Gender and agricultural Productivity: Econometric evidence from Malawi, Tanzania, and Uganda

[1]  B. Bravo‐Ureta,et al.  Gender and Productivity Differentials in Smallholder Groundnut Farming in Malawi: Accounting for Technology Differences , 2021, The Journal of Development Studies.

[2]  N. Phiri,et al.  Gender-differentiated impacts of plant clinics on maize productivity and food security: Evidence from Zambia , 2021 .

[3]  G. Stoeglehner,et al.  Reducing gender inequalities through land titling? The case of Gozamin Woreda , 2021 .

[4]  F. Thorne,et al.  Analyzing the Impact of Subsidies on Beef Production Efficiency in Selected European Union Countries. A Stochastic Metafrontier Approach , 2021 .

[5]  A. Hill,et al.  Peers in the Field: The Role of Ability and Gender in Peer Effects among Agricultural Workers , 2021 .

[6]  K. Deininger,et al.  Investment Impacts of Gendered Land Rights in Customary Tenure Systems: Substantive and Methodological Insights from Malawi , 2021, Policy Research Working Papers.

[7]  R. Meinzen-Dick,et al.  Women’s empowerment and gender equality in South Asian agriculture: Measuring progress using the project-level Women’s Empowerment in Agriculture Index (pro-WEAI) in Bangladesh and India , 2021, World development.

[8]  B. Bravo‐Ureta,et al.  Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis , 2020 .

[9]  Robert Cull,et al.  The Role of Gender in Agent Banking: Evidence from the Democratic Republic of Congo , 2020, Policy Research Working Papers.

[10]  C. Doss,et al.  Spousal Concordance in Joint and Separate Households: Survey Evidence from Nepal , 2020, World Development.

[11]  A. Agrawal,et al.  Capital, labor, and gender: the consequences of large-scale land transactions on household labor allocation , 2020, The Journal of Peasant Studies.

[12]  Jikun Huang,et al.  Technical Efficiency of Bacillus thuringiensis Cotton in China: Results from Household Surveys , 2020, Economic Development and Cultural Change.

[13]  Gayatri B. Koolwal,et al.  Getting the (Gender-Disaggregated) Lay of the Land : Impact of Survey Respondent Selection on Measuring Land Ownership and Rights , 2020 .

[14]  Rui Benfica,et al.  Does relative deprivation induce migration? Evidence from Sub‐Saharan Africa , 2020 .

[15]  Nicholas E. Rada,et al.  Evaluating Agricultural Productivity and Policy in Russia , 2020, Journal of Agricultural Economics.

[16]  Kanika Mahajan.  Back to the plough: Women managers and farm productivity in India , 2019 .

[17]  G. Karagiannis,et al.  Stochastic frontier models with correlated effects , 2019, Journal of Productivity Analysis.

[18]  B. Bravo‐Ureta,et al.  Examining irrigation productivity in U.S. agriculture using a single-factor approach , 2019, Journal of Productivity Analysis.

[19]  Nicholas E. Rada,et al.  Assessing farm performance by size in Malawi, Tanzania, and Uganda , 2019, Food Policy.

[20]  C. O'Donnell,et al.  Decomposing agricultural productivity growth using a random-parameters stochastic production frontier , 2018, Empirical Economics.

[21]  Nicholas E. Rada,et al.  Evaluating research and education performance in Indian agricultural development , 2018 .

[22]  L. Liverpool‐Tasie,et al.  Land Markets and Land Access Among Female-Headed Households in Northwestern Tanzania , 2017 .

[23]  M. Rosenzweig,et al.  Are There Too Many Farms in the World? Labor Market Transaction Costs, Machine Capacities, and Optimal Farm Size , 2017, Journal of Political Economy.

[24]  B. Bravo‐Ureta,et al.  Agricultural productivity in Latin America and the Caribbean in the presence of unobserved heterogeneity and climatic effects , 2017, Climatic Change.

[25]  S. Akter,et al.  Women's empowerment and gender equity in agriculture: A different perspective from Southeast Asia , 2017 .

