3,417 research outputs found
Can Education Be a Barrier to Technology Adoption?
The objective of this study is to test the widely‐held belief that the effect of education has a positive impact on technology adoption. Using 2006 Agricultural Resource Management Survey "ARMS" data, we estimate a simultaneous equations model to integrate farmers’ labor allocation decision with adoption of GM crops and precision farming. We confirm that the marginal effect of education on technology adoption is significantly larger for large farms for both GM crops and precision farming and it is unexpectedly negative for GM crops at all levels of farm size. These results suggest that formal education can be a barrier to technology adoption, especially for small scale farmers who have higher tendency to work off‐farm.Education, Technology Adoption, Off‐farm Labor Supply, Precision Farming, Genetically Modified Crops, Simultaneous Equations Model, International Development, Labor and Human Capital, Research and Development/Tech Change/Emerging Technologies, Q10, Q12,
Use of Direct Marketing Strategies by Farmers and Their Impact on Farm Business Income
Direct marketing strategies increasingly have been recognized as a viable business option in U.S. agriculture as they allow producers to receive a better price by selling products directly to consumers. The objective of this study is twofold. Using a national survey, we first estimated a zero-inflated negative binomial model to identify factors affecting the total number of direct marketing strategies adopted by farmers. Then we estimated a quantile regression model to assess the impact of the intensity of adoption of direct marketing strategies on gross cash farm income. The results show that the intensity of adoption has no significant impact on gross cash farm income and that participation in farmers markets is negatively correlated with gross cash farm income at all five quantiles estimated.direct marketing strategies, count data, gross cash income, quantile regression, Agribusiness, Agricultural Finance, Farm Management, Production Economics,
The Impact of Natural Amenity on Farmland Values: A Quantile Regression Approach
The objective of this study is to estimate the impact of natural amenity on farmland values in the contiguous United States using a quantile regression approach and data from the 2006, 2007, and 2008 Agricultural Resource Management Surveys. The contribution of this study is three-fold. First, we explicitly include variables representing natural amenity and soil characteristics of farmland. Second, we employ a quantile regression approach to examine potentially heterogeneous impacts of natural amenity and soil characteristics at different quantiles of farmland values. Third, we utilized data from a nationwide survey of farm household to examine findings in studies using regional data are consistent at a national scale. Our quantile regression analysis offers some insightful results. Natural amenity is positively correlated with farmland values and its impact is often more pronounced at a higher price range of farmland.Farmland Values, Quantile Regression, Natural Amenity, Environmental Economics and Policy, Land Economics/Use, C14, Q15, Q24,
Learning by Doing, Risk Aversion and Use of Risk Management Strategies
Using a national survey, double hurdle models are estimated to examine the impact of farmers’ risk attitude on use of production and marketing contracts. Risk averse farmers are less likely to use contracts but risk attitude does not have any significant impact on the intensity at which contracts are adopted.Risk attitude, Double hurdle model, production contracts, marketing contracts, Agribusiness, Crop Production/Industries, Farm Management, Livestock Production/Industries, Marketing, Risk and Uncertainty, Q10, Q13, D81,
Are Organic Farmers Really Better Off Than Conventional Farmers?
We employed the propensity score matching and estimated the causal effect of being certified organic crop producers on farm household income and its various components in the United States. Contrary to the standard assumption in economic analysis, certified organic farmers do not earn significantly higher household income than conventional farmers. Certified organic crop producers earn higher revenue but they incur higher production expenses. In particular, certified organic producers spend significantly more on labor expenses, insurance payments, and marketing charges than conventional farmers. The results suggest that early adopters of organic farmers have done so for non pecuniary reasons and the lack of economic incentives can be an important barrier to conversion to organic farming in the United States.organic farming, propensity score matching, nearest neighbor matching, average treatment effect, Agribusiness, Crop Production/Industries, Farm Management, Marketing, Q10, Q13, J43, C21,
AN ANALYSIS OF TAX-DEFERRED RETIREMENT SAVINGS OF FARM HOUSEHOLDS
The retiring farmer generally tries to balance the desire to keep the farm intact as a going concern with the need for a secure assets portfolio to finance retirement. This problem becomes more complex in situations where younger family members choose not to be active in the farm business. Tax-deferred savings are potentially an important component of a retirement plan and could represent a very substantial increase in tax-free assets for many individuals. This study examines the tax deferred retirement savings of farm households. The model is estimated using Agricultural Resource Management Survey (ARMS) 1999 farm-level national data and the Double-Hurdle estimation method. Results indicate that farm household's source of income, age of the farm operator, marginal tax rate, regional location, and participation in government programs are factors that significantly affect investment in tax-deferred savings.Farm Management,
Tax-Deferred Retirement Savings of Farm Households: An Empirical Investigation
This study examines factors affecting tax-deferred retirement savings among farm households. A double-hurdle model is estimated using 2003 Agricultural Resource Management Survey (ARMS) farm-level national data. Results indicate that demographic factors, total household income, off-farm work, and risk preference play important roles in retirement savings plan participation. Retirement savings increase with household size, intensity of off-farm work by farm operator and spouse, and size of farming operation. We find that the amount of retirement savings decreases with operator’s age and increases with spouse’s age, and that cash grain and dairy farmers have lower retirement savings.double-hurdle estimation, farm households, probit, retirement savings, risk preference, total household income, Agricultural Finance, Consumer/Household Economics,
An Empirical Analysis of Internet Use by U.S. Farmers
The Internet may reduce constraints on a farmerÂ’s ability to receive and manage information, regardless of where the farm is located or when the information is used. Using a count data estimation procedure, this study attempts to examine the key farm, operator, regional, and household characteristics that influence the number of Internet applications used by farm households. Findings indicate that educational level of the farm operator, farm size, farm diversification, off-farm income, off-farm investments, and regional location of the farm have a significant impact on the number of Internet applications used.computers, count data method, education, farm households, Internet applications, Farm Management,
Precautionary wealth among U.S farm households
Using a cross sectional farm-level data we find that farm households who face higher income uncertainty save more and accumulate more wealth. Precautionary savings is about 6 percent of the total farm household wealth. In addition to precautionary saving, and consistent with theory we found that the age, education, occupation, and the number of acres operated are all important factors that influence wealth accumulation by U.S farm households.Agricultural Finance, Consumer/Household Economics, Risk and Uncertainty, precautionary savings, wealth, income risk, farm households,
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