The econometrics of female labor supply and children

This is a survey of applied econometric research on the effects of children on female labor supply. Reasons for interest in the topic, and a basic model and terminology, are reviewed. Concerns are raised about the possible endogeneity of child status variables, and about the instrumental variables approach for dealing with this problem. Alternative ways of conceptualizing and estimating child status effects are considered, together with selected empirical evidence. Relevant developments from the household demand literature are summarized. Basic issues of model choice are also discussed.     

Inferences for a Partially Varying Coefficient Model With Endogenous Regressors

In this article, we propose a new class of semiparametric instrumental variable models with partially varying coefficients, in which the structural function has a partially linear form and the impact of endogenous structural variables can vary over different levels of some exogenous variables. We propose a three-step estimation procedure to estimate both functional and constant coefficients. The consistency and asymptotic normality of these proposed estimators are established. Moreover, a generalized F-test is developed to test whether the functional coefficients are of particular parametric forms with some underlying economic intuitions, and furthermore, the limiting distribution of the proposed generalized F-test statistic under the null hypothesis is established. Finally, we illustrate the finite sample performance of our approach with simulations and two real data examples in economics.     

OLS and IV estimation of regression models including endogenous interaction terms

We analyze a class of linear regression models including interactions of endogenous regressors and exogenous covariates. We show how to generate instrumental variables using the nonlinear functional form of the structural equation when traditional excluded instruments are unknown. We propose to use these instruments with identification robust IV inference. We furthermore show that, whenever functional form identification is not valid, the ordinary least squares (OLS) estimator of the coefficient of the interaction term is consistent and standard OLS inference applies. Using our alternative empirical methods we confirm recent empirical findings on the nonlinear causal relation between financial development and economic growth.     

Secondary school dropout and work outcomes in ten developing countries

This paper analyzes the impact of secondary school dropout on the work outcomes of young people in ten developing countries. Understanding such a phenomenon is important because it may affect work prospects, exacerbate income inequality and determine macroeconomic lasting effects given that the formation of a skilled workforce is a key element of economic development and growth.When accounting for endogeneity, we find that secondary school dropout decreases the probability of being employed in non-elementary occupations, suggesting that unskilled workers fail to meet the increasing demand for a skilled workforce. Secondary school dropout, indeed, hinders the accumulation of adequate levels of human capital and anticipates entry into the unskilled labor market.Thus, policy-makers should aim at the extension and efficacy of compulsory education to the secondary level to avoid future under-education problems to promote a skilled workforce and encourage economic development and growth in the long run.     

Leadership,creativity, and innovation: A critical review and practical recommendations

Leadership is a key predictor of employee, team, and organizational creativity and innovation. Research in this area holds great promise for the development of intriguing theory and impactful policy implications, but only if empirical studies are conducted rigorously. In the current paper, we report a comprehensive review of a large number of empirical studies (N?=?195) exploring leadership and workplace creativity and innovation. Using this article cache, we conducted a number of systematic analyses and built narrative arguments documenting observed trends in five areas. First, we review and offer improved definitions of creativity and innovation. Second, we conduct a systematic review of the main effects of leadership upon creativity and innovation and the variables assumed to moderate these effects. Third, we conduct a systematic review of mediating variables. Fourth, we examine whether the study designs commonly employed are suitable to estimate the causal models central to the field. Fifth, we conduct a critical review of the creativity and innovation measures used, noting that most are sub-optimal. Within these sections, we present a number of taxonomies that organize extant research, highlight understudied areas, and serve as a guide for future variable selection. We conclude by highlighting key suggestions for future research that we hope will reorient the field and improve the rigour of future research such that we can build more reliable and useful theories and policy recommendations.     

Testing for Causal Effects in a Generalized Regression Model With Endogenous Regressors

A unifying framework to test for causal effects in nonlinear models is proposed. We consider a generalized linear‐index regression model with endogenous regressors and no parametric assumptions on the error disturbances. To test the significance of the effect of an endogenous regressor, we propose a statistic that is a kernel‐weighted version of the rank correlation statistic (tau) of Kendall (1938). The semiparametric model encompasses previous cases considered in the literature (continuous endogenous regressors (Blundell and Powell (2003)) and a single binary endogenous regressor (Vytlacil and Yildiz (2007))), but the testing approach is the first to allow for (i) multiple discrete endogenous regressors, (ii) endogenous regressors that are neither discrete nor continuous (e.g., a censored variable), and (iii) an arbitrary “mix” of endogenous regressors (e.g., one binary regressor and one continuous regressor).     

The Effect of Pseudo-Exogenous Instrumental Variables on Hausman Test

Hausman test is popularly used to examine the endogeneity of explanatory variables in a regression model. To derive a well-defined asymptotic distribution of Hausman test, the correlation between the instrumental variables and the error term needs to converge to zero. However, it is possible that there remains considerable correlation in finite samples between the instruments and the error, even though their correlation eventually converges to zero. This article investigates the potential problem that such “pseudo-exogenous” instruments may create. We show that the performance of Hausman test is deteriorated when the instruments are asymptotically exogenous but endogenous in finite samples, through Monte Carlo simulations.     

Applying a Treatment Effects Model to Investigate Public Amenity Effect on Physical Activity of the Elderly

The increasing elderly population puts significant health, economic, and social burdens on society. Physical activity is one of the most cost-effective ways to maintain the health of the elderly. This study adopts a treatment effects model to investigate the causal relationship between environment attributes and physical activity among the elderly, while taking endogeneity into account. The data were collected from 274 participants by face-to-face interviews in Taichung, Taiwan. Performing physical activity regularly in parks is the most important measure of the amount of physical activity by the elderly. Providing sufficient and accessible parks in metropolitan residential neighborhoods could be one of the most cost-effective ways to promote physical activity for the elderly living in midsize Asian cities.     

Inference in Censored Models with Endogenous Regressors

This paper analyzes the linear regression model y = xβ+ε with a conditional median assumption med (ε| z) = 0, where z is a vector of exogenous instrument random variables. We study inference on the parameter β when y is censored and x is endogenous. We treat the censored model as a model with interval observation on an outcome, thus obtaining an incomplete model with inequality restrictions on conditional median regressions. We analyze the identified features of the model and provide sufficient conditions for point identification of the parameter β. We use a minimum distance estimator to consistently estimate the identified features of the model. We show that under point identification conditions and additional regularity conditions, the estimator based on inequality restrictions is normal and we derive its asymptotic variance. One can use our setup to treat the identification and estimation of endogenous linear median regression models with no censoring. A Monte Carlo analysis illustrates our estimator in the censored and the uncensored case.     

性别、家庭财富与不同年龄阶段儿童辍学行为——基于2006年中国营养与健康调查数据

基于2006年中国营养与健康调查截面数据中农村教育阶段儿童样本的研究,本文发现,儿童性别、教育阶段、母亲最高教育年限及父亲身体健康状况是影响儿童辍学的重要因素,然而,随着儿童年龄增长性别歧视和家庭财富状况的影响逐渐减弱,并且会在一定年龄阶段改变影响方向。儿童辍学行为的影响因素中家庭财富状况由家庭父母教育程度和职业内生决定。