Debt Crisis and Risk Sharing:
The Role of Markets versus Governments
Sebnem Kalemli-Ozcan Emiliano Luttini University of Maryland, CEPR and NBER University of Houston
Bent Sørensen University of Houston and CEPR
November 2012
Abstract
The impact of output shocks on consumption has typically been smoothed by pro-cyclical savings (risk sharing). Governments may perform this role better than private actors during major crises because private agents often are credit constrained in downturns. What happens when governments themselves face limits to borrowing during severe events such as the Euro- zone crisis? We show that Portugal, Italy, Greece, and Spain all have experienced a collapse in total risk sharing because their sovereigns did not save during good times and cannot borrow from international markets during bad times given their unsustainable debt.
JEL #: E2, E6, F15, G15 Keywords: Income Insurance, Capital Markets, International Financial Integration.
1 1 Introduction
“The weather soon turned cold. All the food lying in the field was covered with a thick white blanket of snow that even the grasshopper could not dig through. Soon the grasshopper found itself dying of hunger. He staggered to the ants’ hill and saw them handing out corn from the stores they had collected in the summer. He begged them for something to eat. What! cried the ants in surprise, haven’t you stored anything away for the winter? What in the world were you doing all last summer?
I didn’t have time to store any food, complained the grasshopper; I was so busy playing music that before I knew it the summer was gone.” Aesop.
During periods of severe financial crises, governments and central banks act as lender of last resort. They provide the needed insurance so that consumption will not fall as much as output, enabling agents to enjoy smooth consumption streams. If the governments themselves are in trouble, they may no longer be able to act as ultimate insurance providers. We investigate the risk sharing role of governments and contrast this to the role played by markets among OECD countries since late 1990s. The role of governments in providing risk sharing is an important policy issue because many have advocated the establishment of single currency and an integrated pan-European financial markets on the basis that this process will render a fiscal union unnecessary because, in theory at least, perfect risk sharing can be achieved through integrated financial markets, without a need for
fiscal transfers.1
In this paper, we measure how risk sharing was provided during the decade following the intro- duction of the euro. We estimate risk sharing for the sub-periods 1999-2007, 2008-2009, and 2010.
We find that, overall, risk sharing in the EU was significantly higher during 2008-2009 than it was during the earlier period, but risk sharing more or less collapsed in 2010. This pattern holds for
PIGS (Portugal, Italy, Greece, and Spain) and non-PIGS (Austria, Belgium, Finland, France, Ger- many, Ireland, and the UK). When we focus on risk sharing through government savings following the onset of the Great Recession, we find that risk sharing from public saving declined steeply for
1Mundell (1961) states four criteria for an optimal currency area to work: 1) Labor mobility, 2) capital mobility, 3) risk sharing as automatic fiscal transfers, 4) similar business cycles. The Delors Report (1988) argues that an integrated financial market which will result from a single currency will achieve third goal. Jacques Delors and his Commissioners are considered to be the“founding fathers” of the euro.
2 the PIGS which are facing sovereign debt crises. This lead to much lower overall risk sharing in these countries which, therefore, suffered large consumption declines in 2010. Although risk sharing from public saving declined for all countries, for the PIGS countries, in particular, the contribution from public saving turned negative; i.e., the austerity programs in these countries forced increased public saving at a time when output was falling.
The relevant literature is segmented into two groups of papers: 1) Theoretical modeling and empirical testing of full risk sharing benchmark and 2) Modeling and testing optimal sovereign debt holdings, where the trade-off is between repaying debt and defaulting. These papers are mainly concerned with tranquil times and not with financial crises. The first group of papers model risk sharing as achieved via complete markets through Arrow-Debreu securities, whereas the second group of papers follow the classic framework of Eaton and Gersovitz (1981), where risk sharing is limited to one period bonds and repayment is enforced by a reputational constraint and the threat of financial autarky.
Both groups of papers fail to match the data in the following sense. The data rejects full risk sharing both at the micro and the macro level. This result has been interpreted as evidence for incomplete markets. The data also reveals many chronic and frequent sovereign defaults, where the models in the framework of Eaton and Gersovitz (1981) imply few defaults, almost none. As a result, the risk sharing literature moves forward, modeling and testing the degree of incompleteness in asset markets asking how much is the deviation from the full risk sharing benchmark? In a similar vein, the sovereign debt literature tries to improve on predictive ability by trying to increase the cost of shocks.2 Our paper sits at the junction of these still segmented literatures on risk sharing and sovereign debt. We investigate the risk sharing provided by governments and markets during crisis times and contrast the findings with risk sharing during tranquil times.
Let us provide some more details. The extent of international risk sharing has been studied both at the business cycle frequency and at the annual frequency. Such studies give an idea about the extent of risk sharing in the short run and in the long run but remain silent on the risk sharing achieved during major crisis events. Identical consumption growth rates in all countries are usually
2See Arellano (2008), who introduced output costs, and Aguiar and Gopinath (2007), who introduced permanent shocks into the standard models.
