Published by THE UNIVERSITY OF MANCHESTER SOCIETY FOR FINANCIAL STUDIES

UNDERGRADUATE JOURNAL OF

Economics

Volume 1 June 2016

ARTICLES

DAVID FARKAS

ECB Interest Rate Cut and QE Policy Analysis Using IS-LM and

AD-AS Models

MICHALIS PAPACOSTAS

Neo-Classical and Post-Keynesian Explanations of Financial Crisis

of 2007-08

ZHONGJIU LU

Analysis of Migration in the United Kingdom

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Disclaimer:

The Undergraduate Journal of Economics is an annual, non peer-

reviewed journal published by the University of Manchester Society for

Financial Studies.

The author of each article in this journal is solely responsible for the

content thereof; the publication of an article does not constitute any

representation by the Society. Authors are responsible for following

conventional research ethics. The Society is not responsible for the

breach of any law.

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ECB Interest Rate Cut and QE Policy Analysis Using

IS-LM and AD-AS Models

David Farkas

After Eurozone is experiencing low and falling inflation rate the European Central Bank (ECB)

decided to introduce a zero-interest rate policy by cutting the nominal interest rate to 0.05% that

is so close to zero the effects of the decision can be treated the same as it would be a zero bound

rate. In addition the launch of purchasing asset-backed security (ABS) was also announced at a

press conference at Frankfurt on 4th September 2014. The first policy change keeps the base rate

at zero per cent to stimulate demand in the economy, as the supply of money is getting cheaper

that makes investment level to increase. In addition the quantitative easing is a suitable policy

when the interest rate is close or equal to zero. The aim of this is also increasing income level by

creating new money for the economy. After a short introduction to the models, the essay will

explicate this phenomenon and the possible short- and long-run outcomes using the IS-LM and

AD-AS models. Beside these alternative actions will also be presented after the analysis.

The IS-LM model was constructed by Sir John Hicks, and it reformed the older fragmented

models, because the short-run equilibrium in this model is the combination of r (interest rate) and

Y (income, output) that satisfies equilibrium conditions in both the goods and money markets.

The goods market is represented by the IS curve, that is derived from the Keynesian cross model

(by John Maynard Keynes), which uses expenditure to determine income. The IS curve is the

graph of all combinations of r and Y, which result in equilibrium. The curve is negatively sloped,

so a decrease in the interest rate motivates companies to boost investment spending that results in

increased total spending (E). To return to equilibrium position output (Y) had to be increased.

The LM curve represents the money market, and it is derived from the Theory of Liquidity

Preference (also by John Maynard Keynes) that is a simple model where money supply and

money demand determines the interest rate. LM curve is the graph for all the combinations of r

and Y that equate the supply and demand for real money balances. This curve has a positive

slope, so money demand is raised by an increase in income. Therefore as the supply of real

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money balances is fixed, this creates excess demand in the money market. To restore equilibrium

interest rate must rise. If we plot these together there will be an equilibrium point that represents

a short-run equilibrium in both markets.

However, if long-run also has to be analysed, that means price level (P) is not fixed any more,

and to show the relationship between P and Y we need the AD (aggregate demand) curve. This is

a downward sloping curve, which is caused by the wealth and the substitution effects. Wealth

effect simply means, if real wealth is higher, spending is increased, so the real GDP demand

increases as well. The level of real wealth is depending on the price level. On the other hand the

substitution effect has two sides. First, the intertemporal substitution effect that states that a price

level rise results in a decreased real value of money and raised interest rates, which makes people

borrow and spend less, so the quantity of real GDP demanded decreases. Second, the

international substitution effect that means, if the price level rises, the price of domestic products

will also rise, therefore imports will increase, while exports decrease. This result in a decrease of

real GDP demanded. In addition to the AD curve this model has the AS (aggregate supply) curve

as well. In the long run, Ȳ (full employment) does not depend on the price level, so LRAS is

vertical. On the other hand in a short-run situation, the many prices are fixed, so for the model

we assume that all of them are fixed, and companies are willing to satisfy demand at a given

price level. In this case the SRAS curve is horizontal, as price level is not dependent on Ȳ. On

the other hand the long run effect should always be derived from short run events. Namely if real

GDP is higher than nominal GDP, then price level will rise, but if it is lower, then the price level

will also fall.

Therefore to analyse the long-run effect of the policy changes made by ECB, the short-run has to

be observed first using the above basically introduced IS-LM model.

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Figure 1

Figure 2

In Figure 1 the effect of the interest rate cut can be seen. When r is reduced from r1 to r2 (1) that

means the cost of borrowing decreases so people and firms in the economy will borrow more,

that makes the money supply (M) to increase. As a result of this the LM curve shifts to the right

or shifts down (2) from LM1 to LM2. As the IS curve is not affected by this policy change, the

equilibrium point also moves along the IS curve from point A to B, and this results in a new

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equilibrium income level (3). In this case Y2 is higher than Y1, which was the initial aim of the

policy change. Therefore according to this model the policy should achieve the desired effects in

the short run.

The ECB also announced an increase in spending, so called quantitative easing that is aimed to

have a double positive effect. First, in Figure 2 we can see how this policy change increases the

income level as well. As the spending level increases, the IS curve shifts to the right (1). This

makes both the interest rate (2) and income level (3) to increase. As we can see the shift of the IS

curve is bigger than the increase of Y that is caused by the effect of the increased interest rate (r).

As IS curve shifts money demand is increased, this increases r, but this reduces investment level,

therefore the increase in Y is smaller than the initial shift of the curve. As a result, a new

equilibrium point is made, by moving along the LM curve from A to B. The second advantage of

this policy is that it makes the interest rate to increase, which makes it a perfect supplemental

policy to the interest rate cut. While boosting output forward it restores r near its initial level,

which is really important as the interest rate has a zero bound, which means it cannot be lowered

at a certain point, because the real rate cannot be lower than zero. In the literature quantitative

easing is identified divisively. In a zero bound situation the central bank might be powerless to

have an effect on the economy any more. Japan is a good example of this. However the situation

has a lot more factors to consider that can result in that the policy will have positive effects, so

there is a general irrelevance proposition for open-market operations (Eggertsson, Woodford

2003). They also point out that it should not be used aiming to have a direct effect, but much

more as a supplement policy, in the way ECB has used it. Thus according to the IS-LM model

short-run effects are promising, but our basic assumption of a fixed price level was needed to

reach these results.

In reality prices are never fixed, and the main difference between short and long run is the

gradual adjustment of prices. As described above the higher real income level in the short-run

results in rising price-level over time.

