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Czech Republic: Selected Issues

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International Monetary Fund
Published Date:
August 2005
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IV. Czech Republic: Household Balance Sheets in a Comparative Perspective21

A. Introduction

50. Recent global structural changes in financial markets and pension systems have shifted risks to the household sector. The tendency to switch from defined-benefit to defined-contribution plans, for example, implies a transfer of the longevity and market risks from the public to the household sector. Changes in the behavior of banks, insurers, and private pension funds also imply that a variety of other risks traditionally managed within the financial sector are flowing directly to the household sector. In emerging markets, such as the Czech Republic, this shift of risks to households is starting to happen, particularly as the public sector cannot continue to bear the full burden of social services and retirement. These developments suggest that the monitoring of household assets and liabilities should be enhanced and integrated into the wider context of financial sector surveillance (see IMF (2005, Chapter III)).

51. This chapter focuses on recent and expected trends in household wealth in the Czech Republic using a balance sheet approach. The analysis focuses on the developments in household assets and liabilities observed in the Czech transition process and on the possible implications for financial stability. The paper also identifies, based on the experience of financially developed countries, what are the likely future trends in household balance sheets, and discusses how Czech households will need to adjust their balance sheets in order to cope with the pressures arising from an aging society.

52. The setting of the chapter is as follows. Section B introduces the balance sheet approach. Section C discusses some recent trends in household financial wealth in the Czech Republic. Section D presents an estimation of models of structural determinants of household assets and liabilities, using a panel of Group of Seven (G-7) countries. The coefficients derived from these estimations are then applied to the Czech Republic in Section E in order to derive “equilibrium” levels of household assets and liabilities and to asses likely future trends. Section F focuses on how households are expected to adjust their balance sheets in response to aging, while Section G draws some conclusions.

B. The Balance Sheet Approach

53. The balance sheet approach is a framework that allows us to monitor financial vulnerabilities on the basis of the analysis of stock variables. This approach was developed in the literature (see Dornbusch (2001) in order to explain some features of emerging-market financial crises that were not adequately captured by traditional models focusing on flow variables (such as Krugman, 1979).

54. Information on household balance sheets is usually difficult to obtain. In many countries, detailed data on household wealth are often only partially available and can be obtained only with significant time lags (see Allen and others (2002)). Given the scarcity of household balance sheet data for new European Union (EU) member states, the international comparisons carried out in this paper will be mostly with G-7 and other financially developed countries.

55. The Czech authorities have made progress in the analysis of household sector balance sheets. Data on household wealth are compiled by the National Accounts Unit of the Czech Statistical Office. The Czech National Bank is also working on the construction of intersectoral balance sheets with the aim of integrating them into the analysis of financial stability. An analysis of household financial trends was included in the Financial Stability Report (Czech National Bank, 2004).

C. Household Balance Sheet Trends in the Czech Transition

56. In line with other countries in the region, the Czech Republic has experienced a significant increase in credit to households. The year-on-year rate of growth of total loans to households increased from one-digit Figures in the mid-1990s to around 30 percent in recent years. Figure 1 shows three household aggregate indebtedness indicators for the 1995-2002 period. All indicators show an acceleration in household indebtedness starting from the late-1990s. The steep increase in the ratio of financial liabilities to financial assets indicates a tendency of liabilities to grow faster than assets, and a bias toward nonfinancial assets in total household wealth. The trends highlighted in Figure 1 reflect various economic factors. On the supply side, the sale of the main commercial banks to foreign strategic investors during 1999-2001 implied a more aggressive targeting of the household sector. This trend was reinforced by competition from the fast-developing nonbank industry. On the demand side, the catching-up process and low interest rates have encouraged household borrowing.

Figure 1.Household Sector: Indicators of Financial Soundness, 1995-2002

(In percent)

Sources: Czech Statistical Office; and IMF staff estimates.

57. One issue to be investigated is whether the rapid increase in household liabilities is justified by structural determinants observed in financially developed countries. The view that credit growth and economic development might go hand in hand is widespread in the literature. Greenwood and Jovanovic (1990), for example, develop a theoretical model in which growth promotes financial intermediation by providing the means to implement costly financial structures. Empirically, King and Levine (1993) find that various measures of the level of financial development are strongly associated with per capita GDP growth. The rapid increase of credit to households in the Czech Republic could, therefore, be a natural consequence of the process of converging to EU standards. In order to test this hypothesis, in this chapter we analyze the relationship between household liabilities and their economic determinants.

