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Household Savings in the Transition
Journal of Comparative Economics 30, 463–475 (2002) doi:10.1006/jcec.2002.1792
Household Savings in the Transition Cevdet Denizer1 The World Bank, 1818 H Street N.W., Washington, DC 20433 E-mail: [email protected]
Holger Wolf Center for German and European Studies, Georgetown University, Washington, DC 20057 E-mail: [email protected]
and Yvonne Ying Oxford University Oxford, England OX1 2RL, United Kingdom E-mail: [email protected] Received October 13, 2000; revised April 30, 2002 Denizer, Cevdet, Wolf, Holger, and Ying, Yvonne—Household Savings in the Transition We explore household savings decision in Bulgaria, Hungary, and Poland during the transition from plan to market, finding four main results. First, except for the age profile, the effects of standard determinants on savings are comparable for transition and market economies. Second, we do not find support for a precautionary savings motive. Third, the evidence on consumption smoothing is mixed. Education of the head of the household, but not employment characteristics, are linked robustly to savings. Fourth, ownership of durables is negatively correlated with savings, consistent with the presence of anticipatory savings. J. Comp. Econ., September 2002, 30(3), pp. 463–475. The World Bank, 1818 H Street N.W., Washington, DC 20433; Center for German and European Studies, Georgetown University, Washington, DC 20057; and Oxford University Oxford, England OX1 2RL, United Kingdom. C 2002 Association for Comparative Economic Studies. Published by Elsevier Science (USA). All rights reserved.
Key Words: household savings; transition; comparative economics. Journal of Economic Literature Classification Numbers: D12, D31, D91, O16, P36. 1 We thank two anonymous referees and John Bonin for very helpful comments. All remaining errors are our own. The household surveys were made available by the World Bank.
0147-5967/02 $35.00
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2002 Association for Comparative Economic Studies Published by Elsevier Science (USA) All rights reserved.
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1. INTRODUCTION In terms of the sheer scope of economic, social, and political change, few events rival the transition from central planning to markets that has been taken place over the past decade in Eastern Europe. The macroeconomic impact of the transition has been dramatic. Output levels collapsed by between 20 and 40% in the early 1990s, while closures and labor force reductions led unemployment levels to rise sharply from near-zero recorded rates. The move from a cradle-to-grave system of stateguaranteed incomes to market-determined wages and the emergence of large-scale unemployment coupled with a sharp reduction in public benefits raised income uncertainty and changed expected future income profiles. The large changes in the determinants of household savings decisions over a very short period create a fertile ground for empirical research. Several authors have studied the comparative evolution of aggregate savings in transition economies (Borensztein and Montiel, 1991; Conway, 1995, 2001; and Denizer and Wolf, 2000) but less is known about the savings behavior of households, with the exception of Gregory, Mokhtari, and Schrettl (1999), which examines the pattern in Russia. In this article, we explore household savings in Bulgaria, Hungary, and Poland in the light of standard consumption theories. 2. MOTIVATION AND HYPOTHESIS The transition from plan to market involved dramatic declines in reported output and real income levels, alongside a dramatically increased level of income uncertainty for most households. These features apply to all three of our sample economies. In the year of the survey (1993 for Hungary and Poland and 1995 for Bulgaria), real GDP remained between 25% (Bulgaria) and 15% (Hungary and Poland) below the 1989 level, while the unemployment rate had increased from near-zero recorded levels to the double-digit range in all three countries. Price liberalization led to high inflation in the early transition years, eliminating any initial monetary overhang. In the sample year itself the CPI inflation rate ranged between a low of 22% in Hungary to a high of 62% in Bulgaria. We explore household surveys for Bulgaria, Hungary, and Poland to answer three questions. First, we examine whether household savings patterns across demographic groups in transition economies resemble the patterns established for market economies. Second, we examine whether the observed savings behavior is consistent with the predictions of the consumption smoothing and precautionary savings models. Third, we examine whether savings behavior was influenced by the combination of pent-up demand for consumer durables and the absence of consumer credit markets. Our primary focus is on the second and third question. The survey evidence permits a tentative identification of groups likely to benefit from the transition to a market economy. Using dummies to separate these groups, we examine whether intergroup differences in household savings patterns match the predictions of the
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consumption smoothing model. Specifically, we assume that households headed by individuals with tertiary education, households deriving most of their income from self-employment and household headed by individuals employed in the private sector face more steeply upward sloping expected income profiles compared to households headed by individuals with lower educational attainment, employed in the public sector, or deriving their income from the social safety net, implying lower contemporaneous savings rates for the former groups. In comparison with market economies, the monetary return to education was small in planned economies. To the extent that past formal education is a good indicator of skills, the transition is likely to lead to a relative income gain and a steeper income profile for bettereducated individuals and a correspondingly lower savings rate, ceteris paribus. The relative income profile of private compared to public employment is influenced by two factors. The more attractive enterprises are likely to have been privatized first; thus, the core growth rate of firms with private ownership is likely to exceed that of firms remaining in public hands. In addition, employment in privatized enterprises was reduced to a much greater extent than it was in publicly owned firms. To the extent that firing decisions were based on worker skills, the remaining employees in private sector firms would have higher average skills compared to public sector employees.2 Finally, as self-employment was rare before the transition, we assume that individuals setting out on their own expect to capitalize on their skills to a greater extent than would be possible in their prior employment. The identification of households facing particularly high income risk is more tentative. We focus on two groups, retirees and public sector employees. Dependency ratios in all three sample countries in the sample year were high relative to market economies of comparable levels of development (EBRD 1996). The dependency ratios, coupled with the general fiscal constraints faced by the transition economies, suggests that the sustainability of real pension levels was subject to some doubt. In consequence, household headed by retirees and dependent on pensions arguably faced particularly high income risk. Reflecting the ongoing privatization process, typically with an accompanying reduction of employment, households headed by public sector employees also arguably faced higher real income risk compared to households headed by individuals in the private sector. Under the precautionary savings motive, these two groups should thus exhibit higher savings, ceteris paribus. We formally test this hypothesis in a dummy regression framework. The survey data also allow us to classify households by their ownership of a set of common durables. In comparison with market economies at similar levels, households in planned economies possessed fewer household durables. The 2 Differences between occupation groups are notoriously difficult to interpret because occupation choice itself is endogenous (Skinner, 1988; Carroll, 1994). In this respect, the transition data are arguably less problematic because it seems reasonable to assume that few households selected their pretransition employment with the expectation of a possible collapse of the socialist system. Furthermore, employment choice was highly restricted under the central planning system.