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Figure 3

Figure 4

As Figure 3 shows as the IS-LM model effects happen (1. interest rate cut, 2. LM curve shift) the

aggregate demand curve also shifts to the right (3), as the demand for real money balances

increase at the given price level. This makes price to increase in the long run (4), as the long run

equilibrium moves along the LRAS (long-run aggregate supply) curve. As a result of higher

prices the investment level decreases, which makes the SRAS curve to move up to the new

equilibrium point. As we can see the economy moves towards equilibrium, which is at the initial

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income level in this case, so as a final result the IS curve also shifts left into the equilibrium

position resulting in a same level of output at a lower level of interest rate.

Similarly the long-run effect of quantitative easing is an increase in price level. In Figure 4 we

can see the short-run IS-LM model (1. IS curve shift, 2. interest rate increase). As the real

income level is higher in this situation again the price level will rise in the long-run, as a result of

the AD curve shifting to the right. Similarly to Figure 3 the SRAS curve also shifts up over-time.

On the other hand in the upper section LM curve shifts to the left over-time to reach the new

equilibrium at the initial income level but at an increased interest rate. After the long-run is also

considered we can see that QE is once more a supplement policy that is countervailing the

interest rate cut, by increasing it in the long run as well. However the overall effect of the policy

changes is not as promising as in the short-run. Without the economy answering positively to

these policy changes both long-run equilibriums are shifting back to the initial level of income,

while the aim was to boost the economy.

Figure 5

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Figure 6

Therefore there is also a possibility that these theoretically must-do policies, actions will not take

the desired effect, as they did not achieved aimed improvements in many places before. The best

known example for this situation might me Japan, where after the central bank introduced these

policies the country sank into a liquidity trap (Krugman, 1998) in the beginning of 2000s.

According to the model this can also happen with sticky and flexible prices, the reason for this

can be seen in Figure 5 and Figure 6, which were also presented by Krugman in a different paper

in 2000. The theory states that in a near zero interest rate situation demand for money becomes

more or less infinitely inelastic that results in a flat section of the LM curve. In this case policies

shifting the LM curve become completely useless, as even the curve shifts the interest rate will

not change. Figure 6 shows the same situation derived to the AD-AS model, where the above

mentioned situation results in a horizontal section of the AD curve, causing the same situation as

above. Thus the only way out is taking further actions and use alternative policies if needed, to

solve the initial problem of the setback of the economy. A suitable solution at low or zero-bound

interest rates can be shaping the interest rate expectations. (Bernanke and Reinhart, 2004) This

can either be conditional or unconditional. Conditional effort would be a promise to hold short-

term interest rates low until a given calendar date. Additional easing would result from

lengthening this period. Alternatively a conditional policy commitment would link the length to

certain economical conditions. Obviously these actions only work if the promises are credible,

otherwise the economy would react unexpectedly or harmfully to the announcements. This

method was also used in Japan, after the interest rate reached zero. They promised to keep the

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rate at zero while the economy is in deflation, but more recently they have detailed the

conditions more that extended the low rate period. Although this action is not a traditional

monetary of fiscal policy tool, it generally means fixing the interest rate (r) at the lowered level.

Figure 3 shows that, in the long run IS curve would not shift back to equilibrium, which would

result in an extended time period at the increased level of output.

After analysing the policy changes using the IS-LM and AD-AS models, we can state that ECB

has done the theoretical must-do in this situation. Lowering the interest rate and applying QE in

addition is one of the most commonly used policies, and according to the analysis they definitely

have positive effects in the short-run, and if the response is positive long-run effects can also

maintain the gained improvements. However these methods do not always work in real life that

was introduced through the example of Japan, where the economy is still not in desirable state.

On the other hand the Euro is not in the same state as the Yuan was. Some argue that the

Eurozone is much more in a savings trap as in a liquidity trap. However, comparing the Euro to

other one nation currencies might not be totally precise in this situation, as there are many more

environmental factors as a result of the fact that the Euro is used in several countries of Europe.

According to several academic papers there is no guarantee that the policy will or will not work,

it all depends on the actual environment and the response of the economy to the policies. In this

case the environment is not really supporting, as many economists are not optimistic about the

quantitative easing programme according to a Financial Times poll. Also the upcoming elections

in three main countries, involving Greece, most probably will give at least one eurosceptic party

power, which can withdraw expectations about the improvements in the Eurozone.

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References

BERNANKE, B. S. & REINHART, V. R. 2004. Conducting Monetary Policy at Very Low

Short-Term Interest Rates. The American Economic Review, 94, 85-90.

BERNANKE, B. S., REINHART, V. R. & SACK, B. P. 2004. Monetary Policy Alternatives at

the Zero Bound: An Empirical Assessment, Finance and Economics Discussion Series Divisions

of Research & Statistics and Monetary Affairs Federal Reserve Board.

EGGERTSSON, G. B. 2011. What Fiscal Policy Is Effective at Zero Interest Rates? . NBER

Macroeconomics Annual 2010, Volume 25. University of Chicago Press.

FINANCIAL TIMES (2015) Lexicon: Definition of zero interest rate policy zirp [Online]

Available from: < http://lexicon.ft.com/Term?term=zero-interest-rate-policy-zirp> [Accessed:

7th January 2015].

FINANCIAL TIMES.(2015) Lexicon: Definition of quantitative easing [Online] Available from:

<http://lexicon.ft.com/Term?term=quantitative-easing> [Accessed: 7th January 2015].

FINANCIAL TIMES (2015) Economists sceptical ECB bond-buying would revive eurozone

[Online] Available from: <http://www.ft.com/cms/s/0/3496a4fa-91aa-11e4-bfe8-

00144feabdc0.html?siteedition=uk#axzz3OKWBHMrG> [Accessed: 4th January 2015].

FINANCIAL TIMES (2014) Fears for fresh Greek crisis after poll called [Online] Available

from: <http://www.ft.com/cms/s/0/e1df99a2-8f46-11e4-b080-

00144feabdc0.html#axzz3OKWBHMrG> [Accessed: 5th January 2015].

FINANCIAL TIMES (2015) A critical few weeks for the eurozone [Online] Available from:

<http://blogs.ft.com/gavyndavies/2015/01/07/gavyn-davies-a-critical-few-weeks-for-the-

eurozone> [Accessed: 7th January 2015].

FUJIKI, H. & SHIRATSUKA, S. 2002. Policy Duration Effect under the Zero Interest Rate

Policy in 1999–2000: Evidence from Japan’s Money Market Data Monetary and

Macroeconomic Studies, January, 1-31.

KRUGMAN, P. 2000. Thinking About the Liquidity Trap. Journal of the Japanese and

International Economies, 14, 221-237.

