Takuya Hasebe

Personal Details

First Name:	Takuya
Middle Name:
Last Name:	Hasebe
Suffix:
RePEc Short-ID:	pha1037
	[This author has chosen not to make the email address public]
Terminal Degree:	2013 Department of Economics; Graduate Center; City University of New York (CUNY) (from RePEc Genealogy)

Affiliation

International Business and Economics
Faculty of Liberal Arts
Sophia University

Tokyo, Japan
https://www.sophia.ac.jp/eng/program/undergraduate_c/UG_LA/
RePEc:edi:iesopjp (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. HASEBE Takuya & KONISHI Yoshifumi & SHIN Kong Joo & MANAGI Shunsuke, 2018. "White Collar Exemption: Panacea for long work hours and low earnings?," Discussion papers 18002, Research Institute of Economy, Trade and Industry (RIETI).

   Cited by:

   1. MORIKAWA Masayuki, 2018. "Uncertainty over Working Schedules and Compensating Wage Differentials: From the viewpoint of labor management," Discussion papers 18015, Research Institute of Economy, Trade and Industry (RIETI).

2. Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2015. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Working Papers 7, City University of New York Graduate Center, Ph.D. Program in Economics.
   • Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2019. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Journal of Human Capital, University of Chicago Press, vol. 13(2), pages 260-292.

   Cited by:

   1. Julen Esteban‐Pretel & Junichi Fujimoto, 2022. "How do marital formation and dissolution differ across employment statuses? Analysis of Japanese non‐regular employees," Pacific Economic Review, Wiley Blackwell, vol. 27(5), pages 425-461, December.
   2. Mustafa Coban, 2021. "rbprobit: Recursive bivariate probit estimation and decomposition of marginal effects," London Stata Conference 2021 20, Stata Users Group.
      • Mustafa Coban, 2022. "rbiprobit: Recursive bivariate probit estimation and decomposition of marginal effects," Italian Stata Users' Group Meetings 2022 08, Stata Users Group.
      • Mustafa Coban, 2021. "rbprobit: Recursive bivariate probit estimation and decomposition of marginal effects," 2021 Stata Conference 21, Stata Users Group.
   3. Abayomi Samuel Oyekale, 2023. "Effect of Health Insurance Uptake on Hesitancy toward COVID-19 Vaccines in Nigeria: A Recursive Bivariate Probit and Decomposition Estimation," IJERPH, MDPI, vol. 20(3), pages 1-16, January.
   4. Abe, Yukiko, 2016. "On the convergence in female participation rates," Discussion paper series. A 301, Graduate School of Economics and Business Administration, Hokkaido University.
   5. Yukiko Abe, 2016. "On the convergence in female participation rates," ERSA conference papers ersa16p473, European Regional Science Association.
   6. Mustafa Coban, 2022. "rbicopula: Recursive bivariate copula estimation and decomposition of marginal effects," 2022 Stata Conference 04, Stata Users Group.
   7. Abe, Yukiko, 2018. "Effects of demographic compositional changes on the convergence of female participation rates," Journal of the Japanese and International Economies, Elsevier, vol. 48(C), pages 97-104.

3. Vijverberg, Wim P. & Hasebe, Takuya, 2015. "GTL Regression: A Linear Model with Skewed and Thick-Tailed Disturbances," IZA Discussion Papers 8898, Institute of Labor Economics (IZA).

   Cited by:

   1. Hasebe, Takuya & Vijverberg, Wim P., 2012. "A Flexible Sample Selection Model: A GTL-Copula Approach," IZA Discussion Papers 7003, Institute of Labor Economics (IZA).

4. Hasebe, Takuya & Vijverberg, Wim P., 2012. "A Flexible Sample Selection Model: A GTL-Copula Approach," IZA Discussion Papers 7003, Institute of Labor Economics (IZA).