3 considered the hallmark of perfect risk sharing. In the one-good Arrow and Debreu model, this is an equilibrium outcome assuming consumers have identical CRRA utility functions and access to a complete set of Arrow-Debreu securities.3 The empirical implication is that consumption in each country is a constant share of aggregate consumption. Starting with Mace (1991), the literature generally tests whether or not the growth rates are identical, where a rejection implies lack of perfect risk sharing. Mace (1991) uses household-level data. Obstfeld (1994) performs a similar exercise using country-level data. Both papers reject full risk sharing. A parallel literature, that started with the influential work of Backus, Kehoe, and Kydland (1992), compares correlations of consumption growth and output growth arriving at a similar conclusion of no risk sharing.4
The above literature tests the existence of full risk sharing against the null of none and hence not helpful in evaluating the amount of risk sharing during a financial crisis. The new theoretical literature changes the set up to incomplete markets in order to match the data better.5 Although this literature is helpful in shedding light on type of frictions limiting the international capital mobility, it still cannot match the actual amount of risk sharing achieved in international markets through the increase in foreign assets and liabilities (or decreased home bias).6 In order to undertake such a task, we follow the methodology of Sørensen and Yosha (1998) who decompose the amount of risk sharing into its channels as provided by markets and by governments. They found risk sharing provided by governments and, in particular, markets to be low during normal times using country level data.7 However, Asdrubali, Sorensen and Yosha (1996), who also decompose risk sharing into channels such as market-provided and government-provided risk sharing, showed that markets provide more risk sharing (60%) than the federal government (20%) for U.S. states 1963–1990.
Kalemli-Ozcan, Sørensen, and Yosha (2003) showed that markets provide a similar amount of risk sharing within European countries (such as regions of Italy and regions of Germany), but much less (around 5%) when we measure risk sharing between EU countries before the introduction of euro. Kalemli-Ozcan, Sørensen, and Yosha (2001) show that risk sharing among European Union
3See Obstfeld and Rogoff (1996). 4See Lewis (1996) and Courdacier and Rey (2012) for extensive reviews. 5See Bengui, Mendoza, and Quadrini (2012) for a recent example and references therein. 6See Benigno and Kucuk (2011) for a similar criticism. 7Notice the difference in spirit of these exercises. Empirical papers, such as Sorensen and Yosha (1998), measure the amount of risk sharing and put a number on the amount of risk sharing and track this through time during the globalization process. The quantitative DSGE literature calibrates the model to see if there is a good match with actual variances and covariances of consumption and output in aggregate data.
4 (EU) countries have increased in step with the introduction of the euro for the Euro-zone countries.
Demyanyk, Sørensen, and Ostergaard (2007) and Kalemli-Ozcan, Papaioannou, and Peydro (2010)
find that this increase in risk sharing is mainly due to the increased cross-ownership of financial assets (banking in particular) for EU countries.
The debt crises literature focuses on why crises and defaults occur and how recoveries take shape.8
Traditional models assume government bonds are held by foreigners and repayment is enforced given the reputational constraints and market exclusion in the absence of repayment, see Eaton and Gersovitz (1981).9 In these type of models, international debt serves as insurance because the demand for international loans derives from a desire to smooth consumption. Otherwise the country must resort to other methods for consumption smoothing or it must accept greater fluctuations in consumption. The sustainable levels of foreign debt are higher, the greater the exclusion cost from the markets, which in turn is higher if domestically available options for consumption smoothing are limited and the world interest rate is low.
Given the failure of these models in predicting enough defaults, Arellano (2008) and Aguiar and Gopinath (2007) try to improve predictive ability by increasing the cost of default and loss of risk sharing. In Aguiar and Gopinath (2007), the productivity process is characterized by a volatile stochastic trend as opposed to transitory fluctuations. The main motivation for this is that the welfare gains from smoothing transitory shocks to consumption around a stable trend are small. They show that this in turn prevents lenders from extending debt. They find realistic levels of defaults by adding a loss of output in autarky, substituting permanent for transitory shocks, and introducing a third-party bail-out mechanism. In related work, Amador, Aguiar and Gopinath
(2009) show that including government impatience and inability to commit into a standard sovereign debt model generate realistic cycles in sovereign debt and foreign investment because debt overhang effects foreign investment negatively. The testable empirical implication of such models is that the risk sharing that is achieved via markets through the use of assets such as FDI and portfolio investment will be reduced by high levels of debt.
8See Reinhart and Rogoff (2009). 9Gertler and Rogoff (1990) question this result as an equilibrium by showing that countries’ financial institutions shape their borrowing by affecting the share of output that can be pledged as collateral to foreigners.
5 A recent focus of the sovereign debt literature is the failure to explain the joint decision of holding sovereign debt and accumulating international reserves which has characterized the development of global imbalances since the late 1990s. Any reserve accumulation in these models reduces the level of sustainable debt due to willingness-to-pay type incentive problems. The recent work that tries to incorporate both reserve accumulation and optimal sovereign debt holdings find that it is difficult to explain the build-up in reserves as insurance against risk of financial crisis.10 This is intuitive, because sovereign countries can reduce the level of sovereign debt if they want to decrease the probability of the crisis. One might argue that reserves might have liquidity benefits which will alleviate the output costs but same thing and a lower probability of crisis can all be achieved via a net asset position by reducing the level of foreign debt.
A final related strand of the literature develops models that investigate the welfare implications when both financial markets and sovereigns are in crisis. Gennaioli, Martin, and Rossi (2010) develop a model where sovereign defaults weaken banks’ balance sheets because domestic banks hold the sovereign bonds, yielding a complementarity between domestic credit and public debt.
The empirical literature on this topic is sparse. Reinhart and Rogoff (2010) document that private and public financial crises occur at the same time. They explicitly show that private debts surge before banking crises, that banking crises precede sovereign debt crises, and that public borrowing accelerates ahead of sovereign debt crises.
To the best of our knowledge, there is no paper in the literature that simultaneously measures the risk sharing role of market based assets and sovereign debt holdings during major financial crises. Our paper can be seen at the junction of the above literatures because it investigates the effect of banking and sovereign debt crisis on risk sharing by decomposing the risk sharing into components provided by government and markets. We will also examine if the risk sharing that is provided by markets suffer due to the unsustainable sovereign debt holdings (comparing PIGS and non-PIGS in 2010). We start by presenting our methodology followed by a description of our data.
