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Abstract
As a significant part of national wealth, households' wealth is a central issue in both policy debate and academic literature. Nevertheless, in Hungary little effort has been made so far to conduct a thorough evaluation of households' wealth over the past decade. This study provides a formal evaluation of Hungarian wealth and connects the development of components of wealth to the wider economy. Based on international comparison and econometric techniques, it is confirmed that the recent level of financial wealth among Hungarian households is still relatively low, whilst the level of current housing wealth is not evidently below the equilibrium level. These results provide an explanation as to why the government's housing subsidy scheme has a major effect on house prices rather than housing supply. Moreover, soaring house prices, supported by housing loans, suppressed financial savings. The ‘saving disaster’, i.e. small or in some periods zero saving rates, experienced in the early 2000s, to a certain extent is the other side of the ‘saving miracle’ of the early and mid-1990s when households rearranged their wealth portfolio from real assets to financial assets implying decreasing house prices and a higher saving rate.
Acknowledgments
Notes
a PMG estimation of CitationKiss and Vadas (2007).
† The author's paper is published posthumously.
1. The sources of Hungarian financial wealth and income data are the Central Bank of Hungary and Hungarian Central Statistical office respectively. Hungarian housing price and wealth data are from CitationVadas (2007).
2. For a more detailed description of Hungarian housing subsidy scheme see CitationHegedüs and Somogyi (2005).
3. In addition to geo- and demographical similarities, Portugal is the closest EU member state to Hungary in the Human Development Index ranking (for more details see Human Development Report 2006). As for specifics, the popularity of foreign exchange denominated loans indicates that Hungary is unlikely to follow a moderate path; the dynamics observed in Hungary probably mirror the dynamics observed in Portugal, where mortgage loans rose to almost 50 per cent of GDP in the last 10 years.
4. Justification of such an approach could come from an ECM-type consumption functions. Incorporating financial wealth into the consumption function is widespread, see for instance CitationMuellbauer and Lattimore (1995), CitationFagan et al. (2001). After housing market booms, in some countries it became inevitable that financial wealth is not sufficient to explain the wealth effect on consumption. As a result, many macro models and analysis, such as CitationGirouard and Blöndal (2001), CitationCase et al. (2005) and CitationPaiella (2007), incorporate housing wealth into consumption function. Under the assumption of long-run homogeneity the ECM-type consumption ensures stable consumption/income and wealth/income ratios. Therefore, the direct estimation between wealth and income seemingly provides appropriate results.
5. Their estimated parameters are α 0 = -879 (00.95), α 1 = 0.620 (0.048), α 2 = 0.234 (0.045), α 3 = 1-α 1-α 2 = 0.146, β 1 = 0.043 (0.0017), β 2 = 1-β 3 = 0.804, β 3 = 0.196 (0.051) and adjusted R2 = 0.93 where standard errors are in brackets.
6. Double maximum test can be applied when the main interest is the existence of structural breaks regardless of their number and the locations.
7. One might argue that the housing stock time series has low variance, so structural break tests are not able to detect the changes. Although this statement has no theoretical foundation, in order to check the robustness of our results, we simulate a time series with the characteristics of housing stock and, in the middle of the sample, new housing starts have been increased by 10 per cent, which is equivalent to 0.1 per cent change in housing stock growth rate. Tests were able to detect the presence and location of the break.
8. The high owner-occupancy rate in Hungary implies very small incomes from rental fees hence house price fluctuations alter disposable income marginally.
9. There is a marginal difference in simulation runs in the long-run. The discrepancy between the new housing stock levels is within 0.1 per cent.
10. Households' confidence index reached its all-time high value in 2002.
11. Note that equation (A-3) and equation (2') are equivalent since HHWr,t = PHr,tHSt and 1+gph,t = PHr,t/PHr,t-1.
12. Gross savings (financial savings plus housing investment) is the difference between income and consumption.
13. One should note the difference between ω and generally displayed HFWr/PDIr ratio. ω means the ratio of the stock of financial wealth to income no matter whether they are annual or quarterly data. Meanwhile, the ratio of wealth to income is generally considered as a ratio of wealth to the annualized income.