The Estimation of Compensating Wage Differentials: Lessons From the Deadliest Catch

ABSTRACT

I use longitudinal survey data from commercial fishing deckhands in the Alaskan Bering Sea to provide new insights on empirical methods commonly used to estimate compensating wage differentials and the value of statistical life (VSL). The unique setting exploits intertemporal variation in fatality rates and wages within worker-vessel pairs caused by a combination of weather patterns and policy changes, allowing identification of parameters and biases that it has only been possible to speculate about in more general settings. I show that estimation strategies common in the literature produce biased estimates in this setting, and decompose the bias components due to latent worker, establishment, and job-match heterogeneity. The estimates also remove the confounding effects of endogenous job mobility and dynamic labor market search, narrowing a conceptual gap between search-based hedonic wage theory and its empirical applications. I find that workers’ marginal aversion to fatal risk falls as risk levels rise, which suggests complementarities in the benefits of public safety policies. Supplementary materials for this article are available online.     

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.     

Testing for Slope Heterogeneity Bias in Panel Data Models

ABSTRACT

Standard econometric methods can overlook individual heterogeneity in empirical work, generating inconsistent parameter estimates in panel data models. We propose the use of methods that allow researchers to easily identify, quantify, and address estimation issues arising from individual slope heterogeneity. We first characterize the bias in the standard fixed effects estimator when the true econometric model allows for heterogeneous slope coefficients. We then introduce a new test to check whether the fixed effects estimation is subject to heterogeneity bias. The procedure tests the population moment conditions required for fixed effects to consistently estimate the relevant parameters in the model. We establish the limiting distribution of the test and show that it is very simple to implement in practice. Examining firm investment models to showcase our approach, we show that heterogeneity bias-robust methods identify cash flow as a more important driver of investment than previously reported. Our study demonstrates analytically, via simulations, and empirically the importance of carefully accounting for individual specific slope heterogeneity in drawing conclusions about economic behavior.     

Evaluating the effect of education on earnings: models, methods and results from the National Child Development Survey

Summary.  Regression, matching, control function and instrumental variables methods for recovering the effect of education on individual earnings are reviewed for single treatments and sequential multiple treatments with and without heterogeneous returns. The sensitivity of the estimates once applied to a common data set is then explored. We show the importance of correcting for detailed test score and family background differences and of allowing for (observable) heterogeneity in returns. We find an average return of 27% for those completing higher education versus anything less. Compared with stopping at 16 years of age without qualifications, we find an average return to O-levels of 18%, to A-levels of 24% and to higher education of 48%.     

High wage workers and low wage firms: negative assortative matching or limited mobility bias?

Summary.  In the empirical literature on assortative matching using linked employer–employee data, unobserved worker quality appears to be negatively correlated with unobserved firm quality. We show that this can be caused by standard estimation error. We develop formulae that show that the estimated correlation is biased downwards if there is true positive assortative matching and when any conditioning covariates are uncorrelated with the firm and worker fixed effects. We show that this bias is bigger the fewer movers there are in the data, which is 'limited mobility bias'. This result applies to any two-way (or higher) error components model that is estimated by fixed effects methods. We apply these bias corrections to a large German linked employer–employee data set. We find that, although the biases can be considerable, they are not sufficiently large to remove the negative correlation entirely.     

流动人口的收入差距对主观幸福感的影响研究

根据国家卫生计生委组织实施的《流动人口动态监测调查问卷》数据,探讨回归模型中解释变量的内生性问题,研究中国流动人口群体内部的收入差距对主观幸福感的影响。研究发现:流动人口的收入差距与主观幸福感之间存在显著的U型关系,这种影响在不同就业身份的流动人口之间存在异质性,个人收入差距对主观幸福感的影响在雇员群体中表现为显著的U型,在雇主群体中表现为显著的线性正相关,在自营劳动者群体中却不具有统计显著性;家庭总收入差距对主观幸福感的影响在雇员和自营劳动者中都表现为显著的U型关系,在雇主群体中却不具有统计显著性。     

Alternative Tests for Parameter Stability

ABSTRACT

We propose new tests for parameter stability based on estimates computed from a sequence of subsamples moving forward and backward across the sample. We obtain a sequence of moving estimates tests and we derive their asymptotic null distribution based on the functional central limit theorem. The critical values are approximated using Durbin's method. Our simulation results show that these tests have comparable size and slightly higher power in detecting structural change than other competing tests.     

