Scholarship & Research
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Item Determinants of participation and coverage level choices in the pasture, rangeland and forage insurance program(Montana State University - Bozeman, College of Agriculture, 2020) DelCurto, Molly Jo; Chairperson, Graduate Committee: Eric BelascoDrought risk has become a primary concern for ranchers as a drought can cause substantial financial losses and have been occurring with more regularity and severity than in years past. The Pasture, Rangeland, and Forage (PRF) insurance program allows ranchers to insure their livestock grazing land against potential losses from low rainfall conditions. This program has undergone substantial changes in its availability and premium prices. We implement a linear fixed effect regression model to estimate changes in participation and coverage level choices in response to changes in factors affecting premium payments. Additionally, we analyze the impacts of future prices, previous year's earnings, and the Livestock Forage Disaster Program (LFP) on participation and coverage level choices. Our results show that increasing county base values (CBVs) has a significant negative impact on participation, suggesting the more costly the premium payment, the lower the participation. Additionally, we find evidence of memory anchoring and rational decision making in the purchasing decisions of participants. Overall, we find preliminary evidence that ranchers display demand sensitivity to changes in CBVs as well as evidence that producers follow expected utility theory in choosing the highest coverage levels, especially when coverage levels have the same subsidy rate.Item The impact of farm-level variables on federal crop insurance coverage level selection(Montana State University - Bozeman, College of Agriculture, 2019) Boyd, Mark Weiderspon; Chairperson, Graduate Committee: Eric BelascoThis thesis evaluates the significance of farm-level variables related to cash flow on coverage level selections as a potential explanation for the well-documented behavioral anomaly in producers' federal crop insurance coverage level selection choices. The current crop insurance literature appears to lack a clear explanation of why producers choose to insure at lower or less than economically optimal coverage levels. To inform this question, the relationship between liquidity factors and insurance coverage level selection are estimated empirically using linear and fixed effects models with data from the Agricultural Resource Management Survey, Risk Management Agency Summary of Business, and the Risk Management Agency Actuarial Data Master. Specifically, this research endeavors to evaluate the associations between variables related to cash flow and coverage level selection, as well as isolate the effect of premium rates on coverage selection, in order to provide evidence that constrained cash flow may be the reason for the appearance of nonutility maximization in coverage level selection. The results indicate that variables directly related to cash flow such as higher costs are associated with significant differences in coverage level selection, though the direction of the association is dependent on the type of costs, whether fixed or variable, while higher revenue higher acreage farms insure at higher coverage levels. In addition, higher premium costs are associated with lower coverage level selection, despite subsidy incentives indicating expected cash flow plays a significant role in coverage level decisions.Item Impacts of copula modeling and parametric variation on revenue policy premium rates in multiple peril crop insurance(Montana State University - Bozeman, College of Agriculture, 2015) Simonds, Seth Neil; Chairperson, Graduate Committee: Vincent H. Smith; Joseph Atwood (co-chair)Federally subsidized multiple peril crop insurance is the primary mechanism by which U.S. farmers receive public income. This study investigates the role of copula modeling in developing revenue product premium rates for multiple peril crop insurance. Simulation and empirical experiments are used to examine the viability of a ratemaking practice that relies on an assumed Normal copula. This study shows that the assumption of a copula cannot be statistically justified and that premium rates generated within copulas and between alternative copulas can diverge as a function of the marginal price and yield distributions, their relationship and the level of protection a producer elects. The current ratemaking practice does not account for the imprecision of premium rates implicit to a copula based approach. A copula selection method is proposed and examined in order to reduce premium rate imprecision resulting from copula misspecification. A non-copula based ratemaking method may better meet the overt policy objectives of multiple peril crop insurance.Item An analysis of the Arizona high school athletic insurance program(Montana State University - Bozeman, College of Education, Health & Human Development, 1970) McCormick, Michael LorenItem Farmers attitudes toward and evaluation and use of insurance for income protection on Montana wheat farms(Montana State University - Bozeman, College of Agriculture, 1960) Rodewald, Gordon E.Item State fire insurance for public school property in Montana(Montana State University - Bozeman, College of Education, Health & Human Development, 1970) Holen, Harold HamptonItem Improving the effectiveness and acceptability of the Federal crop insurance program(Montana State University - Bozeman, College of Agriculture, 1965) Myrick, Dana H.Item The effects of optional units on crop insurance indemnity payments(Montana State University - Bozeman, College of Agriculture, 2002) Kuhling, John; Chairperson, Graduate Committee: Myles Watts; Joseph Atwood (co-chair)The federal government supports numerous agricultural programs including Multiple Peril Crop Insurance (MPCI). Currently, the Risk Management Agency of the United States Department of Agriculture is legally required to determine actuarially sound premiums for MPCI. A variety of producer and production characteristics affect expected MPCI indemnity payments and thereby actuarially sound premiums. Qualifying producers may choose to split their cropland into "optional units." For the purposes of calculating crop insurance indemnity payments, the Risk Management Agency considers each optional unit a separate insurance contract. This thesis investigates whether the number of optional units a farmer is eligible to insure affects expected per acre indemnity payments. Using regression analysis and Monte Carlo simulations, this thesis statistically tests whether the number of optional units insured, separately or consolidated into a single parcel, affects expected indemnities per acre. The predictions are that the number of optional units insured separately does not affect expected indemnities per acre and that the number of optional units consolidated into a single parcel does affect expected per acre indemnities. This thesis finds a per acre premium decrease for farmers who insure available optional units as a single parcel and that the decrease in the premium be positively related to the number of optional units consolidated. In addition, this thesis finds the RMA's practice of increasing per acre premiums for farmers who separately insure two or more optional units versus the premium per acre for farmers who insure a single optional unit.Item The effects of adverse selection and effective coverage levels on crop insurance participation(Montana State University - Bozeman, College of Agriculture, 1999) Anderson, Ian T.; Chairperson, Graduate Committee: Myles Watts.The effects of crop insurance premium levels (adverse selection) and insurance coverage levels (effective coverage) on crop insurance participation are examined. A simulation of premium rates, coverage levels, and participation rates over time models the implications of random yield fluctuations using farm and county level data from Chouteau County, Montana, wheat producers. A statistical analysis measuring participation as a function of expected indemnity payments, effective coverage levels, and premium rates is conducted using cotton regional level data from the majority of the cotton producing states using a weighted ordinary least squares regression. The simulation shows that as rates increase (decrease) and coverage levels decrease (increase), participation levels decrease (increase). It also demonstrates that by indexing producers' insurable yields, participation rates stabilize. The regression results yield a significant, positive coefficient for the expected indemnity variable. However, contrary to expectations, the coefficient for effective coverage is insignificant and negative. The premium rate coefficient is insignificant and negative.Item Bank risk classification and optimal regulatory choice(Montana State University - Bozeman, College of Agriculture, 1991) Wang, Xiujun; Chairperson, Graduate Committee: Ann L. Adair.A theory of bank regulation is formed in this study by choosing an optimal classification scheme so as to minimize specific costs with assumed fixed regulatory instruments and relative costs. The likelihood of failure of a financial institution can be estimated using the financial data of that institution. Previous research studies have attempted to predict the probability of failure by using one year of data or lagged data. In these studies, a bank on a failure trajectory was counted as a nonfailure until it actually failed. The estimation was biased in favor of nonfailures, meaning that a failing bank was more likely to be classified as a survivor. This study develops a multinomial ordered logit model which uses several years of data to classify banks into a larger number of categories. Instead of just predicting banks that will fail in the following year, it can predict the probability of failure within multiple time periods. The major empirical results of this study state that the probability of failure of financial institutions can be estimated using a multinomial ordered logit model. Financial ratios based on capital, assets, total loans, nonaccruing loans, loans 90 days past due and net income were found to be significant variables in predicting failure probabilities. The results present evidence that banks can be classified into high or low risk categories which could be used by regulators to minimize the costs of regulation and bank failure. Better predictive ability would allow regulators to take action sooner to assist banks in maintaining solvency and reduce the number of failures and their associated costs.