   Cited by:

   1. Pablo Mitnik & David Grusky, 2018. "The Intergenerational Elasticity of What? The Case for Redefining the Workhorse Measure of Economic Mobility," Working Papers 2018-043, Human Capital and Economic Opportunity Working Group.
   2. Pigini Claudia, 2015. "Bivariate Non-Normality in the Sample Selection Model," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 1-22, January.
   3. Juliana Araujo & Povilas Lastauskas & Chris Papageorgiou, 2015. "Evolution of Bilateral Capital Flows to Developing Countries at Intensive and Extensive Margins," Cambridge Working Papers in Economics 1502, Faculty of Economics, University of Cambridge.
      • Juliana D. Araujo & Povilas Lastauskas & Chris Papageorgiou, 2017. "Evolution of Bilateral Capital Flows to Developing Countries at Intensive and Extensive Margins," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(7), pages 1517-1554, October.
      • Juliana Araujo & Povilas Lastauskas & Chris Papageorgiou, 2016. "Evolution of Bilateral Capital Flows to Developing Countries at Intensive and Extensive Margins," Bank of Lithuania Working Paper Series 37, Bank of Lithuania.
   4. Marra, Giampiero & Wyszynski, Karol, 2016. "Semi-parametric copula sample selection models for count responses," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 110-129.
   5. Karol Wyszynski & Giampiero Marra, 2018. "Sample selection models for count data in R," Computational Statistics, Springer, vol. 33(3), pages 1385-1412, September.
   6. Wojtyś, Magorzata & Marra, Giampiero & Radice, Rosalba, 2016. "Copula Regression Spline Sample Selection Models: The R Package SemiParSampleSel," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 71(i06).

Articles

1. Takuya Hasebe, 2020. "Endogenous switching regression model and treatment effects of count-data outcome," Stata Journal, StataCorp LP, vol. 20(3), pages 627-646, September.

   Cited by:

   1. Mbalenhle Gwacela & Mjabuliseni Simon Cleopas Ngidi & Simphiwe Innocentia Hlatshwayo & Temitope Oluwaseun Ojo, 2024. "Analysis of the Contribution of Home Gardens to Household Food Security in Limpopo Province, South Africa," Sustainability, MDPI, vol. 16(6), pages 1-13, March.
   2. Serrano-Alarcón, Manuel & Hernández-Pizarro, Helena & López-Casasnovas, Guillem & Nicodemo, Catia, 2022. "Effects of long-term care benefits on healthcare utilization in Catalonia," Journal of Health Economics, Elsevier, vol. 84(C).
   3. Jan Willem Nijenhuis, 2021. "Estimation of ordered probit model with endogenous switching between two latent regimes," 2021 Stata Conference 22, Stata Users Group.
   4. Wanglin Ma & Puneet Vatsa & Hongyun Zheng & Yanzhi Guo, 2022. "Does online food shopping boost dietary diversity? Application of an endogenous switching model with a count outcome variable," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-19, December.

2. Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2019. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Journal of Human Capital, University of Chicago Press, vol. 13(2), pages 260-292.
   • Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2015. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Working Papers 7, City University of New York Graduate Center, Ph.D. Program in Economics.
   See citations under working paper version above.
3. Takuya Hasebe, 2018. "Treatment effect estimators for count data models," Health Economics, John Wiley & Sons, Ltd., vol. 27(11), pages 1868-1873, November.

   Cited by:

   1. Mgendi, By George & Mao, Shiping & Qiao, Fangbin, 2022. "Does agricultural training and demonstration matter in technology adoption? The empirical evidence from small rice farmers in Tanzania," Technology in Society, Elsevier, vol. 70(C).
   2. Jan Willem Nijenhuis, 2021. "Estimation of ordered probit model with endogenous switching between two latent regimes," 2021 Stata Conference 22, Stata Users Group.

4. Hasebe, Takuya & Sakai, Tadashi, 2018. "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, Elsevier, vol. 48(C), pages 79-89.