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absence of retail credit markets implied that any households wishing to purchase such durables after the transition would have to save the purchase price first, a possibility that has recently attracted attention in the savings literature.3 In this case, households with a small initial stock of durables would have higher savings ratios, ceteris paribus. Again using dummies to identify groups with high and low ownership of durables, we test this hypothesis directly. 3. DATA AND DESCRIPTIVE STATISTICS Our results are based on three surveys contained in the World Bank Household Expenditure and Income Data for Transitional Economies database. Using stratified random samples, the household surveys cover 2,466 households in Bulgaria (survey year 1995), 8,105 households in Hungary (survey year 1993), and 16,051 households in Poland (survey year 1993). The original surveys were conducted by different institutions and were placed into a consistent format by the World Bank4 to achieve comparability across the three countries. Each survey contains detailed information regarding the household’s expenditure (8 categories) and its income sources (12 categories for Poland and Bulgaria and 11 categories for Hungary). Savings is defined as the difference between disposable household income and household expenditure.5 In addition, the data set contains information about household asset ownership (5 categories for Poland and Bulgaria and 4 categories for Hungary), household size and location (urban/rural) as well as, for the head of household, the age, gender, type and sector of employment/income and highest level of education attained. Based on this information, we construct a set of explanatory variables used in the regressions reported below. The variables are split into characteristics of the head of household and characteristics of the household. The log and the squared log of the age of the head of household proxy for life-cycle factors. To capture education effects, we include four dummy variables set equal to 1 if the highest level of education attained by the head of the household was primary, secondary, vocational, or tertiary, respectively. In the regression analysis, we exclude the dummy for tertiary education. Three groups of dummies capture the socioeconomic group and the employment characteristics of the head of household. The data set classifies the socioeconomic 3
See Hayashi (1985), Zeldes (1989), Browning and Lusardi (1996), and Jappelli and Pagano (1989). See Household Expenditure and Income Data for Transitional Economies (HEIDE), Appendix 2 of RAD project “Poverty and Targeting of Social Assistance in Eastern Europe and the Former Soviet Union.” 5 Household savings rates are notoriously difficult to measure accurately even in mature market economies because of reporting errors. Considerable effort has been made to purge the dataset of clear outliers. In addition, we drop all observations with an implied dissavings rate above 50%. The frequency distribution did not suggest outliers on the right-hand-side tail of the distribution, while all three samples contain several extremely large negative savings rates, which are eliminated by this threshold condition. 4
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group of the head of household as belonging to one of five groups: (1) wageearner, (2) self-employed, (3) pensioner, (4) recipient of other social benefits, and (5) recipient of other income. While the first three groups are defined consistently, the definitions of the latter two groups differ in their classification of unemployment benefits. Hence, we group categories (4) and (5) into a single new category “Benefits/Other,” which includes all heads of households for whom social benefits (including unemployment benefits) and income that does not fall under categories (1), (2), or (3) constitutes the greatest share of household income. In the regression, this new category is the excluded reference group. For Hungary and Poland, the survey classifies separately the labor force status of the head of household as being employed, unemployed, or inactive. We define three corresponding dummies; in the regression analysis, the inactive category is the excluded reference group. The labor force status data are not reported for Bulgaria. Finally, the survey reports the sector of employment of the head of household for Bulgaria and Poland, distinguishing between employment in the public sector, the private sector and the mixed/other sector. We define the three corresponding dummies. For the regression analysis, the public sector is the excluded reference group. An extensive set of dummies controls for the effect of various household characteristics on savings. We use dummies set equal to 1 if, respectively, the household is located in a rural area, the household is large (defined as households with more than four residents), the household owns land (only for Bulgaria and Poland), and the household owns productive assets. To capture any role of the relative income position, we include five dummies set equal to 1 if the household belongs to the lowest, second lowest, third lowest, fourth lowest, and highest quintile in the income distribution, respectively. For the regression analysis, we exclude the dummy for the highest quintile. To capture any temporary increase in the savings rate to satisfy a latent demand for durables, we construct four dummy variables. The first three are set equal to 1 if the household owns more than three, one to three, or zero of a set of common durables, respectively. The latter two dummies are excluded in the regression analysis.6 The fourth dummy is set equal to 1 if the household owns its residence. Tables 1 through 3 report the mean and median savings rates along with the standard deviation disaggregated by a subset of these household and head-ofhousehold characteristics. For the entire sample, median (mean) reported savings rates range from a low of 0.2% (1.7%) for Bulgaria to 1.1 (0.2%) for Hungary and 8.6% (8.3%) for Poland. The tables reveal a number of features. First, across age-groups, savings rates are lower for the midcareer group (30–49 years of age) than for the younger (18–29) group. For Bulgaria and Hungary the age distribution takes a U shape, 6 The set comprises a car, a black-and-white TV, a color TV, a refrigerator, a sewing machine, a PC, a VCR, a stereo, a car-washing device, a microwave, and a motorcycle. Data for all 11 items are available for Hungary; however, for Bulgaria (10 items) and Poland (5 items), the available information is less comprehensive.
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TABLE 1 Savings Rates by Group: Bulgaria
Full sample Household Characteristics Rural Urban Small Household (size ≤ 4) Large Household (size > 4) Durables Ownership More than 3 durables 1–3 durables 0 durables Asset Ownership Owns productive assets Does not own productive assets Owns Dwelling Does not own dwelling Owns Land Income Quintile Lowest 20% 2nd lowest 20% 3rd lowest 20% 4th lowest 20% Highest 20% Head of Household Characteristics Female head Age 19–29 30–49 50–64 65+ Highest education level Primary Secondary Vocational Tertiary Income Source Wage Earner Self-employed Pensioner Sector of Employment Public Private Mixed
Median
Mean
SD
Obs.
.002
.017
.298
1622
.046 −.021 .006 −.044
.066 −.010 .021 −.007
.318 .282 .298 .296
570 1052 1407 215
−.047 .014 .048
−.027 .034 .071
.276 .301 .344
510 1000 112
.060 −.005 .001 .026 .034
.080 .013 .016 .034 .056
.299 .297 .297 .304 .301
88 1534 1517 105 714
−.020 −.084 −.029 .008 .126
−.008 −.036 −.020 .027 .122
.299 .296 .282 .292 .293
321 326 324 325 326
.023
.028
.299
348
.051 −.051 −.015 .045
.062 −.031 .016 .058
.309 .279 .296 .310
60 493 488 546
.042 −.032 −.025 −.018
.050 −.021 −.015 −.012
.310 .286 .265 .281
828 455 106 226
−.026 .118 −.018
−.014 .113 .003
.279 .326 .292
746 288 549
−.031 .051 .020
−.014 .046 .018
.282 .289 .213
511 112 57
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TABLE 2 Savings Rates by Group: Hungary
Full sample Household Characteristics Rural Urban Small Household (size ≤ 4) Large Household (size > 4) Durables Ownership More than 3 durables 1–3 durables 0 durables Asset Ownership Owns productive assets Does not own productive assets Owns dwelling Does not own dwelling Income Quintile Lowest 20% 2nd lowest 20% 3rd lowest 20% 4th lowest 20% Highest 20% Head of Household Characteristics Female head Age 19–29 30–49 50–64 65+ Highest Education Level Primary Secondary Vocational Tertiary Income Source Wage Earner Self-employed Pensioner Labor Force Status Employed Unemployed Inactive
Median
Mean
SD
Obs.