58. An international comparison with G-7 and other new EU member countries gives mixed evidence on whether household indebtedness in the Czech Republic is in line with its level of economic development. A simple way to compare credit dynamics in an international setting is to control for the level of development of the economy, proxied by per capita GDP (see Cottarelli, Dell’Ariccia, and Vladkova-Hollar (2003)). Figures 2 to 4 illustrate the relationship between the three indebtedness indicators presented in Figure 1 and per capita GDP for a sample of countries. Using both household bank loans and total household liabilities as ratios to GDP, the position of the Czech Republic is very close to the fitted line. This suggests that the level of indebtedness of households is justified by the level of development. However, a look at the ratio of financial liabilities to financial assets (Figure 4), for which the position of the Czech Republic is well above the fitted line, suggests that household indebtedness could be higher than warranted by the level of per capita GDP.

Figure 2.Selected Countries: Household Bank Loans-to-GDP Ratio and Per Capita GDP, 2003

Sources: National Banks of respective countries; IMF, WEO database; and IMF staff estimates.

Figure 3.Selected Countries: Household Financial Liabilities as Percent of Disposable Income and Per Capita GDP, 2002

Sources: Czech Statistical Office; National Bank of Hungary; OECD; IMF, WEO database; and IMF staff estimates.

Figure 4.Selected Countries: Household Financial Liabilities-to-Financial Assets Ratio and Per Capita GDP, 2002

Sources: Czech Statistical Office; National Bank of Hungary; OECD; IMF, WEO database; and IMF staff estimates.

D. Structural Determinants and Likely Future Developments of Household Assets and Liabilities in the Czech Republic

59. Estimating models of structural determinants of assets and liabilities can provide a more formal analysis of the financial position of households. Since summarizing economic fundamentals only by per capita GDP gives mixed results, we now turn to a multidimensional analysis. We estimate structural models of determinants of household assets and liabilities using a panel comprising G-7 countries, and then we apply the derived coefficients to the Czech Republic.22 A similar approach is used by Cottarelli, Dell’Ariccia, and Vladkova-Hollar (2003) in their study of bank credit to the private sector in transition countries. Such a methodology appears appropriate in our case for at least two reasons: (i) given the short length of the time series for household balance sheet data and for the structural determinants for the Czech Republic, it would be difficult to estimate the model directly on Czech data; and (ii) the methodology gives an idea of the “equilibrium” levels of household assets and liabilities in the Czech Republic and allows us to evaluate how far the actual values are from this equilibrium, thus suggesting the likely direction of financial developments.

60. Household financial assets are assumed to be determined by macroeconomic conditions, the degree of financial market development, old age-related government spending, and demographic factors. The estimated panel regression includes the ratio of household assets to disposable income as a dependent variable. Among the explanatory variables, per capita GDP and inflation are included as proxies of macroeconomic conditions. The ratio of market capitalization of listed companies to GDP is included as a proxy for financial market development, which is expected to increase the level of assets held by households. Since the more the government is willing to assume pension risks the smaller is the incentive of households to save for this purpose, the ratio of public old age-related spending to GDP is expected to reduce the level of assets. The old-age dependency ratio is also included among the explanatory variables.23 The standard life cycle theory predicts a reduction of savings for old-age cohorts.24 This would imply that a reduction of aggregate household assets should follow an increase in the dependency ratio. This effect, however, could be mitigated or even reversed if younger cohorts perceive that the aging process is putting pressure on the fiscal sustainability of the public pension system, and as a result increase their current level of savings for retirement. We therefore have an agnostic a priori expectation about the sign of the coefficient on the dependency ratio in the regression.25

61. The econometric estimation for the G-7 countries panel indicates that financial market development, and the transfer of old age-related spending risk from the public to the household sector, as well as aging itself, tend to increase the level of assets. The results of the estimation are shown in Table 1. The financial market development variable (market capitalization) has the expected positive sign and is statistically highly significant. Old age-related public spending has the expected negative sign and is also statistically significant. This implies that household assets increase as the public sector withdraws from pension spending. GDP per capita has the expected positive sign and is statistically significant. Inflation is also statistically significant and tends to reduce the level of household assets. The dependency ratio displays a positive sign that is also statistically significant, indicating that population aging tends to increase the level of household assets.

Table 1.Structural Model of Determinants of Household Financial AssetsRandom effects panel estimation, G-7 countries, 1992-2000Dependent variable: household financial assets/disposable income
CoefficientStandard Errort-statisticsProb.
GDP per capita0.0020.0012.6890.009
Market capitalization/GDP1.0800.08213.1050.000
Inflation-5.0832.316-2.1950.032
Old-age related public spending/GDP-10.8265.921-1.8280.073
Old-age dependency ratio11.3082.8553.9610.000
Total panel (balanced) observations63
R-squared0.97
Source: See Appendix.

