently follow the changes in GDP per capita for a panel of countries the function is on

logarithmic scale and the subscripts i and t indicating country and year are added

( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)

where ln yit ndash ln yit-1 is an approximation of the yearly growth in GDP per capita (for

relatively small changes in y) The mechanisms of economic integration will now be

presented They are illustrated with the well-known Edgeworth-box named after Francis

Ysidro Edgeworth A frequently used way of illustrating the integration process is otherwise

the Solow-diagram (see eg Baldwin 1989) However when comparing two or more

countries in a process of resource reallocation the Edgeworth-box serves as a more suitable

tool Finland and Estonia are used as a hypothetical example of how a richer economy with a

relatively higher degree of capital intensity in the production process can be integrated with a

poorer one with a relatively higher degree of labor intensity

The initial position with an allocation where Finnish production is more capital intensive than

the Estonian is shown below The interpretation is as follows labor increases in Finland

relative Estonia when L(Fin) moves to the right on the horizontal axis Capital in Finland

increases relative Estonia when K(Fin) moves upwards on the vertical axis Labor increases in

Estonia relative Finland when L(Est) moves to the left on the horizontal axis and capital

increases in Estonia relative Finland when K(Est) moves downwards The different

16

allocations between the countries are purely relative measures where K and L are in terms of

the otherrsquos disposal and the vertical and horizontal axis of the box symbolizes the aggregate

supply of the two factors in the region The capital intensity in Finland is K(Fin)L(Fin) and in

the proposed allocation below it is higher than in Estonia this since K(Fin)L(Fin) gt

K(Est)L(Est) Allocations along the diagonal line imply equal intensities and complete

integration in terms of factor prices and factor intensities

Figure 4

42 Integration through internal accumulation of capital

In this case the level of output depends on savings rate productivity depreciation and

employment Only growth in productivity and employment rate can increase per capita

output given that the investment rate equals the rate of depreciation ie the economy is in

steady state If not in steady state the economy will grow as long as the marginal product of

capital yields an investment rate higher than the rate of depreciation However because of the

assumption of diminishing marginal returns to capital economies will over the phase of time

converge to the similar level given that they have matching production functions The figure

below shows a situation where Estonia by internal saving accumulates own capital up to its

steady state Thus the aggregate capital stock in the whole region grows (the box grows

upwards) the capital intensity in Estonia increases relative Finlandrsquos and there is convergence

between the two countries In the analysis of section 5 the impact of internal accumulation of

17

capital will be analyzed by comparing data on gross fixed capital formation stemming from

domestic sources

Figure 5

The constraint connected with the basic Solow model when studying integration and

convergence is that it treats the economy as closed Thus internal accumulation of capital can

only force absolute convergence if production functions are identical and the resulting

convergence speed will be low (Baldwin and Wyplosz 2006 ch 7) Economic integration

becomes more dynamic when allowing the factors of production to be internationally mobile

A theoretical situation in which borders are open better resembles the European reality and

results in new possibilities to efficiently allocate capital and labor

43 Integration through capital mobility

In the following sections the basic Solow model is extended to allow for cross border

reallocation of capital and labor Capital mobility in an enlarged economic area gives capital

owners the opportunity to reallocate their resources more efficiently This means intra-

regional reallocation (within the box) as well as a relative change in investments from non-EU

economies (from outside the box) Another difference compared to integration only through

internal accumulation is that the expected speed of convergence in this case is higher

(Baldwin and Wyplosz 2006 ch 7)

18

One could consider the reallocation of capital to a less capital-rich economy as giving this

economy an ldquoinduced capital formation effectrdquo or ldquomedium-run growth bonusrdquo concepts

introduced by Baldwin (1989) This effect could be seen as an exogenous increase in the

investment rate in the relatively capital-poor country and vice versa in the capital-richer In

the original Solow-setting the investment rate equaled the savings rate and was assumed to be

constant From a welfare perspective this implied that citizens in order to invest more must

save more and consume less In the case where capital is reallocated across borders an

economy can enjoy increased investment activity without forgoing consumption

Figure 6

The figure above illustrates a situation in which capital is reallocated from the relatively

capital-richer Finland to the relatively capital-poorer Estonia This takes place since the

marginal returns to capital diminish and are higher in the relatively capital-poor economy

)()( kfL

LKFy == is output per capita (or worker)

)acute(kfr = is the marginal returns to capital and

0)acuteacute()acute(lt=

partpart kf

kkf based on the law of diminishing returns

19

Thus the derivation of this integration mechanism as well as convergence theory in general

is highly dependent on the assumption of diminishing returns to capital This integration

mechanism will be analyzed by comparing inward foreign direct investments (FDI) in the

catch-up economies both as a share of GDP and as a share of gross fixed capital formation

This mechanism is expected to have a large impact on labor productivity thus decisive for

