Off-farm labor supply by farm operators and spouses: a comparison of estimation methods

This thesis studies the off-farm labor supply decision of farm operators and their spouses in the United States. The data used in this study is from the Agricultural Resource Management survey, 2006. The objective of this study is twofold. First, to identify those factors that affect off-farm labor supply of farm operators and their spouses. In particular, this study investigates the impact of human capital of farm operators and spouses, personal, family, farm and location characteristics on labor allocation for on- and off-farm work. Empirical results indicate that farm operators’ and their spouses’ human capital are positively correlated with off-farm labor supply. In addition, the number of children in a household is inversely related to a spouse’s off-farm employment. Similarly, a household’s net worth and farm size have a negative impact on off-farm labor allocation decisions by both farm operators and their spouses. Payments from government programs have a negative effect on labor allocation for non-farm work. The availability of health insurance to farm operators and their spouses from off-farm employment has a positive effect on labor supply for off-farm work. The second objective of this study is to compare results obtained from a parametric probit model and a semiparametric additive probit model of off-farm labor supply by farm operators and spouses. One of the most important aspects of semiparametric analysis is to identify smoothing or nonparametric variables in a regression model. The Blundell and Duncan (1998) approach shows that farm size is such a smoothing variable in the off-farm labor supply model. A semiparametric additive regression model identifies a few significant covariates as compared to a parametric probit model; however, the Hong and White (1995) specification test and likelihood ratio test favor a semiparametric model in this study. In particular, the graphical plots of fitted values from parametric and semiparametric models also show that a semiparametric model is preferred. The semiparametric model helps to formulate appropriate functional form of off-farm labor supply in the United States, which might be the subject of further study of this research

Environmental Kuznets Curve In Water Pollution: A Semiparametric Approach

The relationship between pollution and per capita income generally appears as an inverted U-shaped curve. This inverted U-shaped curve is known as the environmental Kuznets curve (EKC). The shape of the curve, however, is very sensitive to the data, location and pollutant considered in the analysis. Since the early 1990s, there has been an exponential growth in the number of empirical studies in this field, but many refute the inverted U-shaped nature of the curve for pollutants across different time periods and geographical regions. This has generated an increased interest in developing a more flexible functional form for model specification and estimation. Our observation is that existing EKC studies have not fully utilized the advances in semiparametric and nonparametric panel econometrics. In order to identify an appropriate functional form between environmental quality and economic growth, we surveyed recent developments in econometrics specifically related to nonparametric and semiparametric models for panel data. We proposed a seemingly unrelated partial linear model (SUPLR) to address potential correlation between pollutants. Simulation study shows that the SUPLR model performs well for our data set. We examined the EKC relationship between water quality indicators (nitrogen, phosphorous, dissolved oxygen and mercury) and income at the watershed level, using environmental quality data from 53 parishes in Louisiana. Additionally, we explored the income-pollution relationship using Global Environment Monitoring System (GEMS) data from sixty eight countries. We found that the relationship followed an inverted U-shaped curve for nitrogen and dissolved oxygen and a cubic shape for mercury. At the global level, an inverted U-shaped relationship is found for three pollutants (dissolved oxygen, fecal coliform and coliform), a cubic relationship is found for three pollutants (mercury, chemical oxygen demand and biological oxygen demand) and an L-shaped relationship is observed for two pollutants (arsenic and lead). Model specification tests suggest that a semiparametric model is better specified to study the income-pollution relationship

Test of Convergence in Agricultural Factor Productivity: A Semiparametric Approach

We tested for club convergence in U.S. agricultural total factory productivity using a sigma convergence test. We used the same club of states as used by McCunn and Huffman as well as different states within 10 clubs identified by the cluster analysis. Results showed convergence was evident only in a few club groups. Clusters group identified using a statistical method identified only converging clubs. Variables affecting total factor productivity among states were identified using parametric, semiparametric and nonparametric methods. Semiparametric and nonparametric methods gave a better fit than a parametric method as indicated by the specification test. Our results indicated that health care expenditure, public research and extension investment, and private expenditure are important variables impacting total factor productivity differences across states.Clubs, sigma convergence, cluster analysis, semiparametric and nonparametric methods, Productivity Analysis, Research Methods/ Statistical Methods,

Why Don't Farmers Adopt Precision Farming Technologies in Cotton Production?

We used the 2009 Southern Cotton Precision Farming Survey data collected from farmers in twelve U.S. states (Alabama, Arkansas, Florida, Georgia, Louisiana, Missouri, Mississippi, North Carolina, South Carolina, Tennessee, Texas, and Virginia) to understand why farmers do not adopt seemingly profitable precision farming technology. Farmers provided cost, time constraint, satisfaction with the current practice and other as reasons for not adopting precision farming technology. Results from a multinomial logit regression model indicated that manure application on field, more formal education, larger farm size, participation in conservation easement or agricultural easement generally decreases the probability of nonadoption of precision agriculture in cotton production.precision agriculture, technology adoption, multinomial logit, Crop Production/Industries, Farm Management, Research and Development/Tech Change/Emerging Technologies, C25, Q16,

