Jeffrey P. Thompson

Post-1970 Trends in Within-Country Inequality and Poverty: Rich and Middle Income Countries

This paper is prepared as a chapter for the Handbook of Income Distribution, Volume 2 (edited by A. B. Atkinson and F. Bourguignon, Elsevier-North Holland, forthcoming). Like the other chapters in the volume (and its predecessor), the aim is to provide a comprehensive review of a particular area of research. We examine the literature on post-1970 trends in poverty and income inequality, up to 2010 or 2011 in most countries. We provide measures of the levels and trends in each of these areas, as well as an integrated discussion of empirical choices made in the measurement of poverty, overall income inequality, and inequality amongst those with top incomes.

Recent Trends in Income Inequality

The impact of the “Great Recession” on inequality is unclear. Because the crises in the housing and stock markets and mass job loss affect incomes across the entire distribution, the overall impact on inequality is difficult to determine. Early speculation using a variety of narrow measures of earnings, income, and consumption yield contradictory results. In this chapter, we develop new estimates of income inequality based on “more complete income” (MCI), which augments standard income measures with those that are accrued from the ownership of wealth. We use the 1989–2007 Surveys of Consumer Finances, and also construct MCI measures for 2009 based on projections of assets, income, and earnings. We investigate the level and trend in MCI inequality and compare it to other estimates of overall and “high incomes” in the literature. Compared to standard measures of income, MCI suggests higher levels of inequality and slightly larger increases in inequality over time. Several MCI-based inequality measures peaked in 2007 at their highest levels in 20 years. The combined impact of the Great Recession on the housing, stock, and labor markets after 2007 has reduced some measures of income inequality at the top of the MCI distribution. Despite declining from the 2007 peak, however, inequality remains as high as levels experienced earlier in the decade, and much higher than most points over the last 20 years. In the middle of the income distribution, the declines in income from wealth after 2007 were the result of diminished value of residential real estate; at the top of the distribution, declines in the value of business assets had the greatest impact. We also assess the level and trend in the functional distribution of income between capital and labor, and find a rising share of income accruing to real capital or wealth from 1989 to 2007. The recent economic crisis has diminished the capital share back to levels from 2004. Contrary to the findings of other researchers, we find that the labor share of income among high-income groups declined between 1992 and 2007.

Do Rising Top Income Shares Affect the Incomes or Earnings of Low and Middle-Income Families?

This paper uses US state panel data to explore the relationship between the share of income received by affluent households and the level of income and earnings received by low and middle-income families. A rising top share of income can potentially lead to increases in the incomes of low and middle-income families if economic growth is sufficiently responsive to increases in inequality. A substantial literature on the impacts of inequality on economic growth exists, but has failed to achieve consensus, with various studies finding positive impacts, negative impacts, and no impacts on growth from increased levels of income inequality. This paper departs from that literature by exploring the effect of inequality on the standard of living of middle-income and low-income families. In the context of rising inequality, increased overall growth is not necessarily a suitable proxy for overall standard of living, since growth patterns are not always uniform for the entire income distribution. The results of this study indicate that increases in the top share of income (particularly the top one percent) are associated with declines in the actual incomes (and earnings) of middle income families, but have no clear impact on families at the bottom of the income distribution.

Exploring the Racial Wealth Gap Using the Survey of Consumer Finances

This paper studies the racial wealth gap using data from the Federal Reserve’s Survey of Consumer Finances from 1989 to 2013. We document that the mean and median wealth (net worth) of white families has consistently been much greater than that of black and Hispanic families, and the gap between them has increased in recent years. We use reduced-form OLS regressions and non-parametric decomposition techniques to assess the contribution to the racial wealth gap of life-cycle patterns, educational attainment, inheritance, attitudes toward saving and investing, and a number of additional factors. Our analysis indicates that the wealth gap between white and Hispanic families can be almost entirely attributed to differences in observable variables. Observable factors account for most of the gap between white and black families, but a substantial unexplained portion remains. Wealth differences between black and white families are completely due to different asset holdings, while wealth differences between black and Hispanic families are mostly a result of different debt holdings. The unexplained portion of the wealth gap, for white families relative to black and Hispanic families, is greater at the top of the wealth distribution.

