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Land is the most valuable capital that farmers own. Land transfer can improve income of farmers through an optimal allocation of factors of production. The land transfer is not only transferring of the ownership but also transferring of the management rights. Chinese rural land system has its unique characteristics: ownership, contract, and management rights. Ownership rights are owned by collectives, farmers have contract management rights which are divided into management transfer rights and contract rights. Since 2008, farmers are provided with both land contract rights and land management transfer rights. This reform has provided farmers with financial opportunities to obtain revenues using different channels. Transferring-in land needs additional capital thereby causing demand effects, but transferring-out land allows farmers to earn income thereby causing supply effects. Land transfer also changes farmer’s agricultural investment and insurance behavior. This paper uses 2014 data from nine Chinese provinces to test farmers’ financial behavior change between land management rights transfer-out and transfer-in. Results from doubly-robust estimator with inverse probability weighting estimator, regression-adjustment, and propensity score matching indicate a significant difference of financial selection between land transfer-in farmers and land transfer-out farmers. Land market gives an unblocked transmission channel to rural financial market through mechanism innovation.

We use recently available Chinese data from 2005m1 to 2016m2 to examine the impact of monetary policy on agricultural price using a factor-augmented vector autoregressive (FAVAR) model proposed by Bernanke et al. (2005). Results show the superiority of a FAVAR model with three variables and three factors over other specifications. Impulse response functions show that both money supply and interest rate have no impact on agricultural price in the long-run (beyond 50 months). However, results indicate the considerable short-run impact of monetary policy on agricultural price. According to forecasting error variance decompositions, the interest rate could account more for the fluctuations in agricultural price than the money supply.

This study identifies factors affecting irrigation technology adoption among soybean producers in Louisiana. We conducted survey to collect information regarding irrigation practices and concerns among the soybean farmers, then estimated technology adoption model using logit framework and analyzed the impact of different factors on irrigation technology adoption. Our estimated results show that the predicted probability for adopting furrow irrigation increases as well depth and land holding size increase. Additionally, farming experience, farm revenue, well drilling cost, education, and maintenance cost have negative effect on adopting furrow irrigation technology.

We examine the changing structure of retail food stores, direct marketing (DM), and its impact on farmers’ financial performance in the United States. We use a maximum simulated likelihood estimation with multinomial treatments and continuous measures of sales to accommodate the treatment effects relative to the base (no direct marketing). Our analyses indicate that on the changing structure of retail food stores, no direct marketing (base case) outlet is the most adopted channel by direct marketers compared to direct market to consumers only (Treatment-1), direct marketing to retailers only (Treatment-2), and direct marketing to both consumers and retailers (Treatment-3). We find that farmers who have chosen no direct marketing option show better earning performance compared to the other treatments or market outlets channel options from which earning decreases by 75%, 19%, and 11%, respectively under Treatment-1, T-Treatment-2 and Treatment-3 from 2008 to 2010. Direct marketers who are more likely to choose either Treatment 1-3 option relative to no direct marketing on the basis of their unobserved characteristics, choose direct marketing less and less., Paper removed at author's request.

This paper examines the demand for natural gas and electricity in residential, commercial and industrial sectors of the Northeastern United States comprising seven states using annual state-level panel data over the period between 1997and 2011. It applies panel unit root and cointegration tests and then estimates the parameters using four alternative estimators: dynamic fixed effect (DFE), mean group (MG), pooled mean group (PMG) and Common correlated effect mean group (CCEMG). PMG showed better performance compared to estimators obtained from other three models. The panel unit root and cointegration tests show that the series are I (1) and variables are cointegrated. The estimated results show that long-run price elasticity for natural gas in residential, commercial and industrial sectors are -0.05, -0.96 and -0.20; and for electricity they are -0.11, 0.10 and -2.07 respectively. The corresponding long-run income elasticities are 3.05, 0.86, & 0.07 for natural gas and 0.93, 0.53 and 0.18 for electricity, respectively. The cooling degree days (CDD) and heating degree days (HDD) have positive effects on demand for electricity and natural gas in all but not for electricity in industrial sector., Paper removed at author's request.

This article argues that any analysis of the Phillips Curve without the inclusion of real interest rate may generate a misleading result as any changes in the interest rate impacts the labor capital input mix in the production process, leading to a change in the level of employment in the economy. We justify this argument by developing an empirical model which includes the real interest rate as one of the explanatory variables in addition to inflation and real wages. The model is estimated using the annual data from Canada for the period 1960 to 2004. The estimated result indicates that interest rate variable is indeed significant in explaining the Phillips Curve. A likelihood ratio test conducted suggests that exclusion of real interest rate leads to a misspecification (omitted variable) problem.

Identification of critical source areas (CSAs) helps to reduce best management practices (BMPs) adoption cost to meet the desired level of water quality in a given watershed. We used Soil and Water Assessment Tool (SWAT) to identify critical source areas within the Saline Bayou Watershed (HUC 11140208), Louisiana. SWAT model was calibrated and validated for discharge and sediment pollution. We then followed up with MAPSHED to assess the effectiveness of implementing different best management practices to reduce nutrient and sediment pollution. Optimization results show that nutrient management and agricultural land retirement can reduce most of the phosphorus runoff in the watershed at the lowest cost. Results are robust to change in parameter sensitivity and alternative weather (dry, normal, and wet) scenarios.

