Abstract: Consumer food purchasing and willingness to adopt a sustainable healthy diet (SHD) is a key factor affecting the sustainability of the entire food system. Studies have developed scales to measure consumer preferences for particular consumption patterns, while others have sought to empirically define the multiple dimensions of a sustainable food system (environmental, social, economic, etc.). This paper builds on these literatures by tracking consumers’ SHD behaviors using a large-scale, longitudinal survey of adults in the United States and mapping them onto multiple systems-level indicators. We wanted to know whether consumers interact with the sustainability of their food along the same principles developed by experts. Our study defines 18 food purchasing behaviors that support the sustainability goals of leading scientific institutions, uses factor analysis to identify the unobserved drivers behind these behaviors, and creates SHD scores to investigate their correlations with other consumer characteristics and behaviors. Factor analysis results show consumer food purchasing is motivated by three underlying sustainability dimensions—Economic Security, Socio-Environment, and Nutrition—which are fewer constructs than often defined by academic researchers. SHD scores reveal higher adoption of behaviors that fall under Economic Security relative to the other two dimensions. All three sustainability constructs are impacted by socio-economic and demographic characteristics.
Abstract:The modern-day food industries are part of a complex agri-food supply chain, where food production has become efficient, yet potentially vulnerable to supply chain risks. The COVID-19 pandemic is a testament to that end. This article measures and identifies the U.S. food manufacturing industries' vulnerability to upstream industries and labor occupations by (i) calculating a food industry's diversification of intermediate input purchases across upstream industries, (ii) quantifying the relative exposure of food manufacturing in a given industry and location to upstream input suppliers and labor occupations, and (iii) estimating each food industry's gross output elasticity of inputs. This article also explores geographic heterogeneity in food industries' vulnerability. Among our results, we find evidence that the animal processing industry's output is relatively vulnerable to production labor, consistent with the observed disruptions to the meatpacking sector during COVID-19, which were largely caused by labor issues. Our results may help academics and practitioners to understand food industries' vulnerabilities to upstream industries and labor occupations.
Abstract:During the COVID-19 pandemic, the U.S. government distributed Economic Impact Payments (EIPs) to ease the economic hardships of American households. Using the Household Pulse Survey, we study the association of first-round EIPs with household-level food insufficiency in a sample of late recipients of EIPs. Studying the late recipients is important for two reasons, first, about 12 million eligible individuals did not automatically receive EIPs, and second, the late receipt of EIPs and the low-income status of late recipients allow us to tease out the relationship between EIPs and food insufficiency. We find that EIPs were associated with a 9.2 percentage points decrease in the likelihood of food insufficiency. However, households kept relying on free food acquisition to fight food hardship. Our results suggest that government efforts to provide more timely stimulus payments could be very impactful and significantly impact household food insufficiency.
[Published Article] [Extension Version for Purdue Ag Econ Report]
Abstract: Understanding how farm household consumption responds to adverse income shocks can provide insight into household well-being and appropriate agricultural policy. Using a split-sample survey of Indiana specialty producers, where we randomly assign respondents to treatments that vary the size of a hypothetical income shock, we estimate the relationship between income loss and household consumption. Given that postdisaster producers' risk preferences are important for business decisions, we elicit producers' risk preferences. We find that food and miscellaneous expenses are the most sensitive to income losses. We also find evidence for decreasing absolute risk aversion among producers after the income loss shock.
Abstract:
Purpose: The study investigates whether there is an association between climate types and farm risk attitudes of principal operators.
Methodology: The study exploits temperature variation in the diverse climate types across the United States and defines
hot- and cold-climate states. Ordered logit and generalized ordered logit models are used to model principal operators’ farm risk attitudes,
which are measured on a Likert scale. The study uses two datasets. The first dataset is a 2017 survey of U.S. large commercial producers.
The second dataset provides a Köppen-Geiger climate classification of the United States at a spatial resolution of 5 arcmin for a 25-year period
(1986-2010).
Findings: The study finds that principal operators in hot-climate states are 4%-5% more likely to have a higher willingness to take
farm risk compared to principal operators in cold-climate states.
Research Implications: It is likely that farm risk mitigation decisions differ between hot- and cold-climate states.
For instance, we show that corn acres’ enrollment in federal crop insurance and computers’ usage for farm business are pursued more
intensely in cold-climate states than in hot-climate states. A differentiation of farm risk attitude by hot- and cold-climate states may
help agribusiness, the government, and economists in their farm product offerings, farm risk management programs, and agricultural
finance models, respectively.
Originality: Based on Köppen-Geiger climate classification, the study introduces hot- and cold-climate concepts to understand the relationship
between climate types and principal operators’ farm risk attitudes.