When Real Estate is the Only Game in Town

Using data on household portfolios and mortgage originations, we find that households residing in a city with few publicly traded firms headquartered there are more likely to own an investment home nearby. Households in these areas are also less likely to own stocks. This only-game-in-town effect is more pronounced for households living in high credit quality areas, who can access financing to afford a second home. This effect also becomes pronounced for households living in low credit quality areas after 2002 when securitization made it easier for these households to buy second homes. Cities with few local stocks have in equilibrium higher price-to-rent ratios, making it more attractive to rent, and lower (primary residence) homeownership rates.The excesses of the historic US housing cycle of the 2000s were concentrated in the Metropolitan Statistical Areas (MSAs) of Arizona, California, Florida and Nevada. Even controlling for leading explanations of this housing cycle, these Sand State MSAs had more than double the mortgage originations, defaults and price fluctuations than other MSAs. We show that these excesses can be explained by Sand State MSAs having an abnormally low supply of publicly traded firms headquartered there relative to total income. Households in these MSAs are more likely to purchase investment homes nearby rather than stocks, amplifying the housing cycle there.

Does Education Loan Debt Influence Household Financial Distress? An Assessment Using the 2007-09 SCF Panel

This paper uses the recent 2007-09 SCF panel to examine the influence of student loans on financial distress. Families with student loans in 2007 have higher levels of financial distress than families without such loans, and these families were more susceptible to transitions to financial distress during the early stages of the Great Recession. This correlation persists once we control for a host of other demographic, work-status, and household balance sheet measures. Families with an average level of student loans were 3.1 percentage points more likely to be 60 days late paying bills and 3 percentage points more likely to be denied credit. During this same time period, families with other types of consumer debt were no more or less likely to be financially distressed. Education loans enable students to go to college and improve their employment and earnings prospects. On average, families with education loans in the 2007-09 SCF saw higher income growth between surveys. Further, the value of completing a degree is evident in the data: families without a degree but with education debt drive much of the correlations between financial distress and education loans.

The Effect of State and Local Sales Taxes on Employment at State Borders

This paper estimates the effect of sales taxes on employment at state borders using county-level quarterly data and a newly developed data set of local tax rates. Sales tax increases, relative to cross-border neighbors, lead to losses of employment, as well as payroll and hiring, but these effects are only found in counties with large shares of residents working in another state. The effects also represent an upper-bound, largely driven by employment shifting across the state border. We also find that employment in food and beverage stores is negatively affected when cross-border neighbors adopt low sales tax rates on food.

Inequality in 3-D : Income, Consumption, and Wealth

We do not need to and should not have to choose amongst income, consumption, or wealth as the superior measure of well-being. All three individually and jointly determine well-being. We are the first to study inequality in three conjoint dimensions for the same households, using income, consumption, and wealth from the 1989-2016 Surveys of Consumer Finances (SCF). The paper focuses on two questions. What does inequality in two and three dimensions look like? Has inequality in multiple dimensions increased by less, by more, or by about the same as inequality in any one dimension? We find an increase in inequality in two dimensions and in three dimensions, with a faster increase in multi-dimensional inequality than in one-dimensional inequality. Viewing inequality through one dimension greatly understates the level and the growth in inequality in two and three dimensions. The U.S. is becoming more economically unequal than is generally understood.

Top Income Concentration and Volatility

Measures of income concentration�?such as the share of income received by the highest income families�?may be biased by pro-cyclical volatility in annual income. Permanent income, though, can smooth away such volatility and sort families by their usual economic resources. Here, we demonstrate this bias using rolling 3-year panels of IRS tax records from 1997 to 2013 as a proxy for permanent income. For example, one measure of 2012 income concentration�?the share of income received by the top 0.1 percent�?falls from 11.3 percent to 8.9 percent when families are organized by permanent income instead of annual income. However, the growth in income concentration cannot be explained by this volatility, as growth rates are comparable in the permanent income and annual income groupings during our sample period. Further, the probability of remaining in the highest income groups, while relatively low at the very top of the distribution, increased slightly during our sample period, suggesting that top incomes have become less volatile in this dimension. These results are confirmed using household income data measured in the Survey of Consumer Finances (SCF)�?a household survey with a large oversample of high-income households and a unique measure of permanent income.

RISING TOP INCOMES AND INCREASED BORROWING IN THE REST OF THE DISTRIBUTION

One potential consequence of rising top‐income concentration is borrowing by less‐affluent households attempting to maintain relative living standards. This paper evaluates the “keeping up with the Joneses” phenomenon, examining the responsiveness of payment‐to‐income ratios for different debt types across the income distribution to changes in income among affluent households. The analysis provides evidence for the responsiveness of debt to rising top incomes. Middle‐ and upper‐middle‐income households take on more housing‐related debt and have higher payments in places with higher top‐income levels. Among lower‐income households non‐mortgage borrowing and debt payments decline, consistent with restrictions in the supply of credit. (JEL D63, D14)