Job Durations With Worker- and Firm-Specific Effects: MCMC Estimation With Longitudinal Employer–Employee Data

We study job durations using a multivariate hazard model allowing for worker-specific and firm-specific unobserved determinants. The latter are captured by unobserved heterogeneity terms or random effects, one at the firm level and another at the worker level. This enables us to decompose the variation in job durations into the relative contribution of the worker and the firm. We also allow the unobserved terms to be correlated in a model that is primarily relevant for markets with small firms. For the empirical analysis, we use a Portuguese longitudinal matched employer–employee dataset. The model is estimated with a Bayesian Markov chain Monte Carlo (MCMC) estimation method. The results imply that unobserved firm characteristics explain almost 40% of the systematic variation in log job durations. In addition, we find a positive correlation between unobserved worker and firm characteristics.     

The internal relocation premium: are migrants positively or negatively selected? Evidence from Italy

This paper analyzes the wage returns from internal migration for recent graduates in Italy. We employ a switching regression model that accounts for the endogeneity of the individual's choice to relocate to get a job after graduation: the omission of this selection decision can lead to biased estimates, as there is potential correlation between earnings and unobserved traits, exerting an influence on the decision to migrate. The empirical results sustain the appropriateness of the estimation technique and show that there is a significant pay gap between migrants and non-migrants; migrants seem to be positively selected and the migration premium is downward biased through OLS estimates. The endogeneity of migration shows up both as a negative intercept effect and as a positive slope effect, the second being larger than the first: bad knowledge of the local labor market and financial constraints lead migrants to accept a low basic wage but, due to relevant returns to their characteristics, they finally obtain a higher wage than the others.     

Job-Match Quality as an Error Component and the Wage-Tenure Profiler A Comparison and Test of Alternative Estimators

The job-matching hypothesis implies that the disturbance of the standard-wage equation is correlated with one of the regressors, tenure, causing an overestimation of the effect of tenure on wages. This hypothesis is tested and consistent estimates of wage-equation parameters obtained using the methods of Hausman (1978). The approach treats job-match quality as a component of the disturbance term, and an error-components estimator is compared to a modified fixed-effects estimator. The results reject the hypothesis of no correlation between the disturbance term and tenure, but the estimated value of the tenure effect is contrary to the matching model. Other models that may be consistent with these results are discussed.     

Fourier-cosine method for pricing forward starting options with stochastic volatility and jumps

This article provides an efficient method for pricing forward starting options under stochastic volatility model with double exponential jumps. The forward characteristic function of the log asset price is derived and thereby forward starting options are well evaluated by Fourier-cosine technique. Based on adaptive simulated annealing algorithm, the model is calibrated to obtain the estimated parameters. Numerical results show that the pricing method is accurate and fast. Double exponential jumps have pronounced impacts on long-term forward starting options prices. Stochastic volatility model with double exponential jumps fits forward implied volatility smile pretty well in contrast to stochastic volatility model.     

Work effort,technical efficiency and productivity growth

This paper develops a model to examine labor-use efficiency associated with the effieciency wage theory and technical effieciency associated with the frontier production model. The generalixed modelcombines these two approaches and derives measures of technical and labor-use efficiency as well as their effects on productivity growth. It also seperates technical inefficiency from industry heterogenity. the model is applied to estimate loss of output due to technical and labor-use inefficiency for 18 two-digit U.S manufacturing industries using time series and cross-sectional data.     

Work effort, technical efficiency and productivity growth

This paper develops a model to examine labor-use efficiency associated with the effieciency wage theory and technical effieciency associated with the frontier production model. The generalixed modelcombines these two approaches and derives measures of technical and labor-use efficiency as well as their effects on productivity growth. It also seperates technical inefficiency from industry heterogenity. the model is applied to estimate loss of output due to technical and labor-use inefficiency for 18 two-digit U.S manufacturing industries using time series and cross-sectional data.     

中国企业出口贸易对劳动者工资的影响研究

随着经济全球化的发展,出口成为企业发展的主题,研究企业出口贸易对于劳动者工资的影响具有重要意义。基于Stolper-Samuelson定理(简称S-S定理)以及Melitz的异质企业模型,分析企业出口对员工工资收入的影响,利用中国工业企业数据库2005-2007年制造业企业数据实证检验出口对企业所支付人均工资的影响。研究认为:中国参与国际市场会带来劳动密集型企业产量增加,这会使中国企业的单位劳动所占资本提高,带来企业生产率水平的提高,进而会带动劳动者工资水平的提高。实证检验认为,企业出口与人均工资呈显著的正相关性,出口对企业工资具有促进作用。     

