Reservation Wages and Starting Wages

We analyse a unique data set that combines reservation wage and actually paid wage for a large sample of Dutch recent higher education graduates. On average, accepted wages are almost 8% higher than reservation wages, but there is no fixed proportionality. We find that the difference between reservation wage and accepted wage is virtually random, as search theory predicts. We also find that most information contained in the accepted wage is included in the reservation wage, as one would predict if individuals are well informed about the wage structure that characterizes their labour market.reservation wages, starting wages, job search

Unobserved Heterogeneity and Risk in Wage Variance: Does Schooling Provide Earnings Insurance?

We apply a recently proposed method to disentangle unobserved heterogeneity from risk in returns to education. We replicate the original study on US men and extend to US women, UK men and German men. Most original results are not robust. A college education cannot universally be considered an insurance against unpredictability of wages. One conclusion is unequivocally confirmed: uncertainty strongly dominates unobserved heterogeneity.wage inequality, wage uncertainty, unobserved heterogeneity, selectivity, education, replication

How Risky is Investment in Human Capital?

The risk of investment in schooling has largely been ignored. We assess the variance in the rate of return by surveying the international empirical literature from this fresh perspective and by simulating risky earnings profiles in alternative options, choosing parameters on basis of the very limited evidence. The distribution of rates of return appears positively skewed. Our best guess of ex ante risk in university education is a coefficient of variation of about 0.3, comparable to that in a randomly selected financial portfolio with some 30 stocks. Allowing for stochastic components in earnings also markedly affects expected returns.education, return, earnings dispersion, risk

Dual Track or Academic Route for Auditors

In the Netherlands auditors can be trained in a part-time educational track in which students combine working and studying or in a full-time educational track. The former training is relatively firm-specific whereas the latter training is relatively general. Applying human capital theory, we expect higher wage growth for full-time educated auditors than for dual-educated auditors. Furthermore, full-time educated auditors may have better outside options than part-time educated auditors. This may make it easier for them to switch employers than for the part-time educated auditors. The predictions on tenure and wages of differently educated auditors are supported by the estimation results in this paper. The part-time, dual track appears an important route for students from a lower socioeconomic background

Unobserved Heterogeneity and Risk in Wage Variance: Does Schooling provide Earnings Insurance?

We apply a recently proposed method to disentangle unobserved heterogeneity from risk in returns to education. We replicate the original study on US men and extend to US women, UK men and German men. Most original results are not robust. A college education cannot universally be considered an insurance against unpredictability of wages. One conclusion is unequivocally confirmed: uncertainty strongly dominates unobserved heterogeneity

Unobserved heterogeneity and risk in wage variance: Does schooling provide earnings insurance?

We apply a recently proposed method to disentangle unobserved heterogeneity from risk in returns to education. We replicate the original study on US men and extend to US women, UK men and German men. Most original results are not robust. A college education cannot universally be considered an insurance against unpredictability of wages. One conclusion is unequivocally confirmed: uncertainty strongly dominates unobserved heterogeneity

R&D and Patents: Which Way Does the Causality Run?

From cross-sectional data of 460 firms that responded to both the 1988 and the 1992 Dutch innovation surveys we have reexamined the causality direction between R&D and patents, using data on contemporaneous and four-year lagged patent applications and R&D expenditures. The two equations have been estimated jointly assuming a bivariate conditional distribution between the two variables, one being discrete and the other one continuous. We have experimented with different specifications of the count data for patent applications. We find that patents Granger-cause R&D in all specifications. One additional patent increases R&D four years later by 7.5%. The reverse causality from R&D to patents vanishes as soon as we depart in one way or another from the simple Poisson specification of patent counts. � partir de données transversales de 460 entreprises néerlandaises ayant répondu aux enquêtes innovation de 1988 et 1992, nous réexaminons le sens de la causalité entre la R-D et les brevets. Les deux équations de comportement ont été estimées simultanément en supposant une distribution bivariée conditionnelle entre ces deux variables, dont l'une est discrète et l'autre continue. Nous avons essayé différentes spécifications pour les données de comptage sur les brevets. Nous trouvons que la causalité à la Granger va des brevets à la R-D dans toutes les spécifications. Un brevet en plus augmente la R-D quatre ans plus tard de 7,5 %. La causalité dans l'autre sens disparaît dès que l'on s'écarte le moindrement d'une distribution Poisson des données de brevets.Innovation survey data, patents, R&D, count data, Enquêtes innovation, brevets, R-D, données de comptage

R&D and Patents: Which Way Does the Causality Run?

À partir de données transversales de 460 entreprises néerlandaises ayant répondu aux enquêtes innovation de 1988 et 1992, nous réexaminons le sens de la causalité entre la R-D et les brevets. Les deux équations de comportement ont été estimées simultanément en supposant une distribution bivariée conditionnelle entre ces deux variables, dont l'une est discrète et l'autre continue. Nous avons essayé différentes spécifications pour les données de comptage sur les brevets. Nous trouvons que la causalité à la Granger va des brevets à la R-D dans toutes les spécifications. Un brevet en plus augmente la R-D quatre ans plus tard de 7,5 %. La causalité dans l'autre sens disparaît dès que l'on s'écarte le moindrement d'une distribution Poisson des données de brevets.From cross-sectional data of 460 firms that responded to both the 1988 and the 1992 Dutch innovation surveys we have reexamined the causality direction between R&D and patents, using data on contemporaneous and four-year lagged patent applications and R&D expenditures. The two equations have been estimated jointly assuming a bivariate conditional distribution between the two variables, one being discrete and the other one continuous. We have experimented with different specifications of the count data for patent applications. We find that patents Granger-cause R&D in all specifications. One additional patent increases R&D four years later by 7.5%. The reverse causality from R&D to patents vanishes as soon as we depart in one way or another from the simple Poisson specification of patent counts

UvA-DARE (Digital Academic Repository) The frequency of visiting a doctor: is the decision to go independent of the frequency?

Abstract In his analysis of the effects of the reform of the German healthcare system, 1 Department of Quantitative Economics, Faculty of Economics and Econometrics, University of Amsterdam, Roetersstraat 11, 1018 WB Amsterdam, The Netherlands. Email: [email protected]. 2 The comments of three referees are gratefully acknowledged. All ML-routines used in this paper are available on request. All estimations are carried out with R (free software, for information see http://www.r-project.org/). This paper is a shorter version of a paper that is available at http://www1.fee.uva.nl/pp/jcmvanophem. This extended version contains additional estimation results, more detailed information on the data etc

HETEROSCEDASTICITY IN SELECTIVITY MODELS

Selectivity models usually consist of two equations: a linear and a qualitative variables equation. This paper investigates the consistency of the ML-estimates of two selectivity models in which the heteroscedasticity of the error term of the linear equation is ignored. Homoscedastic estimation of a heteroscedastic model is proved to yield inconsistent estimates. Some Monte Carlo evidence is also provided