ESRA 2017 Programme

Tuesday 18th July      Wednesday 19th July      Thursday 20th July      Friday 21th July     

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Tuesday 18th July, 16:00 - 17:30 Room: Q4 ANF3

Income and wealth inequality

Chair Professor Carlos Farinha Rodrigues (Lisbon School of Economics and Management, Universidade de Lisboa )

Session Details

The study of income inequality and poverty using cross sectional survey data, such as Eurostat’s EU-SILC, is well established and has produced an important body of literature and an accepted methodology. However, no comparable research exists on the distribution of wealth, although it has been gaining importance due to the growing availability of cross sectional survey data that has shown how wealth is much more unequally distributed than income.

This session invites papers discussing the conceptual and methodological problems of analysing wealth distribution and inequality using cross sectional survey data such as the Household Finance and Consumption Survey (HFCS) conducted by the European Central Bank or the Survey of Consumer Finances (SCF) conducted by the Federal Reserve Board. In particular we welcome substantive research which investigates the distribution of different types of wealth and their relationship with income and savings, and intergenerational transfers (gifts and inheritances), presents novel methodological approaches, as well as postulates “good practices” in analysing such data.

The topics include, but are not restricted to:
- wealth measurement and definition, plus specific methodologic problems of dealing with a stock variable;
- wealth inequality by type of assets: real assets, in particular the household main residence, and financial assets; relationship between wealth and income inequality;
- intergenerational transfers, particularly inheritances and savings;
- theoretical models of wealth formation and lifetime.

Paper Details

1. The role of pension entitlements on wealth
Ms Laura Ravazzini (University of Neuchâtel)
Dr Ursina Kuhn (FORS)

Pension entitlements are a wealth component often omitted in the analysis on wealth. The role of this component depends strongly on the system for old-age provision (e.g.: capital funded vs. pay-as-you go) and on the respective level of benefits. If pension entitlements are not correctly taken into account, any wealth comparison between occupational groups or welfare regimes will be largely incorrect. Pension entitlements differ from financial assets in several ways. Acquired entitlements of old-age pension benefits represent a notional asset because in most cases they are granted only when the standard age threshold has been reached. For this reason, pension entitlements cannot be completely used for bequest motives or for investment purposes. Despite these disadvantages, the importance of pension entitlements for wealth should not be underestimated (OECD, 2013). Even if not perfectly liquefiable, when pension entitlements are included in the measure of net worth, wealth inequality significantly decreases (Frick & Grabka, 2010; 2013). In addition to this, the level of wealth of specific population groups, such as of the self-employed and of the elderly, changes in a radical way (Frick & Headey, 2009). This has been found to condition retirement behavior in the US (Gustman & Steinmeier, 2001). Although several attempts to estimate pension entitlements have been made in the USA (Stolyarova et al., 2008), research on the impact of pension entitlements on wealth in Europe is still scarce. This contribution aims at estimating the role of pension entitlements on the wealth distribution in Switzerland. Different approaches are tested to determine the best possible strategy. Record linkage is possible in Switzerland because SILC data is linked to the pension registry. Respondent-reported pension information is available in panel data such as the Swiss Household Panel (SHP 2012) and the German Socio-Economic Panel (SOEP 2013). This information can be used, but the accuracy must be checked to avoid systematic understatement. Other methods include statistical matching through similar observable characteristics (Rasner et al., 2013), simulations with the use of earnings history and estimations with aggregate statistics.

Frick, J.R., Grabka, M.M., 2010. Old-age pension entitlements mitigate inequality—but concentration of wealth remains high. DIW Wkly. Rep. 82010 55-64.

Frick, J.R., Grabka, M., 2013. Public Pension Entitlements and the Distribution of Wealth, in: Gornick, J., Jäntti, M. (Eds.), Income Inequality: Economic Disparities and the Middle Class in Affluent Countries. Stanford University Press, 362–388.

Frick, J.R., Headey, B.W., 2009. Living Standards in Retirement: Accepted International Comparisons are
Misleading. Schmollers Jahrb. 129, 309–319.

