It is a pleasure for me to celebrate with you the award of the 2019 Bernácer Prize to Gabriel Zucman, Assistant Professor of Economics at the University of California, Berkeley. Gabriel’s creative work on measuring household wealth over time and across countries and his studies on the effects of taxation and globalisation on the accumulation of wealth have become increasingly influential among academic economists and policymakers. He is a deserved recipient of the Bernácer Prize, which is awarded each year to an outstanding young European economist working in the fields of macroeconomics and finance and globalization.
This year’s prize has been awarded specifically for Gabriel’s “influential research on wealth inequality and the redistributive effects of globalisation”. Gabriel, together with his co-authors Thomas Piketty and Emmanuel Saez, has been one of the pioneers in this field, showing us how to use various data sources – aggregate sectoral accounts, household surveys, fiscal data, historical administrative data and unofficial records – to estimate the evolution and determinants of the wealth distribution over centuries. Such a long time range is important, as many of the movements in wealth inequality are very gradual, which means that these changes can only be estimated reliably once enough data are available. At the same time, retrieving historical information on wealth poses multiple challenges. First, data on household wealth are much scarcer than, say, data on household income. Second, the wealth distribution is heavily skewed toward its top tail, such that relatively few households hold a large fraction of aggregate wealth in the economy. Consequently, to be able to measure wealth inequality, it is important that we include information about the very richest households. Third, and especially for the richest households, one should account for all assets, including those held abroad, which tend to be more difficult to trace.
A key approach used by Gabriel to overcome these challenges is the “income capitalisation method”, which uses fiscal data on capital income to estimate the wealth distribution. Although not always easily accessible, fiscal data are available for several decades and also cover the richest households. The method is therefore useful in estimating the evolution of the wealth distribution over long periods of time. Using this approach, Gabriel has provided us with estimates of the top wealth shares in the United States over the last century.1 This influential work shows that wealth concentration in the United States was high at the beginning of the 20th century, fell from 1929 to 1978, and has continuously increased since then. The substantial increase in wealth inequality since the early 1980s has been driven by the very richest households (the top 0.1% of the wealth distribution and above).
Gabriel then used the estimates of the wealth distribution to construct “distributional national accounts” for the United States.2 These accounts combine tax, survey and national accounts data to estimate the distribution of national income across households. Importantly, in contrast to previous estimates which only capture the income recorded in aggregate statistics in an incomplete fashion, distributional national accounts consistently cover all national income in aggregate data. In addition, this work provides estimates for both pre-tax and after-tax income, documenting the extent to which the tax system has dampened the increase in US income inequality over the past few decades.
Gabriel’s findings for the United States have recently been extended to many other countries, including large emerging economies, in the “World Inequality Database”, which provides data on household inequality calculated using a common and consistent methodology. The time series in the World Inequality Database are the result of an ingenious combination of various data sources, including survey data, tax data and, sometimes, information from named lists of wealthy individuals to improve estimates of the very top of the wealth distribution.
The World Inequality Database has substantially benefited the academic community by providing easily accessible data, and it has spurred a wider debate about the causes and consequences of inequality. For example, the database has documented diverse trends in the dynamics of income and wealth inequality since 1980 across countries, suggesting national institutions play a key role in affecting inequality. The data show that in recent decades incomes of the poorer half of the global population grew significantly thanks to high growth in Asia, in particular in China and India.
Gabriel’s extensive work measuring the distribution of wealth and income has allowed us to think more rigorously and in quantitative terms about the main determinants of changes in household wealth distribution.
At this point, allow me to stress that this topic is especially important in the euro area, where the public debate on the expansionary stance of monetary policy is sometimes caricatured in terms of a clash between “winning” borrowers and “losing” savers. This representation is simplistic because it ignores the various other channels through which monetary policy affects household wealth, including its indirect impact on incomes and employment. In fact, new approaches to modelling and analysing household heterogeneity have recently stressed the importance of these indirect channels of monetary transmission, which operate through the responses of higher wages and employment to monetary easing.3 A key quantitative finding of that literature is that this indirect income channel disproportionately stimulates incomes and consumption in the lower part of the distribution.
In line with this work, internal ECB research finds that low short rates do hurt “savers”, i.e., households owning non negligible amounts of liquid assets, via a direct effect – that is, via the reduction in their income from those assets. Low short rates, however, also benefit savers, like all other households, via an indirect effect – that is, the reduction in their unemployment rate and the increase in their labour income. The indirect effect dominates from a quantitative perspective. In addition, through the reduction of the unemployment rate of poorer households, the indirect effect reduced income inequality. On the whole, these results support the finding that monetary policy in recent years benefited most households and did not contribute to an increase in wealth, income or consumption inequality.4 This debate illustrates that we need increasingly precise ways to measure wealth in order to foster a more informed public debate about the effects of various policies and other factors on the distribution of wealth. As you may know, the Eurosystem has for many years contributed to the measurement and analysis of the wealth distribution and its components across countries by collecting and providing the Household Finance and Consumption Survey micro data.
My overview of Gabriel’s work has been quite selective, focusing on topics related to the measurement and determinants of inequality in household wealth, but Gabriel has also worked on an impressive range of other areas, such as the substitution between illegal tax evasion and legal tax avoidance, effects of wealth taxes on household saving and the role of tax havens and tax competition in profit-shifting by large multinational firms.
Dedicated research to measure inequality around the globe and the analysis of its root causes is an established priority among major institutions. This is an important development. We should however not lose focus. Despite impressive progress in combating poverty over the past decades, poverty persists at unacceptable levels.
That’s why, in face of a global economic slowdown, economic policy needs to ensure that people continue to move out of poverty in the years to come.
Please join me in congratulating Gabriel on being awarded this year’s Bernácer Prize. Gabriel, I wish you continued success and look forward to following your future work.