Takuya Hasebe - Academia.edu (original) (raw)

Papers by Takuya Hasebe

Research paper thumbnail of Determinants of distributional changes in body mass index over time in the United States: Decomposition method

Research paper thumbnail of The Type of Contract and Starting Wage and Wage Growth: The Evidence from New Graduates from Post-Secondary Schools in the Netherlands

The AlmaLaurea working paper series is designed to make available to a wide readership selected w... more The AlmaLaurea working paper series is designed to make available to a wide readership selected works by AlmaLaurea staff or by outside, generally available in English or Italian. The series focuses on the study of the relationship between educational systems, society and economy, the quality of educational process, the demand and supply of education, the human capital accumulation, the structure and working of the labour markets, the assessment of educational policies. Comments on this series are welcome and should be sent to pubblicazioni@almalaurea.it. AlmaLaurea is a public consortium of Italian universities which, with the support of the Ministry of Education, meets the information needs of graduates, universities and the business community. AlmaLaurea has been set up in 1994 following an initiative of the Statistical Observatory of the University of Bologna. It supplies reliable and timely data on the effectiveness and efficiency of the higher education system to member universities' governing bodies, assessment units and committees responsible for teaching activities and career guidance. AlmaLaurea: facilitates and improves the hiring of young graduates in the labour markets both at the national and international level; simplifies companies' search for personnel reducing the gap between the demand for and supply of simplifies companies search for personnel, reducing the gap between the demand for and supply of qualified labour (www.almalaurea.it/en/aziende/); makes available online more than 1.5 million curricula (in Italian and English) of graduates, including those with a pluriannual work experience (www.almalaurea.it/en/); ensures the optimization of human resources utilization through a steady updating of data on the careers of students holding a degree (www.almalaurea.it/en/lau/). Each year AlmaLaurea plans two main conferences (www.almalaurea.it/en/informa/news) in which the results of the annual surveys on Graduates' Employment Conditions and Graduates' Profile are presented.

Research paper thumbnail of Endogenous models of binary choice outcomes: Copula-based maximum-likelihood estimation and treatment effects

The Stata Journal: Promoting communications on statistics and Stata

In this article, I describe the commands that implement the estimation of three endogenous models... more In this article, I describe the commands that implement the estimation of three endogenous models of binary choice outcome. The command esbinary fits the endogenously switching model, where a potential outcome differs across two treatment states. The command edbinary fits the endogenous dummy model, which includes a dummy variable indicating the treatment state as one of the explanatory variables. After one estimates the parameters of these models, various treatment effects can be estimated as postestimation statistics. The command ssbinary fits the sample-selection model, where an outcome is observed in only one of the states. The commands fit these models using copula-based maximumlikelihood estimation.

Research paper thumbnail of On the treatment effects of a binary choice outcome model

Economics Letters

Abstract This paper discusses an econometric model to estimate treatment effects for binary choic... more Abstract This paper discusses an econometric model to estimate treatment effects for binary choice outcomes. We use a copula to model the dependence of unobservable terms. The copula-based approach allows for various dependence structures. A simulation study shows the misspecification of the dependence structures results in biased estimation of the treatment effects.

Research paper thumbnail of WORKING PAPER SERIES Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act

to use the Japanese Panel Survey of Consumers for this research. We thank

Research paper thumbnail of A Flexible Sample Selection Model

In this paper, we propose a new approach to estimating sample selection models that combines Gene... more In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick-or thintailed behavior in the data that it represents. Copulas help create versatile representations of bivariate distribution. The versatility arising from inserting GTL marginal distributions into copula-constructed bivariate distributions reduces the dependence of estimated parameters on distributional assumptions in applied research. A thorough Monte Carlo study illustrates that our proposed estimator performs well under normal and nonnormal settings, both with and without an instrument in the selection equation that fulfills the exclusion restriction that is often considered to be a requisite for implementation of sample selection models in empirical research. Five applications ranging from wages and health expenditures to speeding tickets and international disputes illustrate the value of the proposed GTL-copula estimator.