The Demand for Lotto: The Role of Conscious Selection

This article presents estimates of the elasticity of demand for lottery tickets using time series data in which there is variation in the expected value of a lottery ticket induced by rollovers. An important feature of our data is that there are far more rollovers than expected given the lottery design. We find strong evidence that individuals do not choose their lottery numbers uniformly from a uniform distribution—that is, conscious selection. We use our estimates to derive the inverse supply function for the industry, and this enables us to identify the demand elasticity. We find the price elasticity to be close to unity, which implies that the operator is revenue maximizing—which is the regulator's objective.     

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.     

Generalized run tests for statistical process control

ABSTRACT

In a sequence of elements, a run is defined as a maximal subsequence of like elements. The number of runs or the length of the longest run has been widely used to test the randomness of an ordered sequence. Based on two different sampling methods and two types of test statistics used, run tests can be classified into one of four cases. Numerous researchers have derived the probability distributions in many different ways, treating each case separately. In the paper, we propose a unified approach which is based on recurrence arguments of two mutually exclusive sub-sequences. We also consider the sequence of nominal data that has more than two classes. Thus, the traditional run tests for a binary sequence are special cases of our generalized run tests. We finally show that the generalized run tests can be applied to many quality management areas, such as testing changes in process variation, developing non-parametric multivariate control charts, and comparing the shapes and locations of more than two process distributions.     

Simulation and quality of a synthetic close-to-reality employer–employee population

It is of essential importance that researchers have access to linked employer–employee data, but such data sets are rarely available for researchers or the public. Even in case that survey data have been made available, the evaluation of estimation methods is usually done by complex design-based simulation studies. For this aim, data on population level are needed to know the true parameters that are compared with the estimations derived from complex samples. These samples are usually drawn from the population under various sampling designs, missing values and outlier scenarios. The structural earnings statistics sample survey proposes accurate and harmonized data on the level and structure of remuneration of employees, their individual characteristics and the enterprise or place of employment to which they belong in EU member states and candidate countries. At the basis of this data set, we show how to simulate a synthetic close-to-reality population representing the employer and employee structure of Austria. The proposed simulation is based on work of A. Alfons, S. Kraft, M. Templ, and P. Filzmoser [{\em On the simulation of complex universes in the case of applying the German microcensus}, DACSEIS research paper series No. 4, University of Tübingen, 2003] and R. Münnich and J. Schürle [{\em Simulation of close-to-reality population data for household surveys with application to EU-SILC}, Statistical Methods & Applications 20(3) (2011c), pp. 383–407]. However, new challenges are related to consider the special structure of employer–employee data and the complexity induced with the underlying two-stage design of the survey. By using quality measures in form of simple summary statistics, benchmarking indicators and visualizations, the simulated population is analysed and evaluated. An accompanying study on literature has been made to select the most important benchmarking indicators.     

Specification Tests for Random-effects Transition Models: An Application to a Model of the British Youth Training Scheme

We develop diagnostic tests for random-effects multi-spell multi-state models focusing on: independence between the unobserved heterogeneity and observed covariates; mutual independence of heterogeneity terms; and distributional form. They are applied to a transition model of the British youth labor market, revealing significant misspecifications in our initial model, and allowing us to develop a considerably better-fitting specification that would have been difficult to reach by other means. The improved specification implies reduced estimates of the effectiveness of the youth training scheme (YTS), but we nevertheless retain the conclusion of significant positive effects of YTS on employment prospects.     

An illustration of the causality relation between government spending and revenue using wavelet analysis on Finnish data

Quarterly data for the period 1960:1 to 1997:2, conventional tests, a bootstrap simulation approach and a multivariate Rao's F-test have been used to investigate if the causality between government spending and revenue in Finland was changed at the beginning of 1990 due to future plans to create the European Monetary Union (EMU). The results indicate that during the period before 1990, the government revenue Granger-caused spending, while the opposite happened after 1990, which agrees better with Barro's tax smoothing hypothesis. However, when using monthly data instead of quarterly data for almost the same sample period, totally different results have been noted. The general conclusion is that the relationship between spending and revenue in Finland is still not completely understood. The ambiguity of these results may well be due to the fact that there are several time scales involved in the relationship, and that the conventional analyses may be inadequate to separate out the time scale structured relationships between these variables. Therefore, to investigate empirically the relation between these variables we attempt to use the wavelets analysis that enables us to separate out different time scales of variation in the data. We find that time scale decomposition is important for analysing these economic variables.     