GDP growth and catch-up speed FDI affects labor productivity directly by increasing the

capital intensity in the production process but is also expected to augment the incorporation

of technology in the economy and therefore boost total factor productivity

44 Integration through migration

When borders are opened up for migration movement from poorer economies to richer ones is

expected according to the theory (Baldwin and Wyplosz 2006 chapter 8) In the capital-rich

economy the labor productivity and the wages are higher In the economy where capital is less

abundant labor productivity and wages are lower The wage asymmetry leads to net migration

from the capital-poor economy to the capital-rich Assuming perfect competition on the factor

markets the relationship between wages and capital intensity can be derived in the following

way

LFFw L partpart

equiv= is the wage

LLKFkfy )()( == is output per capita (or worker)

)acute(kfr = is the unit cost of capital

kkfrk )acute(= is the per capita cost of capital in the economy which gives that

wkkfy =minus )`( since the per capita labor cost equals the average wage

By taking the derivative of the last expression with respect to k we get the effect on wages

when the capital intensity is increased

0)acuteacute( gtminus=partpart kkf

kw since facuteacute(k)lt 0

20

Less capital intensive production processes thus have a less productive labor force (the

marginal product of labor is lower) and lower wages other things equal If the assumptions

hold labor migration eg from Estonia to Finland lowers the wages in Finland (since the

capital intensity falls) and increases the wages in Estonia (because of increased capital

intensity) other things equal If overlooking externalities and changeover costs (and assuming

that the migrants are active laborers) the effect on GDP will be unambiguously positive in

Finland and negative in Estonia

Figure 7

In the figure above labor migrates from Estonia to Finland Capital intensity will increase in

Estonia given that to rapid capital depreciation not counteracts boosting convergence in

factor prices and labor productivity (Baldwin and Wyplosz 2006 ch 8) Although this aspect

of economic integration unambiguously hampers convergence in GDP the effect on per

capita GDP is ambiguous The effect on convergence in per capita GDP depends on whether

the migrants were working in Estonia and if they find a job in Finland Other aspects eg

crowding out on the respective labor markets and the level of skills of the migrants are also

important to take into account but are beyond the scope of this paper Therefore the analysis

will be restricted to solely relate the expected (and most basic) effects from changes in

employment and population to the respective catch-up performances Other things equal

increases in hours of labor per economically active participation rate and the share of the

population in working age will have positive effects on per capita GDP while an increase in

21

total population will affect per capita GDP negatively Accordingly these variables will be

the basis of the analysis in section 5

45 Integration through trade

Cross-border trade and specialization can also function as a mechanism of integration causing

convergence Based on a set of assumptions it can be showed that countries can converge

through the prices of traded goods (and services) without the need for mobility of capital and

labor A fundamental concept is Ricardian trade and comparative advantages which shows

how trade leads to complete specialization in the production of goods (Ricardo 1821) In the

case with only two goods and two countries each country would end up supplying only the

good it produces the most efficiently and trade with each other Heckscher and Ohlin (1933)

and Samuelson (1948) has taken the concept further and shown that international trade gives

rise to factor price equalization through the goods markets given equal levels of technology

Figure 8

Factor price equalization takes place within a restricted area in which incomplete

specialization prevails However the countries keep producing both goods although they tend

to export the one which is produced more efficiently Thus convergence in factor prices can

be brought about without cross-border mobility of capital and labor given that the goods and

services are traded on an international market and that further specialization is possible What

22

factor price equalization does demand is that the factors of production are mobile between

sectors and industries If eg laborers are unwilling to switch sector or accept lower wages the

resulting effect will be unemployment Thus given that convergence of factor prices gives

rise to convergence in per capita output (this will be elaborated in section 54) the degree of

openness to trade will influence the catch-up performances I will analyze this relationship by

comparing data on trade integration (ie the average of imports and exports to GDP)

46 Summing up integration mechanisms causing convergence

Based on the outline above a number of important variables affecting growth in per capita

GDP and thus the convergence (or divergence) of economies can be listed The productivity

of labor is a crucial factor affecting the growth rate and the convergence trend If the

productivity of labor increases faster in a poorer economy than in a richer counterpart

convergence will be fostered other things equal Labor productivity is determined by total

factor productivity and the capital intensity in the production process The capital intensity

can be enhanced by internal accumulation of capital and foreign investments

Since the per capita GDP for a given size of the population depends positively on hours of

work per economically active an increase in this variable will boost convergence Holding the

other variables constant positive changes in the participation rate and the share of total

population in working age will affect GDP per capita positively Because of the per capita

approach total population will be negatively correlated with the speed of convergence when

holding the amount of work constant Based on the fourth integration mechanism it is also to

expect that the degree of openness to trade affects the speed of convergence A proxy for the

degree of openness is the economyrsquos trade integration of goods and services as a share of

GDP In the following section these variables (which are summarized in table 3 on the

following page) will be compared with the convergence performances of the catch-up

countries

Table 3

Summary of key variables affecting speed of convergence

23

Variable of interest Expected effect on per capita GDP and convergence speed other things equal

