Agricultural Economics最新文献

The Supplemental Nutrition Assistance Program (SNAP) is the nation's largest domestic food and nutrition assistance program for low-income Americans. Recent studies that examined the effect of SNAP on dietary quality focus on the average effects. Using the USDA's 2012 National Household Food Acquisition and Purchase Survey (FoodAPS) and an unconditional quantile estimator, we examine the distributional impacts of SNAP on dietary quality as measured by Healthy Eating Index-2010 (HEI-2010). To identify the differential impacts of SNAP across the distribution of dietary quality, we exploit exogenous variation in state's maximum weekly unemployment insurance benefits and state outreach spending per capita as instrumental variables. We find that SNAP has no significant impact on households’ dietary quality on average. However, for households with initially low-to-intermediate dietary quality, SNAP participation reduces their HEI scores by over 17% or more than 7 points out of a total score of 100. The negative impacts of SNAP on these HEI quantiles are mainly driven by an increased acquisition of empty calories.

This study examines how the expansion of mobile phone networks affects rural development in Mongolia. The database is a detailed household panel survey with four waves implemented in western Mongolia, spanning the 2012–2021 period, which we combine with data on mobile phone towers. Our identification strategy exploits the uneven roll-out of mobile phone networks across rural areas over time. Using a two-way fixed effects approach, we show that network expansion strongly and significantly increases total household income of pastoralist households. The effect is driven by increased income from agriculture, particularly by higher producer prices for animal byproducts, improved access to transfer income, and increased household mobility. The expansion of mobile phone networks decreases income diversification among pastoralists. Instead, households specialize in agriculture. While findings suggest that investments in telecommunication infrastructure can help rural households to sustain a livelihood in the agricultural sector, the specialization in agriculture may increase households’ vulnerability to climate change.

The adoption of advanced agricultural technologies in Sub-Saharan Africa remains disappointingly low, particularly among the millions of poor smallholders who account for most of the agricultural production. We conducted a randomized control trial in Ghana to assess the impact of easing drought-risk constraints in the agricultural credit market, by bundling joint liability agricultural loans with index insurance, on smallholder farmers’ agricultural technology adoption decisions. In the micro-insurance treatment, any index insurance payouts go directly to farmers, while in the meso-insurance treatment, payouts are issued to banks to be used to expunge farmers’ debts. We find evidence that bundling joint liability lending with micro-insurance increases adoption of fertilizer.

This article investigates the causal effect of farm participation in two Austrian agri-environmental schemes (AES), Immergrün (ground cover) and Zwischenfrucht (catch cropping), on fertilizer and plant protection expenditures in the 2014 programming period. Combining European Farm Accountancy Data Network data with information on scheme participation from administrative control data offers identifying farm participation in specific schemes targeted at reducing input intensity. Given the overall small sample, we maximized the utilizable sample size by combining difference-in-difference and kernel matching with automated bandwidth selection. To address the remaining post-matching covariate imbalances, we used double machine learning (DML) techniques for a guided selection of potential confounding covariates. Our results suggest that, given the available sample, we cannot substantiate moderate effects of AES participation, and that guided covariate selection by DML offers no gain over non-guided covariate selection for the small sample. Our results underline the need to increase the number of farms and the duration in available farm panels to substantiate future counterfactual-based evaluations of policy.

The economic growth convergence between advanced nations and the rest of the world has been found to reduce global income inequality. However, less is known about convergence within nations, especially in developing economies with substantial regional heterogeneities. Using the neoclassical framework, this study tests for farm income convergence in India, where agriculture employs over 200 million workers. Household farm income is estimated in 599 districts using three pan-India situation assessment surveys (2003, 2013, and 2019). The conditional convergence model—augmented to capture spatial spillovers—shows farm incomes are converging across Indian districts but at slower rates in recent years and among farmers in the left-tail of the income distribution. Irrigation infrastructure, crop diversification, and distance to the urban market explain farm income growth, and hence, spatial income disparities. Returns to these factors are high for middle-income farmers than for the rich or poor. Spatial spillovers, likely from technological change, captured in residuals also had a positive impact on farm incomes. Results remain unchanged when farm income was replaced by its value added. Connecting the poorest to the markets, strengthening infrastructure and promoting diversification for the middle-income groups, and nudging high-income farmers toward value chains could help equitable economic development.

