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Farm machinery use and maize yields in China: an analysis accounting for selection bias and heterogeneity
Author(s) -
Zhou Xiaoshi,
Ma Wanglin,
Li Gucheng,
Qiu Huanguang
Publication year - 2020
Publication title -
australian journal of agricultural and resource economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.683
H-Index - 49
eISSN - 1467-8489
pISSN - 1364-985X
DOI - 10.1111/1467-8489.12395
Subject(s) - production (economics) , quantile regression , quantile , selection (genetic algorithm) , selection bias , economics , china , econometrics , agricultural economics , statistics , microeconomics , mathematics , geography , computer science , archaeology , artificial intelligence
Crop production in developing and emerging countries is increasingly dependent on the usage of farm machinery. However, it remains unclear whether low‐productive and high‐productive farmers benefit equally from farm machinery use. To address the research gap, this study examines the potential heterogeneous effects of farm machinery use on maize yields, using an unconditional quantile regression model and survey data from China. We employ a control function approach to address the selection bias issue associated with farm machinery use. The empirical results show that the use of farm machinery significant increases maize yields for all the selected quantiles (except for the 80th quantile); the low‐productive farmers tend to benefit more from farm machinery use relative to their high‐productive counterparts; and farm machinery use reduces the inequality and variability of maize yields.