Research paper thumbnail of Endogenous switching regression model and treatment effects of count-data outcome

The Stata Journal: Promoting communications on statistics and Stata, 2020

In this article, I describe the escount command, which implements the estimation of an endogenous... more In this article, I describe the escount command, which implements the estimation of an endogenous switching model with count-data outcomes, where a potential outcome differs across two alternate treatment statuses. escount allows for either a Poisson or a negative binomial regression model with lognormal latent heterogeneity. After estimating the parameters of the switching regression model, one can estimate various treatment effects with the command teescount. I also describe the command lncount, which fits the Poisson or negative binomial regression model with lognormal latent heterogeneity.

Research paper thumbnail of GTL Regression: A Linear Model with Skewed and Thick-Tailed Disturbances

SSRN Electronic Journal, 2015

If the disturbances of a linear regression model are skewed and/or thick-tailed, a maximum likeli... more If the disturbances of a linear regression model are skewed and/or thick-tailed, a maximum likelihood estimator is efficient relative to the customary Ordinary Least Squares (OLS) estimator. In this paper, we specify a highly flexible Generalized Tukey Lambda (GTL) distribution to model skewed and thick-tailed disturbances. The Maximum-Likelihood-based GTL-regression estimator is consistent and asymptotically normal. We demonstrate the potential gains of the GTL estimator over the OLS estimator in a Monte Carlo study and in two applications that are typical of applied economics research problems: a study of trade creation and trade diversion that result from preferential trade agreements, and an analysis of speeding tickets.

Research paper thumbnail of A Flexible Sample Selection Model: A Gtl-Copula Approach

SSRN Electronic Journal, 2012

In this paper, we propose a new approach to estimating sample selection models that combines Gene... more In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick-or thintailed behavior in the data that it represents. Copulas help create versatile representations of bivariate distribution. The versatility arising from inserting GTL marginal distributions into copula-constructed bivariate distributions reduces the dependence of estimated parameters on distributional assumptions in applied research. A thorough Monte Carlo study illustrates that our proposed estimator performs well under normal and nonnormal settings, both with and without an instrument in the selection equation that fulfills the exclusion restriction that is often considered to be a requisite for implementation of sample selection models in empirical research. Five applications ranging from wages and health expenditures to speeding tickets and international disputes illustrate the value of the proposed GTL-copula estimator.

Research paper thumbnail of Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act

Journal of Human Capital, 2019

Research paper thumbnail of Treatment effect estimators for count data models

Health Economics, 2018

In this paper, we consider a switching regression model with count data outcomes, where the possi... more In this paper, we consider a switching regression model with count data outcomes, where the possible outcome differs across two alternate states and individuals endogenously select one of the states. We assume lognormal latent heterogeneity. Building on the switching regression model, we derive estimators of various treatment effects: the average treatment effect, the average treatment effect on the treated, the local average treatment effect, and the marginal treatment effect. We illustrate an application that examines the effects of public insurance on the number of doctor visits using the data employed by previous studies.

Research paper thumbnail of Are elderly workers more likely to die in occupational accidents? Evidence from both industry-aggregated data and administrative individual-level data in Japan

Japan and the World Economy, 2018

As a result of recent government policies, Japanese firms have a growing number of elderly worker... more As a result of recent government policies, Japanese firms have a growing number of elderly workers. However, little attention has been given to the various costs of an aging workforce, one of which is an increase in occupational accidents. Based on the industry-aggregated data and publicly available administrative individual-level data from the late 2000s, during which many policies aimed at promoting elderly employment have been implemented, this study investigates whether the probability of having a work-related accident rises with a worker's age and whether injury (or illness) due to an accident is more likely to be fatal when the worker is older. We found a positive and statistically significant impact of a worker's age on the probability of having a workrelated accident, after controlling for factors such as industry and firm size. We also found that occupational accidents are more likely to cause death to sufferers in their 60 s or later. However, the impact of age on workrelated accidents has remained almost unchanged throughout the period of our analysis.

