Source: VIRGINIA POLYTECHNIC INSTITUTE submitted to NRP
FOOD AT HOME AND FOOD AWAY FROM HOME: THE WELFARE EFFECTS
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
1031210
Grant No.
2023-67023-40799
Cumulative Award Amt.
$555,220.00
Proposal No.
2022-12144
Multistate No.
(N/A)
Project Start Date
Aug 15, 2023
Project End Date
Aug 14, 2026
Grant Year
2023
Program Code
[A1641]- Agriculture Economics and Rural Communities: Markets and Trade
Recipient Organization
VIRGINIA POLYTECHNIC INSTITUTE
(N/A)
BLACKSBURG,VA 24061
Performing Department
(N/A)
Non Technical Summary
Two facts in the U.S. food system motivate this project. First, over the last 10 years the share of food expenditures spent on food-away-from-home (FAFH) has overtaken the share spent on food-at-home (FAH). Second, corresponding to this trend, the farmer's share of the FAFH food dollar has declined while the share of the FAH dollar has generally increased. These two facts lead to multiple questions regarding price and quantity relationships, market structures, and welfare distributions throughout the market channel that have not been explored or answered. Our project aims to understand the effects of the changing pattern of consumers' expenditure on food-at-home (FAH) to food-away-from-home (FAFH) on welfare distribution throughout the food supply chain, while recognizing that the effects will depend on the underlying market structure and consumer socioeconomic, demographic, and environmental factors. We formulate four interconnected objectives: estimation and decomposition of the food-farm marketing margin, estimation of consumer surplus through a demand system framework, a flexible theoretical model of market structure allowing for imperfect competition in the food supply chain, and welfare calculation for a range of alternative scenarios and policies. Consequently, the project will integrate four well-established research areas that have not been integrated before to understand important policy-relevant questions regarding price and quantity relationships, market structure, and welfare distribution throughout the market channel. To achieve our objectives, we will utilize public-use consumer expenditure survey microdata from the Bureau of Labor Statistics, NBER-CES Manufacturing Industry Database, and estimates from the literature. Our integrated framework will answer important policy and scenario questions related to socioeconomic and demographic profile of consumers, COVID-19, Ukraine war, etc. on welfare distribution throughout the food supply chain, while extending our knowledge on the four strands of literature and a unique way of integrating them.
Animal Health Component
40%
Research Effort Categories
Basic
60%
Applied
40%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
60362303010100%
Knowledge Area
603 - Market Economics;

Subject Of Investigation
6230 - Marketing systems and sectors thereof;

Field Of Science
3010 - Economics;
Goals / Objectives
Objective 1: Estimate and decompose the effect of FAH and FAFH prices on the food-farm marketing margin while considering the effects of changes in socioeconomic, demographic, and environmental factors, such as COVID-19.Objective 2: Estimate the change in consumer surplus for FAH and FAFH corresponding to the change in FAH and FAFH expenditures and how differences in socioeconomic, demographic, and environmental factors, such as COVID-19, affect the surplus measures.Objective 3: Develop an integrated theoretical model of market structure that allows for the interaction of market power and consumer demand factors by considering varying degrees of market power of the intermediary processing sector, for both upstream and downstream markets, that will have market differentiation as a function of socioeconomic, demographic, and environmental factors, such as the COVID-19.Objective 4: Calibrate and simulate the economic welfare changes for consumers, producers, and the intermediary processing sector as FAH and FAFH expenditures change as functions of socioeconomic, demographics and environmental factors, such as COVID-19, while also exploring the interacting effects of intermediary market power, both on the input- and output-side.
Project Methods
Efforts: The analysis will proceed according to the objectives. For objectives 1 and 2, we will assemble data from several sources: Consumer expenditure survey (CES) microdata from the Bureau of Labor Statistics (BLS), the NBER-CES Manufacturing Industry Database (NBER-CES 2022), and the Office of Productivity and Technology of BLS cost and productivity data, and price indices from BLS. For objective 1, we will develop a vector autoregressive time series system consisting of equations for the price of FAH, FAFH, Food and the Farm price. This will allow us to decompose the effects of changes in the FAFH and FAH prices on the farm price and margin and how the exogenous drivers have affected the FAFH, FAH, food, and farm prices differently. For objective 2, we will estimate the Lewbel and Pendakur (2009) Exact Affine Stone Index (EASI) demand system. The demand system will include FAH and FAFH as well as a broader set of goods (e.g. utilities, transportation, apparel) and allow the elasticity estimates to vary by other variables such as socioeconomics, demographics, and environmental factors. From this system we will calculate consumer surplus for FAH and FAFH and and how they may differ by socioeconomic, demographic, and environmental factors.For objectives 3 we will develop a theoretical model of the FAH and FAFH and the Farm sector that allows foar varying degrees of market power to interact with the demand system attributes of socioeconomic, demographic, and environmental factors.For objective 4 we will use the model developed in objective 3 to simulate various changes of sociodemographic, demographic, environemental as they interact with market power specifications to determine how welfare for consumers, producers, and intermediary processors change.Evaluation: For each objective we will have, and will be required, milestones on data collection and data analysis, and interpretation. The project is very sequential and thus will proceed sequentially, with accompanying stages needed to be completed before moving to the next objective.

