The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China
Abstract
This paper examines the role of individual risk attitudes in the decision to adopt a new form of agricultural biotechnology in China. I conducted a survey and a field experiment to elicit the risk preferences of Chinese farmers, who faced the decision of whether to adopt genetically modified Bt cotton a decade ago. In my analysis, I expand the measurement of risk preferences beyond expected utility theory to incorporate prospect theory. I find that farmers who are more risk averse or more loss averse adopt Bt cotton later. Farmers who overweight small probabilities adopt Bt cotton earlier.
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Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Regression Models and Life-Tables
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Advances in prospect theory: Cumulative representation of uncertainty
Tversky, A., & Kahneman, D. (1992) · Journal of Risk and Uncertainty · doi:10.1007/bf00122574 · Cited by 15,467
Adoption of Agricultural Innovations in Developing Countries: A Survey
Feder, G., Just, R. E., & Zilberman, D. (1985) · Economic Development and Cultural Change · doi:10.1086/451461 · Cited by 3,482
Learning about a New Technology: Pineapple in Ghana
Conley, T. G., & Udry, C. R. (2010) · American Economic Review · doi:10.1257/aer.100.1.35 · Cited by 2,180
Learning by doing and learning from others: Human capital and technical change in agriculture
Foster, A. D., & Rosenzweig, M. R. (1995) · Journal of Political Economy · doi:10.1086/601447 · Cited by 2,038
Recent developments in modeling preferences: Uncertainty and ambiguity
Camerer, C., & Weber, M. (1992) · Journal of Risk and Uncertainty · doi:10.1007/bf00122575 · Cited by 1,795
Does Market Experience Eliminate Market Anomalies?
List, J. A. (2003) · The Quarterly Journal of Economics · doi:10.1162/00335530360535144 · Cited by 1,183
Yield effects of genetically modified crops in developing countries
Qaim, M., & Zilberman, D. (2003) · Science · doi:10.1126/science.1080609 · Cited by 757
Cited by
Learning about a New Technology: Pineapple in Ghana
Conley, T. G., & Udry, C. R. (2010) · American Economic Review · doi:10.1257/aer.100.1.35 · Cited by 2,180
Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam
Tanaka, T., Camerer, C. F., & Nguyen, Q. (2016) · Behavioral Economics of Preferences, Choices, and Happiness · doi:10.1007/978-4-431-55402-8_1 · Cited by 731
Smallholder Participation in Contract Farming: Comparative Evidence from Five Countries
Barrett, C. B., Bachke, M. E., Bellemare, M. F., Michelson, H. C., Narayanan, S., & Walker, T. F. (2012) · World Development · doi:10.1016/j.worlddev.2011.09.006 · Cited by 730
Amygdala damage eliminates monetary loss aversion
De Martino, B., Camerer, C. F., & Adolphs, R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0910230107 · Cited by 444
Rural Women’s Access to Financial Services: Credit, Savings, and Insurance
Fletschner, D., & Kenney, L. (2014) · Gender in Agriculture · doi:10.1007/978-94-017-8616-4_8 · Cited by 258
Metadata
- Authors
- Liu, E. M.
- Venue
- The Review of Economics and Statistics
- Publisher
- MIT Press
- Published
- 2013-10-01
- Volume
- 95
- Issue
- 4
- Pages
- 1386-1403
- ISSN
- 0034-6535 (ISSN-L)
- 1530-9142
- OpenAlex
- W2102886298
- Cited by
- 584
- References
- 9
- FWCI
- 29.21
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liu, E. M. (2013). Time to Change What to Sow: Risk Preferences and Technology Adoption Decisions of Cotton Farmers in China. The Review of Economics and Statistics. https://doi.org/10.1162/rest_a_00295
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
