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Tenure Security and Farm Efficiency Analysis Correcting for Biases from Observed and Unobserved Variables: Evidence from Benin
Author(s) -
Lawin Kotchikpa G.,
Tamini Lota D.
Publication year - 2019
Publication title -
journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.157
H-Index - 61
eISSN - 1477-9552
pISSN - 0021-857X
DOI - 10.1111/1477-9552.12275
Subject(s) - selection bias , propensity score matching , productivity , matching (statistics) , selection (genetic algorithm) , sample (material) , econometrics , economics , agriculture , statistics , mathematics , computer science , geography , economic growth , archaeology , chemistry , chromatography , artificial intelligence
We analyse the impact of land tenure security on the technical efficiency of a sample of smallholder farmers in Benin, based on an output‐oriented stochastic distance function. We use propensity score matching to correct for selection bias from observed variables. The Greene ([Greene, W., 2010]) sample selection model is used to correct for selection bias due to unobserved variables. We estimate meta‐frontiers to analyse agricultural productivity and efficiency differences between landowners and non‐owners. Our results show that non‐owners have consistently higher levels of technical efficiency and productivity.