MAOLONG CHEN
PHONE: (734)-926-6306
Maolong Chen
Ph.D. Candidate
Agricultural, Food, and Resource Economics
Michigan State University
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M.S.
Agricultural, Food, and Resource Economics
Michigan State University
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B.S.
Mathematics
China Agricultural University
ABOUT
I have been a Ph.D. candidate since 2015 at Michigan State University (MSU) where I am studying agricultural technology adoption and transient technology use in Africa. My research is focused on explaining farmer's switching back and forth between modern and traditional technologies in order to get a better understanding of the essence of technology adoption in Africa. My areas of research also include: applied econometrics, behavioral economics, dynamic optimization, and choice experiment.
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I will be available for interviews at the 2018 AEA/ASSA meeting in Philadelphia.
RESEARCH
PUBLICATIONS
Ortega, D. L., Wang, H., & Chen, M. (2015). Emerging Markets for US Meat and Poultry in China. Choices, 30(2), 1-4.
Ortega, D. L., Chen, M., Wang, H., & Shimokawa, S. (2017) Emerging Markets for U.S. Pork in China: Experimental Evidence from Mainland and Hong Kong Consumers. Journal of Agricultural and Resource Economics, 42(2):275-290.
WORK IN PROGRESS
Understanding Transient Technology Use Among Smallholder Farmers in Africa: A Dynamic Programming Approach. (Job Market Paper)
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A dynamic programming model is developed to explain transient technology choice (switching back and forth between a traditional and a modern technology). The model is calibrated and solved numerically using a dynamic programming algorithm. Simulations of the model illustrate how changes in switching costs, relative profitability, and productivity uncertainty can lead to different patterns and duration of transient technology use.
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Estimation of Dynamic Panel Data Discrete Choice Model with Irregular Spacing
Irregularly spaced data invalidates all existing approaches to estimating nonlinear dynamic panel data models. In this paper, I develop several new estimators for dynamic panel data discrete choice model with irregular spacing and compare their finite sample performance to the application of existing estimators when ignoring irregular spacing.
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Transient Use of Hybrid Maize and Fertilizer: Panel Evidence from Kenya
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A triple-hurdle is developed to estimate determinants of transient hybrid maize and fertilizer use in Kenya. The maize production decision is broken into three stages, including hybrid participation, fertilizer participation, and fertilizer allocation. The dynamic estimators are corrected through a simulation approach to addressing the irregular spacing problem. Results provide new evidence on the relative importance of different factors in determining transient technology use in Kenyan maize production.
CONTACT ME
Thank you for reviewing my webpage. Please get in touch to find out more.
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Maolong Chen
Ph.D Candidate at MSU
Agricultural, Food, and Resource Economics