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Swift response models are vital tools for emergency assistance agencies. The COVID-19 pandemic revealed the lack of economic models for short-run policy relevant research to anticipate local impacts and design effective policy responses. The most direct effects of the pandemic and lockdown tended to be concentrated in urban areas; however, markets quickly transmitted impacts to rural areas as well as among poor and non-poor households. General equilibrium modeling is a tool of choice to capture indirect, spillover effects of exogenous shocks. This article describes an unusual micro general-equilibrium (GE) modeling approach that we developed to quickly simulate impacts of the pandemic and lockdowns on poor and non-poor rural and urban households across sub-Saharan Africa. Monte Carlo bootstrapping was used to construct four stylized regional GE models from 34 existing local economy-wide impact evaluation (LEWIE) models. Simulations revealed that the pandemic and policy responses to curtail its spread were likely to affect rural households at least as severely as urban households. Simulated income losses are greater in poor households in both urban and rural settings. These findings are relatively consistent across models spanning sub-Saharan Africa. Because COVID-19 impacts are so far-reaching, all types of economies experience downturns. Our research underlines the importance of modeling assumptions. We find total annualized impacts of around a 6-percent loss of GDP, smaller than estimates from single-country models that ignore price effects, such as SAM-multiplier models, but in line with The World Bank's baseline forecast of a 5.2% contraction in global GDP in 2020. The largest negative impacts are on poor rural households. Published version

AbstractUtilizing a rich export restriction database that covers 527 agricultural products at the six‐digit Harmonized System (HS) code level in 168 countries from 2005 to 2015, this article investigates the political and economic determinants of countries’ export restriction decisions. Empirical analysis shows that a one standard deviation increase in a commodity's market power increases the probability of an export restriction on that commodity by 5.5%, and a one standard deviation increase in a country's number of Regional Trade Agreement (RTA) partners decreases the probability of an export restriction by 6.0%. There is also evidence that higher market power of the downstream sector, which purchases inputs from the upstream sector, leads to a higher probability of export restrictions in the upstream sector. Macroeconomic variables, including urbanization rate, agricultural land per capita, and weather variables, are also important determinants of export restrictions. This article highlights the potential role of RTAs and competitive market structure in both the sector of interest and its downstream sector in disciplining export restrictions.

AbstractAdvice from managementprofessionals can help small‐ and medium‐sized firms reach complex financial goals in low‐ and middle‐income countries. We apply lessons learned in the firm literature to determine the degree in which farmer associations face constraints to management and planning capacity that can be alleviated by the provision of advice from external consultants. In particular, we conducted a randomized control trial in 42 water user associations (WUAs) in Mozambique to examine whether more intensive attention from financial consultants through repeated follow‐up visits prompts households to save and invest in agricultural equipment. All WUAs received a financial literacy training and were eligible to receive a matching grant. Twenty‐one WUAs were randomized into the treatment group that additionally were visited by private consultants quarterly, who tailored their advice to meet individuals’ own savings and investment objectives. We find the follow‐up visits increase ‘hidden savings’ in the form of new capital investments on farmers’ own account. Thus, the visits may have changed savings’ habits by leading farmers to invest in technologies that were not directly subsidized. Our ability to detect an additional effect on the type of investments farmers targeted through the matching grant and, hence, the savings for the respective investments is limited given the power of our study design. Although the proportion of households saving increased, the intervention was likely less cost‐effective than other modalities aimed to enhance the proclivity to save.

AbstractThis analysis quantifies changesin global agricultural markets for maize, rice, soybeans, and wheat due to yield changes triggered by climate change. The scenarios include four representative concentration pathways (RCP), five global climate models, three shared socioeconomic pathways (SSPs) capturing differences in population levels and economic growth, and enhanced CO‐fertilization. Yield projections incorporate the influence of SSPs on nitrogen application and agricultural technology. Depending on the SSP and comparing the RCP8.5 ensemble yields (with CO‐fertilization) to a no climate change scenario in 2050, price increases for maize (61.3%–80.9%), soybeans (36.7%–51.7%), and wheat (5.4%–11.1%) are observed. Large wheat producers in temperate regions expand wheat production under climate change. Rice benefits from CO fertilization resulting in a relatively uniform price decrease across scenarios of 19.5%–19.9%. Cropland expansion between 2015 and 2050 is lowest for the high economic growth scenario. Depending on the crop and region, there are significant reductions in production especially for maize. Absolute changes in trade patterns are most pronounced for wheat and least for rice. Using trade as a means to dampen the negative welfare effects of climate change will be important and so is economic growth.