62. Household liabilities are assumed to be determined by macroeconomic conditions, by the level of unemployment, and by the degree of credit crowding in from the corporate sector. In addition to GDP per capita and inflation, explanatory variables include short-term interest rates, a measure of corporate indebtedness, and the unemployment rate. A higher unemployment rate is expected to lower the level of liabilities, since it is more difficult to get credit if unemployed. The corporate indebtedness variable is expected to capture the effect of crowding in: the lower the level of credit demanded by enterprises, the more banks are expected to move toward the household sector. This trend is likely to be reinforced in a low-interest-rate environment, in which the spread between the commercial and household sector rates makes bank lending to households more profitable. Low interest rates also capture demand factors, since they encourage household borrowing. We therefore expect negative coefficients on the interest rates and corporate indebtedness variables.

63. The estimation of a household liabilities model for the G-7 panel confirms the a priori expectations about the effects of the structural determinants. The results of the estimation are shown in Table 2. In the estimated equation, the ratio of household liabilities to disposable income enters as a dependent variable. The negative signs on the interest rates and on corporate indebtedness variables (both of which are also highly significant) confirm the relevance of the crowding-in assumption, and the presence of significant demand effects of low interest rates. The negative sign on unemployment also confirms the expectation that lower unemployment makes it easier to get credit and therefore raises the level of liabilities. The positive inflation coefficient, although not significant, is consistent with the intuition that higher inflation reduces the real value of liabilities, at least to the extent that these are not fully indexed, and, therefore, stimulates household indebtedness by making it less costly.

Table 2.Structural Model of Determinants of Household LiabilitiesRandom effects panel estimation, G-7 countries, 1992-2001.Dependent variable: household liabilities/disposable income
CoefficientStandard Errort-statisticsProb.
GDP per capita0.0010.0002.1680.034
Interest rates-1.5390.567-2.7160.009
Inflation0.8591.0970.7830.437
Corporate indebtedness-1.0190.263-3.8790.000
Unemployment-1.8440.696-2.6480.010
Total panel (balanced) observations70
R-squared0.960
Source: See Appendix.

E. Equilibrium Levels of Household Assets and Liabilities in the Czech Republic

64. Applying the coefficients derived from the G-7 panel to the Czech Republic suggests that further increases in both household assets and liabilities would be justified. Table 3 compares the predicted values of some household indebtedness indicators derived from our methodology, with actual values for the Czech Republic for 2001.26Table 3 shows that the equilibrium levels of the various indicators are higher than the actuals, suggesting that the current level of the structural determinants in the Czech Republic would justify further growth of both household assets and household liabilities in the convergence process.

Table 3.Czech Republic: Comparison of Actual and Predicted Variables, 2001(In percent)
Actual ValuePredicted ValueAbsolute Deviation
(a)(b)(a-b)
Financial assets/disposable income145.5216.9-71.4
Liabilities/disposable income45.693.9-48.3
Liabilities/financial assets31.343.3-12.0
Sources: Czech Statistical Office and IMF staff calculations.

65. Although, based on the estimated model, further increases in both household assets and liabilities would be justified, recent trends show that liabilities have been growing faster than financial assets. The dynamics of the ratio of liabilities to financial assets presented in Figure 1 also makes this clear. In addition, the year-on-year rates of growth for the 1996-2002 period, shown in Table 4, confirm that liabilities have been growing faster than financial assets in recent years.

Table 4.Czech Republic: Year-on-Year Rates of Growth of Household Financial Assets and Liabilities, 1996-2002
1996199719981999200020012002
(Percent)
Financial assets growth8.213.67.84.25.78.35.0
Liabilities growth28.710.65.117.922.124.17.7
Sources: Czech Statistical Office and IMF staff calculations.

66. A key priority for preserving household sector financial stability is to ensure that the growth of financial assets will not lag behind the growth of financial liabilities in the convergence process. Comparing the actual indebtedness indicators with the equilibrium values implied by the model gives no immediate reason for concern regarding the financial sustainability of the household sector in the Czech Republic. However, the fact that liabilities have been growing faster than financial assets in recent years, combined with the results of the empirical estimation showing that the growth of liabilities is in part supply driven, suggest that the risk of an unbalanced dynamics of assets and liabilities cannot be ruled out in the medium term.