.011
.002
.234
7006
.001 .037 .008 .041
−.025 .025 −.000 .025
.238 .228 233 .242
3215 3791 6408 598
−.007 .022 .112
−.019 .015 .080
.233 .229 .264
3312 3339 355
.006 .011 .011 .079
−.009 .003 −.006 .055
.243 .233 .233 .235
447 6559 6094 912
−.036 −.017 −.003 .019 .085
−.040 −.021 −.015 .007 .080
.223 .234 .233 .227 .233
1402 1401 1401 1400 1402
.003
−.006
.230
2318
.035 −.003 −.004 .002
.012 −.009 −.006 .019
.242 .234 .237 .223
617 2872 1746 2260
.012 .007 −.005 .041
.005 −.002 −.013 .035
.231 .235 .239 .228
3439 1338 1621 608
.022 −.047 .006
.012 −.050 −.002
.236 .247 .228
3712 185 2739
.019 −.065 .006
.009 −.054 −.002
.237 .237 .228
3897 296 2807
differing from the inverted U shape prevalent in market economies (Paxson 1996) but matching the finding for Russia by Gregory, Mokhtari, and Schrettl (1999), suggesting that it may be a characteristic unique to transition economies. The differences are, however, statistically nonsignificant.
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TABLE 3 Savings Rates by Group: Poland
Full sample Household Characteristics Rural Urban Small household (size ≤ 4) Large household (size > 4) Durables Ownership More than 3 durables 1–3 durables 0 durables Asset Ownership Owns productive assets Does not own productive assets Owns dwelling Does not own dwelling Owns land Income Quintile Lowest 20% 2nd lowest 20% 3rd lowest 20% 4th lowest 20% Highest 20% Head of Household Characteristics Female head Age 19–29 30–49 50–64 65+ Highest Education Level Primary Secondary Vocational Tertiary Income Source Wage Earner Self-employed Pensioner Labor Force Status Employed Unemployed Inactive Sector Public Private Mixed
Median
Mean
SD
Obs.
.086
.083
.237
14663
.114 .075 .083 .102
.107 .071 .079 .098
.254 .227 .236 .238
4697 9966 11913 2750
.094 .082 .048
.090 .079 .046
.234 .238 .261
5131 9454 78
.122 .084 .103 .068 .108
.118 .080 .099 .063 .101
.229 .237 .246 .223 .246
895 13768 7890 6773 7320
−.013 .046 .076 .115 .217
−.021 .041 .076 .106 .212
.228 .221 .219 .222 .228
2932 2934 2933 2931 2933
.064
.060
.237
4860
.104 .084 .089 .074
.108 .079 .084 .077
.245 .229 .242 .238
1296 7268 3791 2304
.081 .081 .085 .116
.078 .079 .082 .110
.250 .226 .231 .236
4581 3799 4834 1449
.088 .126 .064
.080 .126 .065
.223 .269 .236
6943 1666 4716
.101 −.002 .063
.096 −.020 .064
.236 .201 .237
9522 306 4835
.098 .110 .062
.089 .111 .071
.226 .251 .241
5966 3869 867
HOUSEHOLD SAVINGS IN TRANSITION
471
Second, savings rates are consistently higher for households at the top compared to households at the bottom of the income distribution, again matching results for Russia by Gregory, Mokhtari, and Schrettl (1999).7 For the remaining characteristics of both households and heads of households, the pattern of the unconditional subgroup means and medians differs across the sample countries. We next turn to regression analysis to explore these features in a conditional setting. 4. DETERMINANTS OF HOUSEHOLD SAVINGS RATES To explore the conditional relationships, we regress household savings rates on standard demographic variables, on proxies for the likelihood that the transition will alter the household’s expected lifetime income profile, on proxies for relative income uncertainty, and on indicators of household durable ownership. Table 4 reports the results. The top rows identify the country, the number of observations, and the R 2 , which falls within the typical range for cross-section regressions based on household surveys. Beginning with the characteristics of the head of household, the estimated age profile of the head of household exhibits a significant nonlinearity, as suggested by the raw statistics reported in Tables 1 through 3. Households headed by women exhibit significantly higher savings rates. Under the assumption that higher education, and in particular tertiary education, is associated with a steeper expected income profile, the smoothing hypothesis predicts higher savings rates for households headed by individuals with lower educational attainment. The regression results are consistent with this prediction. Eight of the nine coefficients on education levels (households headed by individuals with primary, secondary, and vocational education; the excluded reference group are households headed by individuals with tertiary education) are positive; five are significant at the 5% level. The coefficient is largest (and statistically significant) for households headed by individuals with primary education for all three sample countries. We assess the consistency of the savings pattern with the predictions of the consumption smoothing and precautionary savings models by examining the empirical support for the hypothesis described under Section 2. We assume that households headed by individuals who are either employed in the private sector or are selfemployed face more steeply upward tilting expected income profiles, resulting in lower contemporaneous savings, ceteris paribus, relative to the excluded reference groups (heads of households employed in the public sector and heads of households deriving income from other sources). For precautionary savings, we assume that households headed by retirees and households headed by public sector employees face above-average income risk, implying a higher savings rate, ceteris paribus. 7 With some exceptions, the literature on savings in developing countries tends to find a positive income elasticity. See, for example, Giovannini (1983), Gersovitz (1988), Collins (1991), and Deaton (1992).