KRUGMAN, P. R. 1998. It's Baaack: Japan's Slump and Return of the Liquidity Trap Brookings

Papers on Economic Activity, 2, 137-205.

SOCIAL EUROPE (2014) Europe Must Escape A Savings Trap, Not A Liquidity Trap [Online]

Available from: < http://www.socialeurope.eu/2014/07/savings-trap> [Accessed: 9th January

2015].

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SVENSSON, L. E. O. 2003. Escaping from a liquidity Trap and Deflation: The foolproof way

and others, National Bureau of Economic Research. 1-22

13

Neo-Classical and Post-Keynesian Explanations of

Financial Crisis of 2007-08

Michalis Papacostas

The financial crisis of 2007 has been characterized as the worst since the Great Depression of

1930. The outbreak of the crisis has evolved debates between different economic schools of

thought. Indeed the crisis itself acted as a criticism of the mainstream Neo-Classical economic

theory and has strengthened the position of previously neglected theories like Post-Keynesians’

alternative theory.

Neo-Classical economics has developed as the mainstream economic theory after the ‘marginal

revolution’. Publications of Neo-Classical economists such as Walras, Jevons and Menger grew

into becoming essential guidelines for economics teachings around the globe. Post-Keynesians

on the other hand base their theory on the ideology of Keynes which is presumed as not well-

presented by other new Keynesian theories. This alternative theory has grown in importance

since the financial crisis as its criticisms of mainstream theory have become more meaningful.

A clear distinction between the two theories arises in the nature of the models used. Neo-

Classicals focus on optimization problems facing individuals while Post-Keynesians, determine

the “flow of funds, the stocks of credit and debt and the systematic risks implied in them”

(Bezemer, 2009, p.27). This emphasises the main difference of Neo-Classical’s study of

equilibrium and Post-Keynesians’ disequilibrium. The latter “rejected the argument

macroeconomics could be derived from microeconomics” (Keen, 2013, p.231) emphasizing their

belief of consumer interdependence and their opposition to mainstream’s optimization. Through

Keynes, Post-Keynesians imply “firms are in a state of uncertainty” (Bezemer, 2009, p.27)

which conflicts the mainstream theory’s assumption of known behaviour equations of costs and

revenues. Moreover, Post-Keynesians through their accounting models differentiate the financial

sector and its shocks from general shocks and its absence in mainstream models. These

fundamental differences have caused an endless disagreement regarding the explanation of the

crisis. An analysis of these differences follows which is focused on opposing views on the

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money supply, budget deficits, production variances, debt, role of equilibriums and the role of

governments.

A fundamental difference between the Neo-Classical and Post-Keynesian schools is their

perception of the money supply and what causes its activity. Neo-Classicals state that money

supply is exogenously determined by the quantity of credit money in existence.They state that

the base money supply is determined by the Central Bank and that credit money follows by the

Central Bank controlling the quantity of both loans and deposits. As Moore illustrates, this

theory, called the money multiplier, implies “banks act simply as intermediaries, lending out the

deposits that savers place with them” (Moore, 1988, p.2). Neo-Classical thought implies that in

order for firms, to borrow money, they need to have savings which Banks will use to finance

requested loans. Mainstream theory suggests responsibility for the financial crisis to Central

Banks as in their opinion they are accountable for controlling the amount of loans, deposits and

reserves in a bank’s balance sheet. Neo-Classicals claim that Central Banks like the FED

increased the fragility of the economy by encouraging over-lending from the low interest rates.

Contradicting this theory, according to Moore, Post-Keynesians believe that “the money supply

is endogenously determined by market forces” (Moore, 1988, p. 384). The essence of this

argument is their belief of banks not simply being intermediates but actually being the creators of

deposit money by responding to the demand of money from bank borrowers. “Commercial

Banks create money in the form of bank deposits by making new loans” (McLeay, Radia and

Thomas, 2014, p.16). This contradicts the mainstream view that banks can only lend out pre-

existing money.The alternative approach uses the theory of Schumpeter who argued investment

is not financed by savings. Post-Keynesians believe that if Banks will be profitable from a

lending procedure they will indeed create money regardless of savings, therefore rejecting

mainstream models like the IS/LM.As Minsky states “money supply has a linear proportional

relation to a well-defined price-level” (Minsky,1992, p.6). This counteracts directly with the

quantity theory of money from the Neo-Classical thought as it validates the innovative nature of

banking and finance that enhances money supply and invalidates the claim that investment relies

on savings. Post-Keynesians insist that the Central Bank’s monetary policy can influence the

banking system’s lending only through interest rates. Interest rates influence directly the

profitability of banks’ lending and therefore affect the level of money creation. Post-Keynesians

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believe that it is the perception of fallen risks of household loans that expanded lending from

banks rather than the actions of the Central Bank (McLeay, Radia and Thomas, 2014).

One may argue that schools of thought use their explanation of the money supply to justify the

financial crisis. Neo-Classicals believe that Central Banks should be criticized as the excessive

creation of loans was implemented from their control of money. Post-Keynesians recognize the

significance of the Central Banks’s monetary policy through setting interest rates but identify the

banking industry’s excessive lending as an independent variable arising from low risk

expectations.

Another main area of debate would be the explanation of the crisis specifically within the

Eurozone. There is a clear argument about whether budget deficits in many European countries

were the cause or the effect of the financial crisis. The mainstream approach “is that the crisis

is fiscal in nature, resulting from financial profligacy of governments of deficit countries in the

periphery”(Blankeburg et al, 2013, pp.463-477). Neo-Classicals use examples like Greece to

emphasise the importance of budget deficits in creating the financial crisis. As Priewe explains

“In Greece, the public deficit was prior to the crisis unsustainably high” (Priewe, 2011, p.5)

emphasising the Neo-Classical view that the countries that suffered the most had withstanding

deficits prior to the crisis which government were unable to deliver.

Post-Keynesian explain that the explanation of the crisis only through fiscal deficits does not

present the whole picture. They suggest that “budget deficits are inevitable and emerge as a

favourite cause of the crisis itself” (Caldentey, 2012, p3). Caldentey and Vernengo convey that

gaps between government revenue and expenditure widened because of the automatic stabilizers

to mitigate the crisis and therefore fiscal budgets should be treated as a result of the crisis than a

cause (Caldentey, 2012). Dejuan, Febrero and Uxo conclude that many countries which suffered

from deep recessions had similar fiscal deficits to core countries which did not suffer that much.

