Declining inter-industry wage dispersion in the US

Industrial effects have long been significant factors in wage inequality. Previous research indicates that wage differentials across industries were increasing through the mid 1980s. Using more recent data, however, we find that the level of inter-industry wage dispersion declined by 36% from 1986 to 2002 despite the continued trend towards increasing inequality in the labor force. This decline in inter-industry wage dispersion is evident across gender and educational groups. Using multilevel growth curve models, our multivariate results indicate that the decline is only weakly related to industrial changes in education, occupation or even productivity despite the fact that the latter variable had been a critical factor in the prior period. Indicators of globalization and downsizing also do not appear to explain this decline. For the more recent period, the most important factors associated with the narrowing of inter-industry wage dispersion are reduced unionization rates and the higher proportion of casual workers. We interpret these results as suggesting that firms may now be less economically obliged to pass on a portion of their rents to broad groups of workers and may instead be engaged in more idiosyncratic processes of negotiation with individual workers based on micro-level sources of bargaining power.     

Application of an adaptive design to a randomized phase II selection trial in gastric cancer: a report of the study design

Randomized phase II selection trials seek to provide unbiased comparisons for the selection of the most promising treatment arm for evaluation in a future phase III trial. In this paper, we present an application of an adaptive design to a randomized phase II selection trial comparing three experimental treatments with a control arm in patients with advanced gastric cancer. The trial design continuously monitors multiple patient outcomes to protect future patients from treatments with unacceptably high toxicity and/or unacceptably low efficacy. We use a Bayesian approach to monitor the trial and carry out simulations to investigate operating characteristics of the trial design. The simulation study also evaluates the sensitivity of the design to the prior distribution by considering two alternative priors.     

Long-Term Earnings Differentials Between African American and White Men by Educational Level

This paper investigates long-term earnings differentials between African American and white men using data that match respondents in the Survey of Income and Program Participation to 30 years of their longitudinal earnings as recorded by the Social Security Administration. Given changing labor market conditions over three decades, we focus on how racial differentials vary by educational level because the latter has important and persistent effects on labor market outcomes over the course of an entire work career. The results show that the long-term earnings of African American men are more disadvantaged at lower levels of educational attainment. Controlling for demographic characteristics, work disability, and various indicators of educational achievement does not explain the lower long-term earnings of less-educated black men in comparison to less-educated white men. The interaction arises because black men without a high school degree have a larger number of years of zero earnings during their work careers. Other results show that this racial interaction by educational level is not apparent in cross-sectional data which do not provide information on the accumulation of zero earnings over the course of 30 years. We interpret these findings as indicating that compared to either less-educated white men or highly educated black men, the long-term earnings of less-educated African American men are likely to be more negatively affected by the consequences of residential and economic segregation, unemployment, being out of the labor force, activities in the informal economy, incarceration, and poorer health.     

Bringing Productivity Back In: Rising Inequality and Economic Rents in the U.S. Manufacturing Sector, 1971 to 2001

Using data on earnings and productivity for U.S. manufacturing industries from 1971 to 2001, we investigate economic rents and rising income inequalities. The results suggest that rents are most significant for managers, professionals, middle‐aged workers, and older workers. Conversely, negative rents are evident for women, Hispanics, single men, and blue‐collar workers. The underpayment of Hispanics appears to have increased while African Americans have gone from being underpaid to being overpaid. Workers with a college degree have become overpaid (i.e., “credentialism”) while “gift‐exchange” efficiency wages have declined. The marginal productivity of labor input has increased but is increasingly underpaid.     

Racial and Ethnic Differentials in Idleness,Highest-Risk Idleness,and Dropping Out of High School

This research investigates three different indicators of at-risk socio-demographic conditions including dropping out of high school, being idle, and being in highest-risk idleness among non-immigrant persons aged 19–24. Using data from the 2000 US Census, our results detail the differentials in these characteristics for 30 different racial/ethnic groups that are further broken down by gender. The findings indicate a wide range in the prevalence of these at-risk socio-demographic conditions. Groups that tend to be the most at-risk in terms of these indicators include African Americans, Cambodians, Laotians, Native Americans, other Hispanic whites, and white Mexicans. With the exception of the other Pacific Islander and Thai, young women have lower high school dropout rates than do young men. However, young women are substantially more likely than young men to be idle which we define as not being in school, the labor force, or the military. After defining highest-risk idleness as never-married persons without children who are idle, however, the rates are slightly lower for young women than for young men.     

The declining significance of race among American men during The latter half of the twentieth century

The extent to which racial minority groups face discrimination in the labor market is the subject of considerable debate. Using William J. Wilson's thesis of the declining significance of race as our theoretical context, we provide further empirical evidence about labor market discrimination by investigating wages among African American, American Indian, Chinese American, Hispanic white, Japanese American, and non-Hispanic white men. We find, during the period before the civil rights movement, that a substantively significant wage disadvantage is evident for these minority groups with controls for observed labor force characteristics. In recent data, these net disadvantages are reduced substantially for each of these groups except Hispanics. With the exception of Hispanics, the results support Wilson's thesis.     

Exploitation in Contemporary Capitalism: An Empirical Analysis of the Case of Taiwan

Abstract

Using data for manufacturing firms in Taiwan, we developed a measure of exploitation and analyzed its prevalence in the labor force. Our results indicated that almost two-thirds of the firms in our sample exploit at least some of their workers. For these firms, the average profit rate is 34 percent, but three-fourths of this figure derives from the expropriated wages of their workers. Female and blue-collar workers are the largest groups that are underpaid relative to their productivity (that is, exploited). Managers, professionals, and workers with seniority are not exploited by our definition because our data showed that these groups are paid according to the market value of their productivity, at least on average. Our analysis demonstrates the feasibility of the empirical investigation of exploitation, which should be further considered in future research.     

Estimate of variance of u-statistics

Let g(x₁,… , x_k) be a symmetric function with k arguments. Let U be a U-statistic based on a random sample of size n with kernel function g . In this paper, the problem of estimating var(U) is considered. Several estimators are compared by computer simulations and we conclude that two estimators, one is constructed as a U-statistic and the other is the bootstrap estimator, give good estimates for many U-statistics.     

Likelihood-based cross-validation score for selecting the smoothing parameter in maximum penalized likelihood estimation

Maximum penalized likelihood estimation is applied in non(semi)-para-metric regression problems, and enables us exploratory identification and diagnostics of nonlinear regression relationships. The smoothing parameter A controls trade-off between the smoothness and the goodness-of-fit of a function. The method of cross-validation is used for selecting A, but the generalized cross-validation, which is based on the squared error criterion, shows bad be¬havior in non-normal distribution and can not often select reasonable A. The purpose of this study is to propose a method which gives more suitable A and to evaluate the performance of it.

A method of simple calculation for the delete-one estimates in the likeli¬hood-based cross-validation (LCV) score is described. A score of similar form to the Akaike information criterion (AIC) is also derived. The proposed scores are compared with the ones of standard procedures by using data sets in liter¬atures. Simulations are performed to compare the patterns of selecting A and overall goodness-of-fit and to evaluate the effects of some factors. The LCV-scores by the simple calculation provide good approximation to the exact one if λ is not extremeiy smaii Furthermore the LCV scores by the simple size it possible to select X adaptively They have the effect, of reducing the bias of estimates and provide better performance in the sense of overall goodness-of fit. These scores are useful especially in the case of small sample size and in the case of binary logistic regression.