pricing risk in a post euro world (new years version)newey

8/12/2019 Pricing Risk in a Post Euro World (New Years Version)NEWEY

1/24

1

Table of Contents

Introduction

Literature Review

Theory

Bonds

Bond Yields

Data

Methodology

Data Analysis

Conclusion

Bibliography

Appendix

Graphs

Correlation Matrices


2/24

2

Introduction

It has been difficult to escape recent news about the Euro-crises and the turbulence on

the sovereign bond markets for PIIGS. Bond yields have reached all time highs and

have caused much distress for the national governments as for the whole EU.

Investors are increasingly worried whether the countries can fix their finances. There

is reason to believe that economic figures released about the state of the countrys

economic health, has had increased importance when it comes to pricing of risk in the

sovereign debt market. Macro-economic data is continuously released and is seen as

an indicator of a countrys economic situation. Credit rating ag encies use macro

economic data when determining whether a country should keep its current rating or

not. When Standar d & Poors downgraded The U.S from AAA to AA+, the rating

was cut partly because of the heavy debt burden and the governments budget deficit.

Even though it is accepted that economic data will have an effect on bond yields, the

question still remains how well the bond markets priced the risk of the PIIGS

economic state and how whether it changed after the 2007 financial crises.

This paper investigates the pricing of risk in the bond markets associated with the

introduction of the euro. Our objective is to determine how accurately the bond

markets priced the risk for the PIIGS economic health when the euro was introduced

in 2002, and whether there are large prediction errors for the bond markets during this

particular period. Essentially, the data should enable us to see what kind of effects

EMU has had on the risk premiums that governments pay. Due to the financial crises,

there is reason to divide the period of 2002 to 2011 into two periods; from the

introduction of the euro to mid 2007 and mid 2007 to present date.

To determine how accurately risk was priced for each country, variables such as

government debt, inflation, unit labor cost and the unemployment rate were testedagainst the 10-year government bond spreads.

This paper is divided up into seven parts. First an introductory section, followed by

literature review where we examine past papers written about this topic. The third

section contains a generalized theoretical discussion about bonds and bond yields.

This is followed by a presentation of the data and what methodology was used.

Finally, the results are presented and analyzed followed by a conclusion and

appendix.


3/24

3

Literature Review

Various types of research have been done in the field of pricing of risk and also more

generally on the effect of macroeconomic variables on bond yields. Aizenman,

Hutchinson, and Jinjarak (2011) estimated the pricing of sovereign risk for PIIGS

before and after the financial crises by using credit default swaps. The estimation is

based on fiscal space and economic fundamentals. The authors find evidence for

mispricing of PIIGS risk given the current economic fundamentals during both after

and before the financial crises. Barrios, Iversen, Lewandowska, Setzer (2009) found

that bond yields spreads react more strongly to domestic factors after that financial

crises.

Additionally, there has been extensive research on the impact of macroeconomic data

on bond yields. In an essay for the Central Bank of Ireland, Liebermann (2011) found

that T-bond yields reacted systematically to news of data that had short publication

lags. She states that one of the most important releases was the unemployment rate.

The report also found that the impact of the variables changed during the financial

crises.

Bonds

A bond is a type of debt instrument that is often referred to as a fixed-income

instrument because it promises either a fixed stream of income or stream of income

that is determined according to formula mentioned on the next page (Bodie, 2011).

The price of a bond is determined by the present value of its future cash flows. That

is, the price an investor would be willing to pay to for a future stream of payments

instead of having them today. This, in turn, is determined by market interest rates andseveral risk premiums caused by other risk factors such as liquidity risk, default risk

and so on.

Bond value= Couponn(1+r)n=1

N + Par value

n(1+r) (BODIE)


4/24

4

Bond yields and prices are highly correlated.