F. Dealing with the Impact of Aging

67. The level and composition of household assets also need to be monitored in relation to the transfer of risks, which will be intensified by an aging population. Demographic trends are expected to place significant demands on public finances in the Czech Republic. Current public pension and health policy would drive up the deficit and debt to unsustainable levels in the absence of reforms.27 The increase in the old-age dependency ratio in the Czech Republic is projected to be among the highest in the world in the coming decades. In this context, a substantial degree of transfer of risk from the public to the private sector seems unavoidable, and households will have to bear a significant part of the expected increase in pension and health care spending (from 14 percent of GDP in 2005 to 22 percent in 2050). From the point of view of household budgets, a simple comparison with the United States of the share of some selected items in total consumer expenditure suggests that Czech household spending in the fields of health, education, and private pension plans might increase considerably (see Table 5). It is therefore important that the level and composition of assets be adequate to deal with these potential future liabilities.

Table 5.Selected Countries: Selected Expenditure Items of Average Household(Percentage of Total Consumer Expenditure)
HealthEducationPersonal Insurance and Pensions
Czech Republic2.30.64.5
United States6.02.010.8
Sources: Czech Statistical Office; U.S. Bureau of Labor Statistics; and IMF staff calculations.

68. The estimation results of the structural model of asset determinants (Table 1) suggest that Czech households will have to increase their assets in response to aging. Table 1 shows that households in G-7 countries have increased the ratio of their financial asset holdings to disposable income by about 11 percent, for an additional 1 percent increase in the elderly dependency ratio. This result contrasts with the predictions of the standard life-cycle theory, which were summarized in Section D. Possible explanations are the following: (i) an increase in savings of younger cohorts, who perceive that aging pressure will make the public pension system unsustainable; (ii) an increase in savings of older cohorts for bequest motives; and (iii) an increase in savings of older cohorts reflecting un-met expectations of pension wealth, a fall in the marginal utility of consumption with aging, or uncertainty about the lifetime.28 The experience of G-7 countries suggests that an increase in financial assets would be an appropriate household strategy to cope with aging in the Czech Republic. This is also confirmed in Figure 5, which displays a U-shaped relationship between household financial assets and the old-age dependency ratio. Figure 5 suggests that, for countries that start aging when the level of household assets holdings is already high, assets might initially decrease but will subsequently rise. Since the Czech Republic is close to the lowest point of the fitted U-shaped curve, this U-shaped dynamics should not apply here, and immediately increasing household assets would seem the more adequate response.29

Figure 5.Selected Countries: Household Financial Assets-to-Disposable Income and Old-Age Dependency Ratios, 2002

Sources: OECD; and IMF staff estimates.

69. In addition to the level of financial assets, the composition of total assets may also need to change. Comparison with other industrialized countries suggests that household wealth in the Czech Republic tends to concentrate on relatively low-marketable nonfinancial assets (Figure 6). The large share of nonfinancial wealth in the Czech Republic is second in this sample only to that of Germany, where strong incentives to invest in housing are in place. On the other hand, claims on insurance and pension companies in the Czech Republic (included in the “Other” category) look remarkably small as a percentage of total assets in an international comparison. Housing constitute the bulk of nonfinancial assets. Given the relatively low marketability of housing wealth and the low propensity of households to borrow against it, this asset structure might not be adequate to deal with the expected transfer of financial risks to households.

Figure 6.Selected Countries: Household Sector: Total Assets Composition

(In percent of total assets)

Sources: Czech Statistical Office; and IMF, Global Financial Stability Report (2005).

70. Household portfolios in the Czech Republic also tend to concentrate on low-volatility assets. Table 6 shows that the ratio of the volatility of Czech households’ net worth to disposable income is lower than in most financially developed countries; the Czech position becomes even more evident when only market-sensitive assets are taken into account.30 A low volatility can be taken as an indicator of welcome stability in household wealth, even during a period of significant transformations in the financial and real sectors. On the other hand, Table 6 also suggests that Czech households tend to concentrate their wealth in low-return assets, which are probably not adequate to save for retirement and to face the other challenges associated with the transfer of risks from the public sector.

Table 6.Selected Countries: Household Balance Sheets: Volatility Measures

(In percent) 1/

Volatility of Net Worth Disposable IncomeVolatility of Market-Sensitive Assets/Disposable Income 2/
Czech Republic (1998-2002)3.85.0
United States (1998-2003)7.010.0
United Kingdom (1998-2003)5.17.5
Netherlands (1998-2003)6.27.5
France (1998-2003)3.810.4
Germany (1998-2003)1.52.5
Japan (1998-2003)2.57.1
Sources: Czech Statistical Office; IMF, Global Financial Stability Report (2005); and IMF staff calculations.

