Progress 07/01/19 to 09/30/19
Outputs
Target Audience:The results of research and findings with respect to agricultural finance, insurance, informational asymmetries, and environmental/disease risk policy have been communicated to a widely dispersed audience ranging from policy makers and readers of professional journals to the general public and several thousand agricultural producers through journal articles, professional meetings, producer meetings and web based reports. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?The results of research and findings with respect to agricultural finance, insurance, informational asymmetries, and environmental/disease risk policy have been communicated to a widely dispersed audience ranging from policy makers and readers of professional journals to the general public and several thousand agricultural producers through journal articles ,professional meetings, and producer meetings. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
A study examining the effects of regulatory increases in California farm labor costs was published. To estimate the impact of future California wage rate increases, an ex ante analysis of labor wage regulatory impacts was developed for the head lettuce industry. An equilibrium displacement model was utilized estimate the direction and size of changes in head lettuce quantity and prices given presumed changes in labor costs based upon California's legislated wage rate increases. The study found that a 20% increase in the wage rate for California agricultural labor will increase the retail price of head lettuce by 7.7% and will reduce the quantity demanded of head lettuce by 4.3%. Portfolio risk assessment, risk control, and optimization continues to play an important role in applied finance and risk management. While mean-variance (EV) models , with variance used as the risk metric, continue to be used in this context, more recent developments have focused upon estimating and controlling a portfolio's Value at Risk (VaR) or conditional Value at Risk (cVaR). For example the Basel II and III standards link a financial institution's reserve requirements to the estimated VaR (potentially cVaR) of the potential losses of the institution's portfolio of assets. Research was continued with respect to potential improvements in utilizing historical data to estimate 1-Day and 10-Day VaR and cVaR banking reserve requirements as suggested in Basel II and Basel III. Preliminary results with respect to out-of-sample or backtested VaR estimation look favorable. Research was also continued with respect to VaR and cVaR constrained portfolio optimization. The VaR constrained portfolio problem is considered to be NP hard. Research with respect to a "non-NP-hard" approximation to the NP-hard RC problem was conducted. Out-of-sample results indicate that non-NP-hard linear programming procedures are numerically feasible and provide accurate VaR constrained solutions. Research with respect to various aspects of crop insurance was continued. The research included the examination and modeling of potential whole farm insurance products, potential weather derivatives, and the effectiveness of current and potential insurance programs and provisions for agricultural producers and agricultural insurance companies. Research was continued with respect to utilizing data envelopment in estimating the effects of U.S. money-laundering-prevention bank regulations upon the relative competitiveness of small and rural banks in states that have legalized the use of marijuana. Results to date indicate that money-laundering-prevention regulations decrease the competitiveness of smaller and rural banks relative to larger commercial banks. A possible result is an acceleration in the rate at which smaller and rural banks are consolidated and/or acquired by larger banks. A large scale historical weather data set has been developed and maintained that contains spatially and temporally indexed daily temperature and precipitation data from over 90,000 world-wide locations including 60,000 locations in Canada and the United States for the period 1850-2020. The weather data was internally utilized in several thesis projects and have been externally utilized by the Montana State University researchers, U.S. Small Business Administration, the University of Oxford, the University of Massachusetts at Amherst, North Carolina State University, North Dakota State university, and RMA contractors in studies of the economic effects of localized drought, temperature trended events, and the effects of climatic variables upon economic activity. This data base will prove an essential component in several ongoing and future departmental research efforts. We anticipate its continued use by external research groups and agencies. Research was initiated that utilized DEA analysis in examining the relationships between weather/climatic data and the levels and variability of crop yields in various regions in the US. Research with respect to the informational content of constant dollar financial statements and performance ratios was continued. Research with respect to comparative farm level technical, financial, and economic efficiency benchmarks was continued using regional and farm level data from the northern High Plains. Data Envelopment Analysis (DEA) has been in use since the 1970's and has proven to be a practical method for assessing comparative firm performance and efficiency in a setting with multiple inputs and/or multiple outputs. DEA is widely utilized by European regulatory agencies as well as by academicians world-wide. However, since their inception, traditional DEA procedures have been legitimately criticized for their limited ability to addresses data outliers and statistical noise. Research conducted under this project led to the development of procedures for identifying quantile based efficiency metrics. Quantile based data envelope procedures were shown to address issues of statistical noise and data outliers when constructing non-parametric efficiency metrics. The Quantile Data Envelopment Analysis (QDEA) thus addressed estimation issues that have limited applied DEA analysis since its inception and should have broad applicability in numerous academic research efforts and in applied fields including European and other regulatory agencies. Procedural improvements and software for this effort were made available to the public via an R package in 2020. The methodology and software were utilized by several Ph.D. and master students at MSU as well as three other universities.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Atwood, J., and S. Shaik. (2020) "Theory and statistical properties of Quantile Data Envelopment Analysis." European Journal of Operational Research. 286:649-661.
- Type:
Journal Articles
Status:
Published
Year Published:
2020
Citation:
Hamilton, L., M. McCullough, G. Brester, and J. Atwood. (2020) "California's Wage Rate Policies and Head Lettuce Prices." Journal of Food Distribution Research. 51(2):92-110.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Shaik, S. and J. Atwood. (2019). "A Comparative Study of Alternative Approaches to Estimate Productivity." Journal of Quantitative Economics. Journal of the Indian Econometric Society. Published Springer Online. December, 2019.
- Type:
Other
Status:
Published
Year Published:
2020
Citation:
Owenhouse, J., J. Atwood, and M. Watts. (2020). "The Effects of Institutional Development Upon Costs of Country Level Private Borrowing." Department of Agricultural Economics and Economics, Montana State University. Staff Paper #2020-2
- Type:
Other
Status:
Published
Year Published:
2019
Citation:
Walden, J. and J. Atwood. (2019). "Measuring Technical Efficiency and Capacity with Data Envelopment Analysis: A foundational approach using the R programming language." (Internally reviewed by NOAA-NMFS). Department of Agricultural Economics and Economics, Montana State University. Staff Paper #2019-2.
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