The price of the bond moves in the opposite direction of the yield. Since the bond

price is the sum of all future cash flows, an increase in the yield would mean that

the present value of future cash flows decreases.The reason for this relationship is that the price of a bond is the net present

value of its future cash flows, and if the discount rate increases, the present value

of the cash flows will decrease (Choudhry, 2010).

The bond type discussed here are sovereign government bonds. Government

bonds are issued by national governments.

YieldsThe yield of a bond is the percentage return an investor can expect to receive

from a bond.

A bond with a higher yield implies a bond with a higher credit risk.

The yield is determined by:

Credit risk

Credit risk can be seen as the main risk when holding a bond. Credit risk is

increasing with maturity. Credit risk can be separate into three categories:

1. Default risk: the probability that the issuer will default on its own debt

and wont be able to meet its obligations of repayment at the time of

maturity.

Bonds of governments that do no conduct sound fiscal policies usually

have higher default risk and therefore investors will require a higher

yield on bonds as compensation.

The default risk of government bonds is rarely an outright default as

much as forced restructuring and renegotiation of its debt (Di, 2005).

2. Credit spread risk; which is the probability that the bond declines more

than other bonds of similar quality.

3. Downgrade risk: the risk of a downgrade from a ratings agency.


5/24

5

Liquidity risk

A liquid market is one where there is sufficient buy and sell orders and where

large-scale orders do not have a strong impact on prices (Manganelli & Wolswijk,

2009).The only market in Europe that has a liquid futures market is Germany. This

increases the demand for German Bunds since you can enter and exit a trade

practically immediately, and that makes it attractive for investors.

Long-term investments require higher yields (Choudhry, 2010).

Risk aversion

Risk aversion measures the investors willingness to take on risk. If risk increases investors seek the flight -safety or flight -to-liquidity, which in

the euro zone has been Germany and it s liquid marke ts (Barrios, Iversen,

Lewandowska, & Setzer, 2009)

For a market to be efficient in its pricing of sovereigns bonds it is necessary that

all governments have access to capital markets on the same terms as borrowers.

Another important necessity is that countries bear the risk of default and takes

responsibility for the financial consequences following a default (Manganelli &Wolswijk, 2009).

The Maastricht Treaty and its no -bail-out clause exists to help markets stay

efficient. This clause may however be undermined, especially in large and

integrated market as the Euro-area since the theory of too-big-to-fail holds

(Gmez-Puig, 2002) and when a crisis like the debt crisis of the PIIGS countries

occur it threatens the entire economy.

Macro variables and their influence on the Bond yields

It is widely accepted that government policy has an impact on the yield curve.

These include policies on public sector borrowing, debt management and open-market

operations. How the market perceives the size of public sector debt will inuence

bond yields; for example, an increase in the level of debt can lead to an increase in

bond yields.


6/24

6

Lebrun and Prez (2011) state that after the EMU was created, unit labor cost growth

differentials have widened in the euro area. Additionally, according to the Economist,

the peripheral countries have lost a large amount of competitiveness (measured in unit

labor cost) compared to Germany since 2000. Therefore we found ULC appropriate as

a measure for economic health between PIIGS and Germany.

We also consider the unemployment rate a useful variable because of its relationship

to bond yields. Poterba and Rueben (1999) found that an increase in a states

unemployment rate is assoc iated with an increase in that states bond yields.

Additionally Palumbo and Schick (2006) state that unemployment figures draw the

attention of credit analysts which in turn have an effect on bond yields.

According to Elmendorf and Mankiw (1998), government debt is supposed to

increase the yields of the bonds since a higher debt level increases the risk of

default and economic instability.

A monetary union such as the EMU may increase the default risk even more at

higher debt levels since the countries inside the union has given up their

possibility of managing their debt thru monetary policy (Bernoth, von Hagen, &

Schuknecht, 2004).

Inflation rate is said to be an indicator of economic stability and as a proxy of

economic management that has a positive impact on the sovereign default risk

(Alexpoulou, Bunda, & Ferrando, 2009).