71. Possible explanations for the current composition of assets include demand- and supply-side factors, as well as policy-induced distortions. Households might not be investing strategically due to a lack of awareness of their future financial responsibilities. An increase in financial education could help stimulate the demand for more strategic investment tools.31 The lack of supply of more sophisticated saving instruments could also be a determinant of the current assets composition. The supply of instruments such as annuities, long-term bonds and “life cycle” products could be promoted in order to encourage strategic investment. From the policy point of view, government subsidies, tax exemptions for mortgage loans, and saving schemes of building societies might be encouraging investment in nonfinancial and short-term financial assets. Heavy regulation of the private pension industry also discourages the supply of personalized pension plans. Phasing out of these government policies might be needed to stimulate long-term investments, which would be more adequate to finance retirement.

G. Conclusions

72. The evidence presented in this chapter suggests that both household assets and household liabilities in the Czech Republic will need to rise to be consistent with the structural determinants observed in financially advanced countries and to prepare for aging. The analysis showed that, although there are no immediate sustainability concerns, the financial position of Czech households could become more fragile going forward, especially if the rates of growth of household liabilities continue to significantly outpace those of financial assets. Given the interlinkages among sectors, a weakening of the households’ financial position would have an impact on financial stability as a whole. In this context, a system of intersectoral balance sheets, such as the one being developed by the Czech authorities, is an adequate surveillance tool which would allow the monitoring of the household sector financial position to be integrated with financial sector surveillance.

73. The analysis also showed that the current composition of assets might not be adequate to face the challenges related to the expected transfer of risks and to aging. Households currently hold a large share of their total assets in nonfinancial assets and low-yield financial assets. This could be in part due to government policies that encourage home ownership over other forms of investment, and create incentives for short-term savings. Demand and supply factors generated by households’ lack of awareness of their future financial responsibilities, as well as a lack of supply of more sophisticated investment tools, might also be playing a role in determining the current assets structure.

APPENDIX I: Econometric Model Specification and Data Description

Econometric models of structural determinants of assets and liabilities were estimated using a balanced panel of the G-7 countries (see Tables 1 and 2 for estimation results). The estimation period was 1992-2000 for the assets model and 1992-2001 for the liabilities model. The choice of the sample was driven by data availability. The estimation technique used is the generalized least squares (GLS) random effects procedure. The equations have the following forms:

ASSit = α0 + α1 * GDPPCit + α2 * MCit + α3 * INFLit + α4 * GOVOLDAGEit + α5 * OLDAGEit + εit

LIABit = α0 + α1 * GDPPCit + α2 * INFLit + α3 * INTit + α4 * FLAit + α5 * UNit + εit,

where the variables are defined as follows:

  • ASS is the ratio of household financial assets to disposable income, available from OECD.

  • LIAB is the ratio of household liabilities to disposable income, available from OECD.

  • GDPPC is per capita GDP from the IMF’s World Economic Outlook (WEO) database.

  • MC, the ratio of market capitalization of listed companies to GDP, is used as an index of financial market development, available from the World Bank’s World Development Indicators database.

  • INFL is the consumer price index (CPI)—annual inflation calculated on the basis of CPI data from the WEO database.

  • GOVOLDAGE is the ratio of old age-related public expenditure to GDP, available from the OECD Social Expenditure Database.

  • OLDAGE is the old-age dependency ratio, calculated using OECD data on labor force Statistics.

  • INT are short-term interest rates from IMF, International Financial Statistics (IFS).

  • FLA, total liabilities of firms as a percentage of assets, available from the IMF’s Corporate Vulnerability Utility database, is used as a proxy for corporate indebtedness.

  • UN is the OECD standardized rate of unemployment.

References

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Prepared by Giovanni Ganelli (EUR).

See the Appendix for details of the econometric model specification and data sources and description.

The old-age dependency ratio is defined as the ratio of population aged 65 and above to the population aged 15-64.

Modigliani and Blumberg (1954), and Friedman (1957). See also Scholz, Seshadri, and Khitatrakun (2004) for a modern reformulation.

Section E focuses in more detail on the impact of aging.

2001 is the most recent year for which data availability makes this comparison possible.

See Chapter III on “The Impact of Aging on Fiscal Sustainability in the Czech Republic.”

Points (ii) and (iii) have been put forward in Moreno-Badia (2005) to explain the “retirement savings puzzle” observed in Ireland.

The results shown in Figure 5 do not contradict the estimation reported in Table 1, since in Figure 5 we do not control for the other structural determinants of household assets.

Net worth is defined as total (financial plus nonfinancial) assets minus liabilities.

Recent research shows that financial education usually results in better financial decision-making practices, especially with regard to long-term savings (Helman and Paladino, 2004; and Lusardi, 2004).

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