Circular agriculture is vital to achieve a substantial reduction of greenhouse gas (GHG) emissions. Optimizing resources and land use are an essential circularity principle. The objective of this article is to assess the extent to which land optimization can simultaneously reduce GHG emissions and increase production on dairy farms. In addition, we explore the potential reduction of GHG emissions under four different pathways. The empirical application combines the network Data Envelopment Analysis (DEA) with the by-production approach. This study focuses on a representative sample of Dutch dairy farms over the period of 2010–2019. Our results suggest that farms can simultaneously increase production and reduce GHG emissions by both 5.1%. However, only 0.6% can be attributed to land optimization. The land optimization results show that on average 25.3% of total farm size should be allocated to cropland, which is 6.7% more than the actual land allocation. GHG emissions could be reduced by 11.79% without changing the level of inputs and outputs. This can be achieved by catching up with the mitigation practices of the best performing peers.

This article develops a theoretical framework to determine the economically optimal grid size when sampling to guide precision application of inputs. Our theoretical model shows that a finer grid is optimal with increases in output price. A coarser grid is optimal with increased sampling costs and increased spatial correlation. With an exponential variogram, for example, the optimal grid size increases as the range increases. An applied example of lime application for winter wheat is used to demonstrate the framework. Spatial variograms for pH and Buffer pH were estimated using data from nine farmer fields. At the average spatial variability from these fields and using typical Oklahoma wheat yields of 40 bu/ac, grid sampling was economical when prices were above $5.43/bu. The optimal grid sizes were slightly larger than the 2.5-acre sizes that are typically used by producers. The empirical example verified the theory in that it found that optimal grid size decreased with higher output prices and crop yields and increased with greater spatial correlation. For example, optimal grid size approximately doubled as the range of the exponential correlation function doubled.

This article studies the economic effects of regulations that restrict farm practices used to produce products sold within a regulating jurisdiction, regardless of where the product was produced. We apply this analysis to the impact of California's law on sow housing and the North American hog/pork supply chain. California's Proposition 12 requires that specified pork products sold in California come from hogs whose mothers were housed according to California requirements. Such regulations, whether imposed by national or subnational authorities, have unique impacts on production, demand, prices, and economic welfare both within and outside the regulating jurisdiction. Our model identifies these effects and quantifies their impacts within a calibrated equilibrium framework. Results show that California consumers will buy less pork under Proposition 12 because retail prices of regulated cuts of pork will rise by about 7%. Compliant hog producers will, on average, earn greater profits, while impacts on prices and quantities of products sold outside of California are minimal. Regulations like Proposition 12 are especially costly ways to affect farm animal treatment because they impose costs throughout the supply chain. We consider a simple alternative policy that would achieve far more change in animal housing at lower cost.

Agricultural productivity is hindered in smallholder farming systems due to several factors, including farmers’ inability to meet crop-specific soil requirements. This article focuses on soil suitability for maize production and creates multidimensional soil suitability profiles of smallholder maize plots in Uganda while quantifying forgone production due to cultivation on less-than-suitable land and identifying groups of farmers that are disproportionately impacted. The analysis leverages the unique socioeconomic data from a subnational survey conducted in Eastern Uganda, inclusive of plot-level, objective measures of maize yields and soil attributes. Stochastic frontier models of maize yields are estimated within each soil suitability class to understand differences in returns to inputs, technical efficiency, and potential yield. Farmers cultivating highly suitable soil have the potential to increase their observed yields by as much as 86%, while those at the opposite end of the suitability distribution (i.e., with marginally suitable land) operate closer to the production frontier and can only increase yields by up to 59%, given the current technology set. There is heterogeneity in potential gains across the wealth distribution, with poorer households facing more heavily constrained potential.

This article presents evidence of misallocation across households in rural Indian agriculture. I show that household demographics predict own farm labor demand for smallholder farmers but not non-smallholder farmers. A simple model of labor allocation predicts a clear consequence of this duality: smallholder farmers will reallocate labor across plots less in response to price changes than non-smallholders. Detailed household panel data confirms this theoretical prediction. Three additional facts suggest that a lack of off-farm labor opportunities may be partly responsible for the behavior of smallholders, leading smallholders to over allocate labor to agricultural production. First, smallholders report fewer hours of involuntary unemployment when their own crop prices increase. Second, yield is substantially higher for smallholders on plots of the same size. Finally, estimated marginal revenue products of labor are consistently lower for smallholders.