This signifies their disagreement with the mainstream approach of fiscal deficits being a direct

cause of the crisis and their belief that “the current euro crisis is rooted in earlier private deficits

and current account imbalances” (Dejuan, Febrero and Uxo, 2013, p.30). Identifying historical

data allows Post-Keynesians to show that countries like Spain and Ireland experienced huge

private and current account deficits which caused the rise of fiscal deficits aiming to tackle them.

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This illustration allows them to claim that the fiscal deficits were simply the result of actions

performed to resolve the real causes.

Post-Keynesians value private and current account deficits as an important cause of the crisis,

directly related to the asymmetry in competitiveness within the Eurozone. Perez-Caldentey and

Vernengo identify that unit labour costs for non-core European countries rose by 24% while in

core countries only by approximately 7%. This enabled core countries according to Post-

Keynesians to implement ‘beggar thy neighbour’ policies, gaining comparative advantages over

peripheral countries. As Perez-Caldentey and Vernengo state, this acted as a devaluation for core

countries enabling them to “pursue export-led growth policies” (Perez-Caldentey and

Vernengo2012, p.19) by enjoying surpluses at the expense of non-core countries. In agreement,

Priewe illustrates that “in Germany lower unit labour costs growth grants competitive

advantages” (Priewe, 2011, p.9). An important reason for non-core countries’ poor economic

conditions was the inability to compete with core-countries, especially because of the restriction

imposed by the fixed currency, therefore causing current and private deficits. This conflicts the

focus of Neo-Classicals purely on non-core countries’ budget deficits and their adverse handlings

from their governments.

Mainstream economics approach the financial crisis as a situation where reductions in

productivity were crucial. According to Ohanian “no large negative capital distortions”

(Ohanian, 2010, p.53) occurred before and during the recession, meaning that capital market

imperfections do not constitute the main cause of the recession. Furthermore, it is illustrated that

the initial cause was an event that triggered the “relationship between the marginal rate of

substitution between consumption and leisure and the marginal product of labour” (Ohanian,

2010, p.12). Via quantitative analysis, Ohanian is able to claim that variances of the labour

market are more distorted than variances of the capital market. In agreement, Mulligan states that

“we might think differently about monetary policy if it depressed the labour markets” (Mulligan,

2009, p.2). Neo-Classicals convey that economic policies such as the mortgage modification

programmes in the USA triggered higher income taxation. This acted as a barrier for working

incentives, shifting supply of labour relative to its demand and therefore damaging the

employment rate and productivity. This counteracts with Post-Keynesian view as it criticizes

heavily public policies and marginalises the focus on the capital market’s inefficiencies.

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The alternative theory suggests that capital accumulation is essential in understanding the

financial crisis. Stockhammer, Guschanski and Köhler support this view by undertaking an

econometric analysis which shows capital accumulation as more influential on unemployment

and economic downturn. In their view “labour market performance is driven by demand shocks,

most importantly by investment behaviour” (Stockhammer, Guschanski and Köhler, 2014, p.14).

Post-Keynesians oppose Neo-Classical claims of the importance of labour supply’s effect on

productivity and believe that public policies’ effects on incentives are not the main cause of

unemployment. “Labour supply behaviour does not matter to Post-Keynesians in determining

money wages and inflation” (Yellen, 1980 p. 18) and this is reflected in their focus on

investment as a main area of interest. This argument highlights the fundamental differences in

the theory of the two schools. The Neo-Classicals focus on the idea that frictions like public

policy disrupted the stable economy and Post-Keynesians focus on the flow of investment whilst

acknowledging labour markets are not necessarily well-behaved and the economy is not

necessarily stable.

Moreover, a fundamental difference between the two schools is their perception of the level of

importance of private debt. As Keen reveals, the Neoclassical perspective states that “lending

makes no difference to the level of aggregate demand” (Keen, 2012, p.4). Neo-Classicals imply

this because of their theory of money neutrality. They believe that changes in the price level are

not able to affect employment and output and therefore focus should be given only to supply side

shocks (Lucas, 1972). Mainstream economists reject the importance of debt since they relate it as

nominal debts which have no particular significance on real economic variables. This approach is

characterized as an ‘income-only perspective’ since Neo-Classicals focus mainly on change of

GDP while Post-Keynesians emphasise the importance of measuring the effect on asset markets

too.

Keen criticizes Neo-Classical theory as neglecting to understand the role of debt since “the level

of private debt has serious macroeconomic effects and plays a dominant role in asset prices’’

(Keen, 2012, p.5). Post-Keynesians base their theory mainly on Minsky’s publications. They

believe that “the general decline in risk aversion sets off growth in investment and asset prices

which is the foundation of its eventual collapse” (Minsky, 1992, p.5). The increased optimism of

investors triggered the same behaviour for the banking sector bringing a “euphoric Economy”

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(Minsky, 1992, p.5). Post-Keynesians adopt euphoric Economy as a state of the economy just

before the crisis. According to Keen this condition permits the development of Ponzi financiers

who benefit “by trading assets and incur significant debt in the process” (Keen, 2012, p.6).

Alternative theory explains that Ponzi financiers are very significant personalities that cause an

increase in the fragility of the system because of the large amounts or risks overtaken. Minsky

further analyses this claim as a natural continuation process where “over a protested period of

good times capitalist economies move towards dominated economies by Ponzi financiers”

(Minsky, 1992, p.8). This helps explain the financial crisis as the result of excessive risk and debt

taken from Ponzi financiers at a period where optimism and high economic growth where

enjoyed. Post-Keynesians believe that it is this good economic performance that decreased risk

aversion and brought rising debt and asset prices proving therefore that “stability is

destabilizing” (Keen, 2012,p.20).

Another area of key interest when assessing the financial crisis would be the interpretation of the

riskiness by financial institutions. Mainstream approach conveys that the misuse of mathematical

models within the banking industry constitutes a main cause of the recession. This contradicts

Post-Keynesians support on Minsky’s interpretation of riskiness arising from the structure of the

euphoric economy. The Neo-Classicals emphasize the adverse effect of the focus given on

mathematical models to measure the risk of underlying assets. As Stutzer illustrates, “the copula

presented limited tails under the assumption that defaults occur independently overtime”

(Stutzer, 2014, p.4). Neo-Classicals believe that models such as the Gaussian model neglected

the possibility that “if one company defaults then it is likely that other companies also default”

(Donnelli and Embrechts, 2010, p.15). Essentially, models treated defaults independently

therefore restricting forward thinking of an acceleration of defaults. The mainstream view is that

models were ignorant of the “importance of correlation and the possibility of price declines”

(Donnelli and Embrechts, 2010, p.15) and therefore were unable to give interpretations of

extreme events. An important reason for that was their reliance on the normal distribution to

estimate results making them unrealistic to account for unexpected results. Such simplistic

modelling meant that “few firms used valuation models for their exposure to super-senior

tranches” (Donnelli and Embrechts, 2010, p.27) which were assumed as risk free. Most firms

could not measure their liquidity risk as models mirrored their assumed risk-free position

regarding defaults but did not identify liquidity problems throughout the whole procedure. The

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mainstream view highlights the limitation of the models used, but as Donnelly and Embrechts

explain, “The problem is not that mathematics was used by the banking industry but was abused”

(Donnelly and Embrechts, 2010, p.2).