We then move on to the empirical analysis and conclusion.
10See Ghosh and Ostry (1997), Durdu, Mendoza, and Terrones (2009), and Alfaro and Kanczuk (2009).
6 2 Methodology: Measuring Risk-Sharing
We estimate overall risk sharing and decompose the amount of risk sharing into contributions from net foreign factor income and saving. We further decompose the risk sharing from saving into contributions from corporate saving, household saving, and government saving. Intuitively, a component, say, government saving, provides risk sharing if it is positive, absorbing income, when Gross Domestic Product (GDP) increase and negative, releasing income, when GDP growth is negative.11
In a one-good economy with perfect Arrow-Debreu markets and agents having identical Con- stant Relative Risk-Aversion utility, consumption growth is the same in all countries and con- sumption should not correlate with anything, in particular country-level income, after world-wide consumption—captured by time-fixed effects—are controlled for. We take GDP growth as exoge- nous in our accounting exercise. We measure lack of risk sharing, following Mace (1991), from the estimated coefficient from a regression, including time-fixed effects, of consumption growth on GDP growth. We refer to this coefficient as the un-smoothed fraction of GDP. We measure smoothing from net international transfers from the degree to which the correlation of Gross National Income
(GNI) growth with GDP growth is less than unity after having controlled for time-fixed effects.
We measure smoothing from saving by measuring the extent to which the correlation of consump- tion growth with GDP growth is less than the correlation of GNI growth with GDP growth. Our measures roughly satisfies that smoothing from net factor income flows plus smoothing from saving plus the un-smoothed fraction adds up to unity.
More explicitly, consider regressions of the form:
k k k ∆GDPit − ∆GNIit=αt + β ∆GDPit + it ,
s s s ∆NNDIit − ∆cit=αt + β ∆GDPit + it , 11We do not perform a full decomposition of risk sharing, see Sørensen and Yosha (1998), because the contribution from the left-out components of the national accounts, depreciation and international transfers, are mechanically imputed and negligible in our sample, respectively.
7 u u u ∆Cit=αt + β ∆GDPit + it
where GDPit, GNIit, NNDIit, Cit are for the log of country i’s year t per capita gross domestic product, gross national income, net national disposable income and consumption, respectively. The first two regressions can alternatively be written as
k kt k ∆ log(1 − NFIit/GDPit) = αt + β ∆GDPit + it (1)
s st s ∆ log(1 + Sit/Cit) = αt + β ∆GDPit + it , (2) which highlight how income and consumption smoothing, if any, are obtained through counter- cyclical foreign net factor income (NFI = GDP − GNI) and pro-cyclical total saving (S = NNDI −C).
A negative (positive) value of the coefficient βk measures the extent to which consumption smoothing (dis-smoothing) is reached by mean of net income from abroad. Moreover, a positive
(negative) value of the coefficient βs shows how much consumption smoothing is achieved by the economy’s net savings. βu measures the fraction of GDP shocks reflected in consumption; i.e., the fraction of risk un-smoothed.
The coefficients are allowed to vary by sub-periods, in particular we focus on the period before the crisis, 2000-2007, the peak of the financial crises, 2008-2009, and the year available so far of the sovereign debt crisis in Europe, 2010.
We estimate panel data regressions of the form:
u 00−07 08−09 10 ∆Cit = αt + β1 ∆GDPit∗D +β2 ∆GDPit∗D +β3 ∆GDPit∗D + it , (3)
where the dummy variable D00−07,D08−09, and D10 take the value unity for years 2000-2007, 2008-
2009, and 2010, respectively, and zero otherwise.
We further allow the coefficient to vary between countries with relatively high and low debt, by
8 estimating the regression
u 00−07 PIGS 08−09 PIGS ∆Cit = αt + β1 ∆GDPit ∗D ∗D +β2 ∆GDPit∗D ∗D
10 PIGS 00−07 NPIGS + β3 ∆GDPit ∗D ∗D +β4 ∆GDPit∗D ∗D
08−09 NPIGS 10 NPIGS + β5 ∆GDPit ∗D ∗D +β6 ∆GDPit∗D ∗D + it ,
where DPIGS takes the value unity for Portugal, Italy, Greece, and Spain and zero otherwise, while
DNPIGS takes the value unity for Austria, Belgium, Finland, France, Germany, Ireland, and the UK, and zero otherwise.
00−07 We perform similar regressions with interaction terms of the form β1∆GDPit ∗D +β2∆GDPit∗
00−07 (D ∗GDit−GD) (for each of the three periods we consider). GD captures total net government debt. Government net debt over the period 00 − 07 have been averaged over the countries and year in order to leave the interpretation of β1 unchanged; i.e., the β1 coefficients measures risk sharing during 2000-2007 for an average level of debt. We include interactions for the other time periods and also for total foreign debt but we abstain from displaying the long formula including all terms.