Technology Positive

Internal accumulation of capital Positive

Foreign direct investment Positive

Hours of work per economically active Positive

Participation rate Positive

Working age population Positive

Total population Negative

Trade integration Positive

5 Explaining catch-up performances

In the preceding section basic theory on economic integration and possible mechanisms

fostering convergence was outlined These mechanisms will now be related to the

performances of the catch-up economies that were briefly presented in section 3 The analysis

is based on descriptive statistics on the key variables presented above and their relation to

economic theory The grouping of the catch-up economies introduced in section 3 is applied

The three groups are (1) the Baltic Member States (2) CEE4 ie the Central and Eastern

European MS and (3) SE4 ie the Southern European MS It was showed in section 3 that

the Baltic group had the lowest initial per capita GDPs and grew faster than CEE4 SE4 had

initial per capita GDPs closest to the average of EU25 and grew slower than CEE4

51 Productivity and investments ndash decisive for convergence

On the basis of the production function the factors contributing to growth are labor

productivity and employment Labor productivity in turn is a broad concept which depends

on both available capital per worker ie the capital intensity and the way in which the factors

of production are exogenously turned into output ie level of technology or TFP Further the

amount of capital depends on internal capital formation and inward foreign direct

investments as well as the consumption of fixed capital ie capital depreciation Evolutions

in capital formation as well as level of technology are expected to be highly decisive for

growth in per capita GDP Firstly the average annual change in labor productivity and per

capita GDP are graphed against each other

24

Figure 9

Labor productivity vs GDP growth

0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)

Per capita GDPLabor productivity


As expected labor productivity and per capita GDP co-varies strongly Although the data is

rather convincing in stressing the importance of the broad concept of labor productivity to

growth and thus catch-up speed there are a few remarks to be done before this concept is to

be further elaborated From the bars above one can distinguish a pattern in which labor

productivity increases by more than per capita GDP for poorer economies and vice versa (the

higher the initial level of per capita GDP the farther to the right the country is located on the

x-axis) The extreme case seems to be Spain for which labor productivity played a relatively

unimportant role in explaining increases in per capita GDP Other comparatively rich nations

such as Greece Portugal and Slovenia also had lower impacts from labor productivity in

contrast to eg Estonia Lithuania and Poland Nevertheless the figures are (with the

exception of Spain) considerably higher than for the non-catching up economies and thus help

to explain convergence In the Euro area as an example the corresponding average annual

labor productivity growth was just one percent (Kaitala 2004)

52 Internal savings foreign investments or technology

As it nearly seems to be an explain-it-all correlation between catch-up and labor productivity

the concept has to be further investigated In section 4 it was showed how internal savings and

cross-border reallocation of capital can deepen economic integration and foster convergence

Besides capital formation an important factor in the integration process is the dispersion and

25

incorporation of technology ie changes in TFP The evolution in TFP can be derived by

estimating the so-called Solow residual However this either demands access to reliable and

comparable capital stock data or own estimations of the respective capital stocks eg under

the perpetual inventory method Since there is a scarcity of comparable capital stock data for

the CEECs the alternative is own estimations This in turn would require baseline

benchmarks of capital-to-output ratios stocks of human capital etc and is beyond the scope

of this paper For the time being the focus will be on formation of physical capital although

some recent findings on dynamics in TFP will be reported

Figure 10

Annual gross fixed capital formation

05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU


In the figure above the evolution in annual gross fixed capital formation (GFCF) as a share of

GDP for the three groups and the non-catching up economies of EU25 (NCU) is graphed The

statistical aggregate of GFCF is a measure of the net new investment in the domestic economy

in fixed capital assets although not accounting for capital depreciation Obviously GFCF is

not a measure of total investment because all kinds of financial assets are excluded but is a

good indicator of the level of investment activity relevant for real variables such as output

The levels have been consistently high for all three groups of catch-up economies over the

time period As a contrast the investment level for the NCUs has been consistently below 20

percent of GDP for the time period When comparing the groups the most striking trend is the

consistent intensification of investment activity in the Baltic economies Although the general

26

trend for catch-up economies seems to be upward sloping it is widely surpassed by the trend

for the Baltic group who even exceeded the 30 percent level in the last four years

The investment activity in the catch-up economies seems to follow the theoretical

expectations laid out in the preceding section It was explained how both internal

accumulation and cross-border reallocation of capital can function as mechanisms of

integration boosting labor productivity That the level of gross investments is higher the

poorer the economy is at an initial stage has according to our data certainly been the case for

EU25 However in section 4 integration through capital formation was divided into internal

accumulation (ie savings) and foreign investments By deducting FDIs from GFCF estimates

of internal accumulation can be made Below the annual average gross investments to GDP

and its two constituents are graphed FDIs as a share of GDP were well above 5 percent for

Latvia Estonia and Czech Republic For Lithuania Slovak Republic and Hungary they were

about 5 percent All of the economies except Greece had levels higher than the 14 percent of

the NCUs thus confirming the theoretical expectations

Figure 11

Investments in the catch-up economies 1994-2005

05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal


As a consequence for economies with lower FDI inflows such as Greece and Slovenia

internal accumulation is more important Internal accumulation accounted for more than 90

percent of GFCF in these two economies To sum up capital formation in general as well as

investments from foreign sources seem to be at higher levels in poorer economies The