   Cited by:

   1. Krzysztof Nowacki & Beata Oleksiak & Karolina Łakomy & Teresa Lis, 2021. "Accident Risk among People Employed in Poland—A Retrospective Cohort Study," Energies, MDPI, vol. 14(6), pages 1-11, March.
   2. Jérémie Tuganishuri & Sang-Guk Yum & Manik Das Adhikari & Tae-Keun Oh, 2023. "Analysis of the Severity and Cause and Effect of Occupational Accidents in South Korea," Sustainability, MDPI, vol. 15(20), pages 1-18, October.
   3. Ralf Dethlefsen & Luisa Orlik & Martin Müller & Aristomenis K. Exadaktylos & Stefan M. Scholz & Jolanta Klukowska-Rötzler & Mairi Ziaka, 2022. "Work-Related Injuries among Insured Construction Workers Presenting to a Swiss Adult Emergency Department: A Retrospective Study (2016–2020)," IJERPH, MDPI, vol. 19(18), pages 1-16, September.
   4. María del Carmen Rey-Merchán & Jesús M. Gómez-de-Gabriel & Antonio López-Arquillos & Sang D. Choi, 2021. "Analysis of Falls from Height Variables in Occupational Accidents," IJERPH, MDPI, vol. 18(24), pages 1-13, December.

5. Takuya Hasebe, 2013. "Copula-based maximum-likelihood estimation of sample-selection models," Stata Journal, StataCorp LP, vol. 13(3), pages 547-573, September.

   Cited by:

   1. Longden, Thomas & Wong, Chun Yee & Haywood, Philip & Hall, Jane & van Gool, Kees, 2018. "The prevalence of persistence and related health status: An analysis of persistently high healthcare costs in the short term and medium term," Social Science & Medicine, Elsevier, vol. 211(C), pages 147-156.
   2. Cheng, T. C. & Trivedi, P. K., 2014. "Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the MABEL Survey," Health, Econometrics and Data Group (HEDG) Working Papers 14/04, HEDG, c/o Department of Economics, University of York.
      • Terence C. Cheng & Pravin K. Trivedi, 2014. "Attrition Bias in Panel Data: A Sheep in Wolf’s Clothing? A Case Study Based on the MABEL Survey," Melbourne Institute Working Paper Series wp2014n14, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
      • Terence C. Cheng & Pravin K. Trivedi, 2015. "Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1101-1117, September.
   3. Dragana Radicic & Geoffrey Pugh & Hugo Hollanders & René Wintjes & Jon Fairburn, 2016. "The impact of innovation support programs on small and medium enterprises innovation in traditional manufacturing industries: An evaluation for seven European Union regions," Environment and Planning C, , vol. 34(8), pages 1425-1452, December.
   4. Mahamadou Roufahi Tankari, 2020. "Rainfall variability and farm households’ food insecurity in Burkina Faso: nonfarm activities as a coping strategy," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(3), pages 567-578, June.
   5. Prayer M. Rikhotso & Beatrice D. Simo-Kengne, 2022. "Dependence Structures between Sovereign Credit Default Swaps and Global Risk Factors in BRICS Countries," JRFM, MDPI, vol. 15(3), pages 1-22, February.
   6. Gabriela Grotkowska & Leszek Wincenciak & Tomasz Gajderowicz, 2018. "Public–private wage differential in a post‐transition economy," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 26(3), pages 495-522, July.
   7. Huang, Ho-Chuan & Yeh, Chih-Chuan & Wang, Xiuhua, 2019. "Inflation targeting and output-inflation tradeoffs," Journal of International Money and Finance, Elsevier, vol. 96(C), pages 102-120.
   8. Henry Penikas, 2022. "Pass-Through of the Bank of Russia Key Rate into Deposit Rates Between 2020 and 2022," Russian Journal of Money and Finance, Bank of Russia, vol. 81(2), pages 20-48, June.
   9. Cao, Yangzhe & Swallow, Brent & Qiu, Feng, 2021. "Identifying the effects of a land-use policy on willingness to pay for open space using an endogenous switching regression model," Land Use Policy, Elsevier, vol. 102(C).
   10. Brandão, Lucas G.L. & Ehrl, Philipp, 2022. "The impact of transmission auctions on Brazilian electric power companies," Utilities Policy, Elsevier, vol. 78(C).
   11. Radicic, Dragana, 2019. "National and international R&D support programmes and technology scouting in European small and medium enterprises (SMEs)," LEAF Working Paper Series 19-05, University of Lincoln, Lincoln International Business School, Lincoln Economics and Finance Research Group (LEAF).
   12. Lin, Zhenguo & Liu, Yingchun & Xie, Jia, 2021. "Banking deregulation and homeownership," Journal of Housing Economics, Elsevier, vol. 52(C).
   13. Sukono & Riza Andrian Ibrahim & Moch Panji Agung Saputra & Yuyun Hidayat & Hafizan Juahir & Igif Gimin Prihanto & Nurfadhlina Binti Abdul Halim, 2022. "Modeling Multiple-Event Catastrophe Bond Prices Involving the Trigger Event Correlation, Interest, and Inflation Rates," Mathematics, MDPI, vol. 10(24), pages 1-18, December.
   14. Temitayo A. Adeyemo & Victor O. Okoruwa, 2018. "Value Addition and Productivity Differentials in the Nigerian Cassava System," Sustainability, MDPI, vol. 10(12), pages 1-22, December.

