CAN HOUSEHOLDS AND WELFARE STATES MITIGATE RISING EARNINGS INSTABILITY?

We compare the evolution of earnings instability in Germany and the United Kingdom, two countries which stand for different types of welfare states. Deploying data from the German Socio‐Economic Panel (SOEP) and the British Household Panel Survey (BHPS), we estimate permanent and transitory variances of male income over the period 1984–2009 and 1991–2006, respectively. Studies in this literature generally use individual labor earnings. To uncover the role of welfare state and households in smoothening earnings shocks, we compute different income concepts ranging from gross earnings to net equivalent household income. We find evidence that the overall inequality of earnings in Germany and the United Kingdom has been rising throughout the period due to both higher permanent earnings inequality and higher earnings volatility. However, taking institutions of the welfare state and risk‐sharing households into account, we find that the volatility of net household income has remained fairly stable. Furthermore, redistribution and risk insurance provided by the welfare state is more pronounced in Germany than in the United Kingdom.     

MEASUREMENT OF THE DISTRIBUTION OF WEALTH IN CANADA

The only periodic data available in Canada on the asset holdings and net worth of the household sector are data collected through a series of household surveys originally initiated in 1954. Some limited data on the holdings of financial claims by the personal and unincorporated business sector are available from flow of funds work. Data are unavailable for estimation from estate tax returns.
The scope of the surveys has been expanded substantially so that the most recent survey obtained a very comprehensive list of asset holdings. The experience with Canadian surveys has been similar to that of other countries; surveys appear to underestimate asset holdings although the estimates are more reliable for widely held assets than for assets with a very skewed distribution. Nevertheless, the surveys appear to trace the accumulated distribution of personal savings over time to a considerable degree and provide useful cross-sectional trend data.
Canadian data show that wealth is more unequally distributed among family units than is income although wealth appears to be more equally distributed between income groups than is income. Wealth is also very unequally distributed within the same income group. Over time, there appears to have been some movement towards a more equal distribution of asset holdings between income groups.     

收入差距与社会地位寻求:一个高储蓄率的原因

我们使用中国城镇住户调查数据证实:在控制家庭收入之后,收入差距仍然会显著减少家庭除教育以外的消费。我们还发现收入差距对低收入或年轻家庭的消费抑制更加明显,但能刺激教育投资的上升。这很可能来源于为提升社会地位而储蓄的动机。更高的社会地位可以带来各种物质或非物质上的收益。而社会不平等的增加意味着进入社会上层可以获得更高的收益,同时提升地位需要更多的财富。这些都可能加强人们为提高社会地位而储蓄的激励。     

Income Mobility, Inequality and Social Welfare

It is often argued that an observation of rising annual income inequality need not have negative normative implications. The argument is that if there has been a sufficiently large simultaneous increase in mobility, the inequality of income measured over a longer time period can be lower despite the rise in annual inequality. In this paper, it is shown by example that if normative implications are drawn from a standard social welfare function, the set of circumstances put forward in the above argument are not sufficient to guarantee that social welfare will improve. The reason is that even though rising mobility does reduce longer term inequality, it also increases the variability of income profiles over time and the latter has a detrimental social welfare effect. Hence, there are two types of mobility: one which reduces inequality (regression to the mean), but another that increases inequality (relative movements uncorrelated with incomes). Further, if individuals' aversion to income variabiltiy is sufficiently larger than the social welfare judge's aversion to inequality, then an increase in mobility, no matter how large, cannot offset the negative normative effect of rising annual inequality.     

ESTIMATING INCOME INEQUALITY IN CHINA USING GROUPED DATA AND THE GENERALIZED BETA DISTRIBUTION

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.     

Household wealth, public consumption and economic well-being in the United States

Standard official measures of household economic well-beingin several countries are based on money income. The generalconsensus is that such measures are limited because they ignorecertain crucial determinants of well-being. We examine two suchdeterminants—household wealth and public consumption—inthe context of the US. Our findings suggest that the level anddistribution of economic well-being is substantially alteredwhen money income is adjusted for wealth or public consumption.Over the 1989–2000 period, median well-being appears toincrease faster when these adjustments are made than when standardmoney income is used. Adding imputed rent and annuity from householdwealth to household income increases measured inequality, whileadding public consumption reduces it. However, all three measuresshow about the same rise in inequality over the period.     

