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The benefits of new technologies accrue not only to high-skilled labor but also to owners of capital in the form of higher capital incomes. This increases inequality. To make this argument, we develop a tractable theory that links technology to the distribution of income and wealth—and not just that of wages—and use it to study the distributional effects of automation. We isolate a new theoretical mechanism: automation increases inequality by raising returns to wealth. The flip side of such return movements is that automation can lead to stagnant wages and, therefore, stagnant incomes at the bottom of the distribution. We use a multiasset model extension to confront differing empirical trends in returns to productive and safe assets and show that the relevant return measures have increased over time. Automation can account for part of the observed trends in income and wealth inequality.

In this article a major channel through which financialisation or finance-dominated capitalism affects macroeconomic performance is examined: the distribution channel. Empirical data for the following dimensions of (re-) distribution in the period of finance-dominated capitalism since the early 1980s is provided for 15 advanced capitalist economies: functional distribution, personal/household distribution and the share and the composition of top incomes. Based on the Kaleckian approach to the determination of income shares, the effects of financialisation on functional income distribution are studied in more detail. Some stylised facts of financialisation are integrated into the Kaleckian approach, and by means of reviewing empirical and econometric literature it is found that financialisation and neoliberalism have contributed to the falling labour income share since the early 1980s through three main Kaleckian channels: 1) a shift in the sectoral composition of the economy, 2) an increase in management salaries and rising profit claims of the rentiers and thus in overheads, and 3) weakened trade union bargaining power.

This paper presents new findings on global inequality dynamics from the World Wealth and Income Database (WID.world), with particular emphasis on the contrast between the trends observed in the United States, China, France, and the United Kingdom. We observe rising top income and wealth shares in nearly all countries in recent decades. But the magnitude of the increase varies substantially, thereby suggesting that different country-specific policies and institutions matter considerably. Long-run wealth inequality dynamics appear to be highly unstable. We stress the need for more democratic transparency on income and wealth dynamics and better access to administrative and financial data.

The paper studies how high household leverage and crises can be caused by changes in the income distribution. Empirically, the periods 1920-1929 and 1983-2008 both exhibited a large increase in the income share of high-income households, a large increase in debt leverage of low-and middle-income households, and an eventual financial and real crisis. The paper presents a theoretical model where higher leverage and crises are the endogenous result of a growing income share of high-income households. The model matches the profiles of the income distribution, the debt-to-income ratio and crisis risk for the three decades preceding the Great Recession.

We study the relation between the distribution of labor earnings and the distribution of wealth. We show, theoretically as well as empirically, that while labor earnings and precautionary savings are important determinants of wealth inequality factors, they cannot by themselves account for the thick tail of (the large top shares in) the observed distribution of wealth. Other determinants, like stochastic returns to wealth, as well as savings rates and rates of returns increasing in wealth, need to be accounted for.

This paper investigates how tax changes for different income groups affect aggregate economic activity. I construct a measure of who received (or paid for) tax changes in the postwar period using tax return data from NBER’s TAXSIM. Variation in the income distribution across US states and federal tax changes generate variation in regional tax shocks that I exploit to test for heterogeneous effects. I find that the positive relationship between tax cuts and employment growth is largely driven by tax cuts for lower-income groups and that the effect of tax cuts for the top 10 percent on employment growth is small.

This article studies the long-run relationship between the capital share in national income and top personal income shares. Using a newly constructed historical cross-country database on capital shares and top income data, we find evidence on a strong, positive link that has grown stronger over the past century. The connection is stronger in Anglo-Saxon countries, in the very top of the distribution, when top capital incomes predominate, when using distributed top national income shares, and when considering gross of depreciation capital shares. Out of-sample predictions of top shares using capital shares indicates several cases of over- or underestimation.

We build an endogenous growth model with automation (the replacement of low-skill workers with machines) and horizontal innovation (the creation of new products). Over time, the share of automation innovations endogenously increases through an increase in low-skill wages, leading to an increase in the skill premium and a decline in the labor share. We calibrate the model to the US economy and show that it quantitatively replicates the paths of the skill premium, the labor share, and labor productivity. Our model offers a new perspective on recent trends in the income distribution by showing that they can be explained endogenously.

This paper presents direct measures of capital costs, equal to the product of the required rate of return on capital and the value of the capital stock. The capital share, equal to the ratio of capital costs and gross value added, does not offset the decline in the labor share. Instead, a large increase in the share of pure profits offsets declines in the shares of both labor and capital. Industry data show that increases in concentration are associated with declines in the labor share.

What do we mean by inequality comparisons? If the rich just get richer and the poor get poorer, the answer might seem easy. But what if the income distribution changes in a complicated way? Can we use mathematical or statistical techniques to simplify the comparison problem in a way that has economic meaning? What does it mean to measure inequality? Is it similar to National Income? Or price index? Is it enough just to work out the Gini coefficient? This book tackles these questions and examines the underlying principles of inequality measurement and its relation to welfare economics, distributional analysis, and information theory. The book covers modern theoretical developments in inequality analysis, as well as showing how the way we think about inequality today has been shaped by classic contributions in economics and related disciplines. Formal results and detailed literature discussion are provided in two appendices. The principal points are illustrated in the main text, using examples from US and UK data, as well as other data sources, and associated web materials provide hands-on learning.