Gustman, A.L., Steinmeier, T.L., 2001. Retirement and Wealth. Soc. Secur. Bull. 64, 66–91.

OECD, 2013. Pensions at a glance. Paris: OECD Publishing.

Rasner, A., Frick, J.R., Grabka, M.M., 2013. Statistical Matching of Administrative and Survey Data An Application to Wealth Inequality Analysis. Sociol. Methods Res. 192–224.

Stolyarova, H., Nolte, M.A., Peticolas, B., 2008. Pension Estimation Program Users Guide. Health and Retirment Study.


2. Gender and social classe in Europe: how deep are the diferences?
Professor Analia Torres (CIEG/ISCSP/University of Lisboa)
Professor Joao Ferreira de Almeida (CIES-IUL)
Professor Rui Brites (ISEG/University of Lisboa)

Income and subjective well being are strong indicators of gender and class inequalities in Europe. There are also strong asymmetries between countries concerning households’ perceived economic difficulties.

Optimism (the degree of confidence in the future) is one more indicator of distinct and growing contrasts in European societies, but also with notorious differences among classes.

Finally, Southern and post-communist societies show, in a stable manner, less social trust and weaker social capital than the others. The same can be said of institutional trust.

Women, particularly those in classes with less capital, suffer heavily from the present processes. Inequalities and discriminations pertaining to gender have, anyway, well known specificities, with symbolic, economic and political dimensions, that tend to disfavor their relative “life chances". The classes with lower resources are, in general, very deeply affected, but it is also the case of some segments of the so called middle classes.

Based on the European Social Survey from 2002 to 2014 we try to analyse differences and contrasts among European countries, also considering social class and gender inequalities.


3. PORTUGUESE WEALTH DISTRIBUTION 2010/2013
Professor Carlos Farinha Rodrigues (CEMAPRE - Lisbon School of Economics and Management - Universidade de Lisboa)
Professor Isabel Andrade (CEMAPRE - Lisbon School of Economics and Management - Universidade de Lisboa)

During the last decades, Portugal remained one of the EU countries with highest income inequality, but even higher wealth inequality, as discussed in Rodrigues and Andrade (2014), Rodrigues et al.(2016) and Costa(2016), for example. Using the 2013 Household Finance and Consumption Survey (HFCS) data, the aim of this paper is to analyse Portuguese wealth inequality and its main driving factors, comparing the results with those of the 2010 survey. A second aim of this paper is to investigate the role played by inherited wealth and undertake a small scale study on Portuguese social mobility.

Early results of the 2013 HFCS (INE (2016) and Costa (2016)) suggest higher wealth inequality than in the previous wave, with the average net wealth of the 10% highest incomes equal to 5.8 times that of the 20% lowest (almost 10 times in terms of the median net wealth). Given the financial crisis and austerity policies followed in the period 2010-14 in Portugal, the comparison of the results becomes particularly relevant. Important inequality factors are the working status (self-employed) and level of education attained (tertiary) by the head of household. Non-financial assets represent 88% of the total household assets, with particular emphasis on the household main residence (HMR), which also accounts for most of the households’ debt, across income and wealth deciles. The composition of the households’ financial portfolio reveals a strong (and persistent) preference for low risk assets (56.0% of financial assets held in savings accounts).

A second objective of this paper is to analyse wealth inequality by focusing on the role played by inheritances and inter vivos gifts. The renewed focus on inherited wealth is linked to the interest generated by Piketty (2014), but its relevance can be judged by the high proportion of Portuguese households, 28.8% of the total in 2010, that had received intergenerational transfers. This proportion varies significantly across the net wealth distribution, from 6.0% of the households in the 1st decile to 47.0% in the 10th.

An important question to be addressed is the substantially more complex methodological issues raised by this type of survey compared to the traditional household surveys, such as the EU-SILC. The choices made by the ECB, particularly in sample definition and missing values treatment will also be discussed in this paper.