中国城镇居民的财产分配

本文利用住户调查数据对 1 995年的中国城镇住户的财产分配状况进行了经验分析 ,包括对财产分配的差距进行了测量 ,影响财产分配的主要因素进行了估计 ,并将中国城镇住户的财产分配进行了国际比较。与大部分市场经济国家相比 ,中国城镇居民之间财产分配的差距并不大。但是中国城镇居民的财产分配差距超过了收入分配差距 ,而且从长期趋势上可能会出现加速扩大的势头。中国城镇居民之间财产分配的不均等并非全是经济市场化过程的结果。一些不均等的原因来自于传统计划经济遗留下来的分配模式。本文还发现 ,在户主一生中财产积累出现了两个高峰值。这是与正统的生命周期理论不同的。本文还表明了财产分配和收入分配之间的较强相关性。     

Consumption,income, and wealth inequality in Canada

In this paper, we document some features of the distribution of income, consumption and wealth in Canada using survey data from many different sources. We find that wage and income inequality have increased substantially over the last 30 years, but that much of this rise was offset by the tax and transfer system. As a result, the rise in consumption inequality has been relatively mild. We also document that wealth inequality has remained fairly stable since 1999. Using both confidential data and publicly available data, we are able to gauge the extent to which the publicly available data conceals aspects of inequality that confidential data reveals.     

How large is income inequality in China: assessment on different estimates of Gini coefficient

The rising income inequality in China has attracted social attentions, especially since SWUFE published the unbelievably high Gini coefficient in December 2012. In order to answer the question how large income inequality in current China is, this paper compares existing different Gini coefficients estimated from four different household surveys, which are the NBS household survey, the CHIP survey, the CHFS of SWUFE, and the CFPS of Peking University, and then assesses these household surveys themselves. The relevant evidences indicate that the national Gini coefficient in current China is between 0.47~0.52. The sampling defects of the CHFS are significantly major and that the national Gini coefficient of 0.61 published by SWUFE is seriously overestimated.     

DOES SIZE MATTER? THE IMPACT OF CHANGES IN HOUSEHOLD STRUCTURE ON INCOME DISTRIBUTION IN GERMANY

Income inequality in Germany has been continually increasing during the past 20 years. One cause of this development, among others, could be structural shifts in household formation due to long‐term societal trends. These affect per capita incomes, which has repercussions for the income distribution even if wages remain constant. The aim of this paper is to quantify the proportion of changing household structures in the increase in inequality. We find that the growth of the income gap in Germany (for both East and West from 1991 to 2007) is indeed strongly related to changes in household structure and employment behavior, and a large part of this increase is compensated by the welfare state.     

Ownership and earnings inequality in urban China

Along with advances in urban state-owned enterprise reform, fast growth of private sector and changes in the wage structure, earnings inequality in urban China has been increasing. Using data from the 1988 and 2007 waves of the urban household survey conducted by China Household Income Project, this paper attempts to examine the impact of the change in ownership structure on earnings distribution in urban China. We find that developing non-state-owned enterprises (nonSOEs) or privatization of state-owned enterprises (SOEs) enlarge earnings inequality, but the difference in earnings level between the two sectors is small. Although workers in SOEs receive higher income than in nonSOEs, the difference is more caused by endowment difference rather than coefficient differences. Introducing market power to wage determination system is more influential to the rising earnings inequality which leads more rewards on working experience and educational attainment.     

Using sparse categorical principal components to estimate asset indices: new methods with an application to rural southeast asia

Asset indices have been used since the late 1990s to measure wealth in developing countries. We extend the standard methodology for estimating asset indices using principal component analysis in two ways: by introducing constraints that force the indices to have increasing value as the number of assets owned increases, and by estimating sparse indices with a few key assets. This is achieved by combining categorical and sparse principal component analysis. We also apply this methodology to the estimation of per capita level asset indices. Using household survey data from northwest Vietnam and northeast Laos, we show that the resulting asset indices improve the prediction and ranking of income both at household and per capita level.     

贫富差距、供求弹性与房价*

近些年，中国的贫富差距和房价居高不下，但现有文献忽视供求弹性与贫富差距交互作用对房价的影响。据此，本文构建结合贫富差距和供求弹性的住房存量调整模型，使用中国2002—2012年7省份33个城市的UHS数据发现，收入和财富的基尼系数对房价有正影响；供求弹性对房价分别有负影响和正影响；收入和财富基尼系数与供求弹性交互项对房价分别有正影响和负影响。据此，为防止房价泡沫，各级政府一方面应缩小贫富差距，另一方面应增加土地和住房供给。     

Reform,Growth, and Inequality in China*

This paper provides a survey of the literature on inequality in China – level, change, causes, and consequences. It attempts to answer six main questions. How much has inequality risen? What is its relation to poverty alleviation? What has happened to wealth inequality? What are the main dimensions of rising income inequality? The dimensions examined are: the rural–urban divide; urban labor market reform; regional divergence; rural–urban migration; and entrepreneurship, rent‐seeking, and corruption. Was it inevitable that inequality should rise so much? Does it matter that inequality has risen? Income distribution in China is bound up with both economic reform and economic growth. This paper concludes by considering the countervailing forces that will determine the path of inequality in future years.     