[26]  A. Mishra,et al.  Gender differentials in farming efficiency and profits: The case of rice production in the Philippines , 2017 .

[27]  Wenkai Sun,et al.  Gender differences in performance-based pay: Evidence from a Chinese University , 2016 .

[28]  Christopher J. O'Donnell,et al.  Using information about technologies, markets and firm behaviour to decompose a proper productivity index , 2016 .

[29]  Abdoul G. Sam,et al.  Does Women’s Land Ownership Promote Their Empowerment? Empirical Evidence from Nepal , 2016 .

[30]  M. Maertens,et al.  Agricultural extension in Eastern Democratic Republic of Congo: Does gender matter? , 2016 .

[31]  Jeffrey M. Riedinger,et al.  Migration, local off-farm employment, and agricultural production efficiency: evidence from China , 2015, Journal of Productivity Analysis.

[32]  Amparo Palacios-López,et al.  The Gender Gap in Agricultural Productivity: The Role of Market Imperfections , 2015 .

[33]  L. Christiaensen,et al.  How much of the labor in African agriculture is provided by women? , 2015, Food policy.

[34]  E. Snowberg,et al.  Loss Attitudes in the U.S. Population: Evidence from Dynamically Optimized Sequential Experimentation (Dose) , 2015 .

[35]  C. Carletto,et al.  Gender and agriculture in sub‐Saharan Africa: introduction to the special issue , 2015 .

[36]  V. Slavchevska.  Gender differences in agricultural productivity: the case of Tanzania , 2015 .

[37]  P. Winters,et al.  Gender and agricultural productivity: implications of the Farm Input Subsidy Program in Malawi , 2015 .

[38]  Kolawole Ogundari.  The Paradigm of Agricultural Efficiency and its Implication on Food Security in Africa: What Does Meta-analysis Reveal?☆ , 2014 .

[39]  B. Shiferaw,et al.  Are there systematic gender differences in the adoption of sustainable agricultural intensification practices? Evidence from Kenya , 2014 .

[40]  Cliff C. J. Huang,et al.  A new approach to estimating the metafrontier production function based on a stochastic frontier framework , 2014 .

[41]  Peter B. R. Hazell,et al.  New Directions for Smallholder Agriculture , 2014 .

[42]  Markus Goldstein,et al.  Explaining Gender Differentials in Agricultural Production in Nigeria , 2014 .

[43]  Nidhiya Menon,et al.  Women’s Land Rights and Children’s Human Capital in Vietnam , 2014 .

[44]  K. Imai,et al.  Covariate balancing propensity score , 2014 .

[45]  Markus Goldstein,et al.  Decomposition of Gender Differentials in Agricultural Productivity in Ethiopia , 2014 .

[46]  Ariel Linden,et al.  Using balance statistics to determine the optimal number of controls in matching studies. , 2013, Journal of evaluation in clinical practice.

[47]  S. Ogutu,et al.  Impact of Information and Communication Technology-Based Market Information Services on Smallholder Farm Input Use and Productivity: The Case of Kenya , 2013 .

[48]  Markus Goldstein,et al.  Caught in a Productivity Trap: A Distributional Perspective on Gender Differences in Malawian Agriculture , 2013 .

[49]  Markus Goldstein,et al.  Gender and Agriculture: Inefficiencies, Segregation, and Low Productivity Traps , 2013 .

[50]  WorldBank.  World development report 2012 Gender equality and development , 2012 .

[51]  Federico Belotti,et al.  Stochastic Frontier Analysis using Stata , 2012 .

[52]  C. O'Donnell,et al.  Nonparametric Estimates of the Components of Productivity and Profitability Change in U.S. Agriculture , 2012 .

[53]  C. Carletto,et al.  Fact or Artefact: The Impact of Measurement Errors on the Farm Size - Productivity Relationship , 2011 .

[54]  E. Nkonya,et al.  Understanding the Complexities Surrounding Gender Differences in Agricultural Productivity in Nigeria and Uganda , 2011 .

