Rice. Photo by IRRI Images.

As social and economic assessment practitioners, we do what we can with the data, methods, and information available while we conduct the specified research. These valuable—and, in most situations scarce—information assets, in conjunction with our best judgments on how to conduct the research and interpret the results of the evaluation process, have to be evaluated in terms of scientific quality, evidence sufficiency, and other measurements of completeness. From a regulatory standpoint, this judgment will have to be done or facilitated by the competent authority who will make a decision for the potential release of GE technology or for reaffirming the provisional permit for release in an ex post framework.

Finally, I find it a bit odd when a literature review (or reviewers) charges the researchers conducting the empirical work being evaluated with doing work that cannot be categorized as state-of-the-art or even with behavior that can be construed as improper, especially in those situations where the empirical work occurred during the earlier stages of adoption.

Most of the work done in South Africa and India was done at the earlier stages of the adoption process where there were data limitations and issues’ knowledge where clearly binding. In my opinion, conclusion in some literature review or commentaries in some published papers, especially those related to China, ignore the context itself of the research and perhaps reflect limitations in terms of conducting field research.

The China team at the institute CCAP lead by Jikun Huang, especially, has what is, in my opinion, one of world’s best track records in disciplinary and multi-disciplinary expertise and use of state-of-the-art methods and publications, including Science, Nature, the American Journal of Agricultural Economics, and other major journals worldwide. In fact, most of the authors in the earlier stages of the adoption process recognized in their work the many limitations of their work, and even proposed alternatives for future work assuming availability of more data over time.