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TABLE 4 Determinants of Household Savings Rates
Observations R2 Constant Head of Household Characteristics Log (Age) [Log(Age)]2 Female Head Education Primary Education Secondary Education Vocational Education Income Source Wage-Earner Self-Employed Pensioner
Bulgaria
Hungary
Poland
1,622 0.1457 2.682 (2.42)∗∗
7,006 0.1116 1.737 (7.72)∗∗∗
14,663 0.1449 2.810 (11.12)∗∗∗
−1.302 (2.28)∗∗ 0.185 (2.454)∗∗∗ 0.051 (2.65)∗∗∗
−0.905 (7.28)∗∗∗ 0.133 (7.83)∗∗∗ 0.021 (3.23)∗∗∗
−1.40 (10.26)∗∗∗ 0.189 (10.32)∗∗∗ 0.009 (2.31)∗∗
0.054 (2.30)∗∗ 0.008 (0.37) 0.0045 (0.14)
0.035 (3.28)∗∗∗ −0.0008 (0.08) 0.015 (1.37)
0.032 (4.33)∗∗∗ 0.019 (2.75)∗∗∗ 0.026 (3.83)∗∗∗
−0.203 (3.69)∗∗∗ −0.142 (2.45)∗∗ −0.160 (2.87)∗∗∗
Labor Force Status Employed
0.01 (2.43)∗∗ 0.012 (0.42)
Unemployed Sector of Employment Mixed Private Sector Household Characteristics Rural Household Large Household Durables Ownership Land Ownership Productive Asset Ownership
0.023 (0.86) −0.018 (0.54) 0.021 (0.77)
0.013 (1.09) 0.010 (2.35)∗∗ 0.030 (1.65)∗ −0.114 (5.183)∗∗∗ −0.088 (4.68)∗∗∗ −0.009 (0.053) 0.001 (0.051)
−0.032 (3.99)∗∗∗ −0.0037 (0.372) 0.003 (0.185) −0.029 (1.685) −0.010 (0.512) 0.0024 (0.60) 0.0295 (3.04)∗∗∗
−0.040 (7.23)∗∗∗ −0.017 (1.67)∗ −0.098 (15.32)∗∗∗
−0.011 (0.87)
0.0262 (4.98)∗∗∗ −0.047 (9.27)∗∗∗ −0.044 (9.85)∗∗∗ −0.002 (0.452) −0.029 (3.05)∗∗∗
HOUSEHOLD SAVINGS IN TRANSITION
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TABLE 4—Continued
House Ownership Lowest Income Quintile 2nd Lowest Income Quintile 3rd Lowest Income Quintile 4th Lowest Income Quintile
Bulgaria
Hungary
Poland
−0.055 (1.53) −0.379 (11.22)∗∗∗ −0.332 (11.85)∗∗∗ −0.234 (9.82)∗∗∗ −0.122 (5.51)∗∗∗
−0.069 (8.58)∗∗∗ −0.269 (21.27)∗∗∗ −0.195 (18.42)∗∗∗ −0.149 (15.89)∗∗∗ −0.0924 (10.70)∗∗∗
−0.0001 (0.01) −0.308 (43.00)∗∗∗ −0.214 (33.87)∗∗∗ −0.162 (26.90)∗∗∗ −0.117 (20.12)∗∗∗
The evidence is mixed. The coefficient on self-employment (the excluded reference group is households receiving social payments) is indeed negative for all three countries, but is significant only for Bulgaria. Furthermore, for both Bulgaria and Poland the coefficient on households headed by wage-earners is also negative, significant, and (in absolute terms) larger. Turning to the sector of employment, the results reject both the consumption smoothing and the precautionary savings hypothesis, conditional on our assumptions.8 The coefficient on heads of households employed in the private sector are positive and statistically significant (data for Hungary are not available for this classification), while the only significant coefficient for households headed by a pensioner is negative. The employment status of the head of household is uniformly insignificant, with mixed signs. Turning to household characteristics, large households exhibit significantly lower savings rates, while no common pattern emerges for rural relative to urban households. The position of the household in the income distribution (measured by dummies for households in each of the bottom four income quintiles) is highly significant. In all three countries, households in higher income quintiles have higher savings rates than households in lower income quintiles, ceteris paribus. The durables ownership dummy (equal to 1 if the household owns more than three of the set of durables described above) is negative and significant in all three regressions.9 The finding is consistent with the credit constraint view discussed 8 The limited support for smoothing is consistent with prior findings for developing market economies (Schmidt-Hebbel, Webb, and Corsetti, 1992; Case, 1995; Paxson, 1996). 9 OLS estimation is potentially problematic because of the endogeneity of the asset ownership variables. To address this potential problem, we follow Mokhtari’s (1996) two-stage least-squares approach. In a probit framework, we first regress the ownership dummies on the age dummies and the dummies for rural households, households with female heads of households, and large households. The fitted values of the probit equation are then used in place of the actual ownership dummies in the second stage. Comparing the results of the OLS and the two stage regressions yields no significant differences for the age, employment, income distribution and education variables. However, the negative savings effect of high durables ownership is reversed in Poland and Hungary, but not in Bulgaria.
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under Section 2, predicting that pent-up demand for durables coupled with the lack of retail credit markets forces households with small initial stocks of durables to accumulate the purchase price prior to buying a durable good. However, the finding is inconclusive because a negative real wealth effect provides an alternative explanation. In the presence of a negative real wealth effect, we would expect to find negative coefficients on the other proxies for household wealth. The evidence is inconclusive on this point; while seven of the eight other coefficients on ownership dummies are negative, only two are significant.10 5. CONCLUSION Using three matching household surveys for Bulgaria, Hungary, and Poland, we explore the savings responses of household to the transition experience. We examine three questions. First, does the household savings pattern in transition economies match the pattern observed in market economies? Second, is the pattern consistent with the predictions of consumption smoothing and precautionary savings models? Third, is there evidence of a credit-constraint motivation for savings? The answer to the first question is affirmative, with the exception of the age pattern, which robustly displays an U-shaped pattern rather than the inverted U-shaped pattern more typically observed in market economies. We find little evidence that consumption smoothing and precautionary savings motives play a major role in determining household savings pattern, with the exception of a negative link between savings and the educational attainment of the head of household. In interpreting these findings, it must be remembered that our tests are only as good as our assumptions that identify particular groups as facing particular income profiles or income risk. Hence, a high degree of intragroup differences that is not picked up by the other explanatory factors reduces the sharpness of the tests. The answer to the last question is positive. We find that households owning only a few standard durables exhibit higher savings rates, ceteris paribus, consistent with the view that these households do not have access to retail credit markets and are hence forced to accumulate savings in advance of durable purchases. However, the evidence is not conclusive since the result could alternatively reflect a negative wealth elasticity of household savings. REFERENCES Avery, Robert B., and Kennickell, Arthur B., “Household Saving in the U.S.” Rev. Income Wealth 37, 4:409–432, Dec. 1991. Borensztein, Eduardo, and Montiel, Peter J., “Savings, Investment and Growth in Eastern Europe” International Monetary Fund Working Paper WP/91/61. Washington, DC, IMF, May 1991. Bosworth, Barry, Burtless, Gary, and Sabelhaus, John, “The Decline in Saving: Evidence from Household Surveys.” Brookings Pap. Econ. Ac. 1:183–241, Winter 1991. 10 See Avery and Kennickell (1991) and Bosworth, Burtless, and Sabelhaus (1991) for a discussion of the real wealth elasticity of savings.
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Browning, Martin, and Lusardi, Annamaria, “Household Saving: Micro Theories and Micro Facts.” J. Econ. Lit. 34, 4:1797–1855, Dec. 1996. Carroll, Christopher D., “How Does Future Income Affect Current Consumption?” Q. J. Econ. 109, 1:111–147, Feb. 1994. Case, Anne, Ed., Symposium on Consumption Smoothing in Developing Countries. J. Econ. Perspect. 9, 3:81–127, Summer 1995. Collins, Susan M., “Saving Behavior in Ten Developing Countries.” In B. Douglas Bernheim and John P. Shoven, Eds., National Saving and Economic Performance, pp. 349–375. Chicago: NBER and University of Chicago Press, 1991. Conway, Patrick J. “Saving In Transition Economies: The Summary Report.” Working Paper No. 1509. Washington, DC: The World Bank, May 1995. Conway, Patrick J., Crisis, Stabilization, and Growth: Economic Adjustment in Transition Economies. Boston, MA: Kluwer Academic, 2001. Deaton, Angus, Understanding Consumption. Oxford, UK: Oxford Univ. Press, 1992. Denizer, Cevdet, and Wolf, Holger, “A Symposium on Saving in Developing Countries—The Saving Collapse during the Transition in Eastern Europe” World Bank Econ. Rev. 14, 3:445–455, Sept. 2000. European Bank for Reconstruction and Development (EBRD), Transition Report, 1996. Gersovitz, Mark, “Saving and Development.” In Hollis B. Chenery and T. N. Srinivasan, Eds., Handbook of Development Economics, Vol. 1, pp. 380–424. Amsterdam: North-Holland, 1988. Giovannini, Alberto, “Interest Elasticity of Savings in Developing Countries: The Existing Evidence.” World Dev. 11, 7:601–607, July 1983. Gregory, Paul R., Mokhtari, Manouchehr, and Schrettl, Wolfram, “Do the Russians Really Save That Much? Alternative Estimates from the Russian Longitudinal Monitoring Survey.” Rev. Econ. Stat. 81, 4:694–703, Nov. 1999. Hayashi, Fumio, “The Effect of Liquidity Constraints on Consumption: A Cross-Sectional Analysis.” Q. J. Econ. 100, 1:183–206, Feb. 1985. Jappelli, Tullio, and Pagano, Marco, “Consumption and Capital Market Imperfections: An International Comparison.” Am. Econ. Rev. 79, 5:1088–1105, Dec. 1989. Mokhtari, Manouchehr, “Savings under Quantity Constraints: What Can Be Learned from Former Soviet Families?” J. Policy Model. 18, 5:561–582, Oct. 1996. Paxson, Christina, “Saving and Growth: Evidence from Micro Data.” Eur. Econ. Rev. 40, 2:255–288, Feb. 1996. Schmidt-Hebbel, Klaus, Webb, Steven B., and Corsetti, Giancarlo, “Household Saving in Developing Countries.” World Bank Econ. Rev. 6, 3:529–547, Sept. 1992. Skinner, Jonathan, “Risky Income, Life Cycle Consumption, and Precautionary Savings.” J. Monetary Econ. 22, 2:237–55, Sept. 1988. Zeldes, Stephen, P., “Consumption and Liquidity Constraints: An Empirical Investigation” J. Polit. Econ. 97, 2:305–346, Apr. 1989.