Further Evidence on the Great Crash,the Oil-Price Shock,and the Unit-Root Hypothesis

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite-sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependent innovations is investigated, in brief, by treating the breakpoint as endogenous, we find that there is less evidence against the unit-root hypothesis than Perron finds for many of the data series but stronger evidence against it for several of the series, including the Nelson-Plosser industrial-production, nominal-GNP, and real-GNP series.     

Some Second-Order Asymptotics for Extreme Value Linear Regression Models

ABSTRACT

In this article we derive finite-sample corrections in matrix notation for likelihood ratio and score statistics in extreme-value linear regression models. We consider three corrected score tests that perform better than the usual score test. We also derive general formulae for second-order biases of maximum likelihood estimates of the linear parameters. Some simulations are performed to compare the likelihood ratio and score statistics with their modified versions and to illustrate the bias correction.     

异质型人力资本与经济发展——基于空间异质性的实证研究

区域经济发展的不平衡性,始终是社会经济研究领域内的热点问题。不同层级的人力资本,应与区域的异质性相一致,以实现各自区域经济发展的最大化。本文在充分考量“四大板块”区域异质性基础上,以人力资本的异质性为视角,利用1987-2017年的省级面板数据构建多种空间面板计量模型,从经济增长和经济运行质量两个维度来探寻不同层次人力资本对区域经济发展效能的空间差异。研究表明：①全国层面,所有层次的人力资本对经济增长均有促进作用;但初级和中级人力资本会遏制产业结构高级化,只有高级人力资本才能推动产业结构高级化。②区域层面,不同层次的人力资本对东、中、西和东北地区经济发展的直接效应和间接效应具有明显的区域空间异质性。     

Abundance estimation with a categorical covariate subject to missing in continuous-time capture-recapture studies

Abstract

In continuous-time capture-recapture experiments, individual heterogeneity has a large effect on the capture probability. To account for the heterogeneity, we consider an individual covariate, which is categorical and subject to missing. In this article, we develop a general model to summarize three kinds of missing mechanisms, and propose a maximum likelihood estimator of the abundance. A likelihood ratio confidence interval of the abundance is also proposed. We illustrate the proposed methods by simulation studies and a real data example of a bird species prinia subflava in Hong Kong.     

Systematically misclassified binary dependent variables

ABSTRACT

When a binary dependent variable is misclassified, that is, recorded in the category other than where it really belongs, probit and logit estimates are biased and inconsistent. In some cases, the probability of misclassification may vary systematically with covariates, and thus be endogenous. In this paper, we develop an estimation approach that corrects for endogenous misclassification, validate our approach using a simulation study, and apply it to the analysis of a treatment program designed to improve family dynamics. Our results show that endogenous misclassification could lead to potentially incorrect conclusions unless corrected using an appropriate technique.     

储蓄、投资与中国资本流动——基于面板协整分析

在对Feldstein—Horioka之谜及其相关研究的基础上,利用中国的省级数据,通过建立、估计和检验面板协整模型,分析各区域之间的资本流动关系。研究结果表明：中国东部地区的资本流动性最强,中部地区的资本流动性次之,西部地区资本流动性最差;东部地区各省份以资本净流人为主,西部地区各省份以资本净流出为主。因此,要提高资本的自由流动程度,尤其要引导资本向中西部地区流动,加速中国经济的一体化进程,缩小不同区域经济发展的差距。     

Comments

In this paper we compare Bartlett-corrected, bootstrap, and fast double bootstrap tests on maximum likelihood estimates of cointegration parameters. The key result is that both the bootstrap and the Bartlett-corrected tests must be based on the unrestricted estimates of the cointegrating vectors: procedures based on the restricted estimates have almost no power. The small sample size bias of the asymptotic test appears so severe as to advise strongly against its use with the sample sizes commonly available; the fast double bootstrap test minimizes size bias, while the Bartlett-corrected test is somehow more powerful.