Research paper thumbnail of Copula-Based Maximum-Likelihood Estimation of Sample-Selection Models

The Stata Journal: Promoting communications on statistics and Stata, 2013

I describe the commands heckmancopula and switchcopula, which implement copula-based maximum-like... more I describe the commands heckmancopula and switchcopula, which implement copula-based maximum-likelihood estimations of sample-selection models.

Research paper thumbnail of Pilot survey of a novel incentive to promote healthy behavior among school children and their parents

Preventive Medicine Reports, 2017

Reversing the obesity epidemic has been a persistent global public health challenge, particularly... more Reversing the obesity epidemic has been a persistent global public health challenge, particularly among low socioeconomic status populations and racial/ethnic minorities. We developed a novel concept of community-based incentives to approach this problem in such communities. Applying this concept, we proposed a school intervention to promote obesity prevention in the U.S. We conducted a pilot survey to explore attitudes towards this future intervention. The survey was collected as a nonprobability sample (N = 137 school-aged children (5-12 years)) in northern California in July 2013. We implemented multivariable logistic regression analyses where the dependent variable indicated the intention to participate in the future intervention. The covariates included the body mass index (BMI) based weight categories, demographics, and others. We found that the future intervention is expected to motivate generally-high-risk populations (such as children and parents who have never joined a past health-improvement program compared to those who have completed a past healthimprovement program (the odds-ratio (OR) = 5.84, p b 0.05) and children with an obese/overweight parent (OR = 2.72, p b 0.05 compared to those without one)) to participate in future obesity-prevention activities. Our analyses also showed that some subgroups of high-risk populations, such as Hispanic children (OR = 0.27, p b 0.05) and children eligible for a free or reduced price meal program (OR = 0.37, p b 0.06), remain difficult to reach and need an intensive outreach activity for the future intervention. The survey indicated high interest in the future school intervention among high-risk parents who have never joined a past health-improvement program or are obese/overweight. These findings will help design and implement a future intervention.

Research paper thumbnail of The tests for the level moment conditions: GMM estimation in a linear dynamic panel data model

Research paper thumbnail of Decomposing racial/ethnic disparities in influenza vaccination among the elderly

Vaccine, Jan 18, 2015

While persistent racial/ethnic disparities in influenza vaccination have been reported among the ... more While persistent racial/ethnic disparities in influenza vaccination have been reported among the elderly, characteristics contributing to disparities are poorly understood. This study aimed to assess characteristics associated with racial/ethnic disparities in influenza vaccination using a nonlinear Oaxaca-Blinder decomposition method. We performed cross-sectional multivariable logistic regression analyses for which the dependent variable was self-reported receipt of influenza vaccine during the 2010-2011 season among community dwelling non-Hispanic African-American (AA), non-Hispanic White (W), English-speaking Hispanic (EH) and Spanish-speaking Hispanic (SH) elderly, enrolled in the 2011 Medicare Current Beneficiary Survey (MCBS) (un-weighted/weighted N=6,095/19.2million). Using the nonlinear Oaxaca-Blinder decomposition method, we assessed the relative contribution of seventeen covariates - including socio-demographic characteristics, health status, insurance, access, preference ...

Research paper thumbnail of Marginal effects of a bivariate binary choice model

Economics Letters, 2013

h i g h l i g h t s • The marginal effects of the copula-based bivariate binary choice model are ... more h i g h l i g h t s • The marginal effects of the copula-based bivariate binary choice model are derived. • The signs of the marginal effects are shown to be determined by the signs of the coefficients using the properties of a copula. • A real-data application is provided.

Research paper thumbnail of Estimating the variance of decomposition effects

Applied Economics, 2015

We derive the asymptotic variance of Blinder-Oaxaca decomposition effects. We show that the delta... more We derive the asymptotic variance of Blinder-Oaxaca decomposition effects. We show that the delta method approach that builds on the assumption of fixed regressors understates true variability of the decomposition effects when regressors are stochastic. Our proposed variance estimator takes randomness of regressors into consideration. Our approach is applicable to both the linear and nonlinear decompositions, for the latter of which only a bootstrap method is an option. As our derivation follows the general framework of m-estimation, it is straightforward to extend to the cluster-robust variance estimator. We demonstrate the finite-sample performance of our variance estimator with a Monte Carlo study and present a real-data application.

