Download 1. Introduction

Financial Markets and Fiscal Policy – Role of the EMU and the
Italian Credit Risk Revisited
Ondřej Schneider, Jan Zápal
Institute of Economic Studies
Charles University, Prague
Abstract
In this paper, we analyse the impact of large public debt accumulation on servicing
costs of public debt. We compare effects of public debt on market interest rates both in the
U.S. and in the European Union. While the U.S. debt and bond-market data at the state level,
as well as pre-EMU European data suggest that financial markets do differentiate among
states/countries with respect to the level of debt. The post-EMU data, though, indicate that the
role of financial markets has diminished as interest rates on most government bonds have
converged. We show, however, that financial markets are sensitive to new fiscal information
as Italy learned in October 2006.
JEL Classification: E6, G15, H63
Keywords: financial markets, fiscal policy, credit rating.
The corresponding author:
Ondřej Schneider
Institute of Economic Studies
Faculty of Social Sciences, Charles University
Opletalova 26, Prague 1, 110 00, Czech Republic
Tel: (+420) 222 112 317
E-mail: schneider@fsv.cuni.cz
Acknowledgements:
Financial support from the IES (Institutional Research Framework 2005-2010,
MSM0021620841) is gratefully acknowledged. We also benefited from earlier studies
supported by a grant from the CERGE-EI Foundation under a program of the Global
Development Network, No. GRCIV-020. The responsibility for all omissions and errors is,
however, solely of the authors.
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I used to think if there were re-incarnation I wanted to come back as the president or the
pope…. But now I want to come back as the bond market. You can intimidate everybody.
James Carville
Former chief strategist to U.S. President Bill Clinton
1. Introduction
Public budgets, namely their deficits remain one of the most intriguing economic
policy issues early in the 21st century. While the 1990s saw a considerable consolidation of
fiscal positions in most countries, the new century has been marked by rapidly deteriorating
fiscal positions in most developed countries. This development is accompanied by the
flouting of fiscal rules by many European governments, chiefly the multilateral stability and
growth pact (SGP), as enacted in 1997 by the European Union (EU) toward European
Monetary Union (EMU). At the same time, financial markets seem to take a benign neglect
approach to high debts of several large (European) countries and do not discriminate against
them by requiring high(er) interest rates on their debt.
In this paper, we focus on the interactions between fiscal policy and financial markets
in multilateral monetary unions, wherein governments relinquish their monetary-policy
capacity. Using a large panel data from the United States, we show that, there, fiscally more
responsible states achieve lower interest rates when they sell their debt on financial markets.
The same effect, albeit a weaker one, is found in European data before the EMU, whereby
excessive borrowing was associated with higher interest rates. However, this relationship all
but disappears after the European countries become members of the EMU. Only recently,
financial markets might have realized different risks associated with holding bonds of
different European sovereigns. It is, however, too early to say whether this represents a new
trend or just a blip in otherwise calm financial markets for government debt in Europe.
The paper is organized as follows: First, we review literature dealing with the financial
markets - fiscal policy relationship. The following chapter empirically analyses market
efficiency in the U.S. bond market and compares it with the EU bond market data before and
after the EMU wake. While this chapter illustrates convergence of bond yields in the EU, the
following chapter shows that the convergence is not guaranteed. We conclude by…
2
2. Financial markets and fiscal policy in a monetary union
As the European Monetary Union (EMU) has been perhaps the most important policy
decision in the international financial markets is the late 20th century, it has attracted attention
of many analysts and researchers. Financial markets may either ignore a government’s debt
level or charge higher interest rates if a government runs excessive deficits. The relationship
between debt and interest rates might be either linear (in which interest rates rise
proportionally with the amount of debt) or exponential (in which interest rates rise rapidly
relative to debt); the latter we refer to as the non-linear relationship. In the first case, fiscal
responsibility rests on the assumption that rising costs of additional debt discourage creditdemanding politicians. In the case of non-linear relationship, credit-demanding politicians
might eventually be denied access to additional credit. As we are concerned mostly with the
monetary-union framework, the literature on monetary-union fiscal policy is the most relevant
to our research.