Household Savings in the Transition Cevdet Denizer1 The World Bank, 1818 H Street N.W., Washington, DC 20433 E-mail: [email protected]
Holger Wolf Center for German and European Studies, Georgetown University, Washington, DC 20057 E-mail: [email protected]
and Yvonne Ying Oxford University Oxford, England OX1 2RL, United Kingdom E-mail: [email protected] Received October 13, 2000; revised April 30, 2002 Denizer, Cevdet, Wolf, Holger, and Ying, Yvonne—Household Savings in the Transition We explore household savings decision in Bulgaria, Hungary, and Poland during the transition from plan to market, finding four main results. First, except for the age profile, the effects of standard determinants on savings are comparable for transition and market economies. Second, we do not find support for a precautionary savings motive. Third, the evidence on consumption smoothing is mixed. Education of the head of the household, but not employment characteristics, are linked robustly to savings. Fourth, ownership of durables is negatively correlated with savings, consistent with the presence of anticipatory savings. J. Comp. Econ., September 2002, 30(3), pp. 463–475. The World Bank, 1818 H Street N.W., Washington, DC 20433; Center for German and European Studies, Georgetown University, Washington, DC 20057; and Oxford University Oxford, England OX1 2RL, United Kingdom. C 2002 Association for Comparative Economic Studies. Published by Elsevier Science (USA). All rights reserved.
Key Words: household savings; transition; comparative economics. Journal of Economic Literature Classification Numbers: D12, D31, D91, O16, P36. 1 We thank two anonymous referees and John Bonin for very helpful comments. All remaining errors are our own. The household surveys were made available by the World Bank.
0147-5967/02 $35.00
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C
2002 Association for Comparative Economic Studies Published by Elsevier Science (USA) All rights reserved.
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1. INTRODUCTION In terms of the sheer scope of economic, social, and political change, few events rival the transition from central planning to markets that has been taken place over the past decade in Eastern Europe. The macroeconomic impact of the transition has been dramatic. Output levels collapsed by between 20 and 40% in the early 1990s, while closures and labor force reductions led unemployment levels to rise sharply from near-zero recorded rates. The move from a cradle-to-grave system of stateguaranteed incomes to market-determined wages and the emergence of large-scale unemployment coupled with a sharp reduction in public benefits raised income uncertainty and changed expected future income profiles. The large changes in the determinants of household savings decisions over a very short period create a fertile ground for empirical research. Several authors have studied the comparative evolution of aggregate savings in transition economies (Borensztein and Montiel, 1991; Conway, 1995, 2001; and Denizer and Wolf, 2000) but less is known about the savings behavior of households, with the exception of Gregory, Mokhtari, and Schrettl (1999), which examines the pattern in Russia. In this article, we explore household savings in Bulgaria, Hungary, and Poland in the light of standard consumption theories. 2. MOTIVATION AND HYPOTHESIS The transition from plan to market involved dramatic declines in reported output and real income levels, alongside a dramatically increased level of income uncertainty for most households. These features apply to all three of our sample economies. In the year of the survey (1993 for Hungary and Poland and 1995 for Bulgaria), real GDP remained between 25% (Bulgaria) and 15% (Hungary and Poland) below the 1989 level, while the unemployment rate had increased from near-zero recorded levels to the double-digit range in all three countries. Price liberalization led to high inflation in the early transition years, eliminating any initial monetary overhang. In the sample year itself the CPI inflation rate ranged between a low of 22% in Hungary to a high of 62% in Bulgaria. We explore household surveys for Bulgaria, Hungary, and Poland to answer three questions. First, we examine whether household savings patterns across demographic groups in transition economies resemble the patterns established for market economies. Second, we examine whether the observed savings behavior is consistent with the predictions of the consumption smoothing and precautionary savings models. Third, we examine whether savings behavior was influenced by the combination of pent-up demand for consumer durables and the absence of consumer credit markets. Our primary focus is on the second and third question. The survey evidence permits a tentative identification of groups likely to benefit from the transition to a market economy. Using dummies to separate these groups, we examine whether intergroup differences in household savings patterns match the predictions of the
HOUSEHOLD SAVINGS IN TRANSITION
465
consumption smoothing model. Specifically, we assume that households headed by individuals with tertiary education, households deriving most of their income from self-employment and household headed by individuals employed in the private sector face more steeply upward sloping expected income profiles compared to households headed by individuals with lower educational attainment, employed in the public sector, or deriving their income from the social safety net, implying lower contemporaneous savings rates for the former groups. In comparison with market economies, the monetary return to education was small in planned economies. To the extent that past formal education is a good indicator of skills, the transition is likely to lead to a relative income gain and a steeper income profile for bettereducated individuals and a correspondingly lower savings rate, ceteris paribus. The relative income profile of private compared to public employment is influenced by two factors. The more attractive enterprises are likely to have been privatized first; thus, the core growth rate of firms with private ownership is likely to exceed that of firms remaining in public hands. In addition, employment in privatized enterprises was reduced to a much greater extent than it was in publicly owned firms. To the extent that firing decisions were based on worker skills, the remaining employees in private sector firms would have higher average skills compared to public sector employees.2 Finally, as self-employment was rare before the transition, we assume that individuals setting out on their own expect to capitalize on their skills to a greater extent than would be possible in their prior employment. The identification of households facing particularly high income risk is more tentative. We focus on two groups, retirees and public sector employees. Dependency ratios in all three sample countries in the sample year were high relative to market economies of comparable levels of development (EBRD 1996). The dependency ratios, coupled with the general fiscal constraints faced by the transition economies, suggests that the sustainability of real pension levels was subject to some doubt. In consequence, household headed by retirees and dependent on pensions arguably faced particularly high income risk. Reflecting the ongoing privatization process, typically with an accompanying reduction of employment, households headed by public sector employees also arguably faced higher real income risk compared to households headed by individuals in the private sector. Under the precautionary savings motive, these two groups should thus exhibit higher savings, ceteris paribus. We formally test this hypothesis in a dummy regression framework. The survey data also allow us to classify households by their ownership of a set of common durables. In comparison with market economies at similar levels, households in planned economies possessed fewer household durables. The 2 Differences between occupation groups are notoriously difficult to interpret because occupation choice itself is endogenous (Skinner, 1988; Carroll, 1994). In this respect, the transition data are arguably less problematic because it seems reasonable to assume that few households selected their pretransition employment with the expectation of a possible collapse of the socialist system. Furthermore, employment choice was highly restricted under the central planning system.