We assessed the food security situation in Bangladesh based on 2011-2012 Bangladesh Integrated Household Survey data using two commonly measured indicators: Food Consumption Score (FCS) and Household Hunger Scale (HHS). Results obtained from ordered probit regression models indicated that remittances play an important role to improve the food security of a household. Other significant variables in the model were wage earn outside of farm, male operated household, remittance, and literacy. Increasing income from other than the agriculture sector significantly raises the probability of a household being food secure. Government should make the agriculture sector strong and provide employment opportunities for households to work outside of the farm.

We conducted biophysical simulations using MAPSHED to determine the effects of adopting best management practices to reduce nutrients and sediment in a watershed dominated by row crop agriculture and poultry production. Reduction of three water pollutants nitrogen, phosphorus and sediment from adopting different BMPs are used in the cost reducing optimization model. We considered three weather scenarios (dry, normal and wet) and various levels of BMP parameter efficiencies. The nutrient management plan and vegetative buffer are the dominant cost-effective BMPs in the normal and wet weather conditions. In the dry weather scenario, vegetative buffer and stream-bank stabilization are the most cost effective BMPs. The cost of per kilogram of phosphorus reduction ranges from $10 to $40 depending on levels of desired phosphorus level reduction and efficiency parameters used in the model. It is costly to reduce phosphorus in a dry weather scenario perhaps because runoff is minimal and total costs associated with BMPs do not get distributed much on a per unit effluent basis.

We analyzed data collected from face to face interviews of farmers in East Chitwan, Nepal to understand the factors affecting the intensity of improved agriculture technologies adoption. We used parametric and nonparametric instrument variable count data models. Results from the Poisson Quasi Likelihood model indicated the positive role of remittance payment on agricultural technology adoption, consistent with the results from the nonparametric model. Additionally, the following variables have a positive impact on technology adoption in the nonparametric model: landholding size and number of animals.

We examine the relationship between income and water pollutants using country-level global water quality data over the period 1980 to 2012. We include civil liberties and political rights in addition to income as explanatory variables. We use recent advances in econometric techniques to address the inclusion of continuous and discrete variables in nonparametric instrumental variable regression models. Results indicate an inverted U-shape relationship between income and pollution for one pollutant (lead) and a cubic shape for three pollutants (nickel, mercury and arsenic). In general, we find that improved civil liberties and political rights are correlated with better water quality. By estimating a nonparametric relationship between political variables and pollution and by accounting for the categorical nature of the political variables, we are able to detect a nonlinear relationship between political variables and pollution, which for some pollutants is an inverted U-shaped curve.

Amenities at recreation sites are important not only to maintain healthy life of recreation sites, but also to provide visitors greater inspiration to visit these sites. Hence, people place importance on site amenities, based on the activities they participated in. Using freshwater-based recreation data from a national survey and employing spectral analysis and rank ordered logit model, we found that closeness and size were the two most important qualities. Further, we found that recreationalist boaters were more likely to place importance on closeness; swimmers, recreationalist boaters, and picnickers were more likely to place importance on water-quality; and recreationalist fishermen and bird/nature viewers were more likely to place importance on wildlife, while participating in freshwater-based recreations. Freshwater recreation managers may benefit from the findings as our results offer guidance in understanding what kind of attributes to manage as well as improve to meet the needs of various types of user groups.

SAEA 2014 Annual Meetings Selected papers, posters, and organized symposia abstracts are posted at: Papers: http://www.saea.org/wp-content/uploads/2014/05/papabs14.pdf Posters: http://www.saea.org/wp-content/uploads/2014/05/postab14.pdf Symposia: http://www.saea.org/wp-content/uploads/2014/01/invite2014.pdf For citation purposes: Authors. ‘‘Title.’’ Journal of Agricultural and Applied Economics. Abstract 46(2014):393.

This article examines what differentiates "socially responsible" farmers (i.e., those who rank environmental benefits higher than profit, based on a Likert style ranking) from farmers who make decisions based solely on financial criteria. A proportional odds model (POM) is proposed to estimate the factors affecting the degree of social responsibility on the technology adoption. The marginal effects indicate that the participation in agricultural easement programs, the perceived importance of precision farming (PF) in the future, as well as the perceived improvement in environmental quality following the precision technologies’ use, all positively influence the decision to adopt for environmental reasons. In contrast, educational attainment and use of University Publications to acquire information about precision agriculture have a positive impact on adoption based on profit motives. These results suggest that there may be a need for further technical advice and information from Extension focusing on environmental benefits of precision agriculture.

Market channel alternatives that include garden centers, landscapers, mass merchandisers and re-wholesalers have contributed to the growth of ornamental crops sales in the United States (U. S.). The homogenous subpopulation of the U.S. nursery producer was clustered using mixture of export method and found that there exist four homogenous group of Nursery Producer. The impact of growers’ business characteristics on shares of sales to these channels by firm size was estimated using multivariate fractional regression and nonparametric model. Important explanatory variables were regions of the U.S., sales of plant groups, kinds of contract sales, and promotional expenses, and their effect varies by cluster. We also found that in some cases nonparametric estimation procedure is better than parametric estimates.