Mark E. Schweitzer

Minimum Wage Effects throughout the Wage Distribution

This paper provides evidence on a wide set of margins along which labor markets can adjust in response to increases in the minimum wage, including wages, hours, employment, and ultimately labor income. Not surprisingly, the evidence indicates that low-wage workers are most strongly affected, while higher-wage workers are little affected. Workers who initially earn near the minimum wage experience wage gains. Nevertheless, their hours and employment decline, and the combined effect of these changes on earned income suggests adverse consequences, on net, for low-wage workers.

The Effects of Minimum Wages on the Distribution of Family Incomes: A Nonparametric Analysis

The primary goal of a national minimum wage floor is to raise the incomes of poor families with members in the work force. We present evidence on the effects of minimum wages on family incomes from March CPS surveys. Using non-parametric estimates of the distributions of family income relative to needs in states and years with and without minimum wage increases, we examine the effects of minimum wages on this distribution, and on the distribution of the changes in income that families experience. Although minimum wages do increase the incomes of some poor families, the evidence indicates that their net effect is, if anything, to increase the proportions of families with incomes below or near the poverty line. Thus, it would appear that reductions in the proportions of families that are poor or near-poor should not be counted among the potential benefits of minimum wages.

The Effects of Minimum Wages on the Distribution of Family Incomes A Nonparametric Analysis

An oft-stated goal of the minimum wage is to raise incomes of poor or low-income families. We present nonparametric estimates of the effects of minimum wages on the distribution of family income relative to needs in the United States. Although minimum wages increase the incomes of some poor families, the evidence indicates that their overall net effect is, if anything, to increase the proportions of families with incomes below or near the poverty line. It would appear that reductions in the proportions of families that are poor or near-poor should not be counted among the potential benefits of minimum wages.

The Effects of Inflation on Wage Adjustments in Firm-Level Data:Grease or Sand?

An analysis of whether inflation facilitates adjustments to shocks or distorts relative prices, examining the wage-setting process across a panel of occupations and employers and finding that the costs of inflation may rise more rapidly than its benefits beyond quite modest rates of increase in the price level.

Does Wage Inflation Cause Price Inflation

Recent attention has turned from unemployment levels to wage growth as an indicator of imminent inflation. But is there any evidence to support the assumption that increased wages cause inflation? This study updates and expands earlier research into this question and finds little support for the view that higher wages cause higher prices. On the contrary, the authors find more evidence that higher prices lead to wage growth.

Knowledge Matters: The Long‐Run Determinants of State Income Growth

State per capita income differences narrowed considerably between 1939 and 1976. However, this convergence has been incomplete. We examined the sources of relative per capita income growth using an augmented growth model and a panel of the 48 contiguous states from 1939 to 2004. We explored the effect of tax burdens, public infrastructure, size of private financial markets, rates of business failure, industry structure, climate, educational attainment, and technology production. Our results show that a states technology and its college attainment rates are the main factors that allow some states per capita income to remain above those of other states.

Ready, Willing, and Able? Measuring Labour Availability in the UK

The unemployment rate is commonly assumed to measure labour availability, but this ignores the fact that potential workers frequently come from outside the current set of labour market participants, the so-called inactive. The UK Longitudinal Labour Force Survey includes information that can be used to predict impending employment transitions. Using this unique dataset, new measures of labour availability, and indicators based on the more familiar unemployment rate alternatives, can be constructed and are reported here. The micro and macroeconomic performance of these labour force availability measures is compared. Two simplified models, which include several categories of reasons for not working as well as demographic variables, perform particularly well in all of the tests. The implications of these preferred models are further studied in the context of regional regressions and comparisons with alternative data sources. These results together illustrate the important role that some groups of the inactive can play as a source of potential workers.

State Growth Empirics: The Long-Run Determinants of State Income Growth

Real average U.S. per capita personal income growth over the last 65 years exceeded a remarkable 400 percent. Also notable over this period is that the stark income differences across states have narrowed considerably: In 1939 the highest income states per capita personal income was 4.5 times the lowest, but by 1976 this ratio had fallen to less than 2 times. Since 1976, the standard deviation of per capita incomes at the state level has actually risen, as some higher-income states have seen their income levels rise relative to the median of the states. A better understanding of the sources of these relative growth performances should help to characterize more effective economic development strategies, if income growth differences are predictable. In this paper, we look for statistically and economically significant growth factors by estimating an augmented growth model using a panel of the 48 contiguous states from 1939 to 2004. Specifically, we control for factors that previous researchers have argued were important: tax burdens, public infrastructure, size of private financial markets, rates of business failure, industry structure, climate, and knowledge stocks. Our results, which are robust to a wide variety of perturbations to the model, are easily summarized: A states knowledge stocks (as measured by its stock of patents and its high school and college attainment rates) are the main factors explaining a states relative per capita personal income.

Rounding in Earnings Data

Earnings data are often reported in round numbers. In fact, in the March 1995 Current Population Survey (CPS), 71% of all full-time earnings responses are some multiple of

Wage flexibility in Britain: some micro and macro evidence

1,000. Rounding is typically ignored in analyses of earnings data, which effectively treats it as noise in the data. Our GMM estimates of a simple model of rounding indicate that this behavior is highly systematic and correlated with the respondents’ earnings level. We find that the systematic nature of rounding can affect some commonly used statistics based on earnings data. The statistics we investigate in this analysis are inequality summary measures, earnings quantiles, kernel density estimates, and frequency plots of wage adjustments. We find that rounding alters most of these statistics substantially, that is, by more than the typical level of annual changes or reported standard errors.