Intragenerational labor mobility in the Indian labor market

The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study....
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Autor*in:	Neog, Bhaskar Jyoti [verfasserIn] Sahoo, Bimal Kishore [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Rechteinformationen:	Open Access Namensnennung 4.0 International ; CC BY 4.0

Übergeordnetes Werk:	Enthalten in: IZA Journal of development and migration - Warsaw : Sciendo, 2017, 11(2020), 1/6 vom: Jan., Seite 1-30
Übergeordnetes Werk:	volume:11 ; year:2020 ; number:1/6 ; month:01 ; pages:1-30

Links:	Link aufrufen Link aufrufen Link aufrufen

DOI / URN:	10.2478/izajodm-2020-0006

Katalog-ID:	1737345293

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allfields	10.2478/izajodm-2020-0006 doi 10419/298678 hdl (DE-627)1737345293 (DE-599)KXP1737345293 DE-627 ger DE-627 rda eng C23 C25 J31 J46 J62 jelc Neog, Bhaskar Jyoti verfasserin (DE-588)1149927801 (DE-627)1010280295 (DE-576)49687425X aut Intragenerational labor mobility in the Indian labor market Bhaskar Jyoti Neog and Bimal Kishore Sahoo 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Sahoo, Bimal Kishore verfasserin (DE-588)1057863203 (DE-627)795348878 (DE-576)41387947X aut Enthalten in IZA Journal of development and migration Warsaw : Sciendo, 2017 11(2020), 1/6 vom: Jan., Seite 1-30 Online-Ressource (DE-627)888074735 (DE-600)2895178-5 (DE-576)488947375 2520-1786 nnns volume:11 year:2020 number:1/6 month:01 pages:1-30 https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml Verlag kostenfrei https://doi.org/10.2478/izajodm-2020-0006 Resolving-System kostenfrei https://hdl.handle.net/10419/298678 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 11 2020 1/6 1 1-30 26 01 0206 3789079014 x1z 29-10-20 2403 01 DE-LFER 3803269407 00 --%%-- --%%-- n --%%-- l01 13-11-20 2403 01 DE-LFER https://doi.org/10.2478/izajodm-2020-0006 2403 01 DE-LFER https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml 26 00 DE-206 56 mobility 26 00 DE-206 56 self-employment 26 00 DE-206 56 gender 26 00 DE-206 56 distress-driven employment 26 00 DE-206 56 transition matrices
spelling	10.2478/izajodm-2020-0006 doi 10419/298678 hdl (DE-627)1737345293 (DE-599)KXP1737345293 DE-627 ger DE-627 rda eng C23 C25 J31 J46 J62 jelc Neog, Bhaskar Jyoti verfasserin (DE-588)1149927801 (DE-627)1010280295 (DE-576)49687425X aut Intragenerational labor mobility in the Indian labor market Bhaskar Jyoti Neog and Bimal Kishore Sahoo 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Sahoo, Bimal Kishore verfasserin (DE-588)1057863203 (DE-627)795348878 (DE-576)41387947X aut Enthalten in IZA Journal of development and migration Warsaw : Sciendo, 2017 11(2020), 1/6 vom: Jan., Seite 1-30 Online-Ressource (DE-627)888074735 (DE-600)2895178-5 (DE-576)488947375 2520-1786 nnns volume:11 year:2020 number:1/6 month:01 pages:1-30 https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml Verlag kostenfrei https://doi.org/10.2478/izajodm-2020-0006 Resolving-System kostenfrei https://hdl.handle.net/10419/298678 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 11 2020 1/6 1 1-30 26 01 0206 3789079014 x1z 29-10-20 2403 01 DE-LFER 3803269407 00 --%%-- --%%-- n --%%-- l01 13-11-20 2403 01 DE-LFER https://doi.org/10.2478/izajodm-2020-0006 2403 01 DE-LFER https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml 26 00 DE-206 56 mobility 26 00 DE-206 56 self-employment 26 00 DE-206 56 gender 26 00 DE-206 56 distress-driven employment 26 00 DE-206 56 transition matrices