Earlier literature has, in most cases, found that high government debt does affect yields of
governments’ bonds. Edwards in 1984 found a positive and significant relationship between
debt and yields for 19 developing countries over a five-year period (Edwards (1984)). Cline
and Barnes (1997) confirmed the positive effect of debt on bonds’ spread for emerging
countries in early 1990’s. Catão and Kapur (2004) argue that government bonds’ spreads are
influenced by the level of debt but also its dynamics
Other studies concentrated on bond yield differentials among US states. A study by Bayoumi,
Goldstein and Woglom (1995), as well as a paper by Poterba and Rueben (1997) both found a
positive impact of US state debt on yields. These studies benefited from relatively large
dataset, as the US “monetary union” consists of 50 states with independent fiscal policies.
Alesina at al. (1992) used a narrower dataset when they analysed yields differential among
twelve OECD countries but they came to the same conclusion. Another study of Lemmen
(1999) found the same relationship when it analysed government bond yields of Australia,
Canada and Germany. Ardagna, Caselli and Lane (2004) show that effect of debt may be
nonlinear and more pronounced for countries with above-average level of debt. In the same
vein, Ardagna (2004) argues that yields fall when a country undergoes a substantial fiscal
adjustment and cuts its expenditures.
Another factor influencing yields of government bonds are credit ratings, as they (should)
indicate a country’s ability to service its debt. In an extensive study, Cantor and Packer (1996)
show that credit rankings do influence yields of sovereign debts on a set of 49 countries. More
recently, Kaminsky and Schmuckler (2001) estimated that a one rate credit downgrade
increases average spread of a sovereign bond by 3% (not percentage points).
Bernoth, Schuknecht and von Hagen (2004) then estimated effects of debt levels on risk
premia of European governments. They confirm existence of a strong positive relation
between bond yields and debt level. However, this relation weakens considerably after the
EMU introduction. Bernoth et al. explain the fall in risk premia by increasing liquidity of
financial market at the dawn of the EMU. Bernoth and Wolff (2006) show that the fall may be
also a consequence of higher transparency of fiscal data as it eliminates financial markets’
uncertainity.
Pagano and von Thadden (2004) illustrate increasing integration of financial markets in the
wake of the EMU. They argue that government bonds are not, yet, perfect substitutes as
markets assign different level of fundamental risk to different governments’ bonds. Thus,
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small yield differences may persist. Akitoby and Stratmann (2006) extend their model to a
large set of emerging countries and argue that fiscal policy instruments may influence bond
yields – they increase when government borrows more and they fall when government cuts its
expenditures.
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Table 1: Empirical findings of recent literature on market-based-discipline hypothesis
Paper
Time period and
jurisdictions
Positive relation between
interest rate on government
debt and debt-to-GDP/GSP
ratio (linear)
Relation between interest
rate on government debt
and debt-to-GDP/GSP
squared ratio (non-linear)
Impact of
fiscal rules
Study concerned with
financial-market differentiation
among states in federations or
among countries in monetary
union
Goldstein and
Woglom
(1992)
37 American states,
1982–1990
Yes
Negative, Insignificant
Yes
Yes
Alesina, De
Broeck, Prati
and Tabellini
(1992)
12 OECD countries,
1974–1989
Yes, only for highly
indebted countries or
countries with quickly
growing debt-to-GDP ratio
n.a.
n.a.
No
Bayoumi,
Goldstein and
Woglom
(1995)
38 American states,
1981–1990
Yes
Positive
Yes
Yes
Mattina and
3 Canadian provinces,
Delorne (1997)
1975–1996
Yes
Positive
n.a.
Yes
Alexander and
Anker (1997)
8 EU countries,
1979–1995
Yes
n.a.
n.a.
No
Poterba and
Rueben (1999)
40 American states,
1973–1995
Yes
n.a.
Yes
Yes
States/provinces
within following
countries:
Lemmen
(1999)
Austria, 1990–1996
Yes for all countries
Negative for all countries
n.a. for
Austria and
Germany
Yes
Yes for
Canada
Canada, 1992–1997
Germany, 1994–1996
Lemmen and
Goodhart
(1999)
13 EU countries,
1987–1996
Yes
n.a.
n.a.
No
Copeland and
Jones (2001)
5 EU countries,
1997–1999
Yes for Italy
n.a.
n.a.