However, higher inflation can be seen as a sign of increased government deficits

which in turn signal a need for higher interest rates. Because of this, higher

inflation is expected to increase the sovereign risk, which will be added to the

bond price.


7/24

7

Data

All the collected data occurs on a monthly basis, except government debt, which has

been interpolated to fit in the model. The data covers January 2002 to June 2011.The time-series have been divided into to sub-periods; the first from January 2002 till

July 2007 and the other sub-period will cover the rest of the time-series, August 2007

to May 2011.This divide is made since August 2007 is seen as the starting point for

the financial crisis (Elliott, 2011).

The countries chosen are referred to as the PIIGS throughout the paper and include:

Portugal, Ireland, Italy, Greece and Spain. These countries are often bundled together

when referring to the financial crises and therefore we saw it as interesting to test all

of them. Germany was included as a benchmark bond. In an essay by Barrios,

Iversen, Lewandowska and Setzer (2009), the German government bond market is

referred to as safest haven and having Germany as a benchmark would explain the

excess premium on the bonds for PIIGS in respect to the macro variables.

As an indicator of risk for the bond market, the harmonized 10-year government bond

spreads were used. The bond yields were retrieved from Eurostat and are reference

rates measured in percentages that have been based on government bonds that have

maturity close to 10 years. To find the spread, the German yield was subtracted from

each of PIIGS yields.

Unit Labour Cost

Real unit labour cost (ULC) is used as a competitive indicator. It measures the

average cost of labor per unit of output. It is computed as the ratio of total labor coststo real output (OECD). This index is useful as it can be compared directly between

countries. The data was published by the IMF and is presented in real effective

exchange rates. This means that the data was acquired by reducing every countrys

trade weighted index of the bilateral nominal rate by a weighted index of unit labor

costs of other countries relative to the unit labor cost in the domestic country (IMF).It

is not a complete measure of competitiveness per se, yet should rather be interpreted

as a reflection of cost competitiveness (OECD).


8/24

8

The ULC was converted into an index where January 2002=100 which was the date

when the Euro was physically introduced.

Unemployment Rate

The Unemployment rate is seasonally adjusted data retrieved from Eurostat and is

measured as a percentage of the total amount of people in the workforce. The work

force includes the total of individuals who are unemployed and employed between the

ages of 15 and 74 (Eurostat). Those considered as unemployed are those who do not

have a job during the reference week, can start work in the next two weeks, and are

actively looking for a job the past four weeks.

Government debt

The government debt data was retrieved from Eurostat on a quarterly basis.

The Quarterly government debt is defined as the total gross debt at nominal

value outstanding at the end of each quarter. The data are measured in million

Euros as a percentage of GDP. (Eurostat)

Since regression models require consistent time intervals, we have interpolated

the data from quarterly to monthly to make it fit in the frequency. This was done

in Stata where we interpolated the change in government debt in each quarter to

then get the monthly change.

Harmonized indices of consumer prices

The harmonized indices of consumer prices (HICPs) was used as a measure for

inflation and retrieved from Eurostat. This type of measurement is useful as it is

designed for cross-country analysis of consumer price inflation.

The HICPs are used to evaluate if the inflation criteria is fulfilled which is

required by the Euro zone countries (Eurostat).The inflation rate should, according to the Maastricht treaty not be more than

1,5% above the inflation level of the three best performing EU member

states(Soltes, 2011).


9/24

9

Methodology

Our multiple regression model consists of four macro variables that have a

according to several previous studies a considerable impact on bond spreads.

Not only was the German yield subtracted from each individual country to get

the bond spreads, but the German data for each of the variables were also

subtracted. We found this necessary because when the difference between the

yields varies (the spread increases or decreases) then this must be matched on

the other side of the equation with the variation between the two countries

variables. For example, even though government debt might be rising in one of

the PIIGS, the spread might be decreasing. This can be due to the fact that there

is a variation on the German side that needs to be taken into account and

therefore we subtract its government debt as well.