AbstractWe study household consumption of various categories of processed food, including ultra‐processed food and meals away from home in Tanzania. We compare peri‐urban versus hinterland rural areas, and large cities versus small towns. Three sets of findings stand out. (1) Contrary to the common view in Africa that processed food is mainly an urban middle‐class phenomenon, we found it has penetrated the diets of the rural areas and the rural and urban poor. In rural areas, surprisingly 60% of food consumption comes from purchases in value terms, and processed food accounts for 76% of purchases and 47% of all food consumed. For the rural poor, purchased processed food is 38% of food consumption. In urban areas processed food's share of purchases (hence consumption) is 78%, similar for the rich and poor. (2) We found that ultra‐processed food (such as sugar‐sweetened beverages and cookies) and meals‐away‐from‐home (MAFH) have emerged as important in urban as well as rural areas. As these foods tend to be high in oil, salt, and sugar, this is a health concern. The share of ultra‐processed foods and MAFH is 21% in rural areas and 36% in cities albeit twice as high in large cities compared with small towns and among richer compared to poorer consumers. (3) Our regressions show the spread of processed food consumption in rural and urban areas, among the rich and poor, is driven mainly by opportunity costs of the time of women and men, and thus the pursuit of saving home‐processing and cooking time, as well as food environment factors. As these drivers are long term trends this suggests processed food consumption will continue to grow.

AbstractLike many exchanges the Chicago Mercantile Exchange allows traders to conceal part of their limit orders, known as a hidden‐limit order (HLO) or iceberg order. With HLOs, market participants have incomplete knowledge of the order book. To assess the effect of this lack of transparency in a period of highly volatile markets, we investigate the patterns and market impacts of HLOs in the U.S. corn and live cattle futures markets. Our conservative estimates indicate that HLOs represent more than 10% (20%) of the total volume in corn (live cattle) futures market. The findings show that the existence of HLOs improves market quality in multiple dimensions: driving trading volume while reducing market volatility and enhancing market liquidity. Our results are critical for regulators and exchanges as they are supportive of a degree of opacity. They are also indicative that market traders hide successfully, which can protect traders who have speed disadvantages in the era of fast trading.

This article provides evidence of the immediate impacts of the first months of the COVID-19 crisis on farming communities in central Myanmar using baseline data from January 2020 and follow-up phone survey data from June 2020 with 1,072 women and men Heterogeneous effects among households are observed Fifty-one percent of the sample households experienced income loss from various livelihood activities, and landless households were more severely affected by the crisis, mainly because of lost farm and nonfarm employment and negative impacts on rural enterprises Women and men in these landless households were equally engaged and affected by lower wages or more difficulties in finding farm work;fewer women were engaged in nonfarm work, but almost all of them lost such nonfarm wage employment Women in landless households are also particularly vulnerable in terms of worsened workload and increased tension in the household during COVID-19 Landed households were also affected through lower prices, lower demand for crops, and difficulties in input access Women and men differ in levels of stress, fear, and pessimism regarding the effects of COVID-19 In most households, there were no signs that household task-sharing and work balance improved, and no clear shift in intrahousehold relations was observed © 2021 The Authors Agricultural Economics published by Wiley Periodicals LLC on behalf of International Association of Agricultural Economists

AbstractIn March 2020, India declared a nationwide lockdown in response to the COVID‐19 pandemic. Such restrictions on mobility interrupted the normal functioning of agricultural value chains. For a sample of 1767 tomato and wheat producers in the state of Haryana, we study to what extent the lockdown limited access to inputs, labor, machinery, and markets to produce, harvest, and sell their crops. We quantify crop income reductions during the first months of the lockdown and analyze to what extent these are associated with borrowing and food insecurity. We find that wheat producers, for whom state‐led procurement guaranteed market access at fixed prices, suffered minimal declines in income. For tomato producers—an already more vulnerable population—income fell by 50% relative to their expected income in a normal year, largely due to a steep fall of tomato prices as they shifted from wholesale markets to local retail markets, resulting in a sharp increase in local supply. Relative to wheat producers affected by the lockdown, reduced income for tomato producers was associated with an increase in borrowing and reduced food security. We conclude that targeting producers of crops that face substantial price risk and introducing policies that stabilize market prices are important in efforts to aid recovery and build resilience of smallholder farmers.