abstract: 'The study estimates marginal impacts of household specific determinants (demographic, skill, security and mobility factors) on wages earned by laborers belonging to different quantile classes in agriculture and non-agricultural sectors. The results demonstrate superiority of varying-coefficients approach (Quantile Regression) over constant-coefficient approach (OLS) in terms of robustness and wider policy implications of estimated associations between variables. Different factors affect wages differently across different quantile classes which imply that policies aiming towards improving wages shall have differential strategies for specific target group. The evidences clearly point towards a strong need to raise education level and impart technical skills to laborers for improving their income, accelerating employment diversification towards non-farm sectors and equitable development in the society. Largely, Indian labor market has been found to be informal and unorganized. The access to social security benefits bears positive association with the wages.' affiliation: 'Srivastava, SK (Corresponding Author), NITI Aayog, New Delhi, India. Balaji, S. J., ICAR Natl Inst Agr Econ \& Policy Res, New Delhi, India. Srivastava, S. K., NITI Aayog, New Delhi, India.' author: Balaji, S. J. and Srivastava, S. K. author-email: shivendraiari@gmail.com author_list: - family: Balaji given: S. J. - family: Srivastava given: S. K. da: '2023-09-28' files: [] issn: 2454-7395 journal: STATISTICS AND APPLICATIONS keywords: 'Quantile regression; Wage determination; Agriculture; Non-farm sector; India' keywords-plus: INEQUALITY language: English number: 1, SI number-of-cited-references: '17' orcid-numbers: 'Balaji, S/0000-0002-7324-4853 ' pages: 261-274 papis_id: 76fa802d12681685cdcad8080dc5b5de ref: Balaji2019interintra researcherid-numbers: 'Balaji, S/J-1864-2019 NIAP, LIBRARY ICAR/ABB-6258-2020 Srivastava, Shivendra Kumar/ABD-7503-2020' times-cited: '0' title: 'Inter and Intra Sectoral Wage Determinants in Indian Casual-Labor Market: Agricultural and Structural Change Implications' type: Article unique-id: WOS:000502090400020 usage-count-last-180-days: '1' usage-count-since-2013: '2' volume: '17' web-of-science-categories: Statistics \& Probability year: '2019'