allfields_unstemmed	10.2478/izajodm-2020-0006 doi 10419/298678 hdl (DE-627)1737345293 (DE-599)KXP1737345293 DE-627 ger DE-627 rda eng C23 C25 J31 J46 J62 jelc Neog, Bhaskar Jyoti verfasserin (DE-588)1149927801 (DE-627)1010280295 (DE-576)49687425X aut Intragenerational labor mobility in the Indian labor market Bhaskar Jyoti Neog and Bimal Kishore Sahoo 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Sahoo, Bimal Kishore verfasserin (DE-588)1057863203 (DE-627)795348878 (DE-576)41387947X aut Enthalten in IZA Journal of development and migration Warsaw : Sciendo, 2017 11(2020), 1/6 vom: Jan., Seite 1-30 Online-Ressource (DE-627)888074735 (DE-600)2895178-5 (DE-576)488947375 2520-1786 nnns volume:11 year:2020 number:1/6 month:01 pages:1-30 https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml Verlag kostenfrei https://doi.org/10.2478/izajodm-2020-0006 Resolving-System kostenfrei https://hdl.handle.net/10419/298678 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 11 2020 1/6 1 1-30 26 01 0206 3789079014 x1z 29-10-20 2403 01 DE-LFER 3803269407 00 --%%-- --%%-- n --%%-- l01 13-11-20 2403 01 DE-LFER https://doi.org/10.2478/izajodm-2020-0006 2403 01 DE-LFER https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml 26 00 DE-206 56 mobility 26 00 DE-206 56 self-employment 26 00 DE-206 56 gender 26 00 DE-206 56 distress-driven employment 26 00 DE-206 56 transition matrices
allfieldsGer	10.2478/izajodm-2020-0006 doi 10419/298678 hdl (DE-627)1737345293 (DE-599)KXP1737345293 DE-627 ger DE-627 rda eng C23 C25 J31 J46 J62 jelc Neog, Bhaskar Jyoti verfasserin (DE-588)1149927801 (DE-627)1010280295 (DE-576)49687425X aut Intragenerational labor mobility in the Indian labor market Bhaskar Jyoti Neog and Bimal Kishore Sahoo 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier DE-206 Open Access Controlled Vocabulary for Access Rights http://purl.org/coar/access_right/c_abf2 The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions. DE-206 Namensnennung 4.0 International CC BY 4.0 cc https://creativecommons.org/licenses/by/4.0/ Sahoo, Bimal Kishore verfasserin (DE-588)1057863203 (DE-627)795348878 (DE-576)41387947X aut Enthalten in IZA Journal of development and migration Warsaw : Sciendo, 2017 11(2020), 1/6 vom: Jan., Seite 1-30 Online-Ressource (DE-627)888074735 (DE-600)2895178-5 (DE-576)488947375 2520-1786 nnns volume:11 year:2020 number:1/6 month:01 pages:1-30 https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml Verlag kostenfrei https://doi.org/10.2478/izajodm-2020-0006 Resolving-System kostenfrei https://hdl.handle.net/10419/298678 Resolving-System kostenfrei GBV_USEFLAG_U GBV_ILN_26 ISIL_DE-206 SYSFLAG_1 GBV_KXP GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2086 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 GBV_ILN_2403 GBV_ILN_2403 ISIL_DE-LFER AR 11 2020 1/6 1 1-30 26 01 0206 3789079014 x1z 29-10-20 2403 01 DE-LFER 3803269407 00 --%%-- --%%-- n --%%-- l01 13-11-20 2403 01 DE-LFER https://doi.org/10.2478/izajodm-2020-0006 2403 01 DE-LFER https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml 26 00 DE-206 56 mobility 26 00 DE-206 56 self-employment 26 00 DE-206 56 gender 26 00 DE-206 56 distress-driven employment 26 00 DE-206 56 transition matrices
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title_auth	Intragenerational labor mobility in the Indian labor market
abstract	The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions.
abstractGer	The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions.
abstract_unstemmed	The present study contributes to the limited literature on labor mobility in India using the India Human Development Survey panel data for the years 2004-2005 and 2011-2012. We use three different tools, viz., transition matrices, multinomial logistic regression, and wage regressions for this study. The results show significant mobility across sectors in the economy. Mobility patterns among workers are found to differ significantly along the lines of gender, caste, education, wealth, and family background, among others. There is a distress-driven movement of workers. Significant earnings differentials exist across paid work statuses. The paper concludes with some policy suggestions.
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title_short	Intragenerational labor mobility in the Indian labor market
url	https://content.sciendo.com/downloadpdf/journals/izajodm/11/1/article-20200006.xml https://doi.org/10.2478/izajodm-2020-0006 https://hdl.handle.net/10419/298678
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doi_str	10.2478/izajodm-2020-0006
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up_date	2024-07-04T22:01:44.938Z
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