工作条件、工资补偿与劳动力市场城乡分割测量

鉴于工资既是对劳动者生产率贡献的支付同时又是对劳动者承受负面工作条件的补偿这一复杂性,鉴于城镇劳动力市场上城乡两类劳动者在艰苦危险程度不等岗位上分布的显著差异性,依据调查工资的城乡差异来测量劳动力市场上城乡分割的程度可能不尽客观。本文关注岗位的工作条件及其工资补偿,依据两类劳动者的可比工资差异观察城乡分割状态。研究发现：在绝对意义上,无论城镇工还是农民工,艰苦危险的工作条件未能带来显著更高的工资正效应;但相对于城镇工,农民工的工资中包含了更多的基于艰苦危险工作条件的岗位补偿部分;在岗位补偿可比口径下,城乡劳动者的工资差异显著大于调查工资口径下的工资差异。以此判断,我国城镇劳动力市场存在以负面工作条件补偿不足为形式的隐性分割,次级劳动力市场中,尤其是哪些最为艰苦和危险的工作岗位上,城乡劳动者看似基本一致的工资水平并不代表农民工获得了平等的生产率回报。     

On variable selection in generalized linear and related regression models

This paper is concerned with selection of explanatory variables in generalized linear models (GLM). The class of GLM's is quite large and contains e.g. the ordinary linear regression, the binary logistic regression, the probit model and Poisson regression with linear or log-linear parameter structure. We show that, through an approximation of the log likelihood and a certain data transformation, the variable selection problem in a GLM can be converted into variable selection in an ordinary (unweighted) linear regression model. As a consequence no specific computer software for variable selection in GLM's is needed. Instead, some suitable variable selection program for linear regression can be used. We also present a simulation study which shows that the log likelihood approximation is very good in many practical situations. Finally, we mention briefly possible extensions to regression models outside the class of GLM's.     

Overeducation and the skills of UK graduates

Summary.  During the early 1990s the proportion of a cohort entering higher education in the UK doubled over a short period of time. The paper investigates the effect of the expansion on graduates' early labour market attainment, focusing on overeducation. We define overeducation by combining occupation codes and a self-reported measure for the appropriateness of the match between qualification and the job. We therefore define three groups of graduates: matched, apparently overeducated and genuinely overeducated. This measure is well correlated with alternative definitions of overeducation. Comparing pre- and post-expansion cohorts of graduates, we find with this measure that the proportion of overeducated graduates has doubled, even though overeducation wage penalties have remained stable. We do not find that type of institution affects the probability of genuine overeducation. Apparently overeducated graduates are mostly indistinguishable from matched graduates, whereas genuinely overeducated graduates principally lack non-academic skills and suffer a large wage penalty. Individual unobserved heterogeneity differs between the three groups of graduates but controlling for it does not alter these conclusions.     

Determination of the functional form of the relationship of covariates to the log hazard ratio in a Cox model

In this paper, we review available methods for determination of the functional form of the relation between a covariate and the log hazard ratio for a Cox model. We pay special attention to the detection of influential observations to the extent that they influence the estimated functional form of the relation between a covariate and the log hazard ratio. Our paper is motivated by a data set from a cohort study of lung cancer and silica exposure, where the nonlinear shape of the estimated log hazard ratio for silica exposure plotted against cumulative exposure and hereafter referred to as the exposure–response curve was greatly affected by whether or not two individuals with the highest exposures were included in the analysis. Formal influence diagnostics did not identify these two individuals but did identify the three highest exposed cases. Removal of these three cases resulted in a biologically plausible exposure–response curve.     

中国与日本产业国际竞争力比较研究 －基于中日投入产出序列表的分析

 本文用投入产出的分析模型,将中日价格差异用中间投入生产率、劳动价格、劳动生产率、固定资本价格、资本生产率和“其他”等6个要素进行解释,并推算出这些要素在整个中日价格差异中所占的比重,从而对中日国际竞争力进行比较分析。从分析结果可以得出,中国各产业的国际竞争力的主要因素是低廉的劳动成本和资本价格,而日本则具有较高的劳动生产率和中间投入生产率。     

中国工资和价格下调刚性下的货币政策非对称性研究

为考察货币政策的非对称性效应,本文将工资下调刚性与价格下调刚性特征构建于宏观结构模型,并利用中国宏观经济季度数据,采用模拟矩方法对上述结构模型中的参数进行估计,最后利用估计得到的参数对模型进行随机动态模拟分析。模型参数的估计结果表明,我国工资和价格的变动具有明显的下调刚性特征。基于估计得到的参数对模型的动态模拟分析说明,信贷政策、存款准备金率政策以及存贷利差政策都在执行方向和力度上对经济系统产生了不同类型的非对称性效应,并且不同种类的货币政策工具对经济产生了不同的影响效果。本文的研究对我国中央银行根据经济状况选择恰当的货币政策工具,以及确定政策工具在数量上的执行力度都有着参考意义。     

Nonparametric Panel Estimation of Labor Supply

In this article, we estimate structural labor supply with piecewise-linear budgets and nonseparable endogenous unobserved heterogeneity. We propose a two-stage method to address the endogeneity issue that comes from the correlation between the covariates and unobserved heterogeneity. In the first stage, Evdokimov’s nonparametric de-convolution method serves to identify the conditional distribution of unobserved heterogeneity from the quasi-reduced model that uses panel data. In the second stage, the conditional distribution is plugged into the original structural model to estimate labor supply. We apply this methodology to estimate the labor supply of U.S. married men in 2004 and 2005. Our empirical work demonstrates that ignoring the correlation between the covariates and unobserved heterogeneity will bias the estimates of wage elasticities upward. The labor elasticity estimated from a fixed effects model is less than half of that obtained from a random effects model.     

