Dread risks

It is a well-established fact that many people view the prospect of premature death by some causes with considerably more disquiet or “dread” than death by other causes. It is equally clear that for most people their personal risk of death by a given cause is also a matter of serious concern. This article reports the findings of a study aimed at estimating the effects of dread and personal risk of death by a specific cause on the willingness-to-pay based Value of Statistical Life (VSL) for that cause. JEL Classification J17     

论声调语言的节奏与重音模式

声调语言的重音及其实现方式一直存在广泛争议,节奏角度可以为此问题带来新的研究思路。nPVI节奏模型主要反映相邻音节时长变化,作为声调语言,成都话的nPVI明显高于普通话,接近被视为重音计时型语言的英语,这与其重音凸显方式密切相关。成都话双音词和三音词的首音节大都具有时长重音,信息焦点也主要依靠时长凸显,有时还辅以焦点前压缩和助词延展。重音可以和声调共存,变调规律有时与重音实现直接相关,声调语言的节奏特征可以反映该语言中重音的作用大小和凸显度差异。     

High Wage Workers and High Wage Firms

We study a longitudinal sample of over one million French workers from more than five hundred thousand employing firms. We decompose real total annual compensation per worker into components related to observable employee characteristics, personal heterogeneity, firm heterogeneity, and residual variation. Except for the residual, all components may be correlated in an arbitrary fashion. At the level of the individual, we find that person effects, especially those not related to observables like education, are a very important source of wage variation in France. Firm effects, while important, are not as important as person effects. At the level of firms, we find that enterprises that hire high-wage workers are more productive but not more profitable. They are also more capital and high-skilled employee intensive. Enterprises that pay higher wages, controlling for person effects, are more productive and more profitable. They are also more capital intensive but are not more high-skilled labor intensive. We find that person effects explain about 90% of inter-industry wage differentials and about 75% of the firm-size wage effect while firm effects explain relatively little of either differential.     

Nonparametric Estimation of Triangular Simultaneous Equations Models

This paper presents a simple two-step nonparametric estimator for a triangular simultaneous equation model. Our approach employs series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding residuals. The second step is the estimation of the primary equation via nonparametric regression with the reduced form residuals included as a regressor. We derive consistency and asymptotic normality results for our estimator, including optimal convergence rates. Finally we present an empirical example, based on the relationship between the hourly wage rate and annual hours worked, which illustrates the utility of our approach.