Review Reports - Sources of Total-Factor Productivity and Efficiency Changes in China’s Agriculture

Round 1

Reviewer 1 Report

Dear Author(s)

You should take into consideration the following comments:

The model provided in Eq. (7) is mi-specified. The reason is that equation (6) indicates that TFP depends on EC and TC. However, model (7) does not show this kind of dependence. In other words, EC and TC do not affect TFP in model (7).
Author(s) should justify why they are using SUR for estimating model (7).
Author(s) use panel data set. However, there is not any discussion of how the estimation process took into consideration the panel structure of the dataset employed.
Author(s) estimated four different models (see Table 2). However, they do not provide the distributional assumptions of each one of these models. In what aspect these models differ between each other?

Author Response

Dear reviewer:

Thank you very much for providing us with the opportunity to revise our manuscript. We are grateful for your insightful and helpful comments and suggestions on this manuscript. We have conducted a revision in response to your thoughtful and critical comments. The changes have been highlighted using yellow color within the manuscript. The major revision of the manuscript includes improvement of the Introduction, Research Method, Empirical Result Analysis and Conclusion and Policy Recommendation. Also, our manuscript has been revised to correct grammatical errors and improve readability by native English speaker.The specific information of the modification is in the attachment.

Thank you so much.

Author Response File: Author Response.docx

Reviewer 2 Report

Review report on “Sources of Total-Factor Productivity and Efficiency Changes in China Agriculture”

This paper measures total factor productivity (TFP) growth in the Chinese agricultural sector and assesses its determinants using a Seemingly Unrelated Regression Estimation (SURE) on the components of efficiency change (or technical efficiency?), technical change and TFP change. The paper is relevant for this journal, but would benefit from proofreading by a native speaker of the English language. I have the following major concerns:

The appropriate reference for the developers of stochastic frontier analysis are Aigner, Lovell and Schmidt (1977) and Meeusen and van Den Broeck (1977), who have independently introduced the method. Please correct the references.
The motivation for using SURE is unclear. In fact, if these z-variables determine the technical inefficiency component, a regression in the second stage will lead to biased estimates. See Wang and Schmidt (2002).
It is unclear whether the authors measure the impact on technical inefficiency or efficiency change.
The translog function used by the authors is prone to violations of the regularity conditions. The authors should report them.
Many determinants (e.g. savings, development, etc.) are clearly endogenous. Yet, the authors interpret the correlations as causal. Please refrain from doing so.

References

Aigner, D., Lovell, C. K., Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of econometrics 6: 21-37.

Meeusen, W. and van Den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International economic review: 435-444.

Wang, H.-j. and Schmidt, P. (2002). One-Step and Two-Step Estimation of the Effects of Exogenous Variables on Technical Efficiency Levels. Journal of Productivity Analysis 18: 129-144.