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01Dissertation.pdf (1.38 MB)
ETD Abstract Container
Abstract Header
Econometric Analysis of Agricultural Policy and Practices
Author Info
Truex-Powell, Elizabeth
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=osu1408923154
Abstract Details
Year and Degree
2014, Doctor of Philosophy, Ohio State University, Agricultural, Environmental and Developmental Economics.
Abstract
This dissertation analyzes agricultural policy and practices using econometric techniques. First, time series methods are used to examine the effect of agricultural policy on US wool production and the number of shepherds. Next, the double cropping decision in the United States is analyzed using cross sectional and panel data methods. The introduction and literature review for the subsequent double cropping analysis are presented along with the means comparison between double cropping adopters and non-adopters. Cross sectional data is used to examine drivers of double cropping adoption and panel data is used to examine a the double cropping decision. Through the use of time series methods, data from 1970 to 2011 is used to assess if there is a correlation between wool policy and wool production. Upon visual inspection several of the variables, including wool production and number of ewes, appear to have a time trend. This trend is confirmed by the augmented Dickey-Fuller test. To eliminate this time trend and make the data stationary, the data is differenced and the augmented Dickey-Fuller test then confirms stationarity. Time series methods (an AR(1) model) are used to model wool production but OLS is determined appropriate for modeling the number of shepherds. Coefficient estimates for the policy variables are not found to be significant. This implies a lack of correlation between US wool policy and US wool production and suggests that wool policy could be eliminated without significantly affecting wool production. The remaining chapters of this dissertation examine double cropping practices - the planting of two crops for harvest on the same land in a given year. First, the differences between double cropping adopters and non-adopters are examined using the differences between the means of these two samples. These results indicate that double crop adopters are more likely to have a certain type of farm and have increased sales. Next, a Tobit model is used to model double cropping adoption and it is found that type of farm, sales, crop prices, and weather conditions are significant drivers to double cropping adoption. The Cragg model, which allows for a two-stage decision process, shows similar results. Finally, the Heckman model, which allows for sample selection, is presented and also shows similar results. The complete panel data set to examine adoption, however it does not account for the two-step decision process. The use of panel data does however compare changes in behavior for individual operations across a period of time. The final chapter synthesizes these results and compares and contrasts them to previous double cropping work.
Committee
Brian Roe, PhD (Advisor)
Elena Irwin, PhD (Committee Member)
Matthew Roberts, PhD (Committee Member)
Pages
115 p.
Subject Headings
Economics
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Citations
Truex-Powell, E. (2014).
Econometric Analysis of Agricultural Policy and Practices
[Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1408923154
APA Style (7th edition)
Truex-Powell, Elizabeth.
Econometric Analysis of Agricultural Policy and Practices.
2014. Ohio State University, Doctoral dissertation.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=osu1408923154.
MLA Style (8th edition)
Truex-Powell, Elizabeth. "Econometric Analysis of Agricultural Policy and Practices." Doctoral dissertation, Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1408923154
Chicago Manual of Style (17th edition)
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Document number:
osu1408923154
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This open access ETD is published by The Ohio State University and OhioLINK.