Luis Servén The World Bank ECLAC January 2005 Latin America’s infrastructure gap: a macroeconomic...
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Transcript of Luis Servén The World Bank ECLAC January 2005 Latin America’s infrastructure gap: a macroeconomic...
Luis ServénThe World Bank
ECLACJanuary 2005
Latin America’s infrastructure gap: a macroeconomic perspective
1. The changing policy framework
2. The infrastructure gap
3. The output cost
4. The lessons
Plan
• Until the 1970s, the public sector dominated infrastructure provision in both industrial and developing countries.
• Since the 1980s (earlier in Chile and the UK) Latin America led the worldwide drive towards opening up of infrastructure to private initiative – in various forms and extents.
• The drive was propitiated by a hardening of fiscal discipline in response to financial instability and macroeconomic crises
• In most countries, the fiscal retrenchment led to a sharp contraction of public infrastructure investment (similarly to the post-Maastritch fiscal adjustment in the EU)
The changing policy framework
Latin America: Public Investment in Infrastructure(weighted average of 7 countries, percent of GDP)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
%
Total Roads plus Rails Power Water Telecommunications
Note: 7 Latin America countries, ARG, BOL, BRA, CHL, COL, MEX, PER.
The changing policy framework
Latin America’s fiscal adjustment: Contribution of consumption and investment
The changing policy framework
Public infrastructure investment
(1)
Public consumption
(2)
Primary surplus
(3)
Public infrastructure investment
-(1)/(3)
Public consumption
-(2)/(3)
Argentina -2.87 8.22 (a) 6.23 0.46 -1.32
Bolivia -2.48 2.38 6.15 (b) 0.40 -0.39Brazil -2.57 9.97 4.12 0.62 -2.42Chile -1.38 -2.51 0.73 1.89 3.45Colombia -0.59 11.30 3.50 0.17 -3.23Mexico -2.20 1.31 5.24 0.42 -0.25Peru -1.43 0.53 0.68 2.10 -0.78
Source: Calderón and Servén (2004b).
Contributions to fiscal adjustment
Changes between 1980-84 and 1999-2001 (percent of GDP)
Latin America: Private Investment in Infrastructure(weighted average of 7 countries, percent of GDP)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
%
Total Roads plus Rails Power Water Telecommunications
Note: 7 Latin America countries, ARG, BOL, BRA, CHL, COL, MEX, PER.
The changing policy framework
The changing policy framework
Latin America: Total investment in Infrastructure
(weighted average of 7 countries, percent of GDP)
The changing policy framework
Latin America: Total investment in Infrastructure
(6 major countries, percent of GDP)
Latin America: Investment in Infrastructure (public + private) (weighted average of 7 countries, percent of GDP)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
%
Total Roads plus Rails Power Water Telecommunications
Note: 7 Latin America countries, ARG, BOL, BRA, CHL, COL, MEX, PER.
The changing policy framework
The private sector response
• Private initiative surged in the 1990s -- but with diversity across industries (and countries)
• Strong response in telecommunications, much less in transport.
• Evidence of public-private complementarity, not only substitution: countries maintaining higher public investment attracted more private investment (Chile, Bolivia, Colombia)
• The rise in private investment was not enough for asset accumulation to keep up with other world regions
• The investment fall contributed to widen Latin America’s infrastructure gap – in terms of quantity and quality -- widened over the 1980s and 1990s
The changing policy framework
Capacity change
Investment
Brazil: the power sector
The changing policy framework
The infrastructure gap
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1980 1985 1990 1995 2001
Power Generation Capacity(megawatts per 1,000 workers, Medians by Region)
LAC (19) EAP7 (7) MIDDLE (64) IND (21)
The infrastructure gap
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1980 1985 1990 1995 2001
Road plus Railway Length(km per area, Medians by Region )
LAC (19) EAP5 (5) MIDDLE (53) IND (21)
The infrastructure gap
0
500
1,000
1,500
2,000
2,500
3,000
1980 1985 1990 1995 2001
Total Telephone Lines(lines per 1,000 workers, Medians by Region)
LAC (19) EAP7 (7) MIDDLE (64) IND (21)
The infrastructure gap
0
1
2
3
4
5
6
LAC (11) EAP7 (7) MIDDLE (27) IND (24)
Figure 2.17. Overall Infrastructure QualityMedians by region and income level, 2000
Question: The quality of the infrastructure is among the best in the world (1=strongly disagree; 7 =strongly agree).Source: World Competitiveness Report.
Perceived infrastructure quality
(Medians by region, 2000)
Why do we care about infrastructure ?
• The availability and quality of infrastructure services is key for productivity and profitability
• Robust association between infrastructure availability and aggregate output / growth within and across countries
• Partly driven by reverse causality (growth encourages demand for infrastructure services)
• But there is broad agreement that infrastructure development has a strong causal effect of on economic development.
