The Type of Contract and Starting Wage and Wage Growth: The Evidence from New Graduates from Post-Secondary Schools in the Netherlands

This paper examines the impact of a type of employment contract on starting wage and short-term wage growth. I estimate the differences in starting wage and wage growth patterns between temporary and permanent workers by using a dataset from the Netherlands. The data contain new graduates from post-secondary schools in the Netherlands. As in the continental European countries, the use of temporary employment is common in the Netherlands, especially among young workers. Those who just graduate from school have less experience in the labor market. It is rather difficult for an employer to find a qualified worker. Because of high firing costs for a permanent worker, an employer has to bear more costs if employing an under-qualified worker. To avoid this, an employer engages in a more intensive search processes when hiring a worker on a permanent worker, which increase search costs. If such costs are passed on to a permanent worker, the starting wage is expected to be lower for a permanent worker than a temporary worker. The empirical comparisons of the starting wage shows evidence of a lower starting wage, but this is not robust to differences in estimation structure. The comparison of the wage growth between the two types of contract shows that wage growth is more suppressed for a temporary worker than for a permanent worker. Since the observations are those who have little job experience, training upon employment is important. As a matter of fact, almost all relevant observations receive training at the beginning, regardless of type of contract. Employers could recoup the costs of training by suppressing the wage growth relative to underlying productivity growth. An employer suppresses wage growth more for a temporary worker than a permanent worker as the shorter employment period of a temporary worker leaves the employer with less time to recoup the costs. The empirical results confirm this hypothesis, and these findings are robust. The empirical strategy in this paper takes into consideration the fact that the type of contract is presumably determined endogenously even after controlling for observable individual characteristics. The empirical results indeed indicate that this selectivity issue is necessary to be considered.

Estimating the Variance of Decomposition Effects

We derive the asymptotic variance of the Blinder-Oaxaca decomposition effects. We show that the delta method approach that builds on the assumption of fixed regressors understates true variability of the decomposition effects when regressors are stochastic. Our proposed variance estimator takes randomness of regressors into consideration. Our approach is applicable to both the linear and nonlinear decompositions, for the latter of which only a bootstrap method is an option. As our derivation follows the general framework of m-estimation, it is straightforward to extend to the cluster-robust variance estimator. We demonstrate the finite-sample performance of our variance estimator with a Monte Carlo study and present a real-data application

Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act

The Japanese Equal Employment Opportunity Act (EEOA) of 1985 aimed to reduce gender discrimination in the labor market, especially for career-oriented jobs. This paper investigates whether this act had an unanticipated effect on women\u27s marriage decisions. Using micro data from the Japanese Panel Survey of Consumers, we model women\u27s interrelated decisions on university education and whether to marry, focusing on whether women have married by age 32. Our results show a negative relationship between university education and marriage that is much greater for post-EEOA cohorts of women than for pre-EEOA cohorts, consistent with our hypothesis that the enhanced career opportunities associated with the EEOA stimulated women to delay or forgo marriage

Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act

Prompted by concordant upward trends in both the university advancement rate and the unmarried rate for Japanese women, this paper investigates whether the Equal Employment Opportunity Act (EEOA), which was passed in 1985, affected women\u27s marriage decisions either directly or via their decisions to pursue university education. To this end, we estimate a model that treats education and marriage decisions as jointly determined using longitudinal data for Japanese women. We find little evidence that the passage of EEOA increased the proportion of women who advance to university, but strong support for the proposition that it increased the deterrent effect of university education on marriage

Fate of Polycyclic Aromatic Hydrocarbons and Radionuclides through Loess over Pan-Japan Sea Area -Reaction, Transportation and Deposition-

金沢大学大学院自然科学研究科金沢大学工学部Nankai, UniversityChinese Academy of SciencesScedule:17-18 March 2003, Vemue: Kanazawa, Japan, Kanazawa Citymonde Hotel, Project Leader : Hayakawa, Kazuichi, Symposium Secretariat: XO kamata, Naoto, Edited by:Kamata, Naoto

Endogenous switching regression model and treatment effects of count-data outcome

In this article, I describe the escount command, which implements the estimation of an endogenous switching model with count-data outcomes, where a potential outcome diers across two alternate treatment statuses. escount al- lows for either a Poisson or a negative binomial regression model with lognormal latent heterogeneity. After estimating the parameters of the switching regression model, one can estimate various treatment effects with the command teescount. I also describe the command lncount, which ts the Poisson or negative binomial regression model with lognormal latent heterogeneity

Endogenous models of binary choice outcomes: Copula-based maximum-likelihood estimation and treatment effects

In this article, I describe the commands that implement the estimation of three endogenous models of binary choice outcome. The command esbinary fits the endogenously switching model, where a potential outcome differs across two treatment states. The command edbinary fits the endogenous dummy model, which includes a dummy variable indicating the treatment state as one of the explanatory variables. After one estimates the parameters of these models, various treatment effects can be estimated as postestimation statistics. The command ssbinary fits the sample-selection model, where an outcome is observed in only one of the states. The commands fit these models using copula-based maximumlikelihood estimation

Copula-based maximum-likelihood estimation of sample-selection models

Sample-selection issues are common problems in empirical studies of labor economics and other applied microeconomics. A common estimation method is maximum likelihood estimation under the assumption of joint normality. It is well known, however, that the violation of distributional assumptions leads to inconsistency of a maximum likelihood estimator. Early work on sample-selection models that relaxes the normality assumption was done by Lee (1983, 1984). His approach was to transform nonnormal disturbances in the models into normal variates that are then assumed to be jointly normally distributed. As we will see, this is a special case of the copula approach that Smith (2003) applies to sample-selection models. The copula approach adds more flexibility to model specifications. In this article, I discuss the maximum likelihood estimation of sample-selection models with the copula approach to relax the assumption of joint normality. Although there are several types of sample-selection models, I discuss two in particular: a bivariate sample-selection model and an endogenous switching regression model. I also introduce the Stata commands heckmancopula and switchcopula, which implement the estimation of each model, respectively

Endogenous switching regression model and treatment effects of count-data outcome

In this article, I describe the escount command, which implements the estimation of an endogenous switching model with count-data outcomes, where a potential outcome diers across two alternate treatment statuses. escount al- lows for either a Poisson or a negative binomial regression model with lognormal latent heterogeneity. After estimating the parameters of the switching regression model, one can estimate various treatment effects with the command teescount. I also describe the command lncount, which ts the Poisson or negative binomial regression model with lognormal latent heterogeneity

Endogenous models of binary choice outcomes: Copula-based maximum-likelihood estimation and treatment effects

In this article, I describe the commands that implement the estimation of three endogenous models of binary choice outcome. The command esbinary fits the endogenously switching model, where a potential outcome differs across two treatment states. The command edbinary fits the endogenous dummy model, which includes a dummy variable indicating the treatment state as one of the explanatory variables. After one estimates the parameters of these models, various treatment effects can be estimated as postestimation statistics. The command ssbinary fits the sample-selection model, where an outcome is observed in only one of the states. The commands fit these models using copula-based maximumlikelihood estimation