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absence of retail credit markets implied that any households wishing to purchase such durables after the transition would have to save the purchase price first, a possibility that has recently attracted attention in the savings literature.3 In this case, households with a small initial stock of durables would have higher savings ratios, ceteris paribus. Again using dummies to identify groups with high and low ownership of durables, we test this hypothesis directly. 3. DATA AND DESCRIPTIVE STATISTICS Our results are based on three surveys contained in the World Bank Household Expenditure and Income Data for Transitional Economies database. Using stratified random samples, the household surveys cover 2,466 households in Bulgaria (survey year 1995), 8,105 households in Hungary (survey year 1993), and 16,051 households in Poland (survey year 1993). The original surveys were conducted by different institutions and were placed into a consistent format by the World Bank4 to achieve comparability across the three countries. Each survey contains detailed information regarding the household’s expenditure (8 categories) and its income sources (12 categories for Poland and Bulgaria and 11 categories for Hungary). Savings is defined as the difference between disposable household income and household expenditure.5 In addition, the data set contains information about household asset ownership (5 categories for Poland and Bulgaria and 4 categories for Hungary), household size and location (urban/rural) as well as, for the head of household, the age, gender, type and sector of employment/income and highest level of education attained. Based on this information, we construct a set of explanatory variables used in the regressions reported below. The variables are split into characteristics of the head of household and characteristics of the household. The log and the squared log of the age of the head of household proxy for life-cycle factors. To capture education effects, we include four dummy variables set equal to 1 if the highest level of education attained by the head of the household was primary, secondary, vocational, or tertiary, respectively. In the regression analysis, we exclude the dummy for tertiary education. Three groups of dummies capture the socioeconomic group and the employment characteristics of the head of household. The data set classifies the socioeconomic 3
See Hayashi (1985), Zeldes (1989), Browning and Lusardi (1996), and Jappelli and Pagano (1989). See Household Expenditure and Income Data for Transitional Economies (HEIDE), Appendix 2 of RAD project “Poverty and Targeting of Social Assistance in Eastern Europe and the Former Soviet Union.” 5 Household savings rates are notoriously difficult to measure accurately even in mature market economies because of reporting errors. Considerable effort has been made to purge the dataset of clear outliers. In addition, we drop all observations with an implied dissavings rate above 50%. The frequency distribution did not suggest outliers on the right-hand-side tail of the distribution, while all three samples contain several extremely large negative savings rates, which are eliminated by this threshold condition. 4
HOUSEHOLD SAVINGS IN TRANSITION
467
group of the head of household as belonging to one of five groups: (1) wageearner, (2) self-employed, (3) pensioner, (4) recipient of other social benefits, and (5) recipient of other income. While the first three groups are defined consistently, the definitions of the latter two groups differ in their classification of unemployment benefits. Hence, we group categories (4) and (5) into a single new category “Benefits/Other,” which includes all heads of households for whom social benefits (including unemployment benefits) and income that does not fall under categories (1), (2), or (3) constitutes the greatest share of household income. In the regression, this new category is the excluded reference group. For Hungary and Poland, the survey classifies separately the labor force status of the head of household as being employed, unemployed, or inactive. We define three corresponding dummies; in the regression analysis, the inactive category is the excluded reference group. The labor force status data are not reported for Bulgaria. Finally, the survey reports the sector of employment of the head of household for Bulgaria and Poland, distinguishing between employment in the public sector, the private sector and the mixed/other sector. We define the three corresponding dummies. For the regression analysis, the public sector is the excluded reference group. An extensive set of dummies controls for the effect of various household characteristics on savings. We use dummies set equal to 1 if, respectively, the household is located in a rural area, the household is large (defined as households with more than four residents), the household owns land (only for Bulgaria and Poland), and the household owns productive assets. To capture any role of the relative income position, we include five dummies set equal to 1 if the household belongs to the lowest, second lowest, third lowest, fourth lowest, and highest quintile in the income distribution, respectively. For the regression analysis, we exclude the dummy for the highest quintile. To capture any temporary increase in the savings rate to satisfy a latent demand for durables, we construct four dummy variables. The first three are set equal to 1 if the household owns more than three, one to three, or zero of a set of common durables, respectively. The latter two dummies are excluded in the regression analysis.6 The fourth dummy is set equal to 1 if the household owns its residence. Tables 1 through 3 report the mean and median savings rates along with the standard deviation disaggregated by a subset of these household and head-ofhousehold characteristics. For the entire sample, median (mean) reported savings rates range from a low of 0.2% (1.7%) for Bulgaria to 1.1 (0.2%) for Hungary and 8.6% (8.3%) for Poland. The tables reveal a number of features. First, across age-groups, savings rates are lower for the midcareer group (30–49 years of age) than for the younger (18–29) group. For Bulgaria and Hungary the age distribution takes a U shape, 6 The set comprises a car, a black-and-white TV, a color TV, a refrigerator, a sewing machine, a PC, a VCR, a stereo, a car-washing device, a microwave, and a motorcycle. Data for all 11 items are available for Hungary; however, for Bulgaria (10 items) and Poland (5 items), the available information is less comprehensive.
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TABLE 1 Savings Rates by Group: Bulgaria
Full sample Household Characteristics Rural Urban Small Household (size ≤ 4) Large Household (size > 4) Durables Ownership More than 3 durables 1–3 durables 0 durables Asset Ownership Owns productive assets Does not own productive assets Owns Dwelling Does not own dwelling Owns Land Income Quintile Lowest 20% 2nd lowest 20% 3rd lowest 20% 4th lowest 20% Highest 20% Head of Household Characteristics Female head Age 19–29 30–49 50–64 65+ Highest education level Primary Secondary Vocational Tertiary Income Source Wage Earner Self-employed Pensioner Sector of Employment Public Private Mixed
Median
Mean
SD
Obs.