Does income inequality hinder economic growth? New evidence using Australian taxation statistics

Using taxation statistics, we first derive consistently defined Gini coefficients for the period 1942–2013 for Australia as a whole as well as its eight states and territories. While income inequality exhibited a downward trend until 1979, it has since been on the rise not only over time, but also across states and territories. We then proceed to examine the effect of inequality on economic growth after controlling for changes arising from investment in physical and human capital using available panel data across all states and territories (1986–2013). We find that inequality adversely affects economic growth with a couple of years delay, an outcome consistent with similar studies undertaken in the United States and Europe. Our findings suggest that policymakers can address rising income inequality by implementing measures that support, and enhance, human capital accumulation given its long-run economic and social benefits.     

Income inequality, consumption, and social-status seeking

Using the Chinese Urban Household Survey data between 1997 and 2006, we find that income inequality has a negative (positive) effect on household consumption net of education expenditures (savings) even after we control for household income. We argue that people save to improve their social status when social status is associated with pecuniary and non-pecuniary benefits. Rising income inequality can strengthen the incentives of status-seeking savings by increasing the benefit of improving status, and by enlarging the wealth level required for status upgrading. We also find that the negative effect of income inequality on consumption is stronger for poorer and younger people and that income inequality stimulates more education investment, which are consistent with the status-seeking hypothesis.     

Evolution of wealth inequality in China

Household wealth is a key indicator that reflects national economic competiveness and individual income levels. The distribution of wealth is central for evaluating social justice in a country. This article uses a data set composed of the 2002 China Household Income Project and the 2010 Chinese Family Panel Survey to analyze the level of wealth and wealth inequality in China during 2002 and 2010. The analysis decomposes the evolution of wealth inequality during that period in terms of the structure and composition of wealth. The findings show that there was a large increase in the quantity of wealth and wealth inequality between 2002 and 2010. The level of wealth in 2010 was four times that of 2002, and housing assets were the greatest component of overall wealth in 2010. Wealth inequality also rose dramatically after 2002, with the Gini coefficient of the distribution of wealth increasing from 0.538 in 2002 to 0.739 in 2010. The rapidly escalating price of housing has been the main contributor to increasing wealth inequality in recent years.     

中国农村的收入差距与健康

随着收入差距的扩大,收入分配对健康和健康不平等的影响日益受到关注。本文利用中国健康营养调查(CHNS)1997年和2000年农村的面板数据回答两个问题:收入差距对健康的影响以及影响健康的方式;收入差距的扩大是否会导致健康不平等的加剧,尤其是低收入人群的健康是否受到更为不利的影响。研究发现,首先收入差距对健康的影响存在滞后效应;其次,收入差距对健康的影响呈现“倒U”型,在收入差距较高时,收入差距对健康的影响主要为负向的,一个可能的原因是收入差距影响到公共卫生设施的供给。再次,收入差距的扩大会加强收入效应,其含义是如果低收入人群的收入更容易受到负向冲击,那么收入差距对低收入人群的健康更为不利。     

Understanding Rising Income Inequality in Germany, 1999/2000–2005/2006

We examine the factors behind rising income inequality in Europe's most populous economy. From 1999/2000 to 2005/2006, Germany experienced an unprecedented rise in net equivalized income inequality and poverty. At the same time, unemployment rose to record levels, part‐time and marginal part‐time work grew, and there was evidence for a widening distribution of labor incomes. Other factors that possibly contributed to the rise in income inequality were changes in the tax and transfer system, changes in the household structure (in particular the rising share of single parent households), and changes in other socio‐economic characteristics (e.g., age or education). We address the question of which factors were the main drivers of the observed inequality increase. Our results suggest that the largest part of the increase was due to increasing inequality in labor incomes, but that changes in employment outcomes and changes in the tax system also contributed considerable shares. By contrast, changes in household structures and household characteristics, as well as changes in the transfer system only seem to have played a minor role.