6. Hasebe, Takuya, 2013. "Marginal effects of a bivariate binary choice model," Economics Letters, Elsevier, vol. 121(2), pages 298-301.

   Cited by:

   1. Mustafa Coban, 2021. "rbprobit: Recursive bivariate probit estimation and decomposition of marginal effects," London Stata Conference 2021 20, Stata Users Group.
      • Mustafa Coban, 2022. "rbiprobit: Recursive bivariate probit estimation and decomposition of marginal effects," Italian Stata Users' Group Meetings 2022 08, Stata Users Group.
      • Mustafa Coban, 2021. "rbprobit: Recursive bivariate probit estimation and decomposition of marginal effects," 2021 Stata Conference 21, Stata Users Group.
   2. Abayomi Samuel Oyekale, 2023. "Effect of Health Insurance Uptake on Hesitancy toward COVID-19 Vaccines in Nigeria: A Recursive Bivariate Probit and Decomposition Estimation," IJERPH, MDPI, vol. 20(3), pages 1-16, January.
   3. Pérez-Urdiales, María & García-Valiñas, María Ángeles, 2016. "Efficient water-using technologies and habits: A disaggregated analysis in the water sector," Ecological Economics, Elsevier, vol. 128(C), pages 117-129.
   4. Hasebe, Takuya, 2021. "On the treatment effects of a binary choice outcome model," Economics Letters, Elsevier, vol. 200(C).
   5. Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2015. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Working Papers 7, City University of New York Graduate Center, Ph.D. Program in Economics.
      • Linda N. Edwards & Takuya Hasebe & Tadashi Sakai, 2019. "Education and Marriage Decisions of Japanese Women and the Role of the Equal Employment Opportunity Act," Journal of Human Capital, University of Chicago Press, vol. 13(2), pages 260-292.
   6. Mustafa Coban, 2022. "rbicopula: Recursive bivariate copula estimation and decomposition of marginal effects," 2022 Stata Conference 04, Stata Users Group.
   7. Minghui Yin & Balekouzou Augustin & Chang Shu & Tingting Qin & Ping Yin, 2016. "Probit Models to Investigate Prevalence of Total Diagnosed and Undiagnosed Diabetes among Aged 45 Years or Older Adults in China," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-13, October.

More information

Research fields, statistics, top rankings, if available.

Statistics

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Rankings

This author is among the top 5% authors according to these criteria:

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Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 5 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-ECM: Econometrics (3) 2012-12-06 2015-03-22 2015-05-09
2. NEP-LAB: Labour Economics (2) 2011-11-01 2015-10-10
3. NEP-DEM: Demographic Economics (1) 2015-10-10
4. NEP-EDU: Education (1) 2015-10-10
5. NEP-LMA: Labor Markets - Supply, Demand, and Wages (1) 2011-11-01
6. NEP-ORE: Operations Research (1) 2015-05-09

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