Abstract: Grocery stockpiling is a common behavioral response to the emergence of disasters. We conceptualize stockpiling as a result of an increase in the fixed cost of making grocery trips. Using a model of household shopping and inventory management, we conduct a laboratory experiment, where stockpiling increases 81% with an increase in trip fixed cost, 64% with imposition of purchase limits, and 42% with price reductions relative to an experiment control. Estimating grocery-cost elasticities of demand of 1.7, we estimate COVID-19 increased fixed cost of grocery shopping by 29%. We find that imposition of purchase limits can exacerbate shortage situations.
Abstract: Climate change is expected to increase the frequency and severity of hurricanes. While aggregate ex post costs of hurricanes are frequently estimated, less is known about the real-time public responses to such disasters. Without causal evidence at granular levels, multi-stakeholder response to extreme weather is challenging, particularly in terms of food supply chains. Considering the 2022 Hurricane Ian landfall in Florida, we show its impact on (i) state-level aggregate food grocery sales across 10 food categories, and (ii) debit/credit card holding consumers' spending at convenience, general retail, and grocery stores. We show how consumers' food shopping behavior dynamically evolved from the first government advisory on Hurricane Ian, hence presenting comprehensive evidence on consumers food shopping during and around the hurricane. Food grocery stockpiling is evident across all food categories, particularly in commercially prepared food, beverages, and meat/egg/nut categories. Despite sharp declines in food sales during Hurricane Ian, there was a pronounced rebound post-hurricane, except for fruits. Upon hearing the earliest news of hurricane, consumers bought in bulk at general retail stores. However, consumers utilized convenience and grocery stores as hurricane approached. We show that early warnings helped Floridians to prepare for the hurricane in terms of food acquisition, but there were likely substantial consumer welfare losses due to potential food waste. As panic buying puts stress on food supply chains and potentially limits food availability for some consumers, this research highlights the need to consider impacts of alternative warnings and supply chain solutions in the midst of extreme weather events.
Abstract: Little is known about the impact of natural disasters on food hardship in the United States. Using a nationally representative survey sample, this study estimates the causal effect of disaster displacement and property damage on household food insufficiency. Household displacement increases food insufficiency by 9.6 percentage points on average, with variations depending on the duration of displacement and the severity of property damages. This study offers insights for policymakers and organizations involved in disaster recovery and food security initiatives, emphasizing the need to understand and address the detrimental effects of natural disasters on food security.
Abstract: The U.S. meatpacking industry is part of a complex meat supply chain. Understanding its vulnerability requires a consideration of the industry's internal and external factors that are spatially heterogeneous. We introduce the county-level Meatpacking Risk Index score, which identifies the riskiness or spatial vulnerability of the U.S. meatpacking industry. Our index is constructed from three county-level indices: (i) potential meatpacking output loss from shock events, (ii) social vulnerability, and (iii) community resilience. A total of 376 (1,445) counties classify as high-risk (low-risk) counties for meatpacking production. Our validation exercise shows that the index can correctly distinguish between high- and low-risk counties, in terms of meatpacking product losses, when exposed to exogenous shocks. Investor and current meat packers may use the index to locate in places with lower risks and disruptions. State and federal governments may use the index to reduce county-level vulnerabilities, and attract investments.
Abstract: We exploit spatial and temporal variation in natural disasters in the United States via a generalized differences-in-differences approach to identify the impact of natural disasters on households’ food-at-home (FAH) spending and quality from 2005 to 2016. Using the Storm Events Database and the Nielsen Consumer Panel Data, we find that floods (hurricanes) have a persistent (immediate) effect on FAH spending. On average, highly damaging floods (hurricanes) decrease 15-day FAH spending by about $1-$2 ($7) in 90 days (30 days) after the events. The FAH spending effect of natural disasters works through both income and price channels. We also find that the natural disasters have an inconsequential or no impact on FAH quality. Our results are robust to the inclusion of county-specific linear trends. Our findings could be of interest to post-disaster relief organizations and their programs.
Abstract: In this study, I investigate household consumption response to realized income shocks when households have reference-dependent preferences for consumption expenditures. I consider households’ reference level of consumption expenditures in the current period to be equal to last period's expenditures. Using longitudinal data on Australian households and exploiting variation in income shocks at the household level, I estimate loss aversion in consumption expenditures. I find that losses in consumption expenditures loom about 1.4 times larger than equal value gains. The magnitude and statistical significance of the loss aversion estimate is robust to an alternative reference point that is based on the average expenditures of last two periods. I also show that retirement-age households (working-age households) have a symmetric (asymmetric) consumption response to realized income shocks.