Mathematically, both legs should be equal and therefore if the government bond

yields (the left part) is considered a safe haven then the variables determining

them should be considered safe as well. (den hr biten kommer utvecklas eller

skrivas om)

We conducted individual regressions for each country. Each variable was tested

whether they had a lagged effect or not. Government debt and unit labour cost

both showed lagged effects of 1 month.

Lagged variables may capture dynamic structures in the dependent variable,

which in this case most likely are caused by inertia. This could be due to

psychological factors where people might not fully understand the effects certain

new announcement might have. It could arise because it is not yet clear whether

or not the change will be permanent or only temporary (Brooks, 2002).


10/24

10

When running a regression model one must check to make sure that the model

fulfils the ordinary least squares assumptions. The OLS describes the linear

relationship between the dependent variable and the independent variables.

The following are all assumptions of the OLS and if one of them is violated themodel no longer contains the best linear unbiased estimators that can be

obtained and improvements can be made.

The first assumption is that the model is linear in its parameters.

The second assumption states that the expected error term should be zero. If not,

the model has unexplained errors, which does not make it BLUE best linear

unbiased estimator.

The third assumption states that the model has to be homoscedastic.

Homoscedasticity means that the variance should be constant and not depending

on x. If this is violated then the residuals are said to be heteroscedastic. If a

regression model contains heteroscedastic error terms they are no longer

correct and need to be replaced with new standard errors that adjust for this.

This can be done by using Newey-West standard errors.

The fourth assumption is about autocorrelation. Autocorrelation occurs when

two on following residuals are correlated with each other. When this occurs the

residuals are said to be serially correlated. This will lead to the same problem as

with heteroscedaticity and give the standard errors that are not in line with

BLUE.

() It is possible to adjust for both autocorrelation and heteroskedasticity by

creating new standard errors. This can be done by using Newey-West, which

creates new standard errors that can be added to the model.

The fifth assumption states that the variable x is not random and must take on at

least two different values.


11/24

11

The sixth and last assumption of the regression model is that the error terms

must be normally distributed about their mean if the values of y are normally

distributed.

A normal distribution is symmetric about its mean. To test if the sample is

normally distributed the test most commonly used is the Bera-Jarque.

The B-J test for normality is based on two measures, skewness and kurtosis.

Skewness measures the extent to which a distribution is not symmetric around

its mean and kurtosis measures how fat the tails of the distribution are.

A normally distributed sample should not have any skewness and the allowed

coefficient of the kurtosis is 3.The Bera-Jarque test statistic:

[ ] T is the sample size and b 1 and b2 can be estimated from the residuals taken from

the regression. The null hypothesis of this normality test is that the model is

normally distributed (Brooks, 2002).

The data was divided into to sub-periods because of the change in the economic

environment and increased economic instability after July 2007. To see if there is

a detectable difference between these periods we conducted a chow-test. A

Chow-test tests if there is any structural change between two different periods.

When conducting the test one divides the sample into different periods, in this

case two, from January 2002 to July 2007 and August 2007 to May 2011.

When the models have been estimated separately, including one for the whole

period, and we have three different sum of squared residuals an F-test can be

made (Ramanathan, 2002).

The unrestricted regression is the one where the restriction has not been

included. The restriction is that the coefficients are equal across the sup-periods


12/24

12

and the restricted regression will be the single regression that covers the entire

sample period.

Data analysis

All the regression models were run through the Ramsey reset test to see if all the

coefficients are significant and if we have any omitted variables. The only model

that did not show signs of omitted variables was Greece in both periods (see

appendix). All other regression models got results telling us that the model could

be improved by including more variables.

When checking for multicollinearity correlation matrices and variance inflationfactor tested the variables and both got results indicating that we have a problem

with collinearity between are variables (see appendix).