.002
.017
.298
1622
.046 −.021 .006 −.044
.066 −.010 .021 −.007
.318 .282 .298 .296
570 1052 1407 215
−.047 .014 .048
−.027 .034 .071
.276 .301 .344
510 1000 112
.060 −.005 .001 .026 .034
.080 .013 .016 .034 .056
.299 .297 .297 .304 .301
88 1534 1517 105 714
−.020 −.084 −.029 .008 .126
−.008 −.036 −.020 .027 .122
.299 .296 .282 .292 .293
321 326 324 325 326
.023
.028
.299
348
.051 −.051 −.015 .045
.062 −.031 .016 .058
.309 .279 .296 .310
60 493 488 546
.042 −.032 −.025 −.018
.050 −.021 −.015 −.012
.310 .286 .265 .281
828 455 106 226
−.026 .118 −.018
−.014 .113 .003
.279 .326 .292
746 288 549
−.031 .051 .020
−.014 .046 .018
.282 .289 .213
511 112 57
HOUSEHOLD SAVINGS IN TRANSITION
469
TABLE 2 Savings Rates by Group: Hungary
Full sample Household Characteristics Rural Urban Small Household (size ≤ 4) Large Household (size > 4) Durables Ownership More than 3 durables 1–3 durables 0 durables Asset Ownership Owns productive assets Does not own productive assets Owns dwelling Does not own dwelling Income Quintile Lowest 20% 2nd lowest 20% 3rd lowest 20% 4th lowest 20% Highest 20% Head of Household Characteristics Female head Age 19–29 30–49 50–64 65+ Highest Education Level Primary Secondary Vocational Tertiary Income Source Wage Earner Self-employed Pensioner Labor Force Status Employed Unemployed Inactive
Median
Mean
SD
Obs.
.011
.002
.234
7006
.001 .037 .008 .041
−.025 .025 −.000 .025
.238 .228 233 .242
3215 3791 6408 598
−.007 .022 .112
−.019 .015 .080
.233 .229 .264
3312 3339 355
.006 .011 .011 .079
−.009 .003 −.006 .055
.243 .233 .233 .235
447 6559 6094 912
−.036 −.017 −.003 .019 .085
−.040 −.021 −.015 .007 .080
.223 .234 .233 .227 .233
1402 1401 1401 1400 1402
.003
−.006
.230
2318
.035 −.003 −.004 .002
.012 −.009 −.006 .019
.242 .234 .237 .223
617 2872 1746 2260
.012 .007 −.005 .041
.005 −.002 −.013 .035
.231 .235 .239 .228
3439 1338 1621 608
.022 −.047 .006
.012 −.050 −.002
.236 .247 .228
3712 185 2739
.019 −.065 .006
.009 −.054 −.002
.237 .237 .228
3897 296 2807
differing from the inverted U shape prevalent in market economies (Paxson 1996) but matching the finding for Russia by Gregory, Mokhtari, and Schrettl (1999), suggesting that it may be a characteristic unique to transition economies. The differences are, however, statistically nonsignificant.
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TABLE 3 Savings Rates by Group: Poland
Full sample Household Characteristics Rural Urban Small household (size ≤ 4) Large household (size > 4) Durables Ownership More than 3 durables 1–3 durables 0 durables Asset Ownership Owns productive assets Does not own productive assets Owns dwelling Does not own dwelling Owns land Income Quintile Lowest 20% 2nd lowest 20% 3rd lowest 20% 4th lowest 20% Highest 20% Head of Household Characteristics Female head Age 19–29 30–49 50–64 65+ Highest Education Level Primary Secondary Vocational Tertiary Income Source Wage Earner Self-employed Pensioner Labor Force Status Employed Unemployed Inactive Sector Public Private Mixed
Median
Mean
SD
Obs.
.086
.083
.237
14663
.114 .075 .083 .102
.107 .071 .079 .098
.254 .227 .236 .238
4697 9966 11913 2750
.094 .082 .048
.090 .079 .046
.234 .238 .261
5131 9454 78
.122 .084 .103 .068 .108
.118 .080 .099 .063 .101
.229 .237 .246 .223 .246
895 13768 7890 6773 7320
−.013 .046 .076 .115 .217
−.021 .041 .076 .106 .212
.228 .221 .219 .222 .228
2932 2934 2933 2931 2933
.064
.060
.237
4860
.104 .084 .089 .074
.108 .079 .084 .077
.245 .229 .242 .238
1296 7268 3791 2304
.081 .081 .085 .116
.078 .079 .082 .110
.250 .226 .231 .236
4581 3799 4834 1449
.088 .126 .064
.080 .126 .065
.223 .269 .236
6943 1666 4716
.101 −.002 .063
.096 −.020 .064
.236 .201 .237
9522 306 4835
.098 .110 .062
.089 .111 .071
.226 .251 .241
5966 3869 867
HOUSEHOLD SAVINGS IN TRANSITION
471
Second, savings rates are consistently higher for households at the top compared to households at the bottom of the income distribution, again matching results for Russia by Gregory, Mokhtari, and Schrettl (1999).7 For the remaining characteristics of both households and heads of households, the pattern of the unconditional subgroup means and medians differs across the sample countries. We next turn to regression analysis to explore these features in a conditional setting. 4. DETERMINANTS OF HOUSEHOLD SAVINGS RATES To explore the conditional relationships, we regress household savings rates on standard demographic variables, on proxies for the likelihood that the transition will alter the household’s expected lifetime income profile, on proxies for relative income uncertainty, and on indicators of household durable ownership. Table 4 reports the results. The top rows identify the country, the number of observations, and the R 2 , which falls within the typical range for cross-section regressions based on household surveys. Beginning with the characteristics of the head of household, the estimated age profile of the head of household exhibits a significant nonlinearity, as suggested by the raw statistics reported in Tables 1 through 3. Households headed by women exhibit significantly higher savings rates. Under the assumption that higher education, and in particular tertiary education, is associated with a steeper expected income profile, the smoothing hypothesis predicts higher savings rates for households headed by individuals with lower educational attainment. The regression results are consistent with this prediction. Eight of the nine coefficients on education levels (households headed by individuals with primary, secondary, and vocational education; the excluded reference group are households headed by individuals with tertiary education) are positive; five are significant at the 5% level. The coefficient is largest (and statistically significant) for households headed by individuals with primary education for all three sample countries. We assess the consistency of the savings pattern with the predictions of the consumption smoothing and precautionary savings models by examining the empirical support for the hypothesis described under Section 2. We assume that households headed by individuals who are either employed in the private sector or are selfemployed face more steeply upward tilting expected income profiles, resulting in lower contemporaneous savings, ceteris paribus, relative to the excluded reference groups (heads of households employed in the public sector and heads of households deriving income from other sources). For precautionary savings, we assume that households headed by retirees and households headed by public sector employees face above-average income risk, implying a higher savings rate, ceteris paribus. 7 With some exceptions, the literature on savings in developing countries tends to find a positive income elasticity. See, for example, Giovannini (1983), Gersovitz (1988), Collins (1991), and Deaton (1992).
