Showing papers in "American Journal of Agricultural Economics in 2021"

COVID-19 and the Demand for Online Food Shopping Services: Empirical Evidence from Taiwan

Abstract: We investigate how the coronavirus pandemic affected the demand for online food shopping services using data from the largest agri-food e-commerce platform in Taiwan We find that an additional confirmed case of COVID-19 increased sales by 5 7% and the number of customers by 4 9% The demand for grains, fresh fruit and vegetables, and frozen foods increased the most, which benefited small farms over agribusinesses The variety of products sold on the e-commerce platform also increased during the pandemic, which suggests the concentration of sales on niche products could increase as more consumers are drawn to online platforms Our investigation of mechanisms for the shift to online food shopping indicates that sales were highly responsive to COVID-19 media coverage and online content © 2020 Agricultural & Applied Economics Association

COVID-19 and Supply Chain Disruption: Evidence from Food Markets in India .

Abstract: This paper looks at the disruption in food supply chains due to COVID-19 induced economic shutdown in India. We use a novel dataset from one of the largest online grocery retailers to look at the impact on product stockouts and prices. We find that product availability falls by 10% for vegetables, fruits, and edible oils, but there is a minimal impact on their prices. On the farm-gate side, it is matched by a 20% fall in quantity arrivals of vegetables and fruits. We then show that supply chain disruption is the main driver behind this fall. We compute the distance to production zones from our retail centers and find that the fall in product availability and quantity arrivals is larger for items that are cultivated or manufactured farther from the final point of sale. Our results show that long-distance food supply chains have been hit the hardest during the current pandemic with welfare consequences for urban consumers and farmers.

Food Consumption and Food Security during the COVID-19 Pandemic in Addis Ababa.

Abstract: International humanitarian organizations have expressed substantial concern about the potential for increases in food insecurity resulting from the COVID-19 pandemic. We use a unique panel survey of a representative sample households in Addis Ababa to study both food security and food consumption during the pandemic. In contrast to some other countries in the region, Ethiopia never went into a full lockdown severely restricting movement. Despite subjective income measures suggesting a large proportion of households have been exposed to job loss or reduced incomes, we find that relative to a survey conducted in August and September of 2019, food consumption and household dietary diversity are largely unchanged or slightly increased by August 2020. We find some changes in the composition of food consumption, but they are not related to shocks found in previous phone surveys conducted with the same households. The results therefore suggest the types of subjective questions about income typically being asked in COVID-19 phone surveys may not appropriately reflect the magnitude of such shocks. They also imply, at least indirectly, that in the aggregate food value chains have been resilient to the shock associated with the pandemic.

Overcoming Global Food Security Challenges through Science and Solidarity

Abstract: The world faces formidable, but manageable, challenges in achieving food security in a world growing beyond 9 billion people in the coming decades. Five big challenges will necessitate shifting innovation strategy to place greater emphasis on sustainable increases in diet quality, on total factor productivity ‐ not just crop yield ‐ growth, on social protection programs, on Africa, on post‐farmgate agri‐food value chains, on risk management, and on reducing the land and water footprint of food production. We must be progressive in both senses of the term, having faith in science as an engine of societal advance, and standing with marginalized populations.

Information and communication technologies to provide agricultural advice to smallholder farmers: Experimental evidence from Uganda

Abstract: Agricultural advisory services generally rely on interpersonal knowledge transfers by agricultural extension agents who visit farmers to provide information. This approach is not always effective and has proved hard to scale sustainably, particularly in highly dispersed smallholder farming systems. Information and communication technologies (ICTs) have been advanced as a promising way to overcome many of the problems associated with conventional agricultural extension. We evaluate the effectiveness of an ICT‐mediated approach to deliver agricultural information in a field experiment conducted among small‐scale maize farmers in eastern Uganda. Three complementary technologies designed to address both informational and behavioral constraints to technical change are considered. First, we investigate the effectiveness of audiovisual messages (video) as a means of delivering information on input use and improved maize management practices to farmers. Second, we quantify the additional impact of complementing video with an interactive voice response (IVR) service. Third, we estimate the incremental effect of time‐sensitive short message services (SMS) messages designed to remind farmers about applying key practices at specific points during the season. We find that households that were shown a short video on how to become better maize farmers were performing significantly better on a knowledge test, more likely to apply recommended practices, and more likely to use fertilizer than households that did not view the video. These same households also reported maize yields about 10.5% higher than those that did not view the video. We find little evidence of an incremental effect of the IVR service or SMS reminders.