No
Codogno,
Favero and
Missale (2003)
11 EMU countries,
1995–2002
n.a.
n.a.
Yes
Ardagna
(2004)
16 OECD countries,
1960–2002
Yes
n.a.
n.a.
No
Bernoth, von
Hagen and
Schuknecht
(2004)
13 EU countries,
1991–2002
Yes, lower for the postEMU period
n.a.
Yes
Akitoby and
Stratmann
(2006)
31 Emerging market
countries, 1994–2003
Positive
n.a.
n.a.
No
Bernoth and
Wolff (2006)
14 EU countries,
1991–2005
No
n.a.
n.a.
Yes
Yes in some countries
No evidence of EMU break
Negative, pre-EMU
Positive, post-EMU
Some basic findings of recent empirical literature on the market-based-discipline
hypothesis are described in Table 1. The second column of the table refers to the countries
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and the time period under consideration, and the third and fourth columns describe the
findings of respective studies’ preferred specifications concerning linear and non-linear
relationships between interest rates on government debt and relevant GDP/GSP ratio. The
fifth column describes whether the respective studies estimated the impact of fiscal rules
(when applicable, appropriate fiscal rules have in general been found to decrease the
borrowing costs of governments). The sixth column simply states whether the respective
study was concerned with market-based discipline within a monetary union or federation.1
Some evidence of market-based fiscal discipline was identified in the empirical
literature we surveyed. Nevertheless, whether financial markets are able to induce sufficient
discipline in governments remains unclear, if not unlikely. There seems to be evidence that
financial markets require higher default premiums for countries or states (even within
federations and monetary unions) with high debt-to-GDP/GSP ratios. On the other hand,
evidence that governments might eventually become credit constrained is rather mixed.
3. Efficiency of the bond markets: An empirical investigation
Let us now turn our attention to the interplay between fiscal policy and financial
markets’ assessment of government debt. Moreover, we are interested in fiscal policy within a
monetary union, as one country’s irresponsible fiscal policy might pose extra costs for others
in the union. High public debt in one country could raise union-wide interest rates, either
through a crowding-out or risk-premium effect, exerting a negative externality on other
members.
As Goldstein and Woglom (1992) and Bayoumi, Goldstein, and Woglom (1995) note,
there are generally three approaches to fiscal discipline within monetary unions. The first, as
stressed in the 1989 Delors Report calls for strict fiscal rules as a means to constrain national
governments. The second approach, proposed by the European Commission (1990a, 1990b),
calls for external fiscal rules in the form of multilateral surveillance and peer pressure. The
third approach, market-based fiscal discipline, is based on the idea that financial markets are
able, willing, and informed enough to be able to credit-constrain irresponsible governments,
so there is no need for intergovernmental interventions.
For this approach to work, there are four additional conditions, namely (i) capital must
be able to move freely, (ii) full information must be available to sovereign borrowers, (iii)
financial markets must be convinced that there are no implicit and explicit guaranties on
government debt and that it will not be monetized, and (iv) the financial system must be
strong enough to withstand a default of a large borrower.
As we are eventually interested in the European bond market we treat the US market
as a benchmark study. There are, surely, differences between the United States and the
European Union with respect to the market-based-discipline hypothesis. First, the United
States is a fiscal federation in which the federal budget ensures income-variation
smoothening. Although original estimates of the extent of such smoothing in the United States
by Sala-i-Martin and Sachs (1992) and by Bayoumi and Masson (1995) were revised by Fatás
(1998), it seems reasonable to expect that the EU is less federalized than the United States.
1
We believe that federated states offer a very close approximation of monetary unions, and, therefore, that the
findings concerned with the behavior of relevant variables within federal nation states should offer clues toward
answering questions about the nature and behavior of relevant variables within monetary unions.
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Still, the US and EU bond markets are very similar in size and structure, as witnessed by the
table 2.
Table 2: The size of government bond market
Outstanding stock in billion of US dollars
1998
3474
3347
2709
Euro 11
United States
Japan
Face value
2000
2834
2993
3627
2002 †
2900
2438
4115
Market value
1998
2000
2266
2430
1838
1740
1282
1733
Source: BIS; OECD; European Commission; Schroeders Salomon Smith Barney.
