Rudy H. Fichtenbaum

Truncation Bias and the Measurement of Income Inequality

kind transfers, fringe benefits, and capital gains, (Danziger, Haveman, and Plotnick 1981). One problem that seems to have been neglected in the literature, however, is the truncation bias caused by the exclusion of income (from a single source) that is greater than

The Market for Jobs: Locational Decisions and the Competition for Economic Development

99,999. Beginning with the March 1986 survey, the CPS raised the truncation limit for earnings received from an employer or own business to a maximum of

THE EFFECTS OF RACE ON THE USE OF PHYSICIANS' SERVICES

299,999, resulting in a rise in the Gini coefficient (index of income concentration) from .383 to .389. Income received in dividends, interest, and rent, however, will still be limited to a maximum of

The Impact of Unions on Labor's Share of Income: A Time-Series Analysis

99,999 (U.S. Bureau of the Census 1986a). The purpose of this article is to demonstrate that the aforementioned truncation bias causes an underesti-

New Evidence on the Labor Market Segmentation Hypothesis

A market for industrial locations has emerged in recent years. On one side of the market, cities compete with each other to attract jobs; on the other side, firms seek subsidy payments for providing jobs. These developments have been noted, but until now have not been viewed as an explicit market. This article provides evidence of the markets development and identifies factors that have stimulated the markets growth. It demonstrates that costs of using the market have declined, but benefits have increased. The study goes on to show that the market can be efficient under certain conditions, but that major impediments to efficiency exist. Finally, it discusses how the market for jobs is likely to evolve.

Racial wage gaps and differences in human capital

In recent years several studies have examined the role of race in determining both health care status and access to care. Most studies in this area have focused primarily on health care status, although the issue of access is often mentioned. While there are many reasons for differences in health status, access to resources may play an important role. Using a Poisson regression, a decomposition analysis, and data from the 1987 National Medical Expenditure Survey, the authors of this article show that significant differences remain in the number of physician office visits for whites and African-Americans. The proportion of the racial differences in the number of office visits not explained by differences in objective factors is relatively large. In fact, the results show that a considerable part of the racial differential can be explained by differential responses to these objective factors. This implies that, even if all the objective factors that affect the demand for visits are equalized across race, significant differences in the utilization of health care services will remain.

Labour Market Segmentation and Union Wage Gaps

Early time-series studies that examined the impact of unions on labors share of income were primarily descriptive. They generally found that unions did not impact labors share of income. In contrast, later studies, using either panel data or cross-section data, have produced mixed results. This study adds to our understanding of this topic by first developing an analytical model based on imperfect competition and then testing the model using time-series data for the US manufacturing sector from 1949–2006. The results demonstrate that unions have a positive impact on labors share of income. They show that for each one percentage point reduction in union density, the proportion of income received by production workers declines by about 0.2 percentage points, holding other factors constant. From 1949 to 2006, labors share of income declined approximately 25 percentage points; around 28% of that decline is explained by the decline in unionization. This paper is distinctive in estimating the proportion of the decline in labors share attributable to declining unionization. It also has important implications for the Employee Free Choice Act and sheds light on whether social or institutional forces can affect the distribution of income.