The amount of smoothing obtained from pro-cyclical saving, βst can be broken down into smooth- ing obtained via government, corporate, and household saving. In order to make the breakdown independent of the order in which we consider these components of saving we linearize. The OLS
s cov(∆NNDI−∆C;∆GDP) formula for the coefficient is β = var(∆GDP) . Now consider
S S ∆NNDI − ∆C=∆ log 1+ it ≈ it Cit Cit
Define Shh, Scp, and Sgov as household, corporate, and government net saving, respectively, then
S = Shh + Scp + Sgov and
Sit cov ∆ C ; ∆GDP βs ≈ it var (∆GDP)
Shh Scp Sgov cov ∆ C ; ∆GDP cov ∆ C ; ∆GDP cov ∆ C ; ∆GDP = it + it + it var (∆GDP) var (∆GDP) var (∆GDP)
9 = βHh + βCorp + βGov .
where βHh, βCorp and βGov estimates the fraction (of GDP shocks) insured through pro-cyclical household, corporate, and government saving, respectively. We estimate those coefficients by run- ning the panel data regressions with time-fixed effects:
Hh Sit Hh Hh Hh ∆ = αt + β ∆GDPit + it , Cit
Gov Sit Gov Gov Gov ∆ = αt + β ∆GDPit + it , Cit
Corp Sit Corp Corp Corp ∆ = αt + β ∆GDPit + it . Cit
3 Data
To carry out our empirical exercise we make use of OECD data. In particular, Gross Domestic
Product, Gross National Income, Net National Disposable Income, (public plus private) consump- tion, corporate, households and government savings were taken from the annual national accounts main aggregates, detailed tables and simplified accounts sections; CPI and nominal exchange rates come from the prices and purchasing power parities statistics, while the population of the coun- tries were provided by the demography and population statistics. In order to make comparable our data across countries and time, Gross Domestic Product, National Income, Disposable Income, consumption, corporate, household and government savings were transformed in real per capita units expressed in 2005 dollars.
In order to perform the augmented regressions by government and external debt variables we use data provided by the World Economic Outlook (WEO) and the European Central Bank (ECB).
In particular, the data on government debt is net government debt (percentage of GDP) from
10 the WEO, where this variable is defined as gross debt of the general government sector minus its
financial assets in the form of debt instruments.12 The data on external debt is the outstanding amount of the financial account of the balance of payments statistics at the end of fourth quarter of each year from the ECB data warehouse.13
Finally, the countries included in our sample are Austria, Belgium, Denmark, Finland, France,
Germany, Greece, Ireland, Italy, the Netherlands, Portugal, Spain, Sweden and for the period
1999-2010.
4 Empirical Analysis
4.1 Graphical exposition
Our story can roughly be told from figures. Figures 1a and 1b, for PIGS and non-PIGS, respec- tively, display GDP growth in percent year-by-year and split the annual amount in the change in consumption (as a share of GDP), which we interpret as risk not shared and the remainder which we interpret as the fraction of GDP risk shared. The figures don’t literally tell a story about risk sharing because there is no adjustment for the aggregate non-insurable component, but the prima facie evidence displayed holds up in the empirical analysis in the next sub-section.
From the pictures, most risk is not shared, although non-PIGS countries shared a non-negligible amount of risk during 2000-2007 while the PIGS shared little risk in those years, in the good year
2006 consumption increased faster than GDP leading to “negative risk sharing.” From 2008 on, it appears that the major amount of risk is shared for non-PIGS while the amount of risk shared in the bad year 2008 is over 100 percent (positive consumption growth in spite of negative GDP growth) for the PIGS, the fraction of risk shared become smaller in 2009 and, in particular, in 2010.
12The WEO defines general government gross debt as all liabilities that require payment or payments of interest and/or principal by the debtor to the creditor at a date or dates in the future (this includes debt liabilities in the form of SDRs, currency and deposits, debt securities, loans, insurance, pensions and standardized guarantee schemes, and other accounts payable). In addition, financial assets in the form of debt instruments include currency and deposits, debt securities, loans, insurance, pension, and standardized guarantee schemes, and other accounts receivable. 13The series were incomplete for France and Belgium, in both cases we filled the missing values with data from Lane and Milesi-Ferretti (2007) (http://www.philiplane.org/EWN.html)
11 Figures 2a and 2b compare the changes in GDP into changes in foreign net factor income, corpo- rate saving, government saving, household saving, and consumption—all as shares of GDP. Shares which are on the same side of the X-axis as GDP growth contributes to smoothing income. We see, for non-PIGS, the dominant role of government saving in smoothing consumption, with negative saving during 2001-2003 and 2008-2009 , and positive saving 2004-2007. Government saving is pos- itive in 2010 but very close to zero, reflecting budget tightening in response to heavy government debt burdens. Corporate debt provides a lot of risk sharing for the non-PIGS countries in the
2008-2010 period while household saving has been counter-cyclical, dis-smoothing consumption.
The most conspicuous feature of Figure 2a is the role of government saving. For the PIGS, almost all risk sharing during 2008 and 2009 was provided by the governments which increased deficits while household and corporate saving increased dramatically in 2009. In 2010, where GDP growth was negative for the PIGS, the sovereign debt crisis forced government savings to dis-smooth as the governments tightened budgets and risk sharing was basically only provided by household saving in 2010. For PIGS, net foreign factor income typically provides risk sharing but its role is dwarfed by the savings components.
Figures 3a and 3b show net government debt and net external (foreign) debt for PIGS and non-PIGS. It is immediately apparent that the governments of the PIGS countries have been more heavily indebted for the full period and, in particular since 2007, the indebtedness of PIGS has increased rapidly. Regarding net external debt, the two groups of countries were at similar debt levels in year 2000 but while net foreign debt has dwindled to nil for non-PIGS it has steadily increase for the PIGS. In year 2010, government debt of PIGS is over 90 percent and net foreign debt is about 80 percent. This is a typical sovereign debt scenario where a heavy government debt burden is reflected in heavy net foreign indebtedness.