†
Projection based on OECD projections of central government deficits.
Second, the number of countries involved in the EMU is much lower than the number
of states in the American federation. Therefore, financial markets might expect an individual
EU country to have greater weight within the EMU, i.e., financial markets might expect a
higher probability of bail-out in EMU than in the United States, which renders market-based
discipline ineffective, and which might offer an additional rationale for the imposition of
some form of fiscal rule.
Third, another feature of federal government in the United States is that there is a
certain degree of automatic fiscal smoothening, regardless of individual state involvement. On
the other hand, there is no international fiscal redistribution within the European Union, so
differences in the business cycle within the EU have a greater impact on the public budget
balance than they would in the United States. Thus, European countries may find useful a
fiscal rule that compels individual country’s to coordinate their fiscal-policy stances, at least
partially.
3.1. The US Model
Our hypothesis is that the risk premium required by financial markets is positively
correlated with the level of public debt in individual U.S. states and European countries. We
thus investigate the hypothesis that financial markets are rewarding fiscally responsible
states/countries with increased access to financial resources at lower costs.
However, we would like to isolate the effect of rising public debt levels on the risk
premium required by financial markets from other sources of variations, such as the economic
cycle, variations in the yields of other investment instruments or special provisions, and, in
the US regression, the limitations of individual American states with respect to their spending
and taxing powers.
We use the following model, which captures the major factors that influence the
borrowing costs of U.S. states.
INTi ,t   i   1  INFt   2  GSPi ,t   3  UN i ,t   4  DEBTi ,t 
  5  TRANFS i ,t   6  SPEi ,t   7  REVi ,t   8  SUPi ,t   9  FEDt   i ,t
In the ideal case, dependent variable in the model would be the interest rate
governments of U.S. states would have to pay on their debt. However, as Bayoumi, Goldstein,
and Woglom (1995), and Poterba and Rueben (1999) have noted, such data are not easily
obtainable for several reasons. First, there is limited trading in most state bond issues. Second,
state bonds differ widely in their call provisions and in other detailed provisions. Third, many
7
state bonds are sold in bundles, making it difficult to estimate the yield to maturity on a single
issue.
We deal with this problem in a rather simple way. With data on state expenditures on
interest payments and overall state debt, we calculated the ratio of the two. This ratio roughly
measures the cost each state (denoted by subscript i ) has to pay on each dollar of debt in a
given year (denoted by subscript t ). This is our first dependent variable, INT (1) i ,t .
Our second dependent variable, INT (2) i ,t , comes from the Chubb Relative Value
Study.2 The Chubb Corporation, a U.S. insurance company based in New Jersey, has since
1973 conducted a semi-annual survey among municipal bond traders who are asked to give
the yield on 5-, 10-, and 20-year maturity general obligation bonds for 39 American states
relative to New Jersey. Data from this survey helps to overcome the problem of the direct
comparability of yields on the general obligation bonds of different states since they refer to a
hypothetical bond, and therefore differences in yields should reflect the different position and
credit-worthiness of individual American states, not the special provisions concerning their
bonds. Since the survey is conducted semi-annually, we average the data for each year to
comply with the rest of our data set, which comprises annual data.
Some important differences between our two dependent variables are worth
mentioning. Our first dependent variable, interest payments over debt ratio is rather a measure
of past decisions, past development of borrowing, and reflects the fact that government
revenues fall behind expenditures. Data from the Chubb survey, on the other hand, captures
the credit-worthiness of each state government as a borrower, market valuations of state
willingness and ability to raise revenues in order to repay debt, and market valuations of state
ability to cope with unpredictable events.
Our set of independent variables includes: a state-specific intercept,  i ; the nationwide change of the consumer price index (to capture a notion of expectations based on past
experience, inflation is lagged by one year in our specification), INFt ; the percentage growth
of product of a given state in a given year, GSPi ,t ; the unemployment rate in a given state and
year, UN i ,t , public debt expressed as a percentage of GSP in a given state and year, DEBT i ,t ;
the amount of transfers from the federal government to the given state expressed as a
percentage of its expenditure in a given year, TRANSFi ,t ; three dummy variables, which take
on value of 1 if a given state in a given year had a special provision limiting expenditures,
SPE i ,t , revenues, REV i ,t , or enacting new taxes, SUPi ,t ; and the yield on federal ten-year
constant-maturity securities in a given year, FEDt .