[55]  Wang-Sheng Lee.  Propensity score matching and variations on the balancing test , 2011, Empirical Economics.

[56]  P. Austin.  An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies , 2011, Multivariate behavioral research.

[57]  P. Adegbola,et al.  Gender discrimination and its impact on income, productivity, and technical efficiency: evidence from Benin , 2010 .

[58]  Elizabeth A Stuart,et al.  Matching methods for causal inference: A review and a look forward. , 2010, Statistical science : a review journal of the Institute of Mathematical Statistics.

[59]  C. Alexander,et al.  Technology Adoption and Technical Efficiency: Organic and Conventional Dairy Farms in the United States , 2010 .

[60]  P. Austin.  Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples , 2009, Statistics in medicine.

[61]  C. Barrett,et al.  Reconsidering Conventional Explanations of the Inverse Productivity-Size Relationship , 2009 .

[62]  B. Shiferaw,et al.  Market Imperfections and Land Productivity in the Ethiopian Highlands , 2008 .

[63]  A. Alene,et al.  Economic Efficiency and Supply Response of Women as Farm Managers: Comparative Evidence from Western Kenya , 2008 .

[64]  G. Battese,et al.  Metafrontier frameworks for the study of firm-level efficiencies and technology ratios , 2008 .

[65]  P. Krishnan,et al.  Poverty and productivity in female-headed households in Zimbabwe , 2007 .

[66]  J. Oladeebo,et al.  Technical Efficiency of Men and Women Upland Rice Farmers in Osun State, Nigeria , 2007 .

[67]  A. Abdulai,et al.  Estimating Technical Efficiency Under Unobserved Heterogeneity with Stochastic Frontier Models: Application to Northern German Dairy Farms , 2007 .

[68]  M. Frölich.  Propensity Score Matching without Conditional Independence Assumption - With an Application to the Gender Wage Gap in the United Kingdom , 2007 .

[69]  Gary King,et al.  Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference , 2007, Political Analysis.

[70]  Peter C Austin,et al.  A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study , 2007, Statistics in medicine.

[71]  D. Solís,et al.  Technical efficiency in farming: a meta-regression analysis , 2007 .

[72]  D. Djurdjević,et al.  Decomposition of the Gender Wage Gap Using Matching: An Application for Switzerland , 2007 .

[73]  M. Farsi,et al.  Unobserved heterogeneity in stochastic cost frontier models: an application to Swiss nursing homes , 2005 .

[74]  William H. Greene,et al.  Reconsidering heterogeneity in panel data estimators of the stochastic frontier model , 2005 .

[75]  Marco Caliendo,et al.  Some Practical Guidance for the Implementation of Propensity Score Matching , 2005, SSRN Electronic Journal.

[76]  C. Barrett,et al.  Shadow Wages, Allocative Inefficiency, and Labor Supply in Smallholder Agriculture , 2005 .

[77]  Michael Lechner,et al.  Long-Run Effects of Public Sector Sponsored Training in West Germany , 2004, SSRN Electronic Journal.

[78]  Damona Doye.  The Use of Electronic Technology in Teaching Farm Record Keeping , 2004 .

[79]  W. Greene,et al.  Efficiency Measurement in Network Industries: Application to the Swiss Railway Companies , 2004 .

[80]  G. Battese,et al.  A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies , 2004 .

[81]  Russell L. Lamb.  Inverse Productivity: Land Quality, Labor Markets, And Measurement Error , 2003 .

[82]  Christopher B. Barrett,et al.  Smallholder Technical Efficiency: Controlling for Environmental Production Conditions , 2002 .

[83]  W. Greene.  Fixed and Random Effects in Stochastic Frontier Models , 2002 .

[84]  Cheryl R. Doss,et al.  Designing Agricultural Technology for African Women Farmers: Lessons from 25 Years of Experience , 2001 .

[85]  Jeffrey A. Smith,et al.  Does Matching Overcome Lalonde's Critique of Nonexperimental Estimators? , 2000 .