Research paper thumbnail of Determinants of distributional changes in body mass index over time in the United States: Decomposition method

Research paper thumbnail of The Type of Contract and Starting Wage and Wage Growth: The Evidence from New Graduates from Post-Secondary Schools in the Netherlands

The AlmaLaurea working paper series is designed to make available to a wide readership selected w... more The AlmaLaurea working paper series is designed to make available to a wide readership selected works by AlmaLaurea staff or by outside, generally available in English or Italian. The series focuses on the study of the relationship between educational systems, society and economy, the quality of educational process, the demand and supply of education, the human capital accumulation, the structure and working of the labour markets, the assessment of educational policies. Comments on this series are welcome and should be sent to pubblicazioni@almalaurea.it. AlmaLaurea is a public consortium of Italian universities which, with the support of the Ministry of Education, meets the information needs of graduates, universities and the business community. AlmaLaurea has been set up in 1994 following an initiative of the Statistical Observatory of the University of Bologna. It supplies reliable and timely data on the effectiveness and efficiency of the higher education system to member universities' governing bodies, assessment units and committees responsible for teaching activities and career guidance. AlmaLaurea: facilitates and improves the hiring of young graduates in the labour markets both at the national and international level; simplifies companies' search for personnel reducing the gap between the demand for and supply of simplifies companies search for personnel, reducing the gap between the demand for and supply of qualified labour (www.almalaurea.it/en/aziende/); makes available online more than 1.5 million curricula (in Italian and English) of graduates, including those with a pluriannual work experience (www.almalaurea.it/en/); ensures the optimization of human resources utilization through a steady updating of data on the careers of students holding a degree (www.almalaurea.it/en/lau/). Each year AlmaLaurea plans two main conferences (www.almalaurea.it/en/informa/news) in which the results of the annual surveys on Graduates' Employment Conditions and Graduates' Profile are presented.

Research paper thumbnail of Endogenous models of binary choice outcomes: Copula-based maximum-likelihood estimation and treatment effects

The Stata Journal: Promoting communications on statistics and Stata

In this article, I describe the commands that implement the estimation of three endogenous models... more In this article, I describe the commands that implement the estimation of three endogenous models of binary choice outcome. The command esbinary fits the endogenously switching model, where a potential outcome differs across two treatment states. The command edbinary fits the endogenous dummy model, which includes a dummy variable indicating the treatment state as one of the explanatory variables. After one estimates the parameters of these models, various treatment effects can be estimated as postestimation statistics. The command ssbinary fits the sample-selection model, where an outcome is observed in only one of the states. The commands fit these models using copula-based maximumlikelihood estimation.

Research paper thumbnail of On the treatment effects of a binary choice outcome model

Economics Letters

Abstract This paper discusses an econometric model to estimate treatment effects for binary choic... more Abstract This paper discusses an econometric model to estimate treatment effects for binary choice outcomes. We use a copula to model the dependence of unobservable terms. The copula-based approach allows for various dependence structures. A simulation study shows the misspecification of the dependence structures results in biased estimation of the treatment effects.

Research paper thumbnail of WORKING PAPER SERIES Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act

to use the Japanese Panel Survey of Consumers for this research. We thank

Research paper thumbnail of A Flexible Sample Selection Model

In this paper, we propose a new approach to estimating sample selection models that combines Gene... more In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick-or thintailed behavior in the data that it represents. Copulas help create versatile representations of bivariate distribution. The versatility arising from inserting GTL marginal distributions into copula-constructed bivariate distributions reduces the dependence of estimated parameters on distributional assumptions in applied research. A thorough Monte Carlo study illustrates that our proposed estimator performs well under normal and nonnormal settings, both with and without an instrument in the selection equation that fulfills the exclusion restriction that is often considered to be a requisite for implementation of sample selection models in empirical research. Five applications ranging from wages and health expenditures to speeding tickets and international disputes illustrate the value of the proposed GTL-copula estimator.

