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How Productive Is Infrastructure? A New Approach and Evidence from Rural India
Author(s) -
Zhang Xiaobo,
Fan Shenggen
Publication year - 2004
Publication title -
american journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.949
H-Index - 111
eISSN - 1467-8276
pISSN - 0002-9092
DOI - 10.1111/j.0092-5853.2004.00594.x
Subject(s) - causality (physics) , productivity , investment (military) , estimation , econometrics , economics , panel data , set (abstract data type) , test (biology) , public infrastructure , macroeconomics , computer science , political science , paleontology , physics , management , quantum mechanics , politics , biology , law , programming language
There have been competing arguments about the effect of public infrastructure on productivity. Level‐based and debate‐based regressions often lead to different estimates. To help reconcile this difference, this article applies the GMM method to first test for causality to check for length of lagged relationships and the existence of reverse causality before specifying a final model and deciding the estimation procedure. This approach is illustrated using a panel data set for India. The results show that infrastructure development in India is productive, providing supporting evidence to reverse the trend of declining investment in rural infrastructure.