The sign and value of  4 determines whether the market-discipline hypothesis is valid
or not. In the event that  4  0 , financial markets are not able to discriminate between
fiscally prudent and irresponsible governments. Conversely, when  4  0 , financial markets
do punish those government that borrow heavily.
2
The same data were used by Goldstein and Woglom (1992), Bayoumi, Goldstein, and Woglom (1995) and
Poterba and Rueben (1999).
8
3.1. The EU Model
We checked similar hypothesis using data for 14 old EU member countries
(Luxembourg was left out due to unavailable data). ANY DISCUSSION OF THE DATA
USED? Given findings of papers from our survey, we did not expect any strong impact of
government debt on interest rates. We used the same variables as in the US model, namely
coefficients 1   4 are defined exactly as in the US model. To capture the impact of fiscal
rules, we use sum of indexes from Hallerberg, Strauch and Hagen (2001) showing strength of
finance minister during budget preparation and implementation stage. To capture impact of
parliament on final budget, which is often taken to be adverse to fiscal outcomes, we subtract
index of parliament influence from the same source. We multiply index of fiscal rules by
government debt variable because fiscal rules might be more important when government
debt is high. Whenever the resulting coefficient  5 takes a negative sign, the fiscal rules are
interpreted by the financial markets as a safeguard against exploding debt and thus increasing
probability of a default.
The final EU model then has the following form:
INTi ,t   i  1  INFt   2  GSPi ,t   3  UN i ,t   4  DEBT i ,t   5  FISCALRULE i ,t   i ,t
Our set of independent variables includes: country-specific intercept,  i ; the EU
country change of the consumer price index (as before, inflation is lagged by one year in our
specification), INFt ; the percentage growth of product of a given country in a given year,
GSPi ,t ; the unemployment rate in a country and year, UN i ,t , public debt expressed as a
percentage of GSP in a given country and year, DEBT i ,t ; the index of the fiscal rule strength
multiplied by the level of government debt of a country in a given year, FISCALRULE i ,t .
Similarly as in the US specification, the sign and value of  4 determines whether the
market-discipline hypothesis is valid or not.
4. Results
4.1. The US Model
We use data for all 50 American states from 1978 through 2000 for our first dependent
variable, and data for 39 American states from 1991 through 2000 for our second dependent
variable. The main data source was the Statistical Abstract of the United States, published by
the U.S. Bureau of Census; data about interest rates on federal securities came from the
Federal Reserve Board; and information about spending and taxing limits come from Poterba
and Rueben (1999) and ACIR (1995).
All the data are in a logarithmic form (except for dummy variables and output growth)
so that the estimated coefficients can be interpreted as elasticities. We estimated the relevant
coefficients using panel-data procedure and report the results in the following table.
9
Table 3: Test of the market-discipline hypothesis – US market
Coefficient
First dependent variable,
INT (1) i ,t
Second dependent variable,
INT (2) i ,t
 1 (inflation)
-0.136 (-9.40)
-0.137 (-9.43)
-0.133 (-9.29)
0.029 (1.47)
0.029 (1.48)
-
 2 (GSP growth)
-0.214 (-1.12)
-0.214 (-1.20)
-
-0.504 (-2.30)
-0.504 (-2.30)
-0.579 (-2.70)
 3 (unemployment)
0.117 (4.77)
0.116 (4.75)
0.126 (5.52)
0.087 (3.49)
0.087 (3.59)
0.101 (4.78)
4
(debt-to-GSP ratio)
0.076 (2.37)
0.076 (2.36)
0.076 (2.43)
0.080 (2.35)
0.080 (2.34)
0.078 (2.17)
 5 (transfers from federal)
-0.351 (-6.41)
-0.348 (-6.32)
-0.368 (-7.16)
-0.025 (-0.49)
-0.025 (-0.49)
-
6
(dummy for spending limit)
-0.050 (-1.82)
-0.047 (-1.83)
-
-0.030 (-1.61)
-0.030 (-1.62)
-
7
(dummy for revenue limit)
0.043 (1.23)
0.047 (1.47)
-
0.001 (0.03)
-
-
 8 (dummy for new tax limitations)
0.016 (0.45)
-
-
0.041 (1.87)
0.042 (2.13)
-
9
0.179 (5.36)
0.179 (5.37)
0.164 (5.60)
0.047 (1.19)
0.047 (1.19)
0.100 (2.53)
0.31
0.31
0.30
0.85
0.85
0.85
1100
1100
1100
390
390
390
(interest on federal securities)
R2
Number of observations
Notes: Data span from 1978 through 2000 for first dependent variable and from 1991 through 2000 for second
dependent variable. Values of heteroskedastic-consistent t-statistics are in parentheses. Both models estimated by
fixed effect procedure (unambiguously suggested for INT(1) variable by Hausman test and not yielding
significantly different results for INT(2) variable).