The VIF is defined as;

When variables are inter correlated it is difficult to disentangle their separate

effects on the explanatory variables (Maddala, 2001). This might have an

increasing effect on the R 2 values without increasing the degree of explainability

of the whole model. The R2 measures how much of the variation in the model

that is explained by the variables. All regression models got increased R 2 values

in the second sub-period.

In almost every case the results gave very high R 2 values. This might also be

because of the high correlation between the macroeconomic variables. When the

correlated variables move together, it may have a positive impact on the R 2 value

without having any real explanation of the variation in the regression model

(Nau). Therefor it is important to not look at other factors when evaluating the

quality of the model such as estimates and their magnitude and directions rather

than the R2 (Hill, 2011).

To test for heteroscedasticity we use Breusch-Pagan. Breusch-Pagan tests if

there are any variables that influence the variance. The results received from

these test tells us that we have a problem with heteroscedasticity and after


13/24

13

conducting test for autocorrelation with Breusch-Godfrey the results clearly

shows that the model has a problem with that as well.

To account for these problems with standard errors that do not use the best

linear unbiased estimators we must create new standard errors using Newey-West. When these new standard errors are included in the model the

heteroscdasticity and autocorrelation is accounted for and we can include these

with the original coefficients obtained from the first regression models.

First Sub-Period

The regression analysis with the corrected standard errors led to varied

significance amongst the independent variables for each country in the firstperiod.

RAdjustedR F-stat Prob.

Portugal 0.017968 0.1141105 0.0283396 0.0372685 0.5519 0.5215 15.23 0.0000

Ireland 0.0015277 0.0579048 0.0119188 0.126773 0.8457 0.8352 47.57 0.0000

Italy 0.0046624 0.0141835 0.0131077 0.0107276 0.4098 0.3698 5.92 0.0004

Greece 0.0019864 0.011489 0.0154649 0.0130428 0.5244 0.4921 9.03 0.0000

Spain 0.0087624 0.0040949 0.0230625 0.0176186 0.5917 0.5641 34.64 0.0000Table 1. Regression table for the first sub-period

For Portugal, the variables found significant were government debt,

unemployment rate and inflation. The government debt coefficient is negative

implying a reverse relationship to the bond spreads. This is obviously a

contradictory result and not in line with theory yet this could indicate that bonds

were mispriced. A one per cent increase in debt indicates a decrease in bond

spreads by 0,04%. The effects of inflation and unemployment are both positive

with and increase on bond spread for every per cent of 0,03% respectively

0,11%. This is in line with the theory that inflation and the unemployment rate

has a positive relationship to bond spreads.


14/24

14

The only variable found significant in the first sub-period for Ireland was

government debt. An increase by one per cent would have a positive impact on

bond spreads by 0,013%.

Government debt and unit labor cost were the only variables that weresignificant for Italy. The coefficients imply that if government debt were to

increase by one percent then the spreads would increase by 0.01 %. Additionally,

if unit labor cost increased by one percent then spreads would increase by 0.004.

Government debt was the only variable that was significant for Greece. It

indicates that spreads will widen 0.013 percent if government debt were to

increase by one percent.

Unit labor cost, government debt and HICP were all significant for Spain. The

coefficient for unit labor cost indicates that if it were to rise by one percent then

the spreads would widen by 0.009 percent. In regards to government debt, the

spreads would increase by 0.17 percent. A one percent increase in HICP would

however have an inversely related effect on the spread where it would decrease

by 0.02.

The first sub period shows that the independent variable that PIIGS had in

common was the government debt. The fact that the other variables had mixed

results on the countries can imply that during a less volatile period these

variables play a less important role for bond investors. Despite this, government

debt still seemed to have some importance.

Second Sub-Period

RAdjustedR F-stat Prob.