Expanding on this, mainstream theory believes the relationship between the state and the market

regarding risky securities as an important factor that determined the financial crisis. Griffin and

Tang performed an econometric model about CDOs and their eligibility to receive their ratings

and further adjustments (Griffin and Tang, 2012). Indeed, “the proportion of CDOs eligible for

AAA status under the CRA credit risk model exhibits a correlation of only 0.49” (Griffin and

Tang, 2012, p.1295). The analysis’ results prove that approximately half the CDOs were over-

rated by credit rating agencies. Griffin and Tang state that “CDOs that received larger

adjustments bear more risk of being downgraded” (Griffin and Tang, 2012, p.1313) showing that

further adjustments diluted the true value of CDOs and created further fragility in the market.

The research suggests the possibility of ‘cronyism’ and the interconnectedness between banks

and CRAs when pricing CDOs. Mainstream approach points out prices were not reflected from

the information available in the market but suggest they were disrupted by the relations of

institutions with rating agencies, reflecting biased pricing.

Post-Keynesians interpret the misuse of mathematical models resulting from the lack of

regulation and government intervention within institutions. This comes into direct conflict with

mainstream theory which “exhibits great confidence in the ability of free markets to deliver

stability and full employment” (Lavoie, 2011, p.52). Post-Keynesians, question whether markets

should be trusted as their inability to self-regulate and their flexible prices cause instability. This

is presumed from the alternative view as a trigger towards the recession. As Minsky conveys,

“the self-interest of bankers, levered investors, and investment producers can lead the economy

to inflationary expansions and unemployment” (Minsky, 1986, p.280). This is reflected from the

trend of adjustments in CDOs which highlights for Post-Keynesians the absence of control over

rating agencies and institutions. It is the fragility created from the lack of intervention that

heterodox theories presume as a direct cause of implemented dangerous strategies like CDOs

which inevitably caused the deep recession.

Contradicting Post-Keynesian focus on intervention Neo-Classicals interpret the economy as an

efficient system which will always move towards anequilibrium. Therefore, they try to explain

20

the recession by referring to market distortions of equilibriums. As Ohanian conveys,

“government policies contributed significantly to the recession” (Ohanian, 2010, p.16). Neo-

Classical literature believes that the stance of governments promoted uncertainty and was a

prime reason for the building up of the recession. Ohanian cites an analysis of sales by Taylor

and conveys that “data shows little immediate impact but sales begin to drop immediately

following the announcement of TARP” (Ohanian, 2010, p.61). Neo-Classicals signify the

negative effect of theory implementation towards public reaction. It is believed that public policy

promoted uncertainty within the economic system and acted as an important reason for lower

productivity since “higher uncertainty increases delaying decisions with fixed costs” (Ohanian,

2010, p.62). Policies affecting financial institutions have a dramatic influence on businesses and

Neo-Clacssicals believe that these policies forced many businesses to remain idle whilst waiting

for the results of such policies. Moreover, “household’s inability to infer the actual state leads

them to reduce market hours until they can deduce the state of the economy” (Ohanian, 2010,

p.62). The public, suffering from asymmetric information, was uncertain about the future and

was motivated to reduce its efficiency through working hours. This highlights directly the effect

of policy in increasing unawareness of the public and distorting the market by damaging

consumption and investment.

Furthermore, Neo-Classicals criticize government policies on their effects on financial

institutions. It is believed that policies during the time before the crisis promoted moral hazard

behaviours with increased risk-taking from financial institutions. According to Samwick

“government assistance inhibits financial institutions from working out their own affairs,

delaying the final resolution of the problem and further undermining confidence in financial

markets” (Samwick, 2009, p.139). Certain government policies, like assuring certain amounts on

deposits, acted as incentives for banks to continue dangerous activities without incorporating

insolvency and liquidity measures. Financial institutions had “a belief that the government would

not allow them to fail” (Donnelly and Embrechts, 2010, p.5). Mainstream theory points out that

the government`s involvement promoted the risky behaviour of financial institutions and their

certainty of rescue after potential unexpected circumstances. This high level of uncertainty is

said to have directly influenced both growth and prosperity.

21

Post-Keynesians disagree with the claim of moral hazard by emphasizing the importance of

government intervention. An acceptance is made that the market economy “can generate

insufficient aggregate demand to guarantee full employment” (Keynes, 1936, p.25). Post-

Keynesians argue that the government is responsible and capable of boosting the aggregate

demand especially when awaiting recessions in order to recover towards full employment.

Furthermore, Post-Keynesians believe that the incentive to increase risk arises from the “paradox

of tranquillity” (Lavoie, 2011, p.48) which states that “as time goes on, memories fade and

economic agents dare to take on higher levels of risk” (Lavoie, 2011, p.48). In an attempt to

justify the acts of governments, Post-Keynesians identify that risks are created not from policies

but from the beliefs and thinking of Ponzi financiers. Through the adaptation of Minsky’s theory,

the accusations towards government intervention are justified as attempting to “keep the

economy operating within reasonable bounds” (Minsky, 1992, p.9).

Concluding, one could argue that the theories developed by both schools of thought are

extremely valuable when assessing the financial crisis. The explanations provided originate from

the fundamental intuition behind each school. By taking into consideration both views a balanced

idea can be accumulated of how the global economy was not prepared for such a crisis and how

the future can be more promising. It is logical therefore to emphasise the benefits of the inclusion

of both theories within the economic world and especially their introduction within the youngest

population. One may argue that this could generate a more meaningful interpretation of the real

world that would assist future economic global issues in a more critical manner.

22

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the Eurozone Cambridge Journal of Economics.Cambridge Journal of Economics.[Online]

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its Remedies. [Online] London, New York: Routledge. Available from:

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keynesian+views+of+the+crisis+and+its+remedies&source=bl&ots=YBf2KMraj0&sig=PRj-

QioCkpIuPkiZFfUq6z2oFcg&hl=en&sa=X&ei=5P6zVL6UL8O4OvrogKgN&ved=0CD8Q6A

EwBA#v=onepage&q=post-

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December 2014].

