Potential impacts of Bt eggplant on economic surplus and farmers' health in India

In this article, the potential impacts of Bt eggplant technology in Indian agriculture are analyzed. Several proprietary Bt hybrids are likely to be commercialized in the near future. Based on field trial data, it is shown that the technology can significantly reduce insecticide applications and increase effective yields. Comprehensive farm-survey data are used to project farm-level effects and future adoption rates. Simulations show that the aggregate economic surplus gains of Bt hybrids could be around US$108 million per year. Consumers will capture a large share of these gains, but farmers and the innovating company will benefit too. As the company has also shared its technology with the public sector, Bt open-pollinated varieties might become available with a certain time lag. This would make the technology more accessible, especially for resource-poor farmers, entailing further improvements in welfare and distribution effects. The wider implications of the private–public technology transfer are discussed. Furthermore, the potential benefits for farmers' health resulting from reduced insecticide applications are examined, using an econometric model and a cost-of-illness approach. These benefits are worth an additional $3–4 million per year, yet they constitute only a small fraction of the technology's environmental and health externalities. More research is needed for comprehensive impact analysis.     

A model of optimal import phytosanitary inspection under capacity constraint

Growth and liberalization of world trade have increased the risks of introduction of quarantine plant pests into importing countries. Import inspection of incoming commodities is a major tool for prevention of pest introductions related to world trade, but inspection capacities are limited. This article develops a theoretical and an empirical model for the optimal allocation of inspection effort for phytosanitary inspection of imported commodities when the inspecting agency has a limited capacity. It is shown that the optimal allocation of inspection effort equalizes marginal costs of pest introduction across risky commodity pathways. The numerical illustration finds the optimal allocation of inspection effort of chrysanthemum cuttings imported in the Netherlands. The numerical results suggest that ceteris paribus , greater inspection effort should be allocated to pathways whose inspection yields a greater reduction in the expected costs of pest introduction. The numerical results also suggest that import inspection has a high marginal benefit. In particular, we found that each additional euro of the inspection capacity decreases the expected costs of pest introduction from 18 to 49 euros, depending on the initial inspection capacity.     

The effects of Mongolia's booming mining industry on its agricultural sector: A test for Dutch disease

Dutch disease occurs when currency strengthening associated with a booming sector of an economy crowds out a lagging trade‐dependent sector. In this study, a Keynesian‐style model is specified to deduce hypotheses about how increased foreign direct investment (FDI) aimed at Mongolia's mining sector affects its agricultural sector. A key finding is that while econometric results suggest the increased FDI strengthened Mongolia's currency, its adverse effect on Mongolia's trade‐sensitive agricultural sector is not sufficiently strong to cause the sector to decline. Although Dutch disease was not detected, the posited mechanism clearly is important. Specifically, when currency strengthening is ignored the reduced‐form elasticity of agricultural value‐added with respect to FDI is 2.7 times larger than when currency strengthening is taken into account (0.103 vs. 0.038). Also, FDI‐induced currency strengthening causes the Keynesian multiplier to drop from 2.40 to 2.00 and the FDI multiplier to drop from 3.05 to 1.89.     

El Niño,La Niña,and world coffee price dynamics

Coffee is produced in equatorial and subequatorial regions of the world, which are also most affected by El Niño Southern Oscillation (ENSO). ENSO events have a tendency to amplify weather conditions such as droughts or excess precipitation in the affected regions, resulting in production shortage or excess supply, subsequently impacting agricultural commodity prices. In this research we assess effects of ENSO events on world coffee price dynamics using the monthly data between March 1989 and December 2010. We employ smooth transition autoregression framework to examine nonlinear dynamics of ENSO and coffee prices, and illustrate the results of this research using generalized impulse‐response functions. We find that ENSO events indeed have short‐term impacts on coffee prices. The research findings are of interest to coffee producers and intermediaries in the coffee markets as well as researchers in the fields of environmental and development economics.     