27

theoretical scenarios laid out in section 4 implying that catch-up can be boosted from internal

accumulation and reallocation of internationally mobile capital seem to be a part of the

explanation to recent convergence in EU25 Although formation of physical capital is

regarded as an important factor in convergence processes some notes on the possible role of

human capital and technology needs to be made

52 Human capital and technology

It is customary to take both physical and human capital into account when estimating capital

stocks and capital formation (see eg Mankiw Romer and Weil 1992) This can be done by

using levels of education for the labor force or measures of education expenditures as proxies

In empirical research on convergence human capital has shown to play a decisive role and be

regarded as a precondition for catch-up Evidence tends to confirm that convergence is

conditioned on a certain level of schooling in the economy However the CEECs have

traditionally had comparably high levels of education ndash most them actually have nearly full

enrolment to basic education and graduation rates close to that of the NCUs (Benacek and

Gacs 2002) The condition of human capital is probably more important when comparing

more dissimilar economies eg studies including Africa or Asia Although the quality of

education as well as the enrolment to higher schooling differs in Europe the basic human

capital condition for convergence is assumed to be fulfilled Nonetheless how education

patterns and expenditures affect convergence dynamics and catch-up speeds in the EU is an

idea for further research

Growth in technology or TFP is an important element in labor productivity growth especially

when it comes to catch-up economies Alvarez-Ayuso et al (2006) has studied convergence in

labor productivity and TFP levels in the 1990s by estimating β-coefficients Based on their

results they argue that capital formation (both physical and human) has a larger impact on

convergence than growth in TFP has However studies covering more recent years show

signficant increases in TFP levels across the CEECs and above all in the Baltic states

Growth in TFP has for these economies contributed to around 40-50 percent of per capita

GDP growth (Kaitila 2004) Hunya (2004) argues that the rapid growth in TFP for these

economiesrsquo could be explained by their close investment relations to the well-developed

Nordic neighbors 74 percent of the FDI stock in Estonia and around 50 percent of the stocks

in Latvia and Lithuania came from the Nordic countries in 2004 (Hunya 2004) Although

28

investments have been concentrated to labor intensive production substantial spillover effects

to the economies as a whole are highly probable

The determinants to TFP growth in the CEECs have been studied by Damijan and Rojec

(2001) They found that FDIs in general have a large impact on overall productivity growth in

the CEECs during the 1990s FDIs not only channel technology across national boundaries

but also between firms ndash in particular between foreign and domestic companies Summing

up both levels of FDI in general as well as the origin of the FDI ie the investment partners

can help explain growth in TFP and labor productivity Although estimates of growth in TFP

for our time period are not presented here one can regard it as an important contributor to

labor productivity growth On the one hand there is probably a general catch-up effect (the

Baltic states grew most rapidly) but on the other hand FDI partners investment structure and

knowledge formation could be plausible determinants to how fast TFP grows

53 Employment and demographic change ndash integration through migration

From the production function the importance of performed labor to level of output can be

directly derived Equation (44) was expanded into equation (45) and (46) in order to

elaborate the employment concept further Hours worked to total population (LN) depends on

hours worked per economically active (LLF) the size of the labor force to working age

population (LFWA) ie the participation rate and the working age population to the total

population (WAN) ie population structure Other things equal worked hours the size of the

labor force and working age population increase labor to total population and thus per capita

output A population increase when holding hours of work constant affects per capita output

negatively

Theory on economic integration proposes that people as a part of the integration process will

move from where the capital intensity and the wages are lower to where the capital intensity

and the wages are relatively higher The changes in labor illustrated in figure 12 below

indicate that there have been significant increases in the least poor member states with Spain

as the strongest example There have also been increases in labor in Portugal and Greece as

well as in the richest one of the accession states Slovenia The figures seems to point out that

catch-up for the group consisting of the more capital intensive economies of SE4 is driven by

increases in labor while labor plays a smaller and more ambiguous role for the other groups

29

Figure 12

Evolution of labor to total population (1994-2005)

-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt


As mentioned above the amount of labor is dependent on both changes on the labor market

and demographic trends Since the incentive behind migration in the integration scenario is

higher return to labor ie wages one could primarily expect economically active residents to

migrate From an aggregated perspective this means that a reallocation process takes place in

which resources (in this case labor) are moved in order to be more efficiently used The net

effect in the relatively richer economies should not only be relative increases in hours of work

and size of the labor force but as an effect also in working age population and total

population Theory thus also suggests that these subgroups of the population as well as total

population as such in relative terms will decrease in the poorer economies

The changes in total population are presented in figure 13 below and follow the theoretical

proposal Major decreases in total population are recorded for the Baltic states in opposite to

considerable increases in SE4 In Lithuania the decrease was close to 10 percent while Spain

recorded an increase of more than 10 percent There was a small increase in the Slovak