Economic Impacts of the COVID−19 Lockdown in a Remittance-Dependent Region

Abstract: The economic impacts of COVID-19 lockdowns on poor and vulnerable households living in rural areas of developing countries are not well understood due to a lack of detailed micro-survey data at the household level Utilizing weekly financial transaction data collected from households residing in a rural region of India, we estimate the impacts of India's COVID-19 lockdown on household income, food security, welfare, and access to local loan markets A large portion of households living in our study region is reliant on remittances from migrants to sustain their livelihoods Our analysis reveals that in the month immediately after India's lockdown announcement, weekly household local income fell by INR 1,022 (US$ 13 5), an 88% drop compared to the long-term average with another 63% reduction in remittance In response to the massive loss in earnings, households substantially reduced meal portions and consumed fewer food items Impacts were heterogeneous;households in lower income quantiles lost a higher percentage of their income and expenditures, but government food aid slightly mitigated the negative impacts We also find an increase in the effective interest rate of local borrowing in cash and a higher demand for in-kind loans, which are likely to have an adverse effect on households who rely on such services The results from this paper have immediate relevance to policymakers considering additional lockdowns as the COVID-19 pandemic resurges around the globe and to governments thinking about responses to future pandemics that may occur © 2020 Agricultural and Applied Economics Association

The Importance of Agriculture in the Economy: Impacts from COVID-19.

Abstract: Much of the attention from COVID-19 has been on the impacts on tourism and other service sectors; but there has been a growing interest in some agricultural and food topics, such as the decline in food away from home (FAFH) expenditures. Our work considers the importance of FAFH in the overall economy, and we also consider changes in agricultural production and trade that have occurred because of COVID-19. We gather data on actual changes to these components, as well as similar shocks to non-agricultural sectors, and employ a simulation model to estimate the impacts on gross domestic product (GDP). Results indicate that changes from agriculture due to COVID-19 have had a larger effect on the overall U.S. economy than the share of agriculture in the economy at the beginning of COVID-19. But the non-agricultural shocks still outweigh the impacts from agriculture by a magnitude of 3. Breaking the results down along the components, we find that the loss in FAFH expenditures is the largest contributor to the change in GDP resulting from shocks to agricultural markets and conclude that agricultural production/trade markets have been very resilient during the pandemic. Our results also indicate that our model (computable general equilibrium) does reasonably well in estimating GDP compared to actual changes due to the inclusion of data on actual demand, supply, and fiscal responses to COVID-19.

Impact of COVID-19 and Nationwide Lockdowns on Vegetable Prices: Evidence from Wholesale Markets in China

Abstract: In this paper, we employ a combination of time regression discontinuity design method (T-RD) and the difference-in-difference method (DID) to identify and quantify the causal effects of the strict lockdown policy on vegetable prices using multiple-year daily price data from 151 wholesale markets of Chinese cabbage. We find that the lockdown policy caused a large and immediate surge in price and price dispersion of Chinese cabbage, though they fluctuated smoothly for the same period in normal years. The DID results further show that the price surge peaked in the fourth week of lockdown but gradually came down to the level of a normal year by week 11. However, the price rose again (though to a much smaller extent) in response to the resurgence of COVID-19 in a few provinces in early-mid April but quickly returned to the normal level in week 15 when the lockdown measures were largely removed. We also find that the supply chain disruption is the driving factor for the price hike. Policy implications are drawn.

