Seasonal Migration and Feminization of Farm Management: Evidence from India

Abstract

Using gender-disaggregated data on land operations from India, this study demonstrates a relationship between seasonal or short-term migration for work and feminization of farm management. Using a nationally representative dataset covering 35,604 rural Indian households in 2013, the study identifies whether women are taking on the role of farm managers in households with short-term migrants. Results show that women are less likely than men to be decision makers on farms. This dynamic changes when there is short-term migration in the household, with a greater probability of women being decision makers on farms. These results are robust to concerns over omitted variables, endogeneity, and sample selection issues. The study highlights the importance of unpacking the feminization process to better understand the role of women as farm managers and the need for supporting this transition to ensure that women farmers realize their full potential.

HIGHLIGHTS

• Short-term migration (STM) is integral to household livelihood strategy in rural India.

• Feminization of agricultural labor is distinct from the feminization of farm management.

• In households with STM, women are more likely to be engaged with farm decisions.

• Effect of STM is stronger for spouse of household head or unmarried daughters.

• Effect of STM is weaker when there are more adult men in the household.

• Individual-level data for time use, agricultural decisions, and migration are important.

KEYWORDS:

• Feminization of agriculture
• women farm managers
• seasonal migration
• agricultural households
• operational holdings
• India

JEL Codes:

• Q1
• R2
• J1

ACKNOWLEDGMENTS

S. Chandrasekhar and Hema Swaminathan are grateful for support from the research initiative “System of Promoting Appropriate National Dynamism for Agriculture and Nutrition” (SPANDAN), which is supported by Global Development Grant Number OPP1029478 from the Bill and Melinda Gates Foundation. Soham Sahoo gratefully acknowledges funding from the Growth and Economic Opportunities for Women (GrOW) initiative, a multi-funder partnership between the UK’s Department for International Development, the Hewlett Foundation, and the International Development Research Centre. An earlier draft of this article was presented at the Poverty Reduction, Equity, and Growth Network (PEGNet) 2016 Conference on “Regional Integration for Africa’s Economic Transformation – Challenges and Opportunities” where we received useful feedback.

SUPPLEMENTAL DATA

Supplemental data for this article can be accessed at https://doi.org/10.1080/13545701.2021.1976808https://doi.org/10.1080/13545701.2021.1976808.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 For cross-country comparisons, FAO’s Gender and Land Rights Database provides information on “land-related statistics disaggregated by gender, including the share of men and women who are agricultural holders.” http://www.fao.org/gender-landrights-database/en/.

2 Since 2004–05, the spurt in short-term, internal migration has been driven by a boom in the construction industry, and a majority of workers in this sector are men (Agrawal and Chandrasekhar 2016). Estimates from NSSO’s Situation Assessment of Agricultural Households conducted in 2013 shows that nearly 83 percent of short-term migrants are men; among these, 46 percent are household heads and 49 percent are sons of the household head (Government of India 2014b).

3 Land used to cultivate different types of crops, and dominant crop dummies at the village level. The results are unchanged even after controlling for these different measures of cropping patterns in the village. While measuring these variables for each household, we exclude that household and calculate the average over all other households in the village. In fact, the main findings are unperturbed even if we include the measure at the household level ignoring possible endogeneity of these variables. These results are not shown but available on request.

4 This data is recorded for every one square kilometer area worldwide by the Operational Linescan System (OLS) flown on the Defense Meteorological Satellite Program (DMSP) satellites. We downloaded the data from National Oceanic and Atmospheric Administration (NOAA; https://ngdc.noaa.gov/eog/dmsp/downloadV4composites.html) and matched it at the district level.

5 The method is explained in the Online Appendix.

6 To show that the instruments are unlikely to have any direct effect on women’s involvement in operational holding, we include an additional control variable measuring the district-level share of women engaged in agriculture as skilled workers. This measure is from 2009 to 2010, and thus it is lagged with respect to the dependent variable but measured after the time period when the instruments are measured. If the instruments directly affect women’s involvement in agriculture, then this variable is likely to capture that effect. We find that our results are undisturbed, both in terms of magnitude and significance of the main coefficients, even with this inclusion in the model.

7 In another sensitivity analysis, we also consider the possibility that our model includes some potentially endogenous variables or “bad controls.” Some of our household-level variables, for example, land ownership patterns are likely to be affected by the presence of a short-term migrant. Therefore, we reestimate all our regressions excluding these household-level covariates. Our main findings remain unchanged.

8 When heterogeneity is analyzed with respect to a continuous variable (that is age, number of adult male members, and area of land possessed), we also include up to third order polynomial of the continuous variable and interact them with STM as well. This makes the specification flexible to account for nonlinearity in effects.

Additional information

Notes on contributors

S. Chandrasekhar

S. Chandrasekhar is Professor at Indira Gandhi Institute of Development Research, Mumbai, India. He holds a PhD in Economics from Pennsylvania State University. His broad areas of interest are rural–urban linkages and mobility of workers.

Soham Sahoo

Soham Sahoo is Assistant Professor at the Centre for Public Policy, Indian Institute of Management Bangalore. His research interest is broadly in development economics, with a focus on education, labor, and political economy. He holds a PhD in Quantitative Economics from Indian Statistical Institute, Delhi.

Hema Swaminathan

Hema Swaminathan is Associate Professor at the Centre for Public Policy, Indian Institute of Management Bangalore, India. She is broadly interested in unpacking household processes using a gender perspective, with a focus on poverty and inequality across a range of welfare outcomes. She previously worked at the International Center for Research on Women and holds a PhD in Agricultural Economics from Pennsylvania State University.