As one might expect,  2 has a positive and  3 a negative sign since favourable
economic development lowers the borrowing costs of governments.
The sign and value of  4 determines whether the market-discipline hypothesis is valid
or not. If  4 were non-significant, financial markets would not be able to discriminate
between fiscally prudent and irresponsible governments. But  4 is positive, which means that
we cannot reject the market-based fiscal discipline hypothesis. The model yields the same
magnitude of estimated variable for the debt-to-GSP ratio, and basically the same significance
level across the specifications. Nevertheless, the coefficient  4 is relatively low compared to
other coefficients of significant variables.
A few other things ought to be mentioned. First, notice in Table 3 the difference
between the coefficients associated with inflation for the first and second dependent variable.
We interpret this given that our first dependent variable, as previously mentioned, is rather a
past-oriented concept, and therefore the negative coefficient captures inflation tax
phenomenon. On the other hand, positive coefficient estimates, based on financial-market
data, a future-oriented concept, captures the attempt of lenders to secure their real interest
rates.
Second, notice that for our first dependent variable, an estimated coefficient for a
dummy variable describing the limitation of government to enact new taxes, is highly
insignificant (therefore, we excluded it in the second column, and, in the third column, we
excluded all remaining insignificant variables). This is consistent with the positive coefficient
for revenue limitations, which yield higher debt-servicing costs simply because governments,
instead of being able to raise revenues, resort to the debt financing of their activities.
10
This brings us to the third point. Notice that the dummy variable for revenue
limitations is insignificant in the model with market-survey data. This is consistent with the
idea that financial markets are not concerned with governments’ overall limitations on
revenue, but that they are concerned with their ability to raise additional revenue through new
taxes.
Last, notice the difference in significance in the coefficient for transfers from the
federal government. Significant estimates for our first dependent variable reveal that higher
federal transfers allow state governments to rely less on debt financing; nevertheless, this is
not taken in account by financial markets, which are concerned primarily with governments’
ability to find additional funds for debt repayment.
4.2. The EU Model
The results for the European regression are summarised in the table 4 below. Data we
use span 1980 through 2004 period and come from the AMECO database. Similarly as for the
US model, we use logarithms (except for dummy variables and output growth). In this case
we use between panel regression procedure. Reason is that had we used fixed effects
estimation, coefficient on government debt would be significantly negative. This is given by
the fact that fixed effect estimation uses only within-country variation. Estimate is then
dominated by two developments. On the one hand, government bond yields markedly
declined during the pre-EMU period. On the other hand, debt levels remained more or less the
same or even increased. For that reason, we think between regression is more appropriate for
the EU model.
Estimates in first two columns of table 4 support literature conclusions that it is
extremely hard to find any significant impact of rising government debt on interest rate. In
other words, there is little evidence of financial market based discipline. If anything,
government debt variable comes closest to statistical significance in third column of table 4
where pre-EMU data are used (p-value 0.36). Notice also in general no significance of
multiple of government debt variable with fiscal rules index.
Another thing to notice is considerable drop in explanatory power of the model in last
two columns where we use data from year 1998 on, in other word since establishment of
common European currency. Drop in explanatory power is given mainly by convergence of
government bond yields in European countries (see chart 1). Macroeconomic coefficients do
not diverge widely from the US regression using the Chubb Relative Value Study data.
