Agricultural Economics & Economics
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Situated jointly within MSU's College of Agriculture and College of Letters and Sciences, our department offers a unique opportunity for students with diverse interests to learn skills in critical analysis, logical problem solving, data and policy analysis, written and oral communication, business management. We train individuals who will make a big difference in the world by applying solid critical thinking skills. Our award-winning faculty has expertise in a wide variety of fields. We conduct cutting-edge research and teach a myriad of courses.
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Item Production Risk Management for Montana Ranches: The Supplemental Federal Agricultural Disaster Programs(2014-09) Belasco, Eric J.; Smith, Vincent H.; Haynes, George W.; Johnson, James B.Montana ranchers are involved in risky enterprises and use a wide range of tools to manage risk and reduce the chances that they will suffer financial losses. They are experienced in formulating strategies for their operations and carefully develop and implement their production risk management strategies.Item Evaluation of Crop Insurance Yield Guarantees and Producer Welfare with Upward Trending Yields(2012-12) Adhikari, Subodh; Knight, T. O.; Belasco, Eric J.Actual Production History (APH) yields play a critical role in determining the coverage offered to producers by the Risk Management Agency’s yield-based crop insurance products. Using both county and individual insured unit data, we examine the impact of APH yield trends for Texas cotton and Illinois corn. Our findings indicate that biases due to using simple average APH yields when yields are trending upward reduce the expected indemnity and actuarially fair premium rate. The estimated welfare effect also varies significantly with different commonly used detrending approaches. This study demonstrates that producer welfare can be enhanced through proper treatment of yield trends in crop insurance programs.Item Using a Finite Mixture Model of Heterogeneous Households to Delineate Housing Submarkets(2012) Belasco, Eric J.; Farmer, M. C.; Lipscomb, C.We use a finite mixture model to identify latent submarkets from household demographics that estimates a separate hedonic regression equation for each submarket. The method is a relatively robust empirical tool to extract submarkets from demographic information with far less effort than suspected. This method draws from latent class models to group observations in a straightforward data-driven manner. Additionally, the unique information about each submarket is easily derived and summarized. Results are also shown to more convincingly sort submarkets than a prior study in the same area that used more comprehensive data.Item Using Quantile Regression to Measure the Differential Impact of Economic and Demographic Variables on Obesity(2012-09) Belasco, Eric J.; Chidmi, B.; Lyford, C. P.; Funtanilla, M.The fight against obesity in the U.S. has become a pressing priority for policy makers due to many undesirable outcomes including escalating health care costs, reduced quality of life and increased mortality. This analysis uses data from the 2007 Behavioral Risk Factor Surveillance System (BRFSS) to evaluate the relationship between behavioral, economic, and demographic factors with BMI while explicitly accounting for systematic heterogeneity using a quantile regression. Results suggest that the effect of exercise, smoking, occupation, and race vary by sizeable amounts from high to low BMI-quantiles. This strongly indicates that future research efforts and policy responses to obesity need to account for these differences in order to develop more effective policies.Item Yield Guarantee Determination and the Producer Welfare Benefits of Crop Insurance(2013) Adhikari, Subodh; Knight, T. O.; Belasco, Eric J.Farm-level crop insurance guarantees are based on a small sample of historical yields. Two measures enacted by Congress, yield substitution and yield floors, are intended to mitigate the erratic nature of small samples in determining yield guarantees. We examine the impact of small samples and related policy provisions on the producer welfare benefits of individual-level yield insurance. Our findings indicate that sampling variability in Actual Production History (APH) yields has the potential to reduce producer welfare and that the magnitude of this effect differs substantially across crops. The yield substitution and yield floor provisions mitigate