中国分行业和总体工资粘性

工资粘性是比价格粘性更加重要的名义刚性,对于分析外生冲击对宏观经济的影响具有至关重要的作用。本文从行业工资粘性的异质性入手,建立多部门DSGE模型并推导出各行业的工资动态方程;通过对行业工资动态方程的结构化GMM估计,得到了我国19个行业的工资粘性,发现各行业的工资粘性存在显著的异质性。本文进一步研究了总体工资粘性的估计问题,发现采用单部门DSGE模型估计总体工资粘性会出现高估的问题,而以各行业工资为权重计算各行业工资粘性的加权中位数可以较好的估计加总工资粘性。     

Hazard ratio inference in stratified clinical trials with time‐to‐event endpoints and limited sample size

The stratified Cox model is commonly used for stratified clinical trials with time‐to‐event endpoints. The estimated log hazard ratio is approximately a weighted average of corresponding stratum‐specific Cox model estimates using inverse‐variance weights; the latter are optimal only under the (often implausible) assumption of a constant hazard ratio across strata. Focusing on trials with limited sample sizes (50‐200 subjects per treatment), we propose an alternative approach in which stratum‐specific estimates are obtained using a refined generalized logrank (RGLR) approach and then combined using either sample size or minimum risk weights for overall inference. Our proposal extends the work of Mehrotra et al, to incorporate the RGLR statistic, which outperforms the Cox model in the setting of proportional hazards and small samples. This work also entails development of a remarkably accurate plug‐in formula for the variance of RGLR‐based estimated log hazard ratios. We demonstrate using simulations that our proposed two‐step RGLR analysis delivers notably better results through smaller estimation bias and mean squared error and larger power than the stratified Cox model analysis when there is a treatment‐by‐stratum interaction, with similar performance when there is no interaction. Additionally, our method controls the type I error rate while the stratified Cox model does not in small samples. We illustrate our method using data from a clinical trial comparing two treatments for colon cancer.     

Variational approximation for heteroscedastic linear models and matching pursuit algorithms

Modern statistical applications involving large data sets have focused attention on statistical methodologies which are both efficient computationally and able to deal with the screening of large numbers of different candidate models. Here we consider computationally efficient variational Bayes approaches to inference in high-dimensional heteroscedastic linear regression, where both the mean and variance are described in terms of linear functions of the predictors and where the number of predictors can be larger than the sample size. We derive a closed form variational lower bound on the log marginal likelihood useful for model selection, and propose a novel fast greedy search algorithm on the model space which makes use of one-step optimization updates to the variational lower bound in the current model for screening large numbers of candidate predictor variables for inclusion/exclusion in a computationally thrifty way. We show that the model search strategy we suggest is related to widely used orthogonal matching pursuit algorithms for model search but yields a framework for potentially extending these algorithms to more complex models. The methodology is applied in simulations and in two real examples involving prediction for food constituents using NIR technology and prediction of disease progression in diabetes.     

The Effect of Estimation of Unknown Degrees of Freedom on Estimation of Remaining Parameters in Spanos’ Conditional t Heteroskedastic Model

This article investigates the effect of estimation of unknown degrees of freedom on efficient estimation of remaining parameters in Spanos’ conditional t heteroskedastic model. We compare by simulation three maximum likelihood estimators (MLEs) of the remaining parameters in the model: the MLE of the remaining parameters when all the parameters are estimated by the MLE, when the degrees of freedom is estimated by a method of moments estimator, and when the degrees of freedom is erroneously specified. The latter two methods are found to perform poorly compared to the former method for the inference of variance parameters in the model. Thus, efficient estimation of degrees of freedom by the MLE is important to estimate efficiently the remaining variance parameters.     

Rounded responses to income questions

Summary: Responses to income questions in surveys are often rounded by the respondents. Though this is widely ignored, rounding can have detrimental effects on the results of a statistical analysis, especially with respect to the consistency of estimates. This paper deals with the analysis of data from the Finnish sub–sample of the European Community Household Panel (ECHP) with respect to factors that influence rounding of personal gross wage and earnings. The finding is that the propensity to observe rounded values can be related to factors like the interview mode, the wage level, and personal characteristics like gender and job type.*Work financed by the European Commission under contract number IST–1999–11101.     

Variance Estimation under Two‐Phase Sampling

We consider the variance estimation of the weighted likelihood estimator (WLE) under two‐phase stratified sampling without replacement. Asymptotic variance of the WLE in many semiparametric models contains unknown functions or does not have a closed form. The standard method of the inverse probability weighted (IPW) sample variances of an estimated influence function is then not available in these models. To address this issue, we develop the variance estimation procedure for the WLE in a general semiparametric model. The phase I variance is estimated by taking a numerical derivative of the IPW log likelihood. The phase II variance is estimated based on the bootstrap for a stratified sample in a finite population. Despite a theoretical difficulty of dependent observations due to sampling without replacement, we establish the (bootstrap) consistency of our estimators. Finite sample properties of our method are illustrated in a simulation study.