One Size Fits All? Experimental Evidence on the Digital Delivery of Personalized Extension Advice in Nigeria

Abstract: Blanket advice on optimal fertilizer application rates has failed to achieve potential yield gains for crop production in much of Sub‐Saharan Africa. However, digital technology now makes it possible to deliver personalized extension services to farmers at a much lower cost. We present results from a randomized control trial designed to evaluate the effectiveness of a mobile application that provides personalized advice on rice nutrient management. We find that households who were just given the personalized advice increase their yield by 7% and increase their profit by 10%. On average, personalized advice increases yields without increasing the overall quantity of fertilizer used. We conclude that the scaling of personalized extension services could improve productivity and livelihoods in Sub‐Saharan Africa without necessarily increasing the total amount of fertilizer in use.

How Do Farmers Learn from Extension Services? Evidence from Malawi

Abstract: Though extension services have long since proved their value to agricultural production and farmer prosperity, their record in sub‐Saharan Africa has been mixed. To study the impact of such programs on farmers' learning about agricultural technologies, we implemented a quasi‐randomized controlled trial and collected detailed panel data among Malawian farmers. Based on those findings, we develop a two‐stage learning framework, in which farmers formulate yield expectations before deciding on how much effort to invest in learning about these processes. Using data centered on farmer beliefs, knowledge, and constraints, we find evidence that beliefs about potential yields hinge on first‐hand and local experience, and that these beliefs significantly impact learning efforts. Consistent with this, we find that farmers who participated in season‐long, farmer‐led demonstration plot cultivation plan to adopt more components of new multi‐component technology, compared to farmers who were invited to attend only field‐day events.

Environmental Externalities from Agriculture: Evidence from Water Quality in the United States

Abstract: Agricultural fertilizer use is widely acknowledged to be a leading cause of water pollution. Yet, no national estimates exist on the effect of fertilizer application on concentrations of agricultural pollutants in US watersheds. This paper employs a watershed‐level panel data on nitrogen and phosphorus pollution readings to examine the impact of fertilizer use on US water quality over a fifty‐five‐year time period from 1951 to 2005. Findings show that a 10% increase in the use of nitrogen and phosphorus fertilizers leads to a 1.52% increase in the concentration of nitrogen and a 1.37% increase in the concentration of phosphorus across watersheds. Results also indicate that there exists heterogeneity in nutrient pollution elasticity estimates across eighteen US water resource regions, ranging from 0.082 to 0.733 in the case of nitrogen and from 0.036 to 0.475 in the case of phosphorus. Combining our results with prior hydrology‐based studies, we find that a 100% increase in the use of nitrogen fertilizers in the Lower Mississippi water resource region expands the size of the hypoxic zone in the Gulf of Mexico by roughly 3,389 square miles, equivalent to about two‐fifths of the estimated size of the dead zone in the Gulf of Mexico.

Measurement Error Mechanisms Matter: Agricultural Intensification with Farmer Misperceptions and Misreporting

Abstract: The mechanism(s) that generate measurement error matter to inference. Survey measurement error is typically thought to represent simple misreporting correctable through improved measurement. But errors might also or alternatively reflect respondent misperceptions that materially affect the respondent decisions under study. We show analytically that these alternate data generating processes imply different appropriate regression specifications and have distinct effects on the bias in parameter estimates. We introduce a simple empirical technique to generate unbiased estimates under more general conditions and to apportion measurement error between misreporting and misperceptions in measurement error when one has both self-reported and objectively-measured observations of the same explanatory variable. We then apply these techniques to the longstanding question of agricultural intensification: do farmers increase input application rates per unit area as the size of the plots they cultivate decreases? Using nationally representative data from four sub-Saharan African countries, we find strong evidence that measurement error in plot size reflects a mixture of farmer misreporting and misperceptions. The results matter to inference around the intensification hypothesis and call into question whether more objective, precise measures are always preferable when estimating behavioral parameters.

Climate Econometrics: Can the Panel Approach Account for Long‐Run Adaptation?