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TABLE 4 Determinants of Household Savings Rates
Observations R2 Constant Head of Household Characteristics Log (Age) [Log(Age)]2 Female Head Education Primary Education Secondary Education Vocational Education Income Source Wage-Earner Self-Employed Pensioner
Bulgaria
Hungary
Poland
1,622 0.1457 2.682 (2.42)∗∗
7,006 0.1116 1.737 (7.72)∗∗∗
14,663 0.1449 2.810 (11.12)∗∗∗
−1.302 (2.28)∗∗ 0.185 (2.454)∗∗∗ 0.051 (2.65)∗∗∗
−0.905 (7.28)∗∗∗ 0.133 (7.83)∗∗∗ 0.021 (3.23)∗∗∗
−1.40 (10.26)∗∗∗ 0.189 (10.32)∗∗∗ 0.009 (2.31)∗∗
0.054 (2.30)∗∗ 0.008 (0.37) 0.0045 (0.14)
0.035 (3.28)∗∗∗ −0.0008 (0.08) 0.015 (1.37)
0.032 (4.33)∗∗∗ 0.019 (2.75)∗∗∗ 0.026 (3.83)∗∗∗
−0.203 (3.69)∗∗∗ −0.142 (2.45)∗∗ −0.160 (2.87)∗∗∗
Labor Force Status Employed
0.01 (2.43)∗∗ 0.012 (0.42)
Unemployed Sector of Employment Mixed Private Sector Household Characteristics Rural Household Large Household Durables Ownership Land Ownership Productive Asset Ownership
0.023 (0.86) −0.018 (0.54) 0.021 (0.77)
0.013 (1.09) 0.010 (2.35)∗∗ 0.030 (1.65)∗ −0.114 (5.183)∗∗∗ −0.088 (4.68)∗∗∗ −0.009 (0.053) 0.001 (0.051)
−0.032 (3.99)∗∗∗ −0.0037 (0.372) 0.003 (0.185) −0.029 (1.685) −0.010 (0.512) 0.0024 (0.60) 0.0295 (3.04)∗∗∗
−0.040 (7.23)∗∗∗ −0.017 (1.67)∗ −0.098 (15.32)∗∗∗
−0.011 (0.87)
0.0262 (4.98)∗∗∗ −0.047 (9.27)∗∗∗ −0.044 (9.85)∗∗∗ −0.002 (0.452) −0.029 (3.05)∗∗∗
HOUSEHOLD SAVINGS IN TRANSITION
473
TABLE 4—Continued
House Ownership Lowest Income Quintile 2nd Lowest Income Quintile 3rd Lowest Income Quintile 4th Lowest Income Quintile
Bulgaria
Hungary
Poland
−0.055 (1.53) −0.379 (11.22)∗∗∗ −0.332 (11.85)∗∗∗ −0.234 (9.82)∗∗∗ −0.122 (5.51)∗∗∗
−0.069 (8.58)∗∗∗ −0.269 (21.27)∗∗∗ −0.195 (18.42)∗∗∗ −0.149 (15.89)∗∗∗ −0.0924 (10.70)∗∗∗
−0.0001 (0.01) −0.308 (43.00)∗∗∗ −0.214 (33.87)∗∗∗ −0.162 (26.90)∗∗∗ −0.117 (20.12)∗∗∗
The evidence is mixed. The coefficient on self-employment (the excluded reference group is households receiving social payments) is indeed negative for all three countries, but is significant only for Bulgaria. Furthermore, for both Bulgaria and Poland the coefficient on households headed by wage-earners is also negative, significant, and (in absolute terms) larger. Turning to the sector of employment, the results reject both the consumption smoothing and the precautionary savings hypothesis, conditional on our assumptions.8 The coefficient on heads of households employed in the private sector are positive and statistically significant (data for Hungary are not available for this classification), while the only significant coefficient for households headed by a pensioner is negative. The employment status of the head of household is uniformly insignificant, with mixed signs. Turning to household characteristics, large households exhibit significantly lower savings rates, while no common pattern emerges for rural relative to urban households. The position of the household in the income distribution (measured by dummies for households in each of the bottom four income quintiles) is highly significant. In all three countries, households in higher income quintiles have higher savings rates than households in lower income quintiles, ceteris paribus. The durables ownership dummy (equal to 1 if the household owns more than three of the set of durables described above) is negative and significant in all three regressions.9 The finding is consistent with the credit constraint view discussed 8 The limited support for smoothing is consistent with prior findings for developing market economies (Schmidt-Hebbel, Webb, and Corsetti, 1992; Case, 1995; Paxson, 1996). 9 OLS estimation is potentially problematic because of the endogeneity of the asset ownership variables. To address this potential problem, we follow Mokhtari’s (1996) two-stage least-squares approach. In a probit framework, we first regress the ownership dummies on the age dummies and the dummies for rural households, households with female heads of households, and large households. The fitted values of the probit equation are then used in place of the actual ownership dummies in the second stage. Comparing the results of the OLS and the two stage regressions yields no significant differences for the age, employment, income distribution and education variables. However, the negative savings effect of high durables ownership is reversed in Poland and Hungary, but not in Bulgaria.
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under Section 2, predicting that pent-up demand for durables coupled with the lack of retail credit markets forces households with small initial stocks of durables to accumulate the purchase price prior to buying a durable good. However, the finding is inconclusive because a negative real wealth effect provides an alternative explanation. In the presence of a negative real wealth effect, we would expect to find negative coefficients on the other proxies for household wealth. The evidence is inconclusive on this point; while seven of the eight other coefficients on ownership dummies are negative, only two are significant.10 5. CONCLUSION Using three matching household surveys for Bulgaria, Hungary, and Poland, we explore the savings responses of household to the transition experience. We examine three questions. First, does the household savings pattern in transition economies match the pattern observed in market economies? Second, is the pattern consistent with the predictions of consumption smoothing and precautionary savings models? Third, is there evidence of a credit-constraint motivation for savings? The answer to the first question is affirmative, with the exception of the age pattern, which robustly displays an U-shaped pattern rather than the inverted U-shaped pattern more typically observed in market economies. We find little evidence that consumption smoothing and precautionary savings motives play a major role in determining household savings pattern, with the exception of a negative link between savings and the educational attainment of the head of household. In interpreting these findings, it must be remembered that our tests are only as good as our assumptions that identify particular groups as facing particular income profiles or income risk. Hence, a high degree of intragroup differences that is not picked up by the other explanatory factors reduces the sharpness of the tests. The answer to the last question is positive. We find that households owning only a few standard durables exhibit higher savings rates, ceteris paribus, consistent with the view that these households do not have access to retail credit markets and are hence forced to accumulate savings in advance of durable purchases. However, the evidence is not conclusive since the result could alternatively reflect a negative wealth elasticity of household savings. REFERENCES Avery, Robert B., and Kennickell, Arthur B., “Household Saving in the U.S.” Rev. Income Wealth 37, 4:409–432, Dec. 1991. Borensztein, Eduardo, and Montiel, Peter J., “Savings, Investment and Growth in Eastern Europe” International Monetary Fund Working Paper WP/91/61. Washington, DC, IMF, May 1991. Bosworth, Barry, Burtless, Gary, and Sabelhaus, John, “The Decline in Saving: Evidence from Household Surveys.” Brookings Pap. Econ. Ac. 1:183–241, Winter 1991. 10 See Avery and Kennickell (1991) and Bosworth, Burtless, and Sabelhaus (1991) for a discussion of the real wealth elasticity of savings.
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