Is there a natural level of capacity utilization

Introduction Since the publication of Glenn Cains article (1976) on the challenge of segmented labor market theory, there have been numerous empirical tests of the effect of segmentation on earnings. A main concern of the segmentation literature has been the question of how to divide the work force among the various segments of the labor market (Taubman and Wachter, 1986). Earlier approaches used individual attributes or human capital characteristics to segment the labor market. However, this approach was shown to be inappropriate because it suffered from truncation bias (Cain, 1976). The estimates were biased because segments were first divided on the basis of high or low income and then used in equations to estimate the rate of return on education (Schervish, 1983). A number of other studies have used industry or product market characteristics to divide the labor market into various segments (Beck, Horan, and Tolbert 1978; Osberg, Apostle, and Clairmont, 1987). An alternative approach has been to use a switching model that estimates a series of earnings functions and a function that estimates the probability of being in the primary labor market (Dickens and Lang, 1985). Anderson, Butler and Sloan (1987) have criticized this approach and alternatively divide the labor market into segments using a hierarchical clustering model with a parametric stopping rule. Another approach has been to use various ranks of occupational prestige to divide the labor market (McNabb and Psacharopoulos, 1981; Neuman and Ziderman, 1986). Most recently, Boston (1990) found evidence to support the labor market segmentation hypothesis. In particular, he found that there are two distinct labor market segments and that a significant portion of the wage differential between segments was unexplained by differences in worker characteristics. However, his results divide the labor market into only two sectors whereas recent literature on labor market segmentation suggests that there may be as many as four distinct segments (Piore, 1975; Edwards, 1979; Gordon, Edwards, and Reich, 1982; and Gordon, 1986). Moreover, Boston derives his two segments using a one dimensional classification scheme and uses only 44 two digit occupations to derive his segments. Using only two segments may result in too much aggregation and hence the loss of important information. The single dimensional classification scheme which uses only a single criterion, whether workers need specific training or skills, also increases the probability of misclassifying workers than a scheme that is multidimensional and uses multiple criteria. For example, using only two segments and a one dimensional criterion results in classifying secretaries, construction workers, and engineers as part of the primary segment. Similarly, all operators, fabricators, and laborers are classified as being in the secondary labor market (Boston, 1990). In contrast, Gordon (1986) suggests using a multidimensional scheme with multiple criteria to establish four distinct labor market segments using industry and occupational classifications at the three digit level. Using Gordons classification scheme places secretaries, construction workers, and engineers into three distinct segments. Gordons scheme also places operators, fabricators, and laborers in the automobile industry -- a core industry -- into a subordinate primary sector whereas operators, fabricators, and laborers in the knitting mill industry -- a peripheral industry -- are in the secondary labor market. The purpose of this paper is twofold. First, the hypothesis put forward by the segmented labor market (SLM) model which divides the labor market into an independent professional and technical segment, an independent craft segment, a subordinate primary segment and a secondary segment will be tested. Second, the differentials between segments will be decomposed into a portion that is explained by differences in worker characteristics and a portion that is unexplained by differences in worker characteristics. …

Redefining poverty: a sensitivity analysis

This paper uses the Cotton/Neumark decomposition methodology and 1990 CPS data to investigate the relative importance of labour market structure and human capital in explaining the white male/Asian, white male/black, white male/Hispanic wage gaps. We find that labour market structure is more important than human capital in explaining the white minority wage gaps. Moreover, most of the labour market structural effects are due to differential returns to white structural characteristics. Our result is robust to the specification of human capital. Our results contradict the results of research that indicate that the white/minority wage gaps can be explained solely by differences in the endowment of human capital. Our results have implications for narrowing the wage gaps between whites and racial minorities.

Dayton, Ohio: A Dramatic Rebound

Abstract There has been a great deal of research regard the effects of unions on union – non-union wage gap. Most of the studies regarding the impact of unions on wages have assumed that apart from the division between union and non-union workers, the labour market is relatively homogeneous. A number of economists, however, have argued that the labour market is segmented, implying that there are distinct labour markets and that some workers employment opportunities are concentrated in “bad jobs” while other workers employment opportunities are concentrated in “good jobs” which are rationed. This paper will explore whether the relative wage differential between union and non-union workers differs between the independent primary, subordinate primary and secondary labour markets. Labour market segments are defined using “job zones”. “Job zones” are distinct groups defined by the level of specific vocational preparation necessary for a particular occupation, allowing for the comparison of skill levels and training for each occupation. The data on “job zones” comes from the Occupational Information Network database (O*Net). We estimate separate equations for union and non-union workers in each segment using data from the Current Population Survey and calculate union non-union differentials for each labour market segment. The findings of this paper suggest that the greatest differentials are in secondary labour markets followed by differentials in the subordinate primary labour market and that the smallest wage differentials are in the independent primary labour market.