Investigating the performance of different estimation techniques for crop yield data analysis in crop insurance applications

We investigate the performance of the ordinary least squares (OLS)‐, M‐, MM‐, and the Theil–Sen (TS)‐estimator for crop yield data analysis in crop insurance applications using Monte Carlo simulations. More specifically, the performance is assessed with respect to trend estimation, prediction of future yield levels, and the estimation of expected indemnity payments. In agreement with earlier findings, other estimators are found to be superior to OLS in simple regression problems if yield distributions are outlier contaminated and heteroscedastic. While this conclusion is also valid for subsequent applications such as yield prediction and the estimation of expected indemnity payments, the difference between the considered estimators becomes less distinct. For these applications, we find particularly the M‐estimator to be a good compromise between high‐breakdown (very robust) estimators and the very efficient OLS‐estimator. Because no regression technique dominates all others in all applications and scenarios for error term distributions, our results underline that the choice of the estimation technique should be dependent on the purpose of the crop yield data analysis. However, alternative estimators such as M‐, MM‐, and TS‐estimator can reduce (and bound) the risk of unreliable or inefficient crop yield data analysis in crop insurance applications.     

The role of health,experience, and educational attainment in agricultural production: Evidence from smallholders in Burkina Faso

We apply parametric and nonparametric methods to data from smallholders in Burkina Faso and assess the role that human capital characteristics play in the agricultural production process. Our results point to the technology‐changing nature of health, education, and experience. However, effects are rather heterogeneous. The productivity elasticity of health is much larger for households in the lowest landholding quintiles, while returns to experience are larger for households in the upper quintile. In terms of policy implications, our results suggest that productivity can be stimulated through the allocation of expenditure to social services that enhance certain types of human capital. Interventions aimed at improving the health status of households with smaller landholdings could have particularly strong welfare effects.     

Effects of scale economies and production seasonality on optimal hub locations: the case of regional fresh produce aggregation

Interest in supporting local and regional food systems is rising and food hubs have attracted considerable attention among Federal, State, and local policymakers. This study explores the problem of endogenous hub location in fresh produce value chains in the Northeastern United States. To overcome limitations in the literature, we incorporate the effects of economies of scale and production seasonality into our models. Three experimental models are designed to examine the effects of alternatively applying yearly, quarterly, and monthly data on model solutions. We explicitly assess how interactions of scale economies and seasonality influence the structure and spatial attributes of an optimal regional produce aggregation hub system. The three models generate marketed different solutions and in many respects they lead to different conclusions about developing local/regional supply chains. The monthly model allows for production seasonality and actual hub operation cycle frequency and thus leads to more efficient hub solution with rich policy implications.     

Matching food security and malnutrition indicators: evidence from Southeast Asia

This article aims to understand the relation between household food security and individual undernutrition. The multitude of indicators available raises the question which aspects of food security are captured by the respective indicator. In our analysis, we first assess the relation between the dimensions of food security and households’ socioeconomic characteristics. Second, we examine whether household indicators detect undernutrition in children. Finally, we investigate the role of individual‐specific characteristics for child undernutrition. The analysis is based on a novel data set of 1,200 rural households from Cambodia and Lao PDR, which combines household‐ and individual‐level data. We capture household food security by three indicators including a dietary diversity score, a consumption behavior measure, and an experiential measure. Individual nutrition status is measured via anthropometric indicators. Our results show that different household‐level indicators capture fundamentally different aspects of food security. Moreover, household food security fails to explain stunting for children under five. Dietary diversity indicators, however, explain underweight in children to a small extent. We call for more research on intrahousehold allocation of food and stress the implications of our research for the design and targeting of food and nutrition support programs.     

Energy‐milk price transmission at the product brand level

This article estimates the pass‐through rates between diesel fuel and retail milk prices at the product brand level. Using a random coefficient logit demand model and taking the direct and indirect impacts of energy prices, this research identifies changes in pass‐through rates before and after the great recession in 2008. Empirical results show that diesel prices significantly impacted the retail prices of milk products and are an important determinant of food price inflation. Pass‐through rates are estimated to range from 0.16 to approximately 0.60 through 2008 with an average of 0.22 for the whole period. Statistical tests indicate that pass‐through rates before June 2008 were significantly higher than after June 2008 when they dropped significantly to 0.04 to 0.17. Interestingly, private label brands have the lowest pass‐through rates, implying that compared to manufacturer brands, private label prices are more insulated from diesel price shocks.     

Do the EU countries import at the same price? The case of coffee

The establishment of the Economic and Monetary Union was expected to determine price convergence in the market of the European Union, leading to the equilibrium theorized by the law of one price. This article investigates prices convergence in the coffee market among European importers. Coffee is not only a tradable and traded good, but also one of the most valuable traded commodities. We account for different qualities of coffee in a hedonic regression model, which isolate and remove the effects of factors that might affect price dispersion. Adjusted import prices result to be significantly different between European Member States, and do not support the hypothesis of a deepening European market integration.