Portugal 0.5908905 1.015671 0.6448951 0.0873556 0.9320 0.9257 62.24 0.0000

Ireland 1.161244 0.7882239 1.016838 0.0546108 0.8948 0.8850 69.41 0.0000

Italy 0.1022214 0.3237773 0.2051403 0.0117671 0.6013 0.5646 122.93 0.0000

Greece 0.1250138 1.016308 0.2918964 0.0130389 0.9406 0.9351 153.09 0.0000

Spain 0.2399331 0.0771073 0.1068272 0.0880985 0.7992 0.7805 103.50 0.0000Table 2. Regression table for the second sub-period

In the second period, debt has lost its significant impact on bonds in Portugal.The variables now significant are unemployment rate, unit labor cost and


15/24

15

inflation. Both unemployment rate and inflation has an increased impact on the

bond spread. Inflation will now, for every percentage increase, increase bond

spreads by 0,64 % and unemployment rate 1,02%.

Ireland has, after testing the second sub-period changed its significant variablesfrom only debt to unit labor cost and inflation. These to have an effect per every

percentage increase of 1,16 and 1,017 percent respectively.

Government debt is not significant for Italy whereas the rest are in the second

sub-period. HICP indicates a negative relationship with the bond spread where a

one percent increase would lead to a 0.2 decrease in spreads. Furthermore, a one

percent increase in unit labor cost would increase bond yields by 0.1 percent.

The coefficient also indicates that unemployment rates would have a positive

effect on spreads, where a one percent increase would have the consequence of a

0.32 percent increase in spreads.

Unit labor cost and unemployment rates were both significant for Greece the

second period. A one percent increase in unit labor cost points to a 0.125 percent

increase in bond spreads. Additionally, if unemployment rate were to increase by

one percent bond spreads would increase by 1.01 percent.

For Spain, HICP was the only variable that was not significant. A one percent

increase in unit labor cost, government debt or unemployment rate points to an

increase in bond spreads by 0.24, 0.88 and 0.77 percent respectively.

In the second sub-period, unit labor cost was the common denominator for the

five countries. Other than that the variables differ greatly as they did with the

first period.

The hypothesis that macro variables importance increases during a financial

crises is supported in our model when one looks at r-squared. Since it increased

between the two periods for all of the countries, it indicates that the model

increased in accuracy. However, not all variables were significant during either

of the two periods. This could partly imply that the bonds were mispriced during

both periods.


16/24

16

Further general analysis

When it comes to the first sub-period, there are other factors that can be taken

into account when it comes to determining the economic state and bond yield

spreads of PIIGS. Firstly, although the countries are often bundled together, theydiffer the economic variables differ between them. Both Ireland and Spain kept

within the debt requirements and ran budget surpluses. Furthermore, when

credit became cheaper, entire nations could take quite different courses (Lewis,

2011). Whilst the money was borrowed by the government in Greece, it was

borrowed by a few banks in Ireland. Despite this, a factor they did have in

common was that the countries had been running unsustainable current

account deficits (the Economist). The low interest rates stimulated domestic

spending and increased inflation in wages and goods. This in turn made exports

more expensive and imports relatively cheaper.

Additionally, investors assumed that a Euro Zone could not default on its debt

(Economist). The Euro zone could have been seen as a safety net and therefore

the state of each individual country did not matter as much. In the book

Boomerang, Michael Lweis states that these peripheral countries enjoyed the

same credit rating as Germany did. This however changed when Germany, in the

middle of the crises, implied that defaults were possible and the investors could

have to bear some of the losses.

The prospects of a default in the Euro Zone lead to a spiral of falling bond prices,

a weakened banking system and slowing growth. New light was shining on

macro variables and the states of the each countrys finances.

Although the results may show signs of mispricing, there is reason be interpret

them with caution. The number of observations used in the regression could

have had an effect on the results because there were just too few to have an

impact.