Abstract: The panel approach with fixed effects and nonlinear weather effects has become a popular method to uncover weather impacts on economic outcomes, but its ability to capture long‐run climatic adaptation remains unclear. Building upon a framework proposed by McIntosh and Schlenker (2006), this paper identifies empirical conditions under which the nonlinear panel approach can approximate a long‐run response to climate. When these conditions fail, the obtained relationship may still be interpretable as a weighted average of underlying short‐run and long‐run responses. We use this decomposition to revisit recently published climate impact estimates. For spatially large panels, the estimated temperature–outcome relationship mostly reflects the long‐run climatic response; this is not so for precipitation. We find some evidence of long‐run climatic adaptation for crop yield outcomes in the United States and France.

Climate-Smart Innovations and Rural Poverty in Ethiopia: Exploring Impacts and Pathways

Abstract: Climate‐smart innovations have been receiving increasing attention in policy dialogues for their potential to transform agricultural systems and improve the well‐being and resilience of farm households. Using recent panel data from Ethiopia combined with novel historical weather data, we provide microeconomic evidence of the welfare effects of conservation agriculture (CA), a climate‐smart agricultural practice. We use a panel data endogenous switching regression model to deal with selection bias and farmer heterogeneity in CA choice. The study finds that the CA practices that play a pivotal role in addressing the exigencies of rural poverty are minimum tillage, cereal‐legume intercropping, and their combination. These practices reduce the incidence and depth of poverty in areas prone to rainfall stress, which is an indication of their risk mitigation role. In contrast, crop residue retention and its combination with minimum tillage appear not to be economically attractive CA options. The results show that CA portfolios that include minimum tillage and cereal‐legume associations can accelerate efforts to reduce rural poverty and improve climate risk management. We caution against exaggerated expectations of CA's economic benefits and a rigid recommendation of CA.

On the Use of Virtual Reality in Mitigating Hypothetical Bias in Choice Experiments

Abstract: Choice experiments have been extensively used in many stated preference studies and disciplines. In order to give external validity to stated preferences, participants must behave the same in an experiment setting as they do in reality. The difference between a decision made in a real experiment and a hypothetical experiment is commonly attributed to “hypothetical bias.” In this paper, we investigate whether virtual reality can reduce hypothetical bias in choice experiments. We conducted a set of experiments using the Food and Drug Administration's new Nutrition Facts Label for yogurts. Participants were randomly assigned to non‐hypothetical and hypothetical experiments, which differed in terms of visual presentations of the product in question: text, picture, and a virtual grocery store. Given the absence of real markets for the new label at the time of the research, we approximate the real market with a binding choice in our non‐hypothetical experiments. Our results suggest that although the hypothetical bias with virtual reality is not statistically significantly different from those using text or picture, it is the smallest. Among participants who did not exhibit high simulator discomfort, results suggest that virtual reality can significantly reduce hypothetical bias in choice experiments.

Links between Maternal Employment and Child Nutrition in Rural Tanzania

Abstract: Improving child nutrition and empowering women are two important and closely connected development goals Fostering female employment is often seen as an avenue to serve both these goals, especially if it helps to empower the mothers of undernourished children However, maternal employment can influence child nutrition through different mechanisms, and the net effect may not necessarily be positive We develop a theoretical model to show that maternal employment can affect child nutrition through changes in income, intrahousehold bargaining power, and time available for childcare The links are analyzed empirically using panel data from farm households in rural Tanzania We find that the links between maternal employment and child height-for-age Z-scores (HAZ) are non-linear Off-farm employment is negatively associated with child HAZ at low levels of labor supply The association turns positive at higher levels of labor supply and negative again at very high levels The associations between maternal on-farm work and child nutrition are weaker and not statistically significant These findings can help to better design development interventions that foster synergies and avoid potential tradeoffs between female empowerment and child nutrition goals

Oil Price Pass through to Agricultural Commodities

Abstract: Energy represents an important share of production costs for many agricultural commodities. Previous studies have found mixed evidence of a pass‐through relationship between oil prices and agricultural commodity prices, a relationship that has the potential to disrupt farm‐level decision making. We propose that these mixed findings are in part due to heterogeneity in the pass‐through relationship across time horizons. We use a new wavelet‐based regression approach to explore horizon‐based heterogeneity in the relationship between oil and agricultural commodity prices. We find strong evidence of heterogeneity across time horizons and commodities. We develop a stylized model of agricultural production and show that agricultural contracts can generate price stickiness that leads to heterogeneity in input price pass through over different horizons. We also find evidence that recent technological shifts have led to a structural change in this horizon‐based heterogeneity.