Figures 4a and 4b show how international capital flows, for PIGS in particular, are dominated by debt flows. It is clear that before the crisis, during 2001–2007, the increased degree of financial integration has channeled the funds from the European core to the periphery as Greece, Spain,
Portugal, and Ireland—countries which experience productivity booms. However, most of these
flows were in the form of debt, specifically government debt. Nowadays, given the negative shocks
12 to the South, it should not be that surprising that European financiers pull out their capital. This is exactly why southern governments must act as a lender of last resort because private capital can easily depart countries within an integrated union.
4.2 Descriptive Tables
Table 1 shows net government and net external debt by country. As expected, the PIGS are heavily indebted, with Greece having government debt equal to 144 percent of GDP and Italy having debt roughly similar to GDP in 2010. Spain’s net debt is lower than that of many non-PIGS. This indicates that the level of debt is just one of several factors determining sovereign debt crises. Net external debt is at the level of GDP for Greece, Portugal, and Spain, but much lower at 24 percent for Italy. Ireland, is here bundled with the non-PIGS although it has high government and external net debt (and, therefore, often is bundled with the PIGS to comprise the PIIGS). However, in terms of risk sharing patterns, we found that Ireland behaved more like the other countries labeled non-PIGS. The level of net government debt varies widely between the non-PIGS from –21 percent of GDP in Sweden to 80 percent in Belgium in 2010. Net external debt is low for all non-PIGS, apart from Ireland, with Belgium’s net foreign assets (negative debt) at 64 percent of GDP.
4.3 Regression analysis
Table 2 displays average risk sharing by main channels and by the chosen sub-periods. For the
2000-2007 period, 67 percent of shocks are not smoothed while about 34 percent are absorbed by pro-cyclical saving. Net factor income from abroad is insignificant with a negative point estimate.14
In general, it appears that we do not have enough degrees of freedom in our data to pin down risk sharing from net factor income flows well and we will focus on the savings channel in the remainder of this section. At the onset of the crises, 2008-2009, the amount of risk un-smoothed rises to 45 percent due to the role of pro-cyclical saving which now absorb 55 percent of GDP fluctuations.
However, as the sovereign crises raises it ugly head, and even Northern European governments
14Kalemli-Ozcan, Sørensen, and Yosha (2005) finds that risk sharing from foreign factor income turns positive in the Euro-area around the time of the introduction of the Euro.
13 tightens their budgets in 2010, risk sharing collapses as 83 percent of GDP fluctuations are left un-smoothed because the role of saving in risk sharing drop to an insignificant 4 percent. Is this collapse due to changes in the behavior of government savings and it is uniform across PIGS and the other countries? We examine those questions next.
From Table 3, the amount of risk sharing obtained for the PIGS countries was lower during
2000-2007. From the descriptive figures, this reflects that the governments of the PIGS were less likely to save in good time. Since the start of the Great Recession, PIGS have seen very little risk sharing, with the contribution from saving being negative. For non-PIGS, risk sharing was at 53 percent 2008-2009 due to more than half of the GDP fluctuations being absorbed by pro-cyclical saving, although the contribution from saving declined steeply in 2010, leaving 63 percent of shocks un-smoothed.
We decompose the role of saving into the contributions from government, corporate, and house- hold saving in Table 4. The contributions vary a lot over the sample periods in ways that do not have obvious intuitive explanation. The contribution from corporate saving is about half of the contribution from government saving in all subperiods, with both turning negative in 2010, while the contribution from household saving was insignificant before 2008, strongly negative 2008-2009, and positive in 2010. A semi-Ricardian mechanism, with consumers off-setting government saving might be at play, although it is hard to conjecture why corporate saving behaves the way it does.
In Table 5, we split the results of the previous table into PIGS and non-PIGS. For non-PIGS, corporate saving is always pro-cyclical although, due to the low degrees of freedom, the results are somewhat tentative with only one the results for 2008-2009 being significant. The risk sharing from government saving was higher for non-PIGS in the 200-2007 period, highly positive for non-
PIGS 2008-2009 and almost fully off-setting the GDP declines for PIGS 2008-2009, while strongly contributing to negative risk sharing for PIGS in 2010. For PIGS, households were able to dis-save in 2010, resulting in the small amount of overall risk sharing found in Table 3. For non-PIGS, no components of saving contributed significantly to negative or positive risk sharing in 2010.
Table 6 pools the coefficients across PIGS and non-PIGS and asks if risk sharing through gov-
14 ernment and private (household plus corporate) saving is correlated with the level of government and/or external debt. Clearly, high government debt correlated negatively with pro-cyclical gov- ernment saving, the coefficient to the interaction term is significant for 2000-2007 and 2010 but not for 2008-2009 where several highly indebted countries dis-saved, but even for those years the point estimate is negative. The interaction with government debt is not significant for the role of private saving in providing risk sharing. High external debt correlated positively with risk sharing through government saving until 2010. This, likely, should not be interpreted as if external debt is good for risk sharing per se, but rather as a reflection of access to international lending markets being good for risk sharing. However, in 2010 external debt correlates negatively with risk sharing through government saving. External debt correlated negatively with risk sharing through private saving during 2008-2009. During the hight of the Great Recession refinancing of loans became very difficult for private lenders which likely causes the result which we observe. In 2010, it appears that private borrowers again had access to international lending markets while highly indebted governments were shut out. The last two columns of the table confirm those results—the results are not very different when both government and external debt are both included implying that these two types of debt are correlated little enough that their relative roles can be gauged from a multivariate regression.