Republic while the other three in this group had smaller decreases These results could

suggest that the contribution from labor to catch-up have been counteracted by changes in

total population (because of the per capita approach) Population changes might have reduced

the magnitude of the positive change in labor in eg Spain and Greece and on the other hand

counteracted otherwise larger decreases in the Baltic states

30

Figure 13

Population change 1994-2005 (in )

-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain


However since the available data does not reveal whether a population change largely

consists of a change in active labor or not it is not possible to be absolutely certain of how

population dynamics affect catch-up Nevertheless it is possible to say something about the

co-variation between the changes in population and labor For quite a few countries the

change in population is accompanied by a change in worked hours of significant size and in

the same direction The change in hours worked as a share of the change in total population

was actually more than 50 percent in all countries except Latvia Although this does not tell us

with certainty that the infusion to total population predominantly consists of active laborers it

suggests that the counteraction effect from changes in total population seems to be trivial The

average annual changes in LLF LFWA WAN and LN for the countries as well as group

averages are presented in detail in appendix 2 To summarize the changes in LLF LFWA

WAN and LN consistently follow the theoretical expectations in the sense that SE4 as a

group outperformed the CEC4 which in turn outperformed the Baltic states

54 Degree of openness ndash integration through trade

How openness to trade through factor price equalization can foster integration was briefly laid

out in section 45 If trade functions as a mechanism of integration one can expect the level of

trade to influence the speed of convergence positively However theory does not provide any

certainty of the relationship between level of trade and convergence in output Even though it

31

is clear that flows of goods and services between countries will lead to convergence in factor

prices at least under the assumptions of the factor price equalization theorem (Samuelsson

1948) empirical results have been rather diverging on whether this implies convergence in

output as well Further even if trade openness and convergence co-exist this does not

necessarily imply that there is a causal relationship between the two

Although the arguments supporting the convergence effect from openness to trade are not as

self-evident as when it comes to investments or employment it still has some important

logical arguments and empirical evidence as support It has for example been argued that a

high degree of openness to trade induces faster dispersion of available technology This

implies convergence in levels of technology which in turn would affect productivity and

growth positively in catch-up economies (see eg Slaughter 1997) A majority of empirical

studies of the connection between openness to trade and convergence in per capita GDP have

also reached a general conclusion stating a significantly positive relationship (see eg Ben-

David 1996 Henrekson et al 1997 and Giles 2001) On the negative side Bernard and Jones

(1996) conclude that freer trade causes divergence rather than convergence in income and

output In summary while the role of trade openness in the convergence process is not crystal

clear a great deal of recent evidence points to a positive association of some sort

When turning the focus to how the degree of openness to trade has changed in the catch-up

economies we find that all of them became more integrated in terms of trade with goods and

services Trade integration is here measured as the average of total exports and imports of

goods and services to GDP This measure is frequently used as indicator of the integration of

the markets for goods and services eg by Eurostat and other EU-institutions In figure 14

below the average annual growth in degree of trade integration and per capita GDP are

compared No noteworthy pattern distinguishing the three groups of countries from each other

seems to exist Thus one can not conclude that the fast growers also increased their openness

to trade faster than the others Although this partly leads to a rejection of the importance of

trade integration to catch-up performance an important note is that all of the studied countries

both grew significantly (Greece had the lowest average annual growth with around 25

percent) and increased their degree of openness

32

Figure 14

Trade integration vs GDP growth

0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)

Per capita GDPTrade integration


55 Summing up what explains catch-up performances in Europe

The results from the analysis of the catch-up performances are summarized in the table below

Four mechanisms of European integration was presented in section 3 and connected to

growths in per capita GDP The mechanisms were linked to the production function and

operationalized by following labor productivity ldquoemployment raterdquo (or worked hours to total

population) and trade integration of goods and services over time Change in labor

productivity seems to be the heaviest contributor to catch-up in EU25 Employment gets more

important the richer the economy is in relative terms which is in line with the theoretical

prospects Trade integration has played a more ambiguous part although it is interesting to

notice that all catch-up economies became more integrated in the international markets for

goods and services along with a general observation of significant absolute convergence for

the region

Table 4

Average annual changes in percent for 1994-2005

YL LN Trade integration GDP per capita Lithuania 7372 -0421 0833 6524 Latvia 6721 0482 6787 6901

33

Estonia 8016 -0120 1529 7543 Baltic average 7370 -0020 3049 6989 Poland 4714 -0335 4279 4235 Slovak Republic 3874 0425 1119 4200 Hungary 3880 0546 8505 4325 Czech Republic 2938 -0252 3337 2618 CEC4 average 3852 0096 4310 3844 Slovenia 2904 1060 2885 3802 Greece 2558 0632 4594 3131 Portugal 1759 0785 0543 2478 Spain 0380 2487 2695 2822 SE4 average 1899 1241 2679 3058


