Journal

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

2
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.

3
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

4
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.

5
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

6
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.

7
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

8
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

9
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

10
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.

11
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].

12
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

14
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

15
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.

16
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.

17
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”

18
(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

19
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
References
BEZEMER, J. D. (2009) ‘No One Saw This Coming’: Understanding Financial Crisis through
Accounting Models. MPRA.[Online] Paper No. 15892 (6). p.1-51. Available from:
http://mpra.ub.uni-muenchen.de/15892/ [Accessed: 19th December 2014].
BLANKENBURG, S., KING L., KONZELMANN S. & WILKINSON F. (2013) Prospects for
the Eurozone Cambridge Journal of Economics.Cambridge Journal of Economics.[Online]
37 (3). Available from: http://cje.oxfordjournals.org/content/37/3/463.full[Accessed: 19th
December 2014].
DEJU N, ., FEBRERO, E. AND U , J. (eds.) (2013) Post-Keynesian Views of the Crisis and
its Remedies. [Online] London, New York: Routledge. Available from:
https://books.google.com.cy/books?id=2bF_AAAAQBAJ&pg=PR1&lpg=PR1&dq=post-
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-
keynesian%20views%20of%20the%20crisis%20and%20its%20remedies&f=false[Accessed:
17th
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:
http://ineteconomics.org/sites/inet.civicactions.net/files/keen-steve-berlin-paper.pdf[Accessed:
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:
http://onlinelibrary.wiley.com/doi/10.1111/1475-4932.12016/pdf[Accessed: 17th
December
2014].
KEYNES, J. M. (1936) The General Theory of Employment, Interest and Money. [Online] London:
Macmillan Cambridge University Press. Available from:
http://cas.umkc.edu/economics/people/facultypages/kregel/courses/econ645/winter2011/genera
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:

23
http://spe.library.utoronto.ca/index.php/spe/article/view/16052/13090[Accessed: 18th
December
2014].
MCLEAY, M., RADIA, A. & THOMAS,R. (2014) Money Creation in the Modern
Economy.Quarterly Bulletin 2014Q1.p.14-27. Available
from:http://www.bankofengland.co.uk/publications/Pages/quarterlybulletin/2014/qb14q1.aspx[
Accessed: 18th
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:
http://www.ie.ufrj.br/hpp/intranet/pdfs/finisntability.pdf[Accessed: 18th
December].
Moore, J. B. (1988) The Endogenous Money Supply. Journal of Post Keynesian
Economics.[Online] 10 (3).p.372-385. Available from:
http://www.jstor.org/discover/10.2307/4538079?sid=21105055397981&uid=2&uid=70&ui
d=4&uid=3737848&uid=2129[Accessed: 18th
December].
MULLIGAN, C. (2009) Is Macroeconomics Off Track? The Berkeley Electronic Press.[Online] p.1-
4. Available from:
http://www.neweconomictheory.org/files/Is%20Macroeconomics%20Off%20Track.pdf[Access
ed: 19th
December 2014].
OHANIAN, L. (2010) The Financial Crisis from a Neoclassical Perspective.Journal of Economic
Perspectives.[Online] 24 (4).p.45-66. Available
from:http://www.econ.ucla.edu/workshops/papers/History/JEP_economic_crisis_ohanian%20e
dit.pdf[Accessed: 19th
December 2014].
PEREZ-CALDENTEY, E. & VERNENGO, M. (2012) Euro Imbalances & Financial
Deregulation.Levy Economics Institute of Bard College. [Online] Working Paper No. 702 (1).
p.1-36. Available from: http://www.levyinstitute.org/pubs/wp_702.pdf [Accessed: 17th
December 2014].
PRIEWE, J. (2011) European Imbalances and the Crisis of the European Monetary Union.[Online]
p.1-15.Available from:http://www.boeckler.de/pdf/v_2011_10_27_priewe.pdf[Accessed: 18th
December].
LUKAS, E. R. (1970) Expectations and the Neutrality of Money. Journal of Economic
Theory.[Online] 4, p.103-124.Available from:
http://www.econ.ucdavis.edu/faculty/kdsalyer/LECTURES/Ecn235a/expectations%20and%20t
he%20neutrality%20of%20money%202.pdf[Accessed: 17th
December 2014].
SAMWICK, A. A. (2009) Moral Hazard in the Policy Response to the 2008 Financial Market
Meltdown.Cato Journal.[Online] 29 (1).p.131-139.Available from:

24
http://object.cato.org/sites/cato.org/files/serials/files/cato-journal/2009/1/cj29n1-
11.pdf[Accessed: 17th
December 2014].
STOCKHAMMER, E., GUSCHANSKI, A. & KÖHLER K. (2014) Unemployment, Capital
Accumulation and Labour Market Institutions in the Great Recession.Post Keynesian
Economics Study Group.[Online] Working Paper 1406.Available
from:http://www.postkeynesian.net/downloads/wpaper/PKWP1406.pdf[Accessed: 17th
December 2014].
STUTZER, M. (2014) The Formula that Felled Wall Street? An Instructor’s Guide to Default
Modelling. Journal of Financial Education.40 (1/2).p.1-13.
YELLEN, J. (1980) On Keynesian Economics and the Economics of the Post-Keynesians.
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
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
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.

Journal

Recommended

Recommended

More Related Content

What's hot

What's hot (19)

Viewers also liked

Viewers also liked (12)

Similar to Journal

Similar to Journal (20)

Journal