Dados Bibliográficos

AUTOR(ES) B. Liu , Sadia Javed , Md. Salamun Rashidin , Wang Jian
AFILIAÇÃO(ÕES) University of International Business and Economics, Beijing, China
ANO 2020
TIPO Artigo
PERIÓDICO SAGE Open
ISSN 2158-2440
E-ISSN 2158-2440
DOI 10.1177/2158244020902091
CITAÇÕES 2
ADICIONADO EM 2025-08-18
MD5 94d1df9cbf89c1e73010b01f4b0cb5c1

Resumo

Currently in Pakistan, the agricultural sector contributes up to 18.9% of the gross domestic product. As a result of modern science and technology development, the source of income for rural households is changing, and nonfarm income has become the main source. This study investigates the effects of nonfarm income on agricultural productivity in rural Pakistan. The current research data has been collected from the Pakistan Social and Living Standards Measurement Survey (PSLM) 2017–2018, a sample of rural and urban areas designed by Pakistan's Federal Bureau of Statistics. In this study, Heckman's two-step procedure is used to tackle the problems of endogeneity and selection bias. The first phase, probit regression, indicates that the accessibility of banks, motorable roads, forest, telecommunication substructure, montane grasslands, and shrublands zone affects nonfarm income. On the other hand, the second stage, ordinary least squares regression, found a negative impact of nonfarm income on per capita farm income. Furthermore, results reveal that nonfarm household income has a significant positive effect on agricultural productivity.

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