Irrespective of trade integration the two main mechanisms that foster integration of

production factors and convergence in per capita GDP followed the expectations Firstly the

sizes of the capital stocks in the poorer economies relative the richer grew through internal

accumulation and cross-border reallocation of capital By analyzing capital formation and

FDIs some of the important dynamics in labor productivity could be explained although a

more thorough analysis of changes in TFP and human capital was omitted Secondly people

in general and workers in particular were expected to migrate to where wages are higher when

economies are integrated to form a larger economic area Flows of workers as well as people

in general seem to be channeled as theory proposes although the impact of this mechanism is

rather small The relatively richer economies eg Spain and Slovenia gained more from

changes in employment than relatively poorer

A possible conclusion is that labor productivity (investments incorporation of technology)

highly important for catch-up but with diminishing impact as the economy closes the gap to

the average As the economy converges the importance of attracting workers grows To

understand why some catch-up economies although they are relatively richer witness

significant increases in employment and population one has to widen the perspective EU is

after all a relatively wealthy place especially if comparing with the neighbors of North

Africa the Balkans and the Middle East If a larger economic region is considered some

catch-up economies of EU25 could all of a sudden be regarded as wealthy non-catching up

economies with relatively high wages and low returns to capital

34

6 Conclusions

This study started off by carrying out a brief assessment of real absolute convergence patterns

in the area of the enlarged EU The estimates of β- and σ-convergence suggested that in the

course of the period 1994-2005 a process of convergence towards the same steady state has

taken place between the per capita GDP levels of the EU25 Member States The speed of

convergence is estimated to about 15 percent ie the gap to the average level of per capita

GDP in the EU25 is closed by 15 percent annually The half-life measure told us that it would

take an average economy about 48 years to close half the gap separating it from the average of

EU25 As regards the catch-up countries all grew faster than the average of EU25 although a

few of them more impressively than others The catch-up countries were grouped based on

initial per capita GDPs (conveniently coinciding with geographical location) but no

significant differences in convergence speeds among the groups where recorded

The analysis within the framework of integration theory left mainly two things of value

behind Firstly it helped to explain some of the dynamics behind the catch-up performances

which in turn could be a lesson to learn for poorer economies in general and coming entrants

into the EU ndash thus highly topical for Bulgaria and Romania ndash in particular Catch-up depends

on a number of factors but can mainly be derived from dynamics in labor productivity Both

total investments and FDIs were higher for the catch-up economies than the richer ones and

thus explain parts of the convergence through labor productivity Technological spillovers and

convergence in TFP which in turn could be boosted from FDI intensity and FDI relations are

also assumed to explain a great deal of increases in labor productivity The Baltic states grew

at the fastest rates and also had high levels of FDIs as a share of GDP Besides a general

catch-up effect close and intensive trade- and investment relations with the Nordic economies

together with early important political and economic reforms are according to Hunya (2004)

probable explanations to why the Baltic as group and Estonia as country top the growth

leagues

Secondly the findings are a clear verification of the neo-classical theories of growth and

economic integration although more detailed research including considerations of TFP and

human capital would deepen the understanding even more The relatively short time period

from which my source data is taken also leaves questions to the suitability of generalization

35

based upon the findings To reach more solid conclusions on catch-up speeds and

convergence patterns the study should cover a longer time frame including all phases of the

business cycle Nevertheless it is interesting to confirm the theory of convergence for an

enlarged European Union as well as to clarify through what mechanisms convergence comes

about More detailed clarifications can still be made mainly by including measures of capital

stocks in the analysis which in turn would enable estimations of Solow residuals and

evolutions in technology

References

Baldwin R 1989 The growth effects of 1992 Economic Policy 9 247-282

36

Baldwin and C Wyplosz 2006 The Economics of European Integration (New York

McGraw-Hill)

Barro R and X Sala-i-Martin 1991 Convergence Across States and Regions Brookings

Papers on Economic Activity 1 pp 107ndash82

Barro R and X Sala-i-Martin 1992 Convergence Journal of Political Economy 100 pp

223ndash251

Barro R and X Sala-i-Martin 1995 Economic Growth (New York McGraw-Hill)

Ben-David D 1996 Trade and convergence among countries Journal of International

Economics 40 279-298

Benacek V and J Gacs 2002 Catching Up and EU Accession - Conditions for Fast Real

Convergence in the Candidate Countries Interim Report IR-02-068 IIASA

Bernard A B and C I Jones 1996 Productivity and convergence across US states and

industries Empirical Economics 21 113-135

Dalgaard C-J and J Vastrup 2001 On the measurement of -convergence Economics

Letters Volume 70 Number 2 February 2001 pp 283-287(5)

Damijan J and M Rojec 2001 What role does FDI absorptive capacity and trade play in

transferring technology to Eastern Europe Evidence from panel data for Estonia and

Slovenia Paper prepared in the framework of the PHARE-ACE research project P97-8112-R

Eurostat 2006 Structural Indicators (Brussels available at laquohttpeceuropaeueurostatraquo)