the negative impact of sampling error but also bias guarantees upward, increasing government cost of the insurance programs.Item High Tunnels Are My Crop Insurance: An Assessment of Risk Management Tools for Small-Scale Specialty Crop Producers(2013-08) Belasco, Eric J.; Miles, C.; Wszelaki, Annette L.; Ponnaluru, S.; Galinato, S.; March, T.High tunnels are being used by specialty crop producers to enhance production yields and quality, extend growing seasons, and protect crops from extreme weather. The tunnels are unheated, plastic-covered structures under which crops are planted directly in the soil, and they provide greater environmental protection and control than open-field production. This study uses field-level experiments to evaluate high-tunnel production. The results suggest that investments in high tunnels can provide increased profits and superior protection against adverse risks relative to crop insurance.Item Determinants of delayed detection of cancers in Texas Counties in the United States of America(2012-05) Gong, Gordon; Belasco, Eric J.; Hargrave, K. A.; Lyford, C. P.; Phillips, B. U. Jr.Introduction: Previous studies have shown that delayed detection of several cancers is related to socioeconomic deprivation as measured by the Wellbeing Index (WI) in Texas, the United States of America (USA). The current study investigates whether delayed cancer detection is related to lack of health insurance, physician shortage and higher percentages of Hispanics rather than WI per se since these factors are directly related to delayed cancer detection and may confound WI. Methods: Cancer data and potential determinants of delayed cancer detection are derived from Texas Cancer Registry, Texas State Data Center, and Texas Department of State Health Services and U.S. Census Bureau. Texas cancer data from 1997 to 2003 are aggregated to calculate age-adjusted late- and early-stage cancer detection rates. The WI for each county is computed using data from the USA Census 2000. A weighted Tobit regression model is used to account for population size and censoring. The percentage of late-stage cancer cases is the dependent variable while independent variables include WI and the aforementioned potential confounders. Results: Delayed detection of breast, lung, colorectal and female genital cancers is associated with higher percentage of uninsured residents (p < 0.05). Delayed detection is also associated with physician shortage and lower percentages of Hispanics for certain cancers ceteris paribus ( p < 0.05). The percentage of late-stage cases is positively correlated with WI for lung, and prostate cancers after adjusting for confounders ( p < 0.05). Conclusions: The percentages of uninsured and Hispanic residents as well as physician supply are determinants of delayed detection for several cancers independently of WI, and vice versa. Identification of these determinants provides the evidence-base critical for decision makers to address specific issues for promoting early detection in effective cancer control.Item The Chronic Kidney Disease Model: A General Purpose Model of Disease Progression and Treatment.(2011-06) Orlando, L. A.; Belasco, Eric J.; Patel, U. D.; Matcher, D. B.Background: Chronic kidney disease (CKD) is the focus of recent national policy efforts; however, decision makers must account for multiple therapeutic options, comorbidities and complications. The objective of the Chronic Kidney Disease model is to provide guidance to decision makers. We describe this model and give an example of how it can inform clinical and policy decisions. Methods: Monte Carlo simulation of CKD natural history and treatment. Health states include myocardial infarction, stroke with and without disability, congestive heart failure, CKD stages 1-5, bone disease, dialysis, transplant and death. Each cycle is 1 month. Projections account for race, age, gender, diabetes, proteinuria, hypertension, cardiac disease, and CKD stage. Treatment strategies include hypertension control, diabetes control, use of HMG-CoA reductase inhibitors, use of angiotensin converting enzyme inhibitors, nephrology specialty care, CKD screening, and a combination of these. The model architecture is flexible permitting updates as new data become available. The primary outcome is quality adjusted life years (QALYs). Secondary outcomes include health state events and CKD progression rate. Results: The model was validated for GFR change/year -3.0 ± 1.9 vs. -1.7 ± 3.4 (in the AASK trial), and annual myocardial infarction and mortality rates 3.6 ± 0.9% and 