17/24

17

Bibliography

Aizenman, J., Hutchinson, M. M., & Jinj, Y. (2011, September).What is the Risk ofEuropean Sovereign Debt Defaults? Fiscal Space, CDS Spreads and Market Pricing

of Risk. Retrieved December 4, 2011, from The National Bureau of EconomicResearch: http://www.nber.org/papers/w17407

Alexpoulou, I., Bunda, I., & Ferrando, A. (2009, September 23).Determinants ofGovernment Bond Spreads in New EU Countries. Retrieved from Social ScienceResearch Network:http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1474275&http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1474275

Barrios, S., Iversen, P., Lewandowska, M., & Setzer, R. (2009, November).

Determinants of intra-euro area government bond spreads during the financialcrisis. Retrieved December 3, 2011, from European Comission Economic andFinancial Affairs:http://ec.europa.eu/economy_finance/publications/publication_summary16253_en.htm

Bernoth, K., von Hagen, J., & Schuknecht, L. (June 2004).Sovereign Risk Premia inthe European Government Bond Market (working paper series). Hmtat frnEuropean Central Bank: http://www.ecb.int/pub/pdf/scpwps/ecbwp369.pdfden 1 December 2011

Bodie, Z., Kane, A., & Marcus, A. J. (2011).Investments And Portfolio Management. New York, N.Y: Mc Graw-Hill Irwin.

Brooks, C. (2002). Introductory Econometrics for Finance. Cambridge: CambridgeUniveristy press.

Choudhry, M. (2010). An Introduction to Bond Markets. West Sussex, U.K: Wiley.

Di, M. (2005, April 20). Retrieved December 27, 2011, from Pricing SovereignBonds: http://www.math.mcmaster.ca/~grasselli/sovereign_bonds.pdf

Elliott, L. (2011, August 7).Global financial crisis: five key stages 2007-2011 .Retrieved December 1, 2011, from The Guardian:http://www.guardian.co.uk/business/2011/aug/07/global-financial-crisis-key-stages

Elmendorf, D. W., & Mankiw, N. G. (1998, January).Government Debt. RetrievedDecember 4, 2011, fromhttp://www.federalreserve.gov/pubs/feds/1998/199809/199809pap.pdf


18/24

18

Eurostat European Comission. (den 10 March 2010). Harmonised unemployment(1 000) - monthly data . Hmtat frnhttp://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/en/lmhu_m_esms.htm

Gmez-Puig, M. (2002).Monetary Integration and the Cost of Borrowing. Barcelona: Universitat de Barcelona.

Hill, C. R. (2011).Principles of Econometrics. Hoboken, N.J: Wiley.

Lebrun, I., & Prez, E. (2011, May).Real Unit Labour Cost Differentiails in EMU:How Big, How Benign and How Reversible? Retrieved December 7, 2011, fromIMF Working Paper:http://www.imf.org/external/pubs/ft/wp/2011/wp11109.pdf

Liebermann, J. (den 18 April 2011). The Impact of Macroeconomic News on Bond

Yields: (In)Stabilities over time and Relative Importance. Hmtat frn Bank forInternational Settlements:http://www.bis.org/cbhub/list/author/author_8219/from_01012011/index.ht m den 4 December 2011

Maddala, G. S. (2001).Introduction to Econometrics. New york, N.Y: Wiley.

Manganelli, S., & Wolswijk, G. (2009). What drives spreads in the euro.Economic Policy, 24 (58), 193-236.

Nau, R. F. (n.d.). Example of regression analysis: predicting auto sales from personal income . Retrieved from Duke University:http://www.duke.edu/~rnau/regex.htmOECD. (2007).Unit Labour Costs-OECD . Retrieved 11 30, 2011, from Glossary ofStatistical Terms: http://stats.oecd.org/glossary/detail.asp?ID=2809

Palumbo, G., Shick, R., & Zaporowski, M. (2006). Factors Affecting aMunicipalitie's Bond Rating: An Empirical Study. Journal of Business andEconomics Research , 4 (11), November.