Household Food Waste and Inefficiencies in Food Production

Abstract: This paper investigates household food waste in the context of inefficient food production. Food waste is typically defined as the proportion of edible food that goes unconsumed, whereas inefficiency is measured by a household's inability to reach some technically efficient production frontier. Because food waste can be avoided through improved efficiency, we focus on the determinants of inefficiency using unique household‐level data on food stock usage and food consumption. We simultaneously estimate the productivity of input usage and the corresponding household‐specific inefficiencies. Inefficiencies are further specified to be a function of observable characteristics. For the general population, we find inefficiencies to be associated with race, age, education, household size, joint preparation of meals, distance traveled to the food store, and food shopping frequency. A latent class model clearly distinguishes two groups of households: a relatively more efficient group (about 16% of the population) and a relatively inefficient group (the remaining 84%). The inefficient group is driving most of the aforementioned results for the general population, and we find relatively little explanatory power of covariates for the efficient group. We find the equivalence of observed food waste, which averages 43% in our data, to estimated input‐oriented inefficiency, which ranges 30–45%, to be dependent upon the estimated reference technology and underlying assumptions. However, we find food waste and input‐oriented inefficiency are highly correlated, such that using either outcome leads to similar policy recommendations in terms of associated factors.

Demand for aflatoxin-safe maize in Kenya: Dynamic response to price and advertising

Abstract: In countries where regulatory enforcement is weak, voluntary third‐party verification of firms' food safety processes can allow concerned consumers to select safer products. However, due in part to their legal ambiguity, and the potential to attract additional regulatory scrutiny, food safety claims are rarely made by firms. As a result, the impact of such claims on consumer demand is not well understood. We examine how labeling maize as tested for aflatoxin, a carcinogen also associated with stunting in children, affects sales. By randomly varying the timing and intensity of a marketing campaign to promote the first maize flour brand in Kenya labeled as tested for aflatoxin, we characterize dynamic consumer response to information about food safety. We find an immediate response in sales to marketing alone, which disappears as soon as marketing ceases. Sales remain elevated in the weeks after a temporary discount is offered, but this effect also fades over time and is not associated with greater awareness of the firm's food safety claims. These results suggest that it is unrealistic to expect for‐profit firms serving mass markets in low‐ and middle‐income countries to invest heavily in marketing based on food safety claims.

U.S. Interstate Trade Will Mitigate the Negative Impact of Climate Change on Crop Profit

Abstract: According to the current Intergovernmental Panel of Climate Change report, climate change will increase the probability of occurrence of droughts in some areas. Recent contributions at the international level indicate that trade is expected to act as an efficient tool to mitigate the adverse effect of future climate conditions on agriculture. However, no contribution has focused on the similar capacity of trade within any country yet. The U.S. is an obvious choice given that many climate impact studies focus on its agriculture and around 90% of the U.S. crop trade is domestic. Combining a recent state‐to‐state trade flow dataset with detailed drought records at a fine spatial and temporal resolution, this paper highlights first that trade increases as the destination state experiences more drought and inversely in the origin state. As a result, crop growers' profits depend on both local and trade partners' weather conditions. Projections based on future weather data convert the crop grower's expected loss without trade into expected profit. As such, this paper challenges the estimates of the current climate impact literature and concludes that trade is expected to act as a $14.5 billion mitigation tool in the near future.