1.6 ± 0.5% vs. 4.4% and 1.6% in the Go study. To illustrate the model's utility we estimated lifetime impact of a hypothetical treatment for primary prevention of vascular disease. As vascular risk declined, QALY improved but risk of dialysis increased. At baseline, 20% and 60% reduction: QALYs = 17.6, 18.2, and 19.0 and dialysis = 7.7%, 8.1%, and 10.4%, respectively. Conclusions: The CKD Model is a valid, general purpose model intended as a resource to inform clinical and policy decisions improving CKD care. Its value as a tool is illustrated in our example which projects a relationship between decreasing cardiac disease and increasing ESRD.Item Correlation of the Ratio of Metastatc to Non-Metastatic Cancer Cases With the Degree of Socioeconomic Deprivation Among Texas Counties(2011-02) Phillips, Billy U. Jr.; Gong, Gordon; Hargrave, Kristopher A.; Belasco, Eric J.; Lyford, Conrad P.Background: Previous studies have demonstrated that cancer registrations and hospital discharge rate are closely correlated with census data-based socioeconomic deprivation indices. We hypothesized that communities with higher degrees of socioeconomic deprivation tend to have a higher ratio of metastatic to non-metastatic cancer cases (lung, breast, prostate, female genital system, colorectal cancers or all types of cancers combined). In this study, we investigate the potential link between this ratio and the Wellbeing Index (WI) among Texas counties. Results: Cancer data in 2000 were provided by the Texas Cancer Registry, while data on the ten socioeconomic variables among the 254 Texas counties in 2000 for building the WI were obtained from U.S. Census Bureau. The ten socioeconomic status variables were subjected to the principal component analysis, and the first principal component scores were grouped into deciles for the WI (1 to 10) and the 254 Texas counties were classified into 10 corresponding groups. Weighted linear regression analyses and a Cochran-Armitage trend test were performed to determine the relationship between the ratio of age-adjusted metastatic to non-metastatic cancer incidence cases and WI. The ratios of metastatic to non-metastatic cases of female genital system cancer (r2 = 0.84, p = 0.0002), all-type cancers (r2= 0.73, p = 0.0017) and lung cancer (r2= 0.54, p = 0.0156) at diagnosis were positively correlated with WI. Conclusions: The ratios of metastatic to non-metastatic cases of all-type, female genital system and lung cancers at diagnosis were statistically correlated with socioeconomic deprivation. Potential mediators for the correlation warrant further investigation in order to reduce health disparities associated with socioeconomic inequality.Item Socioeconomic deprivation as a determinant of cancer mortality and the Hispanic paradox in Texas, US(2013-04) Gong, Gordon; Belasco, Eric J.; Markide, K.; Phillips, B. U. Jr.Introduction: We have recently reported that delayed cancer detection is associated with the Wellbeing Index (WI) for socioeconomic deprivation, lack of health insurance, physician shortage, and Hispanic ethnicity. The current study investigates whether these factors are determinants of cancer mortality in Texas, the United States of America (USA). Methods: Data for breast, colorectal, female genital system, lung, prostate, and all-type cancers are obtained from the Texas Cancer Registry. A weighted regression model for non-Hispanic whites, Hispanics, and African Americans is used with age-adjusted mortality (2004–2008 data combined) for each county as the dependent variable while independent variables include WI, percentage of the uninsured, and physician supply. Results: Higher mortality for breast, female genital system, lung, and all-type cancers is associated with higher WI among non-Hispanic whites and/or African Americans but with lower WI in Hispanics after adjusting for physician supply and percentage of the uninsured. Mortality for all the cancers studied is in the following order from high to low: African Americans, non-Hispanic whites, and Hispanics. Lung cancer mortality is particularly low in Hispanics, which is only 35% of African Americans’ mortality and 40% of non-Hispanic whites’ mortality. Conclusions: Higher degree of socioeconomic deprivation is associated with higher mortality of several cancers among non-Hispanic whites and African Americans, but with lower mortality among Hispanics in Texas. Also, mortality rates of all these cancers studied are the lowest in Hispanics. Further investigations are needed to better understand the mechanisms of the Hispanic Paradox.