Poterba, J. M., & Rueben, K. S. (1999).Fiscal Rules and State Borrowing Costs:Evidence from California and Other States. California: Public Policy Institute ofCalifornia.

Ramanathan, R. (2002). Introductory Econometrics with Applications. Fort worth:Harcourt College Publishers.

Ready for the ruck? Taking over the European Central Bank puts Mario Draghi ina position as perilous as Europes. (2011, October 22). The Economist .

Soltes, D. V. (2011, September 14). The Euro Crisis: Euro as a Victim of the Decade

Long Ignorance of the Maastricht Treaty Criteria by the EU Institutions and Euro Zone Member States. Retrieved December 05, 2011, from Social Science Research


19/24

19

Network:http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1927189&http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1927189


20/24

20

Appendix

Graph 1. Government Debt

Graph 2. Unemployment Rate

Graph 3. Unit Labour Costs

0

5 0

1 0 0

1 5 0

2002m1 2004m1 2006m1 2008m1 2010m1 2012m1date

DEBTPO DEBTIT

DEBTIR DEBTGR

DEBTSP DEBTGER

5

1 0

1 5

2 0

2002m1 2004m1 2006m1 2008m1 2010m1 2012m1date

URPO URIR

URIT URGR

URSP URGER

9 0

1 0 0

1 1 0

1 2 0

1 3 0

1 4 0

2002m1 2004m1 2006m1 2008m1 2010m1 2012m1date

ULCPO ULCIR

ULCIT ULCGR

ULCSP ULCGER


21/24

21

Graph 4. Harmonized Indices for Consumer Prices

Graph 5. Government Bond Yield Spreads

- 4

- 2

0

2

4

6

2002m1 2004m1 2006m1 2008m1 2010m1 2012m1date

HICPPO HICPIR

HICPIT HICPGR

HICPSP HICPGER

0

5

1 0

1 5

2002m1 2004m1 2006m1 2008m1 2010m1 2012m1date

SPREADPO SPREADIR

SPREADSP SPREADGR

SPREADIT


22/24

22

Source: The Economist

Correlation Matrices GreecePeriod1

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate

Spread 1.0Unit Labor Cost 0.4476 1.0Government Debt 0.6258 0.6818 1.0HICP 0.1659 0.1699 0.1443 1.0UnemploymentRate 0.2938 0.0726 0.0327 0.5215 1.0

Period 2

Spread

Unit

LaborCost

GovernmentDebt HICP

UnemploymentRate


Ireland

Period 1Spread Unit Government HICP Unemployment


23/24

23

LaborCost

Debt Rate


Period 2

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate


ItalyPeriod 1

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate

Spread 1.0Unit Labor Cost 0.2456 1.0Government Debt 0.1267 0.7531 1.0HICP 0.2659 0.7080 0.5088 1.0Unemployment

Rate 0.0999 0.9111 0.7988 0.6982 1.0Period 2

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate

Spread 1.0Unit Labor Cost 0.2624 1.0Government Debt 0.5001 0.2964 1.0HICP 0.3756 0.3419 0.3027 1.0

Unemployment Rate 0.8326 0.1734 0.66690.3961

1.0


24/24

24

SpainPeriod 1

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate


Period 2

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate


PortugalPeriod 1

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate

Spread 1.0Unit Labor Cost 0.5572 1.0Government Debt 0.2011 0.0958 1.0HICP 0.3090 0.9267 0.2461 1.0Unemployment Rate 0.6310 0.3621 0.4672 0.1647 1.0

Period 2

Spread

UnitLaborCost

GovernmentDebt HICP

UnemploymentRate

Spread 1.0Unit Labor Cost 0.8508 1.0Government Debt 0.2011 0.1261 1.0HICP 0.8803 0.9722 0.1684 1.0Unemployment Rate 0.5901 0.4804 0.2417 0.4852 1.0

pricing risk in a post euro world (new years version)newey

Documents