• Evidence that infrastructure development helps reduce income inequality – makes it easier for the poor to access economic opportunities, jobs, health and education.
The output cost
Infrastructure Stocks and Economic Growth (1960-2000)
ZWE
ZMB
ZAF
VEN
USA
URYUGA
TZA
TWN
TUR
TUN
TTO
THA
SYRSWE
SLV
SLE
SGP
SENRWA
ROM
PRY
PRT
POL
PNG
PHLPER
PANPAK
NZLNPL
NORNLD
NICNGA
NER
MYS MUS
MRT
MLI
MEX
MDG
MARLKA
KOR
KEN
JPN
JOR
JAM
ITAISR
IRN
IRL
IND
IDN
HUN
HND
HKG
GTM
GRC
GNB
GIN
GHA
GBRFRA
FIN
ETH
ESP
EGY
ECUDZA
DOM
DNKDEU
CYP
CRICOL
CIV
CHN
CHL
CHE
CAN
BWA
BRA
BOL
BGDBFA
BELAUT
AUS
ARG
y = 0.0056x + 0.0206
R2 = 0.2547
-2%
-1%
0%
1%
2%
3%
4%
5%
6%
7%
8%
-4 -3 -2 -1 0 1 2 3
Index of Infrastructure Stocks (1st. Principal Component)
Gro
wth
Ra
te o
f G
DP
pe
r c
ap
ita
Source: Calderón and Servén (2004b)
Infrastructure accumulation and growth (1960-2000 country averages, percent)
y = 0.505x + 0.0006R2 = 0.3253
-3%-2%
-1%0%1%2%
3%4%5%
6%7%
-2% 0% 2% 4% 6% 8% 10%
Growth in infrastructure stocks per worker
Gro
wth
in
GD
P p
er
wo
rke
r
Rest lac eap7
Source: Calderón, Easterly and Servén (2003)
Infrastructure Stocks and Income Inequality (1960-2000)
ZWE
ZMBZAF
YSR
VEN
USA
URY
UGATZA
TWN
TUR
TUN
TTOTHA
SWE
SLV
SGP
SEN
RWAROM
PRY
PRT
POL
PNGPHL
PERPAN
PAK
NZLNOR
NLD
NGA MYS
MUS
MEX
MDG
MARLKA
KOR
KEN
JPNJOR
JAM
ITA
ISR
IRN
IRL
INDIDN
HUN
HND
HKG
GTM
GRCGHA
GBR
FRA
FIN
ETH
ESP
EGY
ECUDOM
DNKDEU
CYP
CRI
COL
CIV
CHN
CHL
CHECAN
BWA
BRA
BOL
BGR
BGD
BFA
BELAUT
AUS
ARG
y = -0.0303x + 0.403
R2 = 0.2157
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
-4 -3 -2 -1 0 1 2 3
Index of Infrastructure Stocks (1st. Principal Component)
Gin
i Co
eff
icie
nt
(0-1
)
Source: Calderón and Servén (2004b)
• What is the contribution of infrastructure services to aggregate output and/or its growth rate ?
Three main empirical approaches in the literature:
1. Empirical growth models
2. Augmented production (or cost) function
3. VARs
Caveats:
-- technical problems often severe (identification / reverse causality, spurious regressions…)
-- all else equal: the costs of “getting there” are not explored – large tax rises or cuts in other expenditures that may have an output cost…
The output cost
The long-run growth approach:
• Adding infrastructure into a standard growth regression
• Infrastructure usually proxied by telecommunications indicators (e.g., Easterly 2001, Loayza et al 2003)
Calderón and Servén 2004b: panel of 100+ countries, 40 years
Consider both infrastructure quantity and quality
Synthetic infrastructure indicator: first principal component of {power, roads, telecom} – accounts for 80% of their variance.
Endogeneity: identification via GMM-IV with (a) internal instruments; (b) demographic variables
Growth contribution of infrastructure quantity and quality is statistically and economically significant.
The output cost
The output cost
Source: Calderón and Servén 2004b
Additional growth in LAC countries due to increased infrastructure development
The augmented production function approach:
• Unlike VARs and growth regressions, it is a structural approach
Y = F (K, H, Z); K = physical capital; H = human capital (often omitted) ; Z = infrastructure capital (power, phone lines, roads)
• Productive services assumed proportional to asset stocks
• In actual data, Z often is already included in K: The coefficient on Z captures the return differential on Z over K
• In addition to usual reverse causality problem, spurious correlation problem when using time series: nonstationarity of Y, K, Z leads to huge infrastructure coefficient estimates (Aschauer 1990)
The output cost
The augmented production function approach
Calderón and Servén 2005: panel time-series estimation for 90 countries, 40 years.