DONNELLY, C. & EMBRECHTS, P. (2010) The Devil is in the Tails: Actuarial Mathematics and

the Subprime Mortgage Crisis. ASTIN Bulletin.[Online] 40(1).p.1-33.Available from:

http://www.macs.hw.ac.uk/~cd134/2010/donemb.pdf[Accessed: 17th

December 2014].

GRIFFIN, M. J. & TANG, Y. D. (2012) Did Subjectivity Play a Role in CDO Credit Ratings?The

Journal of Finance.[Online] 67 (4/8). p. 1293–1328. Available from:

http://www.sef.hku.hk/~yjtang/GriffinTang2012JF-

Subjectivity%20in%20CDO%20Ratings.pdf[Accessed: 17th

December 2014].

KEEN, S. (2012) Instability in Financial Markets: Sources and Remedies. INET Conference, Berlin

Instability in Finance Markets: Sources &Remedies. [Online] (4). p.1-23. Available from:

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19th

December 2014].

KEEN, S. (2013) Predicting the ‘Global Financial Crisis’: Post-Keynesian Macroeconomics.

Economic Record.[Online] Wiley Online Library, 89 (285/6).p.228-254. Available from:

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December

2014].

KEYNES, J. M. (1936) The General Theory of Employment, Interest and Money. [Online] London:

Macmillan Cambridge University Press. Available from:

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ltheory.pdf[Accessed: 18th

December 2014].

LAVOIE, M. (2011) The Global Financial Crisis: Methodological Reflections from a Heterodox

Perspective. Studies in Political Economy.[Online] 88.p.1-57. Available from:

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December

2014].

MCLEAY, M., RADIA, A. & THOMAS,R. (2014) Money Creation in the Modern

Economy.Quarterly Bulletin 2014Q1.p.14-27. Available

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December].

MINSKY, P.H.(1986) Stabilizing an Unstable Economy. [Online] New Haven: Yale University

PressAvailable from: https://www.ucm.es/data/cont/media/www/pag-

41460/Minsky%20theory%20of%20financial%20crisis.pdf[Accessed: 18th

December].

MINSKY, P.H. (1992) Financial Instability Hypothesis.Levy Economics Institute of Bard College.

[Online] Working Paper No.74 (5).p.1-10. Available from:

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December].

Moore, J. B. (1988) The Endogenous Money Supply. Journal of Post Keynesian

Economics.[Online] 10 (3).p.372-385. Available from:

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d=4&uid=3737848&uid=2129[Accessed: 18th

December].

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4. Available from:

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Perspectives.[Online] 24 (4).p.45-66. Available

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Deregulation.Levy Economics Institute of Bard College. [Online] Working Paper No. 702 (1).

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December 2014].

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December].

LUKAS, E. R. (1970) Expectations and the Neutrality of Money. Journal of Economic

Theory.[Online] 4, p.103-124.Available from:

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he%20neutrality%20of%20money%202.pdf[Accessed: 17th

December 2014].

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Meltdown.Cato Journal.[Online] 29 (1).p.131-139.Available from:

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December 2014].

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Accumulation and Labour Market Institutions in the Great Recession.Post Keynesian

Economics Study Group.[Online] Working Paper 1406.Available

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December 2014].

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American Economic Review.[Online] 70 (2/5).p.15–19. Available

from:https://www.aeaweb.org/yellen_articles/aer.70.2.15.pdf [Accessed: 17th December 2014].

25

Analysis of Immigration in the U.K.

Zhongjiu Lu

The economic impact of immigration has been studied for many years and is still of great

interests to many sectors such as public opinion and policymakers. Some statistics reveal the

importance of immigration in many countries such as USA and the EU. For example, migrants

accounted for 47% of the increase in the workforce in the USA and 70% in Europe over last

decade. In public sector, the evidence shows that migrants contribute more in taxes than they

receive in form of benefits (OECD, 2014)

This paper will look at the fiscal effect of immigrants arriving to the UK. The first section

focuses on the impact of immigrants on the UK economy measured by the Gross Domestic

Product (GDP) performance. The second section concentrates on the influence on the labour

market; in particular, unemployment rate in the UK. The last section introduces a multiple

regression model explaining the immigration effect on the GDP performance together with the

unemployment rate. The methodology used for analysis includes basic econometric techniques

such as time series models, linear regression, and multiple linear regression in different

functional forms.

The paper “The fiscal effects of immigration to the UK”, conducted by Centre for Research and

Analysis of Migration, University College London in November 2013. This paper researched on

overall immigration for the period between 1995 and 2012, which has similar time scale.

However, it not only went deep in recent immigrants who arrived after 2000, but also

distinguished between EU immigrants and Non-European countries. Additionally, this paper

concluded a significant outcome that EEA immigrants have a positive impact on fiscal

contribution to the UK and particularly noticeable for recent immigrants who arrived after 2000,

even specified the benefits, social housing, expenditure and revenues of immigrants in detail.

The data is used in this paper primarily from British Labour Force Survey (LFS), it uses LFS as

the main source of information on native and immigrant population. The public expenditure data

is from “total expenditure on service by sub-function” table from “public expenditure statistical

26

analyses (PESA). To conclude, this paper provided an economics analysis of the impact of

immigration through varies techniques that are beyond my ability.

GDP figures are collected from Eurostat database; GDP figures are measured at market prices in

million Euros, base year is 2010. Immigration figures are obtained from the International

Passenger Survey (IPS) and downloaded from the Office for National Statistics (ONS) website,

and they relate to actual migration of persons who have stayed in the UK for more than 12

months. Moreover, the UK unemployment rate data (16+ unemployment rate data) is from ONS

webpage.

In Figure 1, trends of the number of immigrants in total, from the EU, and non-EU countries are

presented. It is observed that the total number of immigrants has more than doubled in the past

two decades, comparing to a period before 1993. Overall, it has been increasing since 1975.

There was a big jump in the immigration from the EU since 2004, when eight Central and

Eastern European countries, together with Malta and Cyprus, joined the EU. On the contrary, the

number of immigrants from the Non-EU countries has decreased since 2004. This was

significantly influenced by immigration policies. (Gov.uk, 2011) However, these policies can

only restrict the Non-EU immigration.

Figure 1: Number of immigrants to the U.K. from 1975 to 2013

27

Figure 2 presents the trend of the size of total immigration flows and GDP performance in the

UK between 1975 and 2013. The left hand vertical axis represents the figure of GDP in the blue

line and right-hand side vertical axis represents the number of inflow immigrants to the UK. It

can be observed that both series follow a similar increasing pattern. We observe recessions in

1979, 1991-1992 and more recently in 2008-2009, which could have led to a decrease in flows of

immigrants.