11
Table 4: Test of the market-discipline hypothesis – EU market
Coefficient
Whole sample
2.629
2.607
(11.1)***
(10.6)***
0.244
0.243
(4.77)***
(4.62)***
Constant
 1 (inflation)
Before EMU
3.154
3.114
(10.5)***
(10.5)***
0.364
0.361
(5.38)***
(5.46)***
After EMU
1.675
1.683
(13.7)***
(12.5)***
0.024
0.026
(0.82)
(0.81)
-0.868
(-0.54)
-0.728
(-0.44)
-1.767
(-0.63)
-1.691
(-0.62)
0.452
(0.54)
0.375
(0.40)
 3 (unemployment)
0.087
(1.59)
0.093
(1.63)
0.158
(1.74)
0.169
(1.89)
-0.005
(-0.17)
-0.005
(-0.18)
4
0.028
(0.45)
-0.010
(-0.12)
0.095
(0.97)
-0.015
(-0.11)
0.035
(1.09)
0.041
(0.98)
-
0.006
(0.68)
-
0.018
(1.19)
-
-0.001
(-0.24)
0.79
0.80
0.83
0.85
0.26
0.26
200
200
103
103
83
83
2
(GDP growth)
(debt-to-GDP ratio)
 5 (debt-to-GDP ratio * fiscal rule)
R2
Number of observations
Notes: Dependent variable is government bond yield at yearly frequency. Data span from 1980 through 2004 for
14 ‘old’ EU member countries (except Luxembourg). EMU break year is 1998. Estimated by between
regression. ***, **, * significant at 1%, 5% and 10% respectively.
Chart 1: Government bond yields in old EU member countries
24
20
16
12
8
4
0
80 82 84 86 88 90 92 94 96 98 00 02 04
Source: AMECO database
5. Sovereign debt ratings and bond yields
There is another way how to test the hypothesis whether markets are or are not able to
distinguish responsible from irresponsible governments. We collected the credit ratings of
individual American states from 1995 through 2004 as conducted by major rating agencies
12
and calculated its correlation with a fiscal variable of our concern––the debt-to-GSP ratio of
individual states.3
Table 5: Correlation of state debt (expressed as % of GSP) with the US state rating
Standard & Poor’s
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
0.23 0.31 0.30 0.37 0.39 0.37 0.30 0.17 0.30 0.27
Moody’s
0.39
0.44
0.44
0.45
0.34
0.32
0.24
0.22
0.34
0.26
Fitch
0.34
0.39
0.39
0.40
0.32
0.31
0.18
0.19
0.35
0.14
Notes: The average number of rated states was 42 by Standard & Poor’s, 40 by Moody’s, and 33 by Fitch. The
correlation is of rating with a one-year lagged debt-to-GSP ratio. The test statistics for the hypothesis of
independence ranges, depending on the number of rated states, from 0.29 to 0.38 at a 5-percent significance
level.
Clearly, there is a relation between the rating of an individual state and its debt-to-GSP
ratio. This is consistent with Standard and Poor’s (2004), who state that debt-to-GSP ratio of
individual states is among the criteria which determine the ratings for each state. Since credit
ratings in many cases serve as the primary source of information many lenders acquire about
their perspective investment, it is clear that debt-to-GSP ratio, through rating agencies, is
positively correlated with the borrowing costs any state must face.
But the correlation lessened in years 2001-2002. In that period of time, rating agencies
seemed to be decreasingly concerned about the debt-to-GSP ratio of American states, but the
correlation increased again in 2003 and 2004.
The European Union witnessed similar developments, where bond yields converged
ignoring differences, albeit small, in the EMU members’ ratings – see chart 1 and table 6. The
markets’ sensitivity to the ratings somewhat increased in 2006 as confirmed by a robust
reaction to the Standard & Poor's cut of the long-term sovereign credit rating on the Republic
of Italy to A+ from AA- on October 19, 2006. The agency quoted poor prospects for a
sustained fiscal consolidation program and a lack of fiscal reform in the 2007 budget as
approved by the Italian government whereby a reduction in deficit is to be achieved through
tax increases. The debt ratio will drop only to 105.7% of GDP by 2010, from 107.6% in 2006,
a negligible decrease.
