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Explaining gender differentials in agricultural production in Nigeria (Inglês)

This paper uses data from the General Household Survey Panel 2010/11 to analyze differences in agricultural productivity across male and female plot managers in Nigeria. The analysis utilizes the Oaxaca-Blinder decomposition method, which allows for decomposing the unconditional gender gap into (i) the portion caused by observable differences in the factors of production (endowment effect) and (ii) the unexplained portion caused by differences in returns to the same observed factors of production (structural effect). The analysis is conducted separately for the North and South regions, excluding the west of the country. The findings show that in the North, women produce 28 percent less than men after controlling for observed factors of production, while there are no significant gender differences in the South. In the decomposition results, the structural effect in the North is larger than the endowment at the mean. Although women in the North have access to less productive resources than men, the results indicate that even if given the same level of inputs, significant differences still emerge. However for the South, the decomposition results show that the endowment effect is more important than the structural effect. Access to resources explains most of the gender gap in the South and if women are given the same level of inputs as men, the gap will be minimal. The difference in the results for the North and South suggests that policy should vary by region.

Detalhes

  • Autor

    Corral Rodas,Paul Andres, Goldstein,Markus P., Siwatu,Gbemisola Oseni, Winters,Paul Conal

  • Data do documento

    2014/03/01

  • TIpo de documento

    Documento de trabalho sobre pesquisa de políticas

  • No. do relatório

    WPS6809

  • Nº do volume

    1

  • Total Volume(s)

    1

  • País

    Nigéria,

  • Região

    África,

  • Data de divulgação

    2014/02/28

  • Disclosure Status

    Disclosed

  • Nome do documento

    Explaining gender differentials in agricultural production in Nigeria

  • Palavras-chave

    Poverty & Inequality;large tracts of land;higher level of education;factor of production;global positioning system;quantity of fertilizer;difference in returns;Gender Gap;diseconomies of scale;gender difference;years of schooling;household level data;number of adults;endowment effect;assessment of gender;small scale farmer;local government area;representative data set;share of woman;analysis of gender;proportion of female;access to technology;access to land;female managers;land size;family labor;agricultural productivity;household head;cash crop;explanatory variable;negative effect;decomposition results;male farmer;fixed effect;summary statistic;productivity gap;adult female;herbicide use;extension service;labor pool;older woman;female farmer;adult male;agricultural household;blinder decomposition;agricultural production;agricultural capital;negative coefficient;fertilizer use;agriculture sector;inverse relationship;positive relationship;regression coefficient;female labor;education level;regional variation;descriptive statistic;productivity differential;production process;productive asset;input use;productive resource;average productivity;decomposition method;family day;dependency ratio;productivity differences;gender indicator;gender relation;Agricultural Extension;female adult;Higher Education;independent variable;oil palm;family size;observed value;fishing net;development policy;agriculture production;causal effect;individual characteristic;commercial agriculture;positive coefficient;old males;random error;enumeration area;tenure security;farm activity;farm activities;constant term;level analysis;natural logarithm;production gap;open access;agricultural growth;demographic structure;disaggregated level;expensive equipment;crop choice;food crop;female productivity;working population;arable land;collected information;subsistence farming;agricultural plot;nonfarm income;input price;agricultural machinery;farming system;agricultural input;geographical level;male value;sensitivity analysis;crop harvest;empirical issue;robustness check;pickup truck;urban level;small farm;interesting case;improved seed;geographical feature;total sample;expected value;water pump;production function;decomposition methodology;allocative efficiency;commercial farmer;increase productivity;populous country;poverty incidence;agricultural activity;agricultural sector;socioeconomic conditions;gender analysis;household module;rural area;individual plot;general literature;comparative advantage;biophysical characteristics;irrigation farming;empirical study;

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