Research paper thumbnail of Endogenous switching regression model and treatment effects of count-data outcome

The Stata Journal: Promoting communications on statistics and Stata, 2020

In this article, I describe the escount command, which implements the estimation of an endogenous... more In this article, I describe the escount command, which implements the estimation of an endogenous switching model with count-data outcomes, where a potential outcome differs across two alternate treatment statuses. escount allows for either a Poisson or a negative binomial regression model with lognormal latent heterogeneity. After estimating the parameters of the switching regression model, one can estimate various treatment effects with the command teescount. I also describe the command lncount, which fits the Poisson or negative binomial regression model with lognormal latent heterogeneity.

Research paper thumbnail of GTL Regression: A Linear Model with Skewed and Thick-Tailed Disturbances

SSRN Electronic Journal, 2015

If the disturbances of a linear regression model are skewed and/or thick-tailed, a maximum likeli... more If the disturbances of a linear regression model are skewed and/or thick-tailed, a maximum likelihood estimator is efficient relative to the customary Ordinary Least Squares (OLS) estimator. In this paper, we specify a highly flexible Generalized Tukey Lambda (GTL) distribution to model skewed and thick-tailed disturbances. The Maximum-Likelihood-based GTL-regression estimator is consistent and asymptotically normal. We demonstrate the potential gains of the GTL estimator over the OLS estimator in a Monte Carlo study and in two applications that are typical of applied economics research problems: a study of trade creation and trade diversion that result from preferential trade agreements, and an analysis of speeding tickets.

Research paper thumbnail of A Flexible Sample Selection Model: A Gtl-Copula Approach

SSRN Electronic Journal, 2012

In this paper, we propose a new approach to estimating sample selection models that combines Gene... more In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick-or thintailed behavior in the data that it represents. Copulas help create versatile representations of bivariate distribution. The versatility arising from inserting GTL marginal distributions into copula-constructed bivariate distributions reduces the dependence of estimated parameters on distributional assumptions in applied research. A thorough Monte Carlo study illustrates that our proposed estimator performs well under normal and nonnormal settings, both with and without an instrument in the selection equation that fulfills the exclusion restriction that is often considered to be a requisite for implementation of sample selection models in empirical research. Five applications ranging from wages and health expenditures to speeding tickets and international disputes illustrate the value of the proposed GTL-copula estimator.

Research paper thumbnail of Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act

Journal of Human Capital, 2019

Research paper thumbnail of Treatment effect estimators for count data models

Health Economics, 2018

In this paper, we consider a switching regression model with count data outcomes, where the possi... more In this paper, we consider a switching regression model with count data outcomes, where the possible outcome differs across two alternate states and individuals endogenously select one of the states. We assume lognormal latent heterogeneity. Building on the switching regression model, we derive estimators of various treatment effects: the average treatment effect, the average treatment effect on the treated, the local average treatment effect, and the marginal treatment effect. We illustrate an application that examines the effects of public insurance on the number of doctor visits using the data employed by previous studies.

Research paper thumbnail of Are elderly workers more likely to die in occupational accidents? Evidence from both industry-aggregated data and administrative individual-level data in Japan

Japan and the World Economy, 2018

As a result of recent government policies, Japanese firms have a growing number of elderly worker... more As a result of recent government policies, Japanese firms have a growing number of elderly workers. However, little attention has been given to the various costs of an aging workforce, one of which is an increase in occupational accidents. Based on the industry-aggregated data and publicly available administrative individual-level data from the late 2000s, during which many policies aimed at promoting elderly employment have been implemented, this study investigates whether the probability of having a work-related accident rises with a worker's age and whether injury (or illness) due to an accident is more likely to be fatal when the worker is older. We found a positive and statistically significant impact of a worker's age on the probability of having a workrelated accident, after controlling for factors such as industry and firm size. We also found that occupational accidents are more likely to cause death to sufferers in their 60 s or later. However, the impact of age on workrelated accidents has remained almost unchanged throughout the period of our analysis.

Research paper thumbnail of Copula-Based Maximum-Likelihood Estimation of Sample-Selection Models

The Stata Journal: Promoting communications on statistics and Stata, 2013

I describe the commands heckmancopula and switchcopula, which implement copula-based maximum-like... more I describe the commands heckmancopula and switchcopula, which implement copula-based maximum-likelihood estimations of sample-selection models.