5 Conclusion
Risk sharing collapsed in Portugal, Italy, Greece, and Spain in 2010. We show that this is the results of government austerity programs which, for these countries, appear to be the effect of reckless borrowing in good times leading to sovereign debt crises in bad times. For other EU countries, the situation is less dire, although risk sharing is presently limited also for this group of countries, many of which have government debt high enough that budgets are being tightened even if these countries do not face outright debt crises.
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18 Figure 1: Risk sharing
(a) Non-PIGS (b) PIGS
0.04 0.03
0.03 0.02
0.02 0.01 0.01
0 0
-0.01 -0.01
Change as a % of GDP -0.02 Change as a % of GDP -0.02
19 -0.03
-0.03 -0.04
-0.05 -0.04 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Year Consumption Risk shared GDP Consumption Risk shared GDP
Notes: Figures 1a and 1b display annual GDP growth and (crisscrossed) consumption growth as a fraction of GDP (∆Ct/GDPt−1), which can be interpreted as the amount of GDP-risk not shared. The difference between GDP growth and consumption growth as a fraction of GDP can be interpreted as the amount of risk shared in a given year. PIGS denotes Greece, Italy, Portugal and Spain, and Non-PIGS denotes Austria, Belgium, Denmark, Finland, France, Germany, Ireland, the Netherlands, Sweden, and the UK. Source: Authors’ own calculations based on OECD data Figure 2: Channels of risk sharing
(a) Non-PIGS (b) PIGS
0.04 0.03
0.03 0.02
0.02 0.01 0.01 0 0
-0.01 -0.01
-0.02 -0.02
-0.03
Change as a % of GDP Change as a % of GDP -0.03 -0.04 -0.04 20 -0.05
-0.05 -0.06
-0.07 -0.06 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Year -NFI Households savings Consumption -NFI Households savings Consumption Corporate savings Government savings GDP Corporate savings Government savings GDP
Notes: The bars in Figures 2a and 2b represent the rate of growth of –Net Factor Income from abroad (defined as Gross Domestic Product minus Gross National Income), government, corporate, and household saving, while the dashed lines represent the rates of growth of consumption and GDP. The height of each bar can be interpreted as the amount of risk shared through a specific factor, and the vertical distance between GDP and consumption as the total amount of risk shared in a given period. PIGS denotes Greece, Italy, Portugal and Spain and Non-PIGS denotes Austria, Belgium, Denmark, Finland, France, Germany, Ireland, the Netherlands, Sweden, and the UK. Source: Authors’ own calculations based on OECD data Figure 3: Government and external debt stocks: Non-PIGS vs PIGS
(a) Net government debt (b) Net external debt
1 1
0.8 0.8
0.6 0.6
0.4 0.4 Net external debt as a % of GDP Net government debt as a % of GDP 0.2 0.2 21
0 0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Year PIGS Non PIGS PIGS Non PIGS
Notes: Net government and external debt are weighted average of net general government and external debt (both as a percent of GDP), respectively, where the weights are the share of each country in aggregate GDP at t − 1 in each group of countries. Net government debt data are from the World Economic Outlook (WEO), while net external debt is the outstanding amount of the financial account of the balance of payments, available from the European Central Bank (ECB). PIGS denotes Greece, Italy, Portugal and Spain and Non-PIGS denotes Austria, Belgium, Denmark, Finland, France, Germany, Ireland, the Netherlands, Sweden, and the UK. Source: Authors’ own calculations based on ECB and WEO data. Figure 4: Government and external debt flows: Non-PIGS vs PIGS
(a) Net government debt flows (b) Net external debt flows
0.1 0.1
0.05 0.05
0 0 Flows as a % of GDP Flows as a % of GDP
-0.05 -0.05 22
-0.1 -0.1
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year Year PIGS-Net government debt flows PIGS-Capital inflows PIGS-Net external debt flows PIGS-Capital inflows Non PIGS-Net government debt flows Non PIGS-Capital inflows Non PIGS-Net external debt flows Non PIGS-Capital inflows
Notes: Net government and external debt flows and capital inflows are weighted averages of the change in net general government and external debt (both as a percent of GDP) and the current account with flipped sign, respectively. Net government debt data comes from the World Economic Outlook (WEO), net external debt is the outstanding amount of the financial account of the balance of payments, available from the European Central Bank (ECB), while the current account data comes from the WEO. PIGS denotes Greece, Italy, Portugal and Spain and Non-PIGS denotes Austria, Belgium, Denmark, Finland, France, Germany, Ireland, the Netherlands, Sweden, and the UK. Source: Authors’ own calculations based on ECB and WEO data. Table 1: Descriptive Statistics: Government and external debt
Government debt External debt 2000-2007 2008-2009 2010 2000-2007 2008-2009 2010 Panel A: Groups PIGS 68.97 80.91 95.59 48.26 74.10 78.91 (5.802) (13.88) (23.48) (4.638) (11.82) (19.89) Non-PIGS 27.92 27.25 35.00 7.638 4.995 -1.091 (3.670) (8.779) (14.85) (2.933) (7.478) (12.58) Panel B: Countries Austria 43.36 45.63 52.45 20.25 12.38 8.112 (2.874) (5.233) . (5.789) (5.658) . Belgium 86.40 76.51 79.78 -37.89 -46.76 -64.32 (2.874) (5.233) . (5.789) (5.658) . Denmark 12.89 -5.303 -1.651 8.341 0.356 -13.18 (2.874) (5.233) . (5.789) (5.658) . Finland -47.46 -57.57 -65.53 44.96 4.830 -11.75 (2.874) (5.233) . (5.789) (5.658) . France 56.38 67.15 76.07 -5.522 11.08 7.827 (2.874) (5.233) . (5.789) (5.658) . Germany 48.09 53.58 56.19 -13.71 -29.50 -34.82 (2.874) (5.233) . (5.789) (5.658) . Greece 94.52 120.8 144.6 65.38 82.81 96.00 (2.874) (5.233) . (5.789) (5.658) . Ireland 21.27 33.30 74.70 16.02 84.22 88.70 (2.874) (5.233) . (5.789) (5.658) . Italy 89.56 92.99 99.10 14.77 24.61 23.82 (2.874) (5.233) . (5.789) (5.658) . Netherlands 25.18 21.90 27.65 7.035 -10.39 -22.60 (2.874) (5.233) . (5.789) (5.658) . Portugal 52.53 73.20 88.89 62.24 102.8 107.1 (2.874) (5.233) . (5.789) (5.658) . Spain 39.28 36.65 49.81 50.66 86.15 88.77 (2.874) (5.233) . (5.789) (5.658) . Sweden -1.910 -15.87 -20.60 20.04 9.776 7.349 (2.874) (5.233) . (5.789) (5.658) . UK 35.04 53.18 70.96 16.86 13.95 23.76 (2.874) (5.233) . (5.789) (5.658) .
