Agricultural Economics最新文献

Despite extensive studies on the effects of armed conflict on household dietary diversity, food security, and nutritional outcomes, the underlying pathways remain underexplored. A better understanding of these mechanisms could unpack the subsequent effects of conflict-induced food insecurity and oft-reported nutritional shortcoming, as well as identify which policy interventions hold promise. We study the effects of terrorist violence in Burkina Faso on household dietary diversity, as proxied by food consumption scores (FCS), and investigate the underlying mechanisms. For this purpose, we combine nationally representative 5-years panel data on households with spatial conflict data. We find negative and significant effects of conflict intensity on household food consumption scores. The decline in household FCS is a result of significant decreased dietary diversity in both food production and purchases. Although households in rural areas partially offset these reductions by food assistance, those reliant solely on farming as livelihoods remain the most affected. Further investigations show evidence that per-capita farm income and food expenditure are pathways linking the intensity of armed conflict to reduced FCS in food purchases, whereas reduced dietary diversity in food production results from decline in crop production. Additional specification tests support our main findings, offering insights that can help policymakers faced with similar scaled-armed conflicts. For instance, conflict-sensitive interventions aimed at supporting crop production and farm income for affected households could effectively improve their dietary diversity and overall food security in a post-conflict environment.

This study explores how differences in market yields of soymeal and soyoil, as derived from market prices compared to those obtained through the physical process of crushing soybeans, impact the returns and volatilities of these commodities. Positive (negative) deviations are associated with negative (positive) changes in return. Additionally, these deviations positively correlate with return volatility, suggesting that variations from the expected yields lead to price shifts and heightened return volatility. In summary, deviations from the crushing estimates significantly shape the modeling of soybean commodity returns and volatilities, with implications for understanding returns, hedging ratios, and portfolio return variance.

The African Continental Free Trade Area (AfCFTA) is expected to provide trade gains for Africa, especially from reducing non-tariff measures (NTM). Unfortunately, data on NTMs is scarce, both by country and sector. Using three underlying NTM data sets and other data sources, we provide a range of estimates to fill the missing gaps in the existing estimates. Focusing on agriculture, we then use a computable general equilibrium model to estimate the effects of the AfCFTA. Results from all three data sets indicate that NTM reduction leads to much greater intra-Africa trade gains than tariff reduction alone.

Perennial crops are important both economically and as a component of a healthy and nutritious diet (e.g., many fruits and nuts). However, the study of perennial crop production and farmer response to output price changes (i.e., supply response) is complex thanks to the dynamic nature of investment and decision making in these industries. The body of literature relevant to perennial crop supply response is also small relative to that of annual commodity crops. In this article, we contribute the first literature review on perennial crop supply response modeling in more than 30 years. We catalog advancements in estimating perennial crop supply response and discuss the application of these methods and trade-offs economists should be aware of when using them. In addition, we highlight future modeling developments that may be valuable to the field, with the hope this research will encourage additional economic research on this interesting and important topic and in turn provide new insights for perennial crop producers and policymakers.

This paper examines the diffusion of external (output and price) shocks to the Association of Southeast Asian Nations (ASEAN) through the agri-food trade channel for the 1990Q1 to 2020Q4 period. For that purpose, the study develops a Global Vector Autoregressive (GVAR) model to simulate the region's economic resilience (output, inflation, interest rate and exchange rate) from various external shocks. We find that the agri-food channel is relevant in the shock propagation to ASEAN. There are more pronounced output effects on ASEAN from global output shocks relative to regional output shocks channeled through agri-food trade. However, the macroeconomic responses of ASEAN to global price shocks are not uniform due to the different consumption intensities of oil and raw materials, with negative and positive output effects from oil price shocks and raw material price shocks, respectively. Overall, ASEAN is more vulnerable to oil price shocks than to raw material price shocks. Our results emphasize that the distributional impacts of the agri-food trade channel and the ASEAN region's ability to mitigate the effects of global shocks depend on the degree of trade linkages and the region's capacity to counter the demand contractions and supply disruptions. The findings suggest that ASEAN should be cautious about the global shocks penetrating through the agri-food channel to address its macroeconomic vulnerabilities and better manage its economic resiliency.

This study assesses the impact of two revolutions—the Tulip Revolution in 2005 and the Melon Revolution in 2010—on household food demand in Kyrgyzstan. Different categories within food products witnessed distinct adjustments in consumer demand. Employing a complete demand system and seemingly unrelated regressions with nationally representative panel data, we find that household food demand fluctuates based on pre-conflict expectations. Despite declining total food expenditure during the first revolution and increasing in the second, the expenditure shares for staples and luxuries display heterogeneous trajectories. Food preferences shifted toward luxuries during the first revolution and staples during the second. Our findings underscore the necessity of a disaggregated perspective in understanding conflict-induced shocks on food demand.

This paper uses comprehensive and long time series monthly food price data and a panel dyadic regression framework to evaluate the impact of the COVID-19 pandemic and associated policy responses on spatial market integration across a diverse set of food items in Nigeria. The empirical results reveal several important insights. First, we show that a significant slowdown in the speed of adjustment and price transmission occurred during the pandemic. For some food items, the speed of adjustment and, by implication, spatial market integration weakened by two- to-threefold after the outbreak of the pandemic. The effect was especially pronounced for perishable food items. Second, lockdown measures and the spread of the pandemic triggered additional dispersion in market prices across markets. For example, lockdown measures were associated with a 5%–10% reduction in the speed of readjustment toward long-term equilibrium. Third, additional underlying attributes of markets, including lack of access to digital infrastructure and distance between markets, exacerbated impacts associated with the pandemic. For instance, access to Internet service reduced the slowdown in the speed of adjustment caused by the pandemic, but longer distances between market pairs induced greater slowdown in the speed of price transmission. Our findings offer important insights for revitalizing the efficiency of food markets affected by the pandemic. The heterogenous impacts of the pandemic across value chains and markets reinforce the need to properly target post-pandemic recovery interventions and investments. Finally, we offer some insights to reduce the vulnerability of food and market systems to disruptions in future pandemics or similar phenomena that inhibit food marketing and trade.

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.

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.