An Analysis of Rank Ordered Data

Many methods are available to analyze rank ordered data. We used a spectral density method to analyze Formosan subterranean termite control options ranked by Louisiana homeowners. Respondents are asked to rank termite control options from the most preferred to the least preferred option. Spectral analysis results indicated that the most preferred termite control choice is a relatively cheap ($0.13 per square foot) option of liquid treatment.FST, rank ordered data, spectral analysis, Research Methods/ Statistical Methods,

A cross sectional study of knowledge, attitude and practices related to fixed dose combinations use among clinicians and resident doctors at a tertiary care teaching hospital in India

Background: In the year 2016, Government of India had banned 350 fixed dose combinations (FDCs) for the safety and efficacy purpose. The present study was conducted to assess the knowledge, attitude and practices of the clinicians and residents about the use of FDCs at a tertiary care hospital.Methods: A questionnaire based study was conducted at a tertiary care hospital after getting approval from institutional ethics committee. A pre-validated questionnaire comprising of 30 items was distributed to 100 participants. The questionnaire focused on the prescribing behaviour, knowledge on therapeutic efficacy, advantages and limitations of FDC use, clinician perception regarding FDC use and the strategies to improve the awareness about the regulatory updates of the marketed drugs.Results: Total 52/100 clinicians responded. Out of these, 88% prescribed FDCs in their practice, 62% prescribed FDCs only after ensuring therapeutic efficacy and 50% prescribed WHO approved FDCs. 64% were aware of the recent ban on some FDCs by DCGI. Internet was the most common source of latest updates on the regulatory status of the drug, as stated by 55% clinicians. All clinicians agreed that efforts are needed to ensure that prescribers remain up to date about the post-marketing regulatory status of the drugs.Conclusions: Even though many clinicians prescribe FDCs regularly, they appreciated the step of banning some FDCs; however, the clinicians need to be trained to update themselves regularly. The source and relevance of these updates should be taught to the undergraduate students during their training period which can be reemphasized during post graduate training period

Economic analysis of fish production using different feed types practiced in Dhanusha district, Nepal

A study on the economic analysis of fish production using different feed types practiced in Dhanusha district was conducted in 2018. Out of 600 fish farmers, sixty fish farmers(10%) from the Fish Superzone region i.e. Janakpur sub-metropolitan city, Bideh municipality, Sahidnagar municipality, Kamala municipality, Hanspur municipality, Janaknandani rural municipality and Aaurahi  rural municipality, selected using simple random sampling, were surveyed using semi-structured questionnaire. The study revealed that locally formulated mash feed was commonly used feed type in which rice bran and mustard oil cake (RB+MOC) was the principle feed ingredient. 55% of the farmers used rice bran and mustard oil cake (RB+MOC), 20% used rice bran, mustard oil cake and soybean (RB+MOC+SOB), 10% used rice bran, mustard oil cake and fish meal (RB+MOC+FM) and 15% farmers mineral and vitamin (RB+MOC+MIN/VIT) in their feed formulation. The productivity of the fish production in feed type RB+MOC+SOB (3.41±1.02) was significantly higher than other feed type.  The total variable cost per ha (5.23±2.11) was found significantly(p<0.05) higher in feed type RB+MOC+SOB. Similarly, gross margin (4.44±2.74) received by farmers of feed type RB+MOC+SOB was also significantly high(p<0.05). The Benefit: Cost (B:C) ratio of the study area was found to be 1.69, high being of feed type RB+MOC+SOB(1.84) compared to others. The feed type RB+MOC+SOB is seen as a economically profitable one in the study area because of the high productivity, profit and B:C ratio. High feed cost was the major problem followed by the unavailability of feed. Fish farming can be a profitable business in Dhanusha with large opportunity to increase the fish production with increasing protein sources in the feed used. Farmers should be provided sufficient information, trainings and be encouraged to incorporate the protein rich sources like soybean and fish meal in the feed prepared to increase the productivity and ultimately return

A prospective study on causality, severity and preventability assessment of adverse drug reactions in a tertiary care hospital in India

Background: The present study was undertaken to evaluate the incidence and pattern of adverse drug reaction (ADRs), causality, severity and preventability of ADRs.Methods: Data was collected and analyzed with the information such as patients’ demographic details, associated co-morbid conditions and detailed drug related information gathered from ADR reporting forms. World Health Organization (WHO) scale was used for assessing causality, modified Hartwig scale was used for assessing severity and modified Schumock and Thorntons scale were used for assessing preventability of ADRs. Data was analyzed using descriptive statistics.Results: Total 154 ADRs were reported in a period of one year (August 2016- July 2017). Out of 154 ADRs analyzed, 120 (77.9%) were in adults, 33 (21.4%) pediatric and 01 (0.7%) in geriatric patients. The most common ADR recorded was cutaneous reactions (43.5%) and the most common causative class of drugs for the same was found to be antimicrobials (46.7%) followed by non-steroidal anti-inflammatory drugs (15.6%). Causality assessment scale indicated 68.8% ADRs possible and 24% ADRs as probable. Severity assessment revealed that 45.5 % were mild, 50.6% moderate and 3.9% ADRs severe. Preventability assessment showed 84.4% of the cases were probably non-preventable.Conclusions: In this study it was found that, most of the ADRs were of possible category with mild to moderate severity and majority being non-preventable. Antimicrobial drugs being the most common offending drug class causing ADRs. Strategies targeting appropriate and cautious use of this class of drugs may benefit in reducing the number of ADRs and therefore the cost involved in the treatment