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In this paper we investigate the relationship between loose monetary policy, low inflation, and easy bank credit and house price booms.

Using a panel of 11 OECD countries from 1920 to 2011 we estimate a panel VAR in order to identify loose monetary policy shocks, low inflation shocks, bank credit shocks, and house price shocks.

We show that during boom periods there is a heightened impact of all three “policy” shocks with the bank credit shock playing an important role. However, when we look at individual house price boom episodes the cause of the price boom is not so clear. The evidence suggests that the house price boom that occurred in the United States during the 1990s and 2000s was not due to easy bank credit.

Shocks from the shadow banking system are not separately identified. These are incorporated into the fourth “catch-all” shock.

Our evidence on housing price booms that expansionary monetary policy is a significant trigger buttresses the case for central banks following stable monetary policies based on well understood and credible rules.

This paper uses historical evidence to evaluate the relative importance of three main causes of house price booms. Our results bring into question the commonly held view that loose bank credit was to blame for the U.S. house price bubble of the later 1990s.

We examine the cardinal gap between wage distributions of the incumbents and newly hired workers based on entropic distances which are well-defined welfare theoretic measures. Decomposition of several effects is achieved by identifying several counterfactual distributions of different groups. These go beyond the usual Oaxaca–Blinder decompositions at the (linear) conditional means. Much like quantiles, these entropic distances are well-defined inferential objects and functions whose statistical properties have recently been developed. Going beyond these strong rankings and distances, we consider weak uniform ranking of these wage outcomes based on statistical tests for stochastic dominance. The empirical analysis is focused on employees with at least 35 hours of work in the 1996–2012 monthly Current Population Survey (CPS). Among others, we find incumbent workers enjoy a better distribution of wages, but the attribution of the gap to wage inequality and human capital characteristics varies between quantiles. For instance, highly paid new workers are mainly due to human capital components, and in some years, even better wage structure.

Between 1995 and 2012, the wage distribution of male workers in Brazil shifted to the right and became less dispersed. This paper attempts to identify the reasons for that movement in male wage distribution, focusing on the impact of education expansion on wage distribution. The Oaxaca-Blinder (OB) and Recentered Influence Function (RIF) decomposition results show that both changes in returns on skills and upgrades in the composition of work skills contribute to increases in the average wage and wages at the 10th and 50th percentiles. The shifts in returns to skills had a decreasing impact on wages at the 90th percentile and are identified as the primary force reducing wage inequality. Education expansion had an equalizing impact on wage distribution, primarily through the decline in return to education.

This study uses migrant household survey data from 2008 to 2009 to examine how parental migration decisions are associated with the nutritional status of children in rural and urban China. Results from instrumental variables regressions show a substantial adverse effect of children’s exposure to parental migration on height-for-age Z scores of left-behind children relative to children who migrate with their parents. Additional results from a standard Blinder–Oaxaca decomposition, a quantile decomposition, and a counterfactual distribution analysis all confirm that children who are left behind in rural villages – usually because of the oppressive hukou system – have poorer nutritional status than children who migrate with their parents, and the gaps are biggest at lower portions of the distribution.

This paper argues that the assumption of a homogeneous workforce, which is implicitly invoked in the decomposition analysis of changes in welfare indicators, hides the role that schooling and its returns may have on the understanding of these changes. Using Peruvian cross-sectional data for a period of 10 years (2004–2013) and counterfactual simulations, this paper finds that the main factor contributing to poverty reduction has been individuals’ changes in labor earnings, and the role of these changes has been less important in reducing income inequality. The main driving force of reduced income inequality has been the fall in returns to education, which at the same time has been one of the important factors to constraining the period’s remarkable progress in poverty reduction and expansion of the middle class.

European countries have the world’s most redistributive tax and transfer systems. While they have been well equipped to deal with vertical inequality – fostering redistribution from the rich to the poor – less is known about their performance in dealing with horizontal inequality, that is, in redistributing across socioeconomic groups. In a context where individuals may not only care about vertical redistribution, but also about the economic situation of the specific groups they belong to, the horizontal dimension of redistribution becomes politically salient and can be a source of social tensions. The authors analyse the performance of the 28 EU countries for redistribution across (i) age groups; (ii) occupational groups; and (iii) household types over the period 2007–2014 using counterfactual simulation techniques. We find a significant degree of heterogeneity across countries: changes in the tax and transfer system have particularly hit the young and the losers of occupational change in Eastern European countries, while households with greater economic security have benefited from these changes. The findings of this study suggest that horizontal inequality is a dimension which policy-makers should take into account when reforming tax and transfer systems.

This paper provides household lifetime inequality indexes derived from representative U.S. labor market data. We obtain this result by using estimates of the household search model proposed by Flabbi and Mabli (2012). Inequality indexes computed on the benchmark model shows that inequality in utility values is substantially different from inequality in earnings and wages and that inequality at the cross-sectional level is significantly different from inequality at the lifetime level. Both results deliver original policy implications that would have not been captured without using our approach. In particular, we find that a counterfactual policy experiment consisting in a mean-preserving spread of the wage offers distributions increases lifetime inequality in wages and earnings but not in utility. When comparing inequality at the individual level between men and women, we find inequality in wages and earnings to be higher for husbands than wives but inequality in utility to be higher for wives. A counterfactual decomposition shows that the job offers parameters are the main source of the gender differential.

Using harmonized wealth data and a novel decomposition approach in this literature, we show that cohort effects exist in the income profiles of asset and debt portfolios for a sample of European countries, the United States, and Canada. We find that the association between household wealth portfolios at the intensive margin (the level of assets) and household characteristics is different from that found at the extensive margin (the decision to own). Characteristics explain most of the cross-country differences in asset and debt levels, except for housing wealth, which displays large unexplained differences for both the under-50 and over-50 populations. However, there are cohort differences in the drivers of wealth levels. We observe that younger households’ levels of wealth, given participation, may be more responsive to the institutional setting than mature households. Our findings have important implications, indicating a scope for policies which can promote or redirect investment in housing for both cohorts and which promote optimal portfolio allocation for mature households.

To explore income inequality in urban China, this paper investigates disparities between- and within-urban locals and rural migrants from 2002 to 2013, using three waves of the China Household Income Project (CHIP) data. While the existing literature concentrates on the wage disparity between these two groups, our results show that the Gini among the migrants increased by 17.86% between 2007 and 2013 and that among the locals increased by 15.54% from 2002 to 2007. The urban–migrant average income gap decreased during the whole period mainly due to higher growth in migrants’ average income. Estimates based on Mincerian earnings functions for both groups reveal the significant role of the education, occupation and type of contract in determining the within-group inequality. In addition, using a recentred influence function (RIF), we observe that short-term and other types of contracts, duration of the job, in-system ownership, marriage and skill have inequality-enhancing effects for migrants. The variation of skills has a larger impact on the income disparity among migrants than on that among urban locals. The RIF-based Blinder–Oaxaca decomposition of the mean difference of incomes shows that labour market discrimination between the two groups is not significant; however, both pure explained and unexplained differences are significant when applying the RIF decomposition to the variance of the logarithms of incomes. While the type of contract significantly reduces the pure explained difference between migrants and urban locals, occupation has a positive impact on this difference between these two groups. The heterogenity analysis shows that the factors influencing incomes in these two groups are different. We recommend labour market intervention to reduce unreasonable occupational and sectoral disparities, especially in the net inflow provinces, to mitigate urban inequality in China effectively.