Figure 2: GDP and number of immigrants to the U.K. from 1975 to 2013

Figure 3 below illustrates the historical trend on unemployment rate and number of immigrants

in the UK between 1975 and 2013. There is a clear trend the immigrants level steadily kept

increasing from 1975 to 1998, and dramatically doubled the figure from 250000 to 500000

between year 1995 and 2005 in only ten-year time. However, the unemployment rate fluctuated

significantly from 1975 and 1993, reached peak level up to nearly 12% unemployment at year

1984 and another peak time at year 1993 with 10.4% unemployment rate. After year 1993, the

unemployment decreased smoothly every year to the recent lowest point at 4.8% in 2004 and

2005, and then kept increasing until the 2008 financial crisis, it sharply increased to 8%. The

overall view of these two time series data, there seems to be no relationship between

unemployment and immigration.

28

Figure 3: Unemployment rate and number of immigrants to the U.K. from 1975 to 2013

The data on immigration, GDP and unemployment were synthesised into Excel spreadsheet.

Analysis was carried out in Excel and Rstudio.

The association between the GDP and immigration flows can be analysed by a regression model

and a correlation coefficient (Figure 4). The number of immigrants is treated as an independent

variable x to explain the dependent variable y, which denotes the GDP. The model for natural

logarithms of both GDP and immigration flows can be written as

lnYt = α + βln t + et,

Where α is an intercept parameter, β is slope and et are iid normally distributed with zero mean

and variance σ2.

29

Figure 4: Scatterplot of GDP and total immigrants from 1975 to 2013

Table 1 below presents the OLS estimates of the model parameters. The slope coefficient for

immigration flows β, is 0.64, which means that for one percent change in immigration flows,

there will be 0.64 percent increase in GDP, according to the linear model. Moreover, T statistic

and P-value show that β is statistically significant. However, the model is very simple. For

instance, it does not take into consideration any other factors such as political issues, fiscal

policies, other macroeconomic variables, global economic situation, which might influence the

GDP. Also, there are various factors that can contribute to changes in immigration, both at the

receiving country (UK) and the rest of the world (the origin of all immigrants).

Table 1: Report table in regression model: lnY = α + βlnX + e.

Coefficients Standard

Error

T

Statistic

P-value

Intercept α 6.051465 0.442104 13.68787 4.69E-16

β 0.637891 0.035122 18.16201 5.07E-20

It can be seen that there is a strong serial correlation (0.95, see ACF plots in Figure 3), which

indicates that there is a strong positive correlation between number of inflow immigrants to the

UK and the GDP. In addition, coefficient of determination R2 (Figure 4) also shows that the

30

linear model fits the data very well. In this case, a simultaneous relationship between GDP and

immigration flows is analysed.

However, the high value of serial correlation may result from the fact that time series are non-

stationarity, thus, it has to be investigated. Stationarity means that the expected value and

variance of time series data stays constant through time. In Figure 5 we observe high

autocorrelation of both the logarithm of GDP and logarithm of immigrants. It suggests that both

variables are non-stationary. Due to the both non-stationarity of the GDP and immigration flows,

there are also obvious not to be stationary. Therefore, the model of lnYt = α + βln t + et

breaches the assumption of stationarity of the data for the time-series analysis. To conclude, this

model should not be trusted.

Figure 5: Logarithm of GDP and Immigrants, U.K. 1975-2013

31

In the next regression model; a lagged logarithm of immigration flows (i.e. in year t-1) is used as

an independent variable, explaining the GDP performance in year t. The regression equation is:

lnYt = α + βlnXt-1 + et.

The purpose of this model is to analyse whether the last year’s total immigration flows have an

impact on the GDP performance, as it can be seen in Figure 6 and Table 2. As expected it also

shows that the explanatory variable is statistically significant in this lagged model, which

indicates that one percentage increase in inflow immigrations from last year, will lead to a

growth in GDP by 0.62 percent on average. However, same limitations adhere as in the

simultaneous model: other potential influential factors are not included in the model. In terms of

correlations, there is a positive correlation between previous year immigration flows, and the

GDP performance in the current year.

Figure 6: Scatterplot of log GDP and lagged log immigrants inflow from 1975 to 2013

Table 2: Report table in regression model lnYt = α + βlnXt-1 + et.

Coefficients Standard

Error

t Statistic P-value

Intercept 6.284277489 0.472327009 13.30492935 1.82185E-15

32

X Variable

1

0.621019905 0.037563709 16.53244387 2.14885E-18

Both models illustrate that the size of immigration flows and GDP performance are strongly

correlated, but it does not demonstrate that immigration causes to increase GDP. There is no

evidence of causality due to the fact that many other factors are not controlled for. Moreover,

the relationship may be in both directions, that is a strong economic performance leads to an

increase in immigration to the UK. This analysis is however beyond of this report.

Checking the stationarity of time series data should be carried out before any models are set up

or conducted. Figure 7 presents autocorrelation functions of one year lagged and log GDP figure,

which is the same to one year lagged of number of immigrant logarithm. In the first figure, the

correlation between the current and lagged variable is not that perfect (approximately 0.45) for a

weakly dependent variable, but the correlation for the further lags converge sufficiently quickly

to not significantly different from 0. Therefore, the first difference of the series is further treated

as stationary series that satisfies the assumption on stationarity in time-series regression model.

Figure 7: Autocorrelation in diff log-log model of immigrant level

33

Figure 8: Autocorrelation in diff log-log model of immigrant level

After the check of autocorrelation of the variables, the model is set as below: X represents the

change (first difference) in log immigration level; Y represents the change in log GDP.

ΔlnYt = α + βΔln t + et

where ΔZt = Zt - Zt-1. Figure 9 is the regression output from R. If we assume a conventional

significance level (5%), the P value is just above 5%, which means that we do not have enough

evidence to reject the null hypothesis of no relationship between the variables. However, if the

significance level is relaxed a bit, for instance, to 10%, we can interpret the statistical inference

saying that 1% increase in growth rate of immigration flows will lead to 0.0575% GDP growth

in the UK. Additionally, this conclusion can be counterpart by a small value of adjusted R

Square, which means that immigration growth rate explains around 7% of variability in the GDP

growth.

34

Figure 9: Output of log-difference regression model and regression graph

In summary, in this section three different model have been investigated the immigration trend in

the UK from 1975 to 2013, in respects of total immigration, and analysed the simultaneous and

lagged impact of immigration flows on the GDP using OLS model in time series data analysis. A

relationship has been discovered between these two variables. The above criticism is also applied

in this section.