Notes: Average values and standard deviations in parentheses. Net government debt data are from the World Economic Out- look (WEO), while net external debt is the outstanding amount of the financial account of the balance of payments, available from the European Central Bank (ECB). Source: Authors’ calculations based on ECB and WEO data.
23 Table 2: Risk sharing channels
NFI (βk) Savings (βs) Unsmoothed (βu) GDP (2000-2007) -6.30 34.2c 67.6c (-.87) (2.64) (7.44)
GDP (2008-2009) 3.89 54.7c 45.2c (.34) (4.67) (3.7)
GDP (2010) -3.24 4.37 82c (-.55) (.46) (6.22) Observations 144 144 144
Notes: The coefficients in the first, second and third column come from k P k running the regressions ∆ log(1 + NF I/GDP )it = αt + βd ∆gdpit × d k s P s s d + it, ∆ log(1 + S/GDP )it = αt + βd∆gdpit × d + it and ∆cit = d u P u u αt + βd ∆gdpit × d + it, respectively, where GDP (gdp) is log Gross d Domestic Product, NFI is net foreign factor income, S is total saving, c is k s u log total consumption and αt , αt and αt control for common shocks across k s countries. A negative and positive value in the coefficients βd and βd, respectively, are interpreted as the percentage of consumption smoothing u obtained through international capital markets and domestic saving. 1−βd is interpreted as the percentage of output shocks smoothed in period d. The three equations were estimated by Generalized Least Squares (GLS) using using annual data 2000–2010. The countries considered in the sample are Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, the Netherlands, Portugal, Spain, Sweden, and the UK. Values in parentheses are t statistics, while a, b, and c denote significance at 10, 5, and 1 percent, respectively.
24 Table 3: Risk sharing channels: Non-PIGS vs PIGS
NFI (βk) Savings (βs) Unsmoothed (βu) GDP (2000-2007) (Non-PIGS) -9.34 38.9c 65.3c (-1.23) (2.92) (6.98)
GDP (2000-2007) (PIGS) 11.2a 6.83 81c (1.69) (0.40) (6.10)
GDP (2008-2009) (Non-PIGS) 4.58 52.8c 46.4c (0.41) (4.87) (3.84)
GDP (2008-2009) (PIGS) 26.7 -7.03 83.8c (1.55) (-0.34) (4.94)
GDP (2010) (Non-PIGS) 1.68 19.9a 66.3c (0.16) (1.75) (3.05)
GDP (2010) (PIGS) -7.88 -10.3 96.8c (-1.39) (-1.47) (8.47) Observations 144 144 144
Notes: The coefficients in the first, second, and third column come from run- k P P k k ning the regressions ∆ log(1 + NF I/GDP )it = αt + βdp∆gdpit × d × p + it, d p s P P s s u ∆ log(1 + S/GDP )it = αt + βdp∆gdpit × d × p + it and ∆cit = αt + d p P P u u βdp∆gdpit × d × p + it, respectively, where d are dummies variables for the periods d p {2000 − 2007, 2008 − 2009, 2010}, p are indicator variables for the groups {PIGS, Non- PIGS} (PIGS denotes Greece, Italy, Portugal and Spain and Non-PIGS denotes Austria, Belgium, Denmark, Finland, France, Germany, Ireland, the Netherlands, Sweden, and the UK) and the remaining variables are defined as those in Table 2. The value of the k s coefficients βdp and βdp, respectively, are interpreted as the percentage of consumption u smoothing obtained through international capital markets and domestic saving. 1−βdp is interpreted as the percentage of the shocks in output that are insured in period d for the group p. The three equations were estimated by GLS using the same sample of countries and period as in Table 2. The values in parentheses are t statistics, while a, b, and c denote significance level at 10, 5, and 1 percent, respectively.