Italy has been an odd EMU member from its inception; as it was never even close to
satisfy its debt criterion. Moreover, Italy has been so far the only EMU member country
whose government officially voiced concerns about the EMU membership. Markets are thus
more sensitive to Italy than to some other EMU members. Indeed, financial markets reacted
swiftly to the downgrade and the Italian government bonds prices fell (and yields increased)
across the yield curve – see chart 2.
3
Since ratings are reported in letterform, we translated them into numerical values. A higher number means a
lower rating. We did not perform regression analysis since credit ratings take on seven different values (nine for
Moody’s) and change discretely.
13
Chart 2: Italian government bond spread vis-à-vis the German bonds (% points)
2Y
3Y
4Y
5Y
6Y
7Y
8Y
10Y
1,2
Italian downgrade
1,0
0,8
0,6
0,4
0,2
0,0
-0,2
1.9.06
8.9.06
15.9.06
22.9.06
29.9.06
6.10.06
13.10.06
20.10.06
Source: Reuters, author’s calculations
The recent developments may thus suggest that the European financial markets’
sensitivity vis-à-vis indicators of fiscal position, including the sovereign bonds rating, may
increase, as the initial hollabaloo of the monetary integration fades. The markets may again
appreciate that countries, even within the EMU, have different associated risks and may
charge different interest rates to them. Table 6 illustrates that as the European Union expands,
and eventually the EMU as well, the heterogeneity of its member countries increases
significantly even when measured by sovereign debt ratings.
Table 6: Standard & Poor's long-term sovereign credit ratings
Austria
Belgium
Finland
Rating of
debt in local
currency
EMU members
AAA
AA+
AAA
France
Germany
Greece
Ireland
AAA
AAA
A
AAA
Country
Outlook
Country
Stable
Stable
Stable
Bulgaria
Cyprus
Czech
Republic
Denmark
Estonia
Hungary
Latvia
Stable
Stable
Stable
Stable
14
Rating of
debt in local
currency
Non EMU members
BBB+
A
A
AAA
A
BBB+
A-
Outlook
Stable
Stable
Positive
Stable
Stable
Negative
Stable
Italy
Luxembourg
Netherlands
Portugal
Spain
Sweden
A+
AAA
AAA
AAAAA
AAA
Stable
Stable
Stable
Stable
Stable
Stable
Lithuania
Malta
Poland
Romania
Slovakia
Slovenia
United
Kingdom
A
A
ABBB
A
AA
AAA
Stable
Stable
Stable
Positive
Stable
Stable
Stable
Source: Standard and Poor’s
6. Conclusion
As discussed above, the European Union, and its monetary integration, present the
most ambitious single-currency project in recent history. If European monetary integration is
successful, i.e. it delivers effective monetary policy, low inflation and stable financial
markets; it will mark the biggest ever voluntary transfer of monetary policy to a supranational
body. However, the EMU’s success is far from foregone conclusion. Perhaps the biggest
threat comes from the fiscal policy which remains the sole macroeconomic tool of national
governments.
It is not surprising then, that national fiscal policies in the EMU diverge, as individual
countries face different challenges in the fiscal policy conduct. In this paper we analysed to
what extent these differences are understood and priced by financial markets. We showed that
the US financial markets do distinguish among US states as borrowers. Every 1% of their
debt/state product share increases yields of the state bonds by some 0,08%.
The European financial markets are much more relaxed in their attitude to the
sovereign debt. As our analysis shows, there is no statistically significant increase in interest
rates when a country increases its debt. Thus, the European financial markets might have been
lulled by the monetary integration of the, so far, thirtheen European countries.
We illustrated that this lull may come to an end, as the EMU gets more heterogeneous
and even some “old” members face increasing fiscal problems. Indeed, the financial markets
seemed alarmed by a credit downgrade of the Italian government debt delivered in October.
The bond spreads of the Italian debt (vis-à-vis the German bonds) increased across the yield
curve during October as markets were expecting the downgrade. It remains to be seen whether
the October 2006 developments, namely increasing spreads of the Italian bonds, will represent
just a brief blip, or rather a lasting return to the more vigilant financial markets that wil punish
irresponsible fiscal policies.
15
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