Technology and Technical Efficiency Change: Evidence from a Difference in Differences Selectivity Corrected Stochastic Production Frontier Model

Abstract: This study presents a new approach to evaluate the economic impact of development projects for cases where baseline and endline data for comparable treated and control samples are available. An important contribution is to bring together propensity score matching (PSM) and difference‐in‐differences (DID) techniques, commonly used in impact evaluation studies, with stochastic production frontiers (SPF) that have become well‐established in the productivity literature. To illustrate our proposed framework, we use baseline and endline data from a rural environmental development program implemented in Nicaragua between 2012 and 2016. The results support the use of the approach proposed and reveal that selectivity from unobservables can be significant. The analysis shows that a severe drought over the period analyzed had significant negative effects on both control and treated farms. However, project beneficiaries enjoyed significantly better results, attributable to the project, compared to the control group. Overall, the results exhibit relatively low levels of technical efficiency with no significant variation across models, time, and treatment status.

Price Dispersion in Farmland Markets: What Is the Role of Asymmetric Information?

Abstract: This article investigates the role played by information, search, and bargaining cost in agricultural land markets to explain price dispersion. Based on a hedonic model under incomplete information, we build a two‐tier stochastic frontier. By linking costs of being information deficient to agent characteristics such as degree of professionalism, we identify relative price effects of buyer and seller types related to information deficiency. We compile a comprehensive data set of more than 10,000 transactions in Saxony‐Anhalt, Germany, between 2014 and 2017. We find institutional sellers to achieve the lowest losses resulting from information deficiency and sell with mark‐ups, whereas other sellers incur losses. This seller group could benefit from investments in professionalism and roughly halve their cost of being information deficient. Tenant buyers can benefit from informational advantages resulting in markdowns with lowest effects in the harvest season. We conclude that Germany's policy makers can do more to support market transparency.

The Pass‐Through of a Tax on Sugar‐Sweetened Beverages in Boulder, Colorado

Abstract: This paper estimates the pass‐through of the largest tax on sugar‐sweetened beverages enacted in the U.S., which is two cents per ounce in Boulder, Colorado. A strength of the paper is that, to achieve as complete a perspective as possible, we estimate the pass‐through of the tax not only to beverage prices in retail stores but also to those in restaurants, and we examine data for the treatment community of Boulder and a comparison community of Fort Collins, Colorado, from four sources: (a) hand‐collected data on prices from stores; (b) Nielsen Retail Scanner Data of store prices; (c) hand‐collected data on prices in restaurants; and (d) web‐scraped data from online restaurant menus. Across the multiple datasets, we find consistent evidence that the tax was largely, but not completely, passed through to consumers. In both the hand‐collected store data and restaurant data, pass‐through is slightly less than 75%, whereas pass‐through is just over 50% using the scanner data; consumers bear most, but not all, of the largest tax on sugar‐sweetened beverages in the United States.

Would A National Sugar‐Sweetened Beverage Tax in the United States Be Well Targeted?

Abstract: Sugar‐sweetened beverage (SSB) taxes have been proposed to discourage excessive sugar consumption, but it is unclear how high‐ versus low‐SSB purchasers respond to such taxes We first examine heterogeneity in the purchase and financial effects of a national SSB tax across different types of households buying varying amounts of SSBs We find high‐SSB purchasers are less responsive to SSB price changes than low purchasers but make larger absolute reductions in SSB purchases in response to the tax, given their notably greater purchase levels prior to the tax Nonetheless, the economic burden of the tax falls more heavily on high‐SSB purchasers who are more likely composed of lower income households We then investigate whether the income regressivity of the tax will be mitigated if low‐income households are targeted by fruit and vegetable (FV) subsidies We show that depending on the tax pass‐through and subsidy rates, FV subsidies can fully offset high‐SSB purchasers’ tax burdens, and subsidy transfers are distributed relatively uniformly across the SSB purchase distribution of low‐income households Therefore, FV subsidy transfers would be financially more beneficial to low‐ and moderate‐SSB purchasers because they bear smaller shares of the tax burden than high‐SSB purchasers