Fagerberg J and B Verspagen 1996 Heading for Divergence Regional Growth in

Europe Reconsidered Journal of Common Market Studies Vol 34 431ndash48

Giles D E A 2001 Output convergence and international trade Time-series and fuzzy

clustering evidence for New Zealand and her trading partners 1950-1992 Econometrics

Working Paper EWP0102 Department of Economics University of Victoria

Henrekson M J Torstensson and R Torstensson 1997 Growth effects of European

economic integration European Economic Review 41 1537-1557

Hlouskova J and M Wagner 2002 The CEEC10`s Real Convergence Prospects Centre for

Economic Policy Research Discussion paper series No 3318

Hunya G 2004 FDI in small accession countries the Baltic states EIB Papers Vol 9 No 2

Kaitila V 2004 Convergence of real gdp per capita in the EU15 How do the accession

countries fit in Working paper No 252004 ENEPRI

McGranahan D 2003 Regional convergence and divergence in the US 1969-1998

Working Party on Territorial Indicators OECD

37

Mankiw G D Romer and DN Weil 1992 A contribution to the empirics of economic

growth Quarterly Journal of Economics vol107 no2 407-437

Islam N 1995 Growth Empirics A Panel Data Approach Quarterly Journal of Economics

Vol CX No 4 pp 1127-1170

Ohlin B 1933 Interregional and International Trade

The Quarterly Journal of Economics Vol 110 No 4 (Nov 1995) pp 1127-1170

Ricardo D 1821 On the Principles of Political Economy and Taxation (London John

Murray)

Alvarez-Ayuso I Delgado-Rodriquez J and M Salinas-Jimenez 2006 Capital

accumulation and TFP growth in the EU A production frontier approach Journal of Policy

Modeling Vol 28 No 2 195-205

Samuelson PA 1948 International trade and the equalization of factor prices Economic

Journal 58 163-184

Slaughter MJ 1997 Per capita income convergence and the role of international trade

American Economic Review 87 194-199

Solow RM 1956 A contribution to the theory of economic growth Quarterly Journal of

Economics vol 70 64-94

Tondl G 1999 The changing pattern of regional convergence in Europe Review of Regional

Research vol 19 1-33

Appendices

Appendix 1

Averages and measures of dispersion for per capita GDP in EU25

38

Year EU25 average (population weighted)

EU25 average (unweighted)

SD of log GDP per capita

Coefficient of variance

1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2


LLF LFWA WAN LN Lithuania -0382 -0196 0186 -0421

Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120

Baltic average 0180 -0430 0214 -0020 Poland -0502 -0816 0939 -0335

Slovak Republic -0220 0255 0397 0425 Hungary 0349 -0342 0546 0546

Czech Republic -0327 -0624 0849 -0252 CEC4 average -0175 -0382 0682 0096

Slovenia -0207 -0783 1065 1060 Greece 0579 -0074 0526 0632 Portugal -0296 0240 0515 0785

Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Author Martin Nybom

Supervisor Christian Nilsson Abstract

The EU25 Member Statesrsquo GDP per capita levels converged in 1994-2005 Convergence

occurred at an average speed of approximately 15 percent per year In the first part of this

paper unconditional convergence is analyzed by looking at both β- and σ-convergence and the

performances of the catch-up economies are compared discussed and related to the

convergence definition In a second stage the catch-up performances are analyzed in relation

to theory of economic integration Substantial increases in labor productivity explain a great

deal of the catch-up for poorer economies such as the Baltic states while increases in

employment have been relatively more important for the less poorer economies such as Spain

Portugal and Slovenia Labor productivity is further elaborated and it is found that both FDIs

and internal savings have been consistently higher for the catch-up economies than the non-

catching-up economies FDIs are also assumed to have indirect effects such as promoting

incorporation of technology

Key words Convergence catch-up EU25 the European Union Economic integration

2







3

1 Introduction


























4





























5
















Kaitala 2004)














6




















capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)





7































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices








3

1 Introduction


























4





























5
















Kaitala 2004)














6




















capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)





7































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


1 Introduction


























4





























5
















Kaitala 2004)














6




















capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)





7































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices






























5
















Kaitala 2004)














6




















capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)





7































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices

















Kaitala 2004)














6




















capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)





7































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices





















capita v ie

2

1

1sum=

⎟⎟⎠

⎞⎜⎜⎝

⎛ minus=

n

i

i

yyy

nc sum

=

equivn

iiy

ny

1

1 (22)

2

1

log1sum=

lowast ⎥⎦

⎤⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛=

n

i

i

yy

nv sum

=

lowast equivn

iiy

ny

1log1log (23)





7































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices
































8

Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Table 1



β -01537 00017 -90545














9

Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 1


-004-002

000200400600801

012014016

7 75 8 85 9 95 10 105


Cha

nge

in G

DP

per c

apita

(log

s)













10

Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 2

σ-convergence

0

02

04

06

08

1

12

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Disp

ersi

on in

per

cap

ita G

DPs

vc


of variance (eq 22)

