[86]  M. Morris,et al.  How does gender affect the adoption of agricultural innovations? The case of improved maize technology in Ghana , 2000 .

[87]  Nick Vink,et al.  Farm size, productivity and returns to scale in agriculture revisited: a case study of wine producers in South Africa , 1998 .

[88]  James J. Heckman,et al.  Characterizing Selection Bias Using Experimental Data , 1998 .

[89]  Petra E. Todd,et al.  Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme , 1997 .

[90]  P. Peters,et al.  Against the Odds , 1997 .

[91]  A. Quisumbing.  Male-female differences in agricultural productivity: Methodological issues and empirical evidence , 1996 .

[92]  C. Udry.  Gender, Agricultural Production, and the Theory of the Household , 1996, Journal of Political Economy.

[93]  Hanan G. Jacoby.  Shadow Wages and Peasant Family Labour Supply: An Econometric Application to the Peruvian Sierra , 1993 .

[94]  G. Battese.  Frontier production functions and technical efficiency: a survey of empirical applications in agricultural economics , 1992 .

[95]  Eugene Jones,et al.  Computer Use by Ohio Commercial Farmers , 1990 .

[96]  P. Schmidt,et al.  Production Frontiers and Panel Data , 1984 .

[97]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[98]  C. Lovell,et al.  On the estimation of technical inefficiency in the stochastic frontier production function model , 1982 .

[99]  D. Aigner,et al.  P. Schmidt, 1977,?Formulation and estimation of stochastic frontier production function models,? , 1977 .

[100]  P. Bardhan.  Size, Productivity, and Returns to Scale: An Analysis of Farm-Level Data in Indian Agriculture , 1973, Journal of Political Economy.

[101]  R. Oaxaca.  Male-Female Wage Differentials in Urban Labor Markets , 1973 .

[102]  Yair Mundlak,et al.  Empirical Production Function Free of Management Bias , 1961 .

[103]  A. Alene,et al.  Gender differences in technology adoption and agricultural productivity: Evidence from Malawi , 2022, World Development.

[104]  W. Greene,et al.  Technology and Technical Efficiency Change: Evidence from a Difference in Differences Selectivity Corrected Stochastic Production Frontier Model , 2020 .

[105]  C. Doss,et al.  Methods for measuring women's empowerment , 2020 .

[106]  H. Kim,et al.  Balance diagnostics after propensity score matching. , 2019, Annals of translational medicine.

[107]  Agnes Andersson Djurfeldt,et al.  "The family farms together, the decisions, however are made by the man" -Matrilineal land tenure systems, welfare and decision making in rural Malawi , 2018 .

[108]  Katia Covarrubias,et al.  How Does the Choice of the Gender Indicator Affect the Analysis of Gender Differences in Agricultural Productivity? Evidence from Uganda , 2016 .

[109]  M. Lechner,et al.  Radius matching on the propensity score with bias adjustment: tuning parameters and finite sample behaviour , 2015 .

[110]  A. Quisumbing,et al.  A review of empirical evidence on gender differences in nonland agricultural inputs, technology, and services in developing countries , 2014 .

[111]  I. Drafor.  Rural household capacity building: Innovative approaches to ensure adoption of record keeping by farm households , 2011 .

[112]  Mohammad Alauddin,et al.  Explaining agricultural productivity growth: an international perspective , 2010 .

[113]  Harold O. Fried,et al.  The Measurement of Productive Efficiency and Productivity Growth , 2008 .

[114]  Hugo Opo.  Matching as a Tool to Decompose Wage Gaps , 2008, The Review of Economics and Statistics.

[115]  J. Heckman,et al.  The Economics and Econometrics of Active Labor Market Programs , 1999 .

[116]  Y. Mundlak.  On the Pooling of Time Series and Cross Section Data , 1978 .

[117]  A. Arslan,et al.  Farmers' Subjective Valuation of Subsistence Crops: the Case of Traditional Maize in Mexico Farmers' Subjective Valuation of Subsistence Crops: the Case of Traditional Maize in Mexico , 2022 .