The relationship between unemployment rate and immigration level can be analysed by

correlation coefficient and regression model. The correlation is displayed as -0.41 in figure 6,

which indicates that there is negative correlation in a decrease in unemployment rate when there

35

is an immigration inflow to the UK. The below model is the same model as above with

unemployment as dependent variable and level of immigration as independent variable.

Yt = α + β t + et

The R square shows that only approximately 17% of the variability in the unemployment rate

can be explained by the inflow of immigrants; this indicates that the model is not a satisfactory

model.

Figure 10: Scatterplot of unemployment rate and number of inflow immigrants from 1975

to 2013

In addition, the below table 3 shows the regression statistics of above model, which is not a

meaningful result because not only these figures are too small to have any economical

interpretation, but also the below autocorrelation functions (ACF) suggest this model should not

be considered as significant.

Table 3: Report table in regression model: Yt = α + βXt + et

Coefficients Standard Error T Stat P-value

Intercept α 0.096952884 0.008540007 11.35278775 1.29368E-13

β -6.87637E-08 2.48696E-08 -2.764966932 0.008825827

36

Figure 11: Autocorrelation function in immigration and unemployment level

The next two regression models are level and log model and one year lagged log model in

immigrant figures, treat Y (dependent) as level of unemployment rate and the logarithm of

immigration as explanatory variables. The first model is written as below:

Yt = α + βlnXt + et

The second model differs from the previous one with one year lagged, which tries to explain the

immigration effect on unemployment rate from last year.

Yt = α + βlnXt-1 + et

The check of time-series assumption of stationarity and ACF graphs are listed below: it is seen

that the variables are not really weakly dependent (the assumption about stationarity of series is

violated) and the graph of them can be clear not stationary. Therefore, this model is questionable.

37

The regression plots and statistical report are displayed below (Figure 13&Table4). It is clear

that these two models are similar. Both models indicate if there is 1% increase in number of

immigrants, it is expected to have 0.02% decrease in unemployment in the UK; the second

model shows the immigrant from last year has same impact on the unemployment in the current

year. Slope parameters from both models are significantly different from 0. However, all other

defects in the models are applied as same as discussed in section 1.

Figure 12: Autocorrelation function in log-immigration and unemployment level

Coefficients Standard Error T Stat P-value

Intercept 0.355390513 0.102415194 3.47009559 0.001338871

β -0.022272567 0.008136216 -2.73746006 0.009460704

38

Figure 13: Scatterplot of unemployment rate and log of number of inflow immigrants from

1975 to 2013 and report table in regression model Yt = α + βlnXt + et

Coefficients Standard Error T Stat P-value

Intercept 0.355390513 0.102415194 3.47009559 0.001338871

β -0.0222725 0.008136216 -2.73746006 0.009460704

In summary, section 2 contains analysis of estimating the number of immigrants influence on

unemployment rate in the UK. From above models, it states that immigrants have positive impact

on the unemployment rate as it is shown above. Nevertheless, it is a small impact and it can be

argued that this small impact on unemployment is due to omitting other factors in the model or

non-stationarity of the variables. However, it is believed that the number of immigrant does not

have negative impact on unemployment rate.

The third part will consist of unemployment rate and number of inflow immigrants. A multiple

linear regression is set up explaining the potential relationship of unemployment rate and lagged

year of percentage change in immigrants to GDP performance. The model is listed below, lnY

represent the percentage change in GDP figure in the UK as dependent variable, A as an

explanatory defines the level of unemployment rate; lnBt-1 is the year lagged inflow immigrants,

coefficient are β1 and β2 respectively.

39

lnYt = α0 + β1At +β2lnBt-1 + et

R is used to conduct this regression and statistical report is showed below. The regression report

15 demonstrates that percentage immigrant is statistically significant, which means that there is a

1% increase in number of immigrants from previous year, there will be expected increase in

GDP by 0.6% conditional on other elements remain constant. f there is a unit increase in

unemployment rate in the UK, it is expected to lead to a decrease in GDP performance. This

interpretation seems reasonable intuitively in economic sense; however, it statistically does not

prove this due to high P-value. In addition, the R-square shows that more than 80% of variation

in dependent variable is explained by explanatory variables, but it cannot assure the causality

relationship. In respect of F-statistics, which also demonstrates these two explanatory variables

explained variations in GDP in the UK. Finally, all variables are non-stationary (see figures in

previous sections).

Figure 10: Regression statistics report from R, model: lnYt = α0 + β1At +β2lnBt-1 + et

40

To conclude, this above regression evidently shows that inflow immigrant has a positive impact

on the performance of GDP in the UK, and unemployment factor seems to be critical at this

point.

The first two models of immigration impact on the UK’s GDP in Section 4.11 and 4.2 are

invalid; however the last model: ΔlnYt = α + βΔln t + et, is more reliable than other two (using

stationary time-series). The above discussed criticism can be further applied and more complex

models can be analysed. In terms of the influence of immigration on the unemployment rate in

the UK, the stationary time series results also show that these models may be meaningless both

statistically and economically.

The final multiple linear regression model: lnYt = α0 + β1At +β2lnBt-1 + et analyses result

shows no statistical significance, therefore a more complex models would be required.

Additionally, it also does not account for stationarity of the series, stationary time series can be

analysed here instead for the purpose of discovering further evidence of this model.

The report applied introductory econometrics knowledge and software applications trying to

analyse and understand the fiscal effect of immigrations to the UK. The fiscal elements involves

GDP and unemployment rate in the UK, it also expands the analysis with combination of these

two factors, these have all been analysed above with given criticisms. To conclude, these models

are not reliable and profound to an economical outcome, in order to explore it further that

requires more studies in econometrics of time series. It is clear that a much more complicated

model should be introduced to understand the explicit effect to the UK due to immigration.

However, immigration is, by its nature, a very complex process (having multiple reasons itself).

The use of microdata (e.g. large scale surveys, such as Labour Force Survey) can also help

understand the impact better.

41

References

Gov.uk, (2011). Prime Minister's speech on immigration - Speeches - GOV.UK. [online]

Available at: https://www.gov.uk/government/speeches/prime-ministers-speech-on-immigration

[Accessed 12 Dec. 2015].

OECD. (2014). Is migration good for the economy?. [online] Available at:

https://www.oecd.org/migration/OECD%20Migration%20Policy%20Debates%20Numero%202.

pdf [Accessed 14 Jan. 2016].

Tommaso Frattini, (2013). The Fiscal Effects of Immigration to the UK. London: Centre for

Research and Analysis of Migration, pp.1,15,16.