11










BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices











BD CD SD



intercept









Table 2



Rα 01607 00579 27744

β -00135 00058 -23440

Bα 00126 00145 08677

Cα -00083 00101 -08225

12

Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Sα -00098 00056 -17407




















13

Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 3


020406080

100120140

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain

EU-25

Perc

ent



















14


the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices



the form

αα minus= 1











( kfy = )

)

(42)









as

( LKfY = (43)


y = ( )NL

LLKf

NY

times= (44)

15





( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices






( )N

WAWALF

LFL


(45)






( )

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟⎠

⎞⎜⎜⎝

⎛=

ti

ti

ti

ti

ti

ti

ti

tititi N

WAWALF

LFL

LLKf

y

lnlnln

lnln (46)
















16







Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices








Figure 4













17


domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices



domestic sources

Figure 5
















18









Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices










Figure 6




)()( kfL




partpart kf


19
















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices

















way

LFFw L partpart

equiv= is the wage









20








Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices









Figure 7













21













Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices














Figure 8






22

























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


























countries

Table 3


23


Technology Positive




























24

Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

Greece

Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices



Technology Positive




























24

Figure 9


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ania

Latvi

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25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

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26















Figure 11


05

101520253035

Estonia

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cent

of G

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27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

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ublic

Hungary

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epub

lic

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Portug

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Cha

nge

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erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

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Poland

Slovak R

epub

lic

Hunga

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Rep

ublic

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31






























32

Figure 14


0123456789

Lithu

ania

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ry

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Rep

ublic

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ia

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Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 9


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

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Rep

ublic

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al

SpainAv

erag

e an

nual

cha

nge

(in

)





















25









Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

Slovak R

epub

lic

Hunga

ry

Czech

Rep

ublic

Slovenia

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Portug

al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

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Poland

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Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices










Figure 10


05

10152025303540

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Perc

ent o

f GDP Baltic

CEE4SE4NCU












26















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

Slovak R

epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

erag

e)

GFCFFDIInternal






27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

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Rep

ublic

Hungary

Poland

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epub

lic

Slovenia

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Portug

alSpa

inNCU

Cha

nge

in p

erce

nt




















30

Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

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a

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Poland

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epub

lic

Hunga

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31






























32

Figure 14


0123456789

Lithu

ania

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ry

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Rep

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Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices
















Figure 11


05

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

Poland

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epub

lic

Slovenia

Greece

Portug

alSpa

inNCU

Per

cent

of G

DP (p

erio

d av

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e)

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27
































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

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Rep

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in p

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30

Figure 13


-15

-10

-5

0

5

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15

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31






























32

Figure 14


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alSpa

inAver

age

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al c

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e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices

































28






















negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

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Rep

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30

Figure 13


-15

-10

-5

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5

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15

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31






























32

Figure 14


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the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices























negatively









29

Figure 12


-10-505

101520253035

Estonia

Latvi

a

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30

Figure 13


-15

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32

Figure 14


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)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 12


-10-505

101520253035

Estonia

Latvi

a

Lithu

ania

Czech

Rep

ublic

Hungary

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epub

lic

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Portug

alSpa

inNCU

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in p

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30

Figure 13


-15

-10

-5

0

5

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15

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31






























32

Figure 14


0123456789

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inAver

age

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al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 13


-15

-10

-5

0

5

10

15

Lithu

ania

Latvi

a

Estonia

Poland

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epub

lic

Hunga

ry

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Rep

ublic

Slovenia

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al

Spain




















31






























32

Figure 14


0123456789

Lithu

ania

Latvi

a

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Poland

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ry

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Rep

ublic

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ia

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Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices































32

Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Figure 14


0123456789

Lithu

ania

Latvi

a

Estonia

Poland

Slovak

Rep

ublic

Hunga

ry

Czech

Rep

ublic

Sloven

ia

Greece

Portug

alSpa

inAver

age

annu

al c

hang

e (in

)














the region

Table 4



33























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices
























34

6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


6 Conclusions

























leagues





35








References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices









References


36


McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices



McGraw-Hill)




223ndash251




























37




Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices





Vol CX No 4 pp 1127-1170




Murray)





Journal 58 163-184







Appendices

Appendix 1


38





1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices






1994 16597 12985 0994 0553 1995 15500 12536 0990 0553 1996 15747 12832 0981 0553 1997 16135 13282 0956 0553 1998 16593 13718 0950 0552 1999 17066 14205 0960 0555 2000 17663 14764 0948 0554 2001 17942 15018 0929 0549 2002 18067 15209 0912 0542 2003 18188 15414 0883 0542 2004 18493 15786 0866 0541 2005 18712 16118 0839 0522


Appendix 2



Latvia 0944 -0735 0270 0482 Estonia -0023 -0358 0187 -0120





Spain 1228 0541 0748 2487 SE4 average 0326 -0019 0713 1241


39

1 Introduction























6 Conclusions

References

Appendices


Convergence of GDP per capita in EU25 - DiVA...

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