The Gender Wealth Gap in Europe: Application of Machine Learning to Predict Individual-level Wealth

This article provides comparative estimates of the gender wealth gaps for 22 European countries, employing data from the Household Finance and Consumption Survey. The data on wealth are collected at the household level, while individual-level data are needed for the estimates of gender wealth gaps. We propose a novel approach using machine learning and model averaging methods to predict individual-level wealth data for multi-person households. Our results suggest that random forest performs best as the predicting tool for this exercise, outperforming elastic net and Bayesian model averaging. The estimated gender wealth gaps tend to be in favor of men, especially at the top of the wealth distribution. Men have 24 percent more wealth than women on average. We also find that a high home ownership rate is associated with a smaller country-level gender wealth gap. Our estimates suggest that the individual-level wealth inequality is on average 3 pp higher than the household-level wealth inequality in multi-member households.     

Estimating Consumption Responses to Income Shocks of Different Persistence Using Self‐Reported Income Measures

Models of intertemporal consumption choice posit that consumption reacts more strongly to income shocks with persistent effects than to shocks with temporary effects. This prediction is tested using data from the Estonian Household Budget Surveys for 2002–07. Questions in the survey make it possible to distinguish between two income components of different persistence, using the individual households’ subjective income classification. Estimations confirm that households distinguish income components of different persistence and react to these differently; the consumption response to income shocks with persistent effects is significantly higher than the response to shocks with only temporary effects. Further analysis reveals, however, that consumption also reacts to lagged shocks to temporary income even when the households are not liquidity constrained, suggesting that their behavior is not fully consistent with the standard forward‐looking unconstrained consumption models.     

Macroeconomic Factors in the Dynamics of Corporate and Household Saving: Evidence from Central and Eastern Europe

This article uses panel data estimations on annual data from 10 Central and Eastern European countries to assess the effect of different macroeconomic variables on the dynamics of corporate and household saving. The analyses show that changes in the macroeconomic environment affect the saving rates in both sectors, but with marked differences across the two sectors. The differences are most pronounced for the output gap, the real interest rate, the inflation rate, and the current account balance. Some variables, including the unemployment rate and changes in the real exchange rate, are unimportant in both sectors. The different results for the two sectors underscore the importance of analyzing the factors driving the dynamics of corporate and household saving separately.