Research paper thumbnail of Pilot survey of a novel incentive to promote healthy behavior among school children and their parents

Preventive Medicine Reports, 2017

Reversing the obesity epidemic has been a persistent global public health challenge, particularly... more Reversing the obesity epidemic has been a persistent global public health challenge, particularly among low socioeconomic status populations and racial/ethnic minorities. We developed a novel concept of community-based incentives to approach this problem in such communities. Applying this concept, we proposed a school intervention to promote obesity prevention in the U.S. We conducted a pilot survey to explore attitudes towards this future intervention. The survey was collected as a nonprobability sample (N = 137 school-aged children (5-12 years)) in northern California in July 2013. We implemented multivariable logistic regression analyses where the dependent variable indicated the intention to participate in the future intervention. The covariates included the body mass index (BMI) based weight categories, demographics, and others. We found that the future intervention is expected to motivate generally-high-risk populations (such as children and parents who have never joined a past health-improvement program compared to those who have completed a past healthimprovement program (the odds-ratio (OR) = 5.84, p b 0.05) and children with an obese/overweight parent (OR = 2.72, p b 0.05 compared to those without one)) to participate in future obesity-prevention activities. Our analyses also showed that some subgroups of high-risk populations, such as Hispanic children (OR = 0.27, p b 0.05) and children eligible for a free or reduced price meal program (OR = 0.37, p b 0.06), remain difficult to reach and need an intensive outreach activity for the future intervention. The survey indicated high interest in the future school intervention among high-risk parents who have never joined a past health-improvement program or are obese/overweight. These findings will help design and implement a future intervention.

Research paper thumbnail of The tests for the level moment conditions: GMM estimation in a linear dynamic panel data model

Research paper thumbnail of Decomposing racial/ethnic disparities in influenza vaccination among the elderly

Vaccine, Jan 18, 2015

While persistent racial/ethnic disparities in influenza vaccination have been reported among the ... more While persistent racial/ethnic disparities in influenza vaccination have been reported among the elderly, characteristics contributing to disparities are poorly understood. This study aimed to assess characteristics associated with racial/ethnic disparities in influenza vaccination using a nonlinear Oaxaca-Blinder decomposition method. We performed cross-sectional multivariable logistic regression analyses for which the dependent variable was self-reported receipt of influenza vaccine during the 2010-2011 season among community dwelling non-Hispanic African-American (AA), non-Hispanic White (W), English-speaking Hispanic (EH) and Spanish-speaking Hispanic (SH) elderly, enrolled in the 2011 Medicare Current Beneficiary Survey (MCBS) (un-weighted/weighted N=6,095/19.2million). Using the nonlinear Oaxaca-Blinder decomposition method, we assessed the relative contribution of seventeen covariates - including socio-demographic characteristics, health status, insurance, access, preference ...

Research paper thumbnail of Marginal effects of a bivariate binary choice model

Economics Letters, 2013

h i g h l i g h t s • The marginal effects of the copula-based bivariate binary choice model are ... more h i g h l i g h t s • The marginal effects of the copula-based bivariate binary choice model are derived. • The signs of the marginal effects are shown to be determined by the signs of the coefficients using the properties of a copula. • A real-data application is provided.

Research paper thumbnail of Estimating the variance of decomposition effects

Applied Economics, 2015

We derive the asymptotic variance of Blinder-Oaxaca decomposition effects. We show that the delta... more We derive the asymptotic variance of Blinder-Oaxaca decomposition effects. We show that the delta method approach that builds on the assumption of fixed regressors understates true variability of the decomposition effects when regressors are stochastic. Our proposed variance estimator takes randomness of regressors into consideration. Our approach is applicable to both the linear and nonlinear decompositions, for the latter of which only a bootstrap method is an option. As our derivation follows the general framework of m-estimation, it is straightforward to extend to the cluster-robust variance estimator. We demonstrate the finite-sample performance of our variance estimator with a Monte Carlo study and present a real-data application.