25 Table 4: Savings and risk sharing
Corporate(βCorp) Government (βGov) Households (βHh) GDP (1990-2007) 12.4 23.5b -1.63 (1.1) (2.28) (-0.16)
GDP (2008-2009) 32.5c 64c -41.8c (3.03) (6.54) (-4.35)
GDP (2010) -5.08 -23.8b 33.3c (-0.39) (-2.02) (2.87) Observations 144 144 144
Notes: The coefficients in the first, second, and third column come from SHh it Hh P Hh Hh jointly regressing the equations ∆ = α + β ∆gdpit × d + , Cit t d it d Corp S SGov it Corp P Corp Corp it Gov P Gov Gov ∆ = α + β ∆gdpit × d + and ∆ = α + β ∆gdpit × d + Cit t d it Cit t d it d d Gov Corp Hh s with the constraints βd + βd + βd = βd , respectively, where gdp is the log of Gross Domestic Product, C is the log sum of private and public consumption, SHh, SGov and SCorp are net household, government, and corporate saving, respectively. d are s dummies variables for the periods {2000 − 2007, 2008 − 2009, 2010}, βd is the percentage of consumption smoothing obtained through domestic saving during period d (see Table 2). Gov Corp Hh Gov Corp Hh αt , αt , and αt control for common shocks across time. βd , βd and βd are interpreted as the amount of risk sharing obtained through government, corporate, and household saving, respectively, during period d. The estimation was carried out by Seemingly Unrelated Regressions (SURE) using annual data 2000–2010 and the countries considered are the same as those in Table 2. Values in parentheses are t statistics, whereas a, b, and c denote significance level at 10, 5, and 1 percent, respectively.
26 Table 5: Savings and risk sharing: Non-PIGS vs PIGS
Corporate(βCorp) Government (βGov) Households (βHh) GDP (2000-2007) (Non-PIGS) 16.7 23.4b -1.21 (1.47) (2.32) (-.12)
GDP (2000-2007) (PIGS) -7.89 18.5 -3.8 (-.49) (1.28) (-.26)
GDP (2008-2009) (Non-PIGS) 30.6c 64.5c -42.2c (2.87) (6.79) (-4.46)
GDP (2008-2009) (PIGS) -43.3 a 92.3c -56c (-1.9) (4.54) (-2.76)
GDP (2010) (Non-PIGS) 9.6 8.01 2.29 (.46) (.43) (0.12)
GDP (2010) (PIGS) -15.4 -57.7c 62.8c (-.77) (-3.24) (3.53) Observations 144 144 144
Notess: The coefficients in the first, second, and third column come from jointly regressing the equations Sj it j P P j j ∆ = α + β ∆gdpit×d×p+ for j ={Corporate, Government, Household }, with the constraints Cit t dp it d p Gov Corp Hh s βdp +βdp +βdp = βdp, where d are dummies variables for the periods {2000 − 2007, 2008 − 2009, 2010}, s βdp is the percentage of consumption smoothing reached by the the economy’s savings during period d for the group p (see Table 3) and the remaining variables and coefficients convey the same meaning as those Gov Corp Hh in Table 3 and 4. βdp , βdp , and βdp are interpreted as consumption smoothing reached through government, corporate, and households savings, respectively, during period d for the group p. All of the above parameters were simultaneously estimated by SURE, using the same countries and period as in Table 2. t statistics are in parentheses, while a, b, and c denote significance level at 10, 5, and 1 percent, respectively.
27 Table 6: Savings, government and external debt and risk sharing
Government Private Government Private Government Private GDP (2000-2007) 35.6c 25.7 41.5c 30.3a 35.3c 28.8a (2.92) (1.40) (3.64) (1.85) (3.07) (1.68) GDP (2008-2009) 56.5c -.175 65.2c -.617 58.9c -2.88 (4.61) (-0.01) (6.58) (-0.04) (5.10) (-0.17) GDP (2010) -16.3 54.9c -22.7a 53.8c -17.3 53.3c (-1.26) (2.81) (-1.67) (2.74) (-1.29) (2.67) GDP × Gov Debt (2000-2007) -44.9c 5.45 -37.3b 2.59 (-2.58) (0.21) (-2.24) (0.10) GDP × Gov Debt (2008-2009) -8.41 -15.6 -10.8 -4.61 (-0.47) (-0.58) (-0.64) (-0.18) GDP × Gov Debt (2010) -43.2b 20 -50.6b 32.4 (-2.09) (0.64) (-2.20) (0.94) GDP × Ext Debt (2000-2007) 47.3c -26.6 42.7c -28.9 (3.39) (-1.32) (3.09) (-1.40) 28 GDP × Ext Debt (2008-2009) 42.9b -120.9c 48.8b -119.9c (2.17) (-4.25) (2.53) (-4.17) GDP × Ext Debt (2010) -44.3 4.56 .347 -21.3 (-1.43) (0.10) (0.01) (-0.41)
Notes: Country-fixed effects regressions. The coefficients in columns one to six Sj it jGD P jGD jGD jGD come from regressing ∆ = α + β + β × (GDit − GDd) ∆gdpit × d + , Cit t d d it d Sj it jED P jED jED jED ∆ = α + β + β × (EDit − EDd) ∆gdpit × d + and regressions of the same form but includ- Cit t d d it d P r Gov ing both GDit − GDd and EDit − EDd, for j ={Government, Private} , respectively, where, S and S are net private and government saving, respectively, d are dummies variables for the periods {2000 − 2007, 2008 − 2009, 2010},
GDit − GDd (Gov Debt in the table) and EDit − EDd (Ext Debt in the table) are the ratios of the net general government debt and external debt to GDP minus the average of those ratios for the set of countries during period d. The αt coefficients control for common shocks across time and the remaining variables and coefficients follow the same definitions as Tables 3 and 4. The values in the parenthesis of the previous equations are interpreted as consumption smoothing reached through private and government saving, respectively, during period d. Each pair of equations were jointly estimated by SURE using annual data on the period 2000–2010 and the countries considered are the same as those in Table 2. Values in parentheses are t statistics, whereas a, b, and c denote significance level at 10, 5, and 1 percent, respectively.