Progress 08/15/24 to 08/14/25

Outputs
Target Audience:No audiences were targeted during this time frame as we had a grduate student leave the university and we had to train a new graduate student to work on the project. Another graduate studentworking on the first objective had some significant health issues which also slowed down the work. Changes/Problems:As alluded to, the main challenge was in terms of losing a key graduate student during the last time period. None of the data or methods changed, but the progresses was slowed by having to recruit a new studentand onboard the student who was not familiar with the project or methods. What opportunities for training and professional development has the project provided?During this time we lost a key graduate student who had been working on the project since its beginning as he decided to leave school. We therefore had to recruit a new studentand onboard this student. This meant training this student in all aspcts of the project, data, and analysis. While the student has leaned many new skills and has done well, this slowed us down a great deal. How have the results been disseminated to communities of interest? Nothing Reported What do you plan to do during the next reporting period to accomplish the goals?Objective 1 probabably needs a month or so more work and will be completed. Specifically, this just involves some polishing of the writing up of the results. We also believe that objective 2 will be completed within 6 months. We are now at the point where we are ready to start estimating the EASI demandsystem with quarterly data and taking into account demographic effects such that the demand elasticites will be functions of the demographic variables. This is important because for objective 3 market power and welfare estimates depend on how elasticities differ by demographics. Thus this will then allow us to turn to objects 3 and 4, which we believe we will make signifincat progress on in the last half of the next period.

Impacts
What was accomplished under these goals? Objective 1: Work continued on objective one by decomposing the effects of changes in food-at-home (FAH) and food-away-from-home (FAFH) prices on the total food (Food) prices. We use monthly Consumer Price Index data on FAH and FAFH from the Bureau of Labor Statistics from December 2003 to July 2024. Two Structural Vector Autoregressive (SVAR) models, one with all exogenous variables and total food price, and the other with all variables, FAH and FAFH prices, are used for our analyses. Results show that the contribution of FAH prices to total food prices is more than FAFH prices. The results from the impulse response analyses show that supply side factors such as farm product prices, transport prices, and wages have persistent positive effects on food prices. The total effect on the total food price seems to be driven by the effect on FAH, in contrast to FAFH, as the effect of almost all shocks on FAH is in the same direction as that of the total food suggesting a higher impact of FAH on total food. Forecast error variance decomposition and historical decomposition highlight the higher impact of supply related factors on food price variability. The findings from this study are important to understand how demand and supply shocks affect the inflation of different categories of food, which could ultimately affect the overall food price inflation. Objective 2: In the previous period we create an annualized data set to conduct the demand analysis. In this period, we used the same data to create a quarterly dataset that would allow us to look at the effects of more naunced temporal isses such as COVID-19 and inflation on the demand for FAH and FAFH. This took a great deal of time (see below for explantion) but we are now at the estimation stage for theEASI demand system we proposed in the project proposal. Objectives 3 and 4: This is a sequential project and objectives 3 and 4 requires the analysis of objective 2 be done first.

Publications


    Progress 08/15/23 to 08/14/24

    Outputs
    Target Audience:Intended audience is general population, professionla economists, and public policy makers with interest in food consumpetion, prices and business and consumer welfare. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Nothing Reported How have the results been disseminated to communities of interest?Partially. The intial results have been disseminated to a professionla audience. What do you plan to do during the next reporting period to accomplish the goals?We plan to refine and extend the anlysis for objectives #1 and #2 as indicated in the proposal. We also plan to start on objective #3.

    Impacts
    What was accomplished under these goals? Objective 1: Data on food-at-home (FAH), food-away-from-home (FAFH), and total food (Food) prices, along with other economic variables, such as energy prices, wage rates, farm price, and various price weights were downloaded from the Bureau of Labor Statistics (BLS). By definition, the Food price is a weighted average of the FAH and FAFH prices, so much time was spent becoming familiar with the weighting process and being able to replicate the construction of the Food price. Basic summary statitics and temporal graphs were created to get a feel for the data. To understand the dynamics and interaction of FAH and FAFH prices, and how they respond to each other and other factors, a bivariate vector autoregression (VAR) was run and impusle response functions (IRFS) and forecast error variance decomposition (FEVD). We are in the process of refining this analysis and determining the contribution to the total food price through the FAH and FAFH using these techniques. Objective 2: Prices and expenditures on food-at-home (FAH), food-away-from-home (FAFH), utilites, transportation, apparel, and other aggregate expenditure categories, along with other demographic variables, were downloaded from the Bureau of Labor Statistics (BLS). Much time was spend understanding the structure of this data to insure before beginning the process of cleaning and transforming the data to get it ready for analysis. Once this was done, we estimated a 9 equation LA-AIDS demand system to estimate the price elasticities and construct consumer welfare estimates that varied over time. We find that price changes in FAH and FAFH primarily affect their own categories, with minimal cross-category impacts. Despite the trend towards higher FAFH spending share, loss in total consumer welfare is more sensitive to FAH price change.

    Publications