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An Analysis of Selectivity in the Productivity Evaluation of Biotechnology: An Application to Corn
Author(s) -
Shi Guanming,
Chavas Jean-Paul,
Lauer Joseph,
Nolan Elizabeth
Publication year - 2013
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 - 10.1093/ajae/aas169
Subject(s) - offset (computer science) , selectivity , selection bias , yield (engineering) , microbiology and biotechnology , productivity , hybrid , economics , biology , agronomy , statistics , mathematics , computer science , biochemistry , materials science , macroeconomics , metallurgy , programming language , catalysis
We investigate selectivity bias in the evaluation of biotech hybrid productivity. The analysis is applied to experimental data on Wisconsin corn yields from 1990 to 2010. Relying on a Heckman‐like factor that accounts for selectivity, we find evidence of selection bias, indicating that some of the observed yield advantage associated with GM hybrids can be attributed to their conventional genes. We document how the rising market concentration of biotech firms has contributed to increasing selectivity bias in corn yield. The impact, however, is offset by the negative effect of the rising adoption rate of GM corn on selectivity bias.