• Spurious regression problem does not arise here (due to large N)
• Only one long-run relation found – resolves identification problem
• Pooled and country-specific estimates – permit assessing heterogeneity across countries / regions
• Synthetic index and disaggregated infrastructure assets
• Results broadly similar to Calderón, Easterly and Servén 2003 – in spite of very different approach (GMM-IV to deal with identification; first-differencing to deal with nonstationarity)
The output cost
Estimated (log) infrastructure coefficients
(DOLS estimates, 1960-2001, synthetic index)
The output cost
Source: Calderón and Servén 2005
Coefficient S.E.
Pooled 0.091 0.013
Country-specific: mean by group
All (89 countries) 0.130 0.019
Industrial (21) 0.080 0.027
Developing (68) 0.145 0.024
Country-specific estimates[Synthetic Infrastructure Index, GLS--PIC (1,1)]
0
5
10
15
20
25
30
35
40
<-0.20
-0.10 0.00 0.10 0.20 0.30
The output cost
Source: Calderón and Servén 2005
• The estimated return on infrastructure assets is significantly higher than that on other physical capital in the vast majority of countries.
• Infrastructure has significantly lower returns than other capital only in 3 out of 89 countries [none in LAC]
• Across LAC countries, some heterogeneity too:
The differential return on overall infrastructure is significantly higher than average in Peru, Mexico, Colombia…
Differences also across assets – e.g., the differential return on power generation capacity is significantly lower than average in Paraguay, but higher in Brazil
The output cost
Estimated (log) infrastructure coefficients(DOLS estimates, 1960-2001)
The output cost
Electricity Generation
CapacityRoads
Main Telephone
Lines
Pooled DOLS 0.074 ** 0.060 ** 0.046 **0.018 0.022 0.015
Country-specific: means by Group
All (89 countries) 0.115 ** 0.104 ** 0.052 **0.022 0.042 0.026
Industrial (21) 0.120 ** 0.135 * -0.0160.030 0.070 0.038
Developing (68) 0.113 ** 0.094 * 0.073 **0.027 0.051 0.032
Source: Calderón and Servén 2005
The output cost
Source: Based on Calderón and Servén 2005
The cost of the widening infrastructure gap: EAP vs LAC
Avg. 1991-00 vs. Avg. 1996-00 vs.Avg. 1981-90 Avg. 1981-85
1. Change in relative infrastructure endowments (%)
Main Phone Lines 27.6 41.1Electricity Generating Capacity 37.9 58.0Roads 30.3 50.3
2. Change in Relative GDP per worker (%) 31.6 41.9
3. Contribution of the infrastructure gap 9.3 14.5
4. Relative contribution (as % of [2]) 29.2 34.7
(1) Fiscal adjustment, as commonly measured and enforced, tends to have an anti-investment bias
• One (not the only) major factor is the use of inappropriate fiscal rules targeting liquidity, the cash deficit and gross public debt – rather than solvency and net worth, which are key to fiscal sustainability.
• Infrastructure projects have a negative short-run liquidity effect -- it takes time to build the assets and get the returns.
• The focus on fiscal liquidity discourages such projects – even if they are consistent with good public economics; i.e., they enhance solvency.
The lessons
(2) Infrastructure investment cuts represent an inefficient fiscal adjustment strategy
• The direct effect of the spending cut is to raise liquidity and public sector net worth
• But there is an opposing indirect effect: less infrastructure means less output and lower fiscal revenues tomorrow
• The indirect effect offsets partly the direct effect – and can even make fiscal adjustment self-defeating.
The lessons
Summary
• Latin America’s infrastructure gap widened in the 1980s and early 1990s, at a substantial cost in terms of output and productivity.
• A major factor in the process was the investment slowdown – caused by a public investment decline not offset (except in telecom) by private sector participation.
• The public investment compression reflected a biased and inefficient fiscal adjustment, encouraged by rules targeting liquidity and debt rather than solvency and net worth.
• Ensuring adequate room for productive spending requires fiscal rules that reconcile solvency and growth.
End
The changing policy framework
Fiscal discipline has led to a public investment fall not only in developing countries – also in the EU
• The fiscal targets imposed in the Maastritch Treaty contributed to a decline in public investment across Europe:
• Out of 9 countries exceeding the Maastritch deficit limit in 1992, 8 met it in 1997. Public investment had fallen in all 8 !
• Infrastructure investment fell along with the total
Fiscal adjustment and public investment(average of 9 EU countries, percent of GDP)
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
% G
DP
-6
-5
-4
-3
-2
-1
0
1
2
3
% G
DP
Transport Investment, mean (left scale)
Primary Deficit, mean (right scale)
Sources: World Development Indicators - World Bank; and provisional data from ECMT.Notes: (a) Total = Roads + Rails + Airports. (b) 9 EU countries: Austria, Finland, France, Netherlands, Norway, Portugal, Spain, Sweden and United Kingdom.
The changing policy framework