Local food in times of crisis: the impact of Covid-19

Last registered on November 18, 2020

Pre-Trial

Trial Information

General Information

Title
Local food in times of crisis: the impact of Covid-19
RCT ID
AEARCTR-0006755
Initial registration date
November 18, 2020

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
November 18, 2020, 9:57 AM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Primary Investigator

Affiliation
The Pennsylvania State University

Other Primary Investigator(s)

PI Affiliation
The Pennsylvania State University
PI Affiliation
The Pennsylvania State University

Additional Trial Information

Status
In development
Start date
2020-11-20
End date
2021-02-28
Secondary IDs
Abstract
In the proposed experiment, we aim to study the impact of the current coronavirus pandemic on preferences for local food and on the support for farmers with a charitable donation decision. We also aim to distinguish the impact of individual or personal concerns from related concerns focused on the communities where these individuals live. We propose an online experiment in which participants are reminded, before answering questions about their preference for local food, about the impact of the current pandemic on either themselves or their community. We plan to recruit around 1,000 participants from the Mid-Atlantic region with the help of the survey provider Dynata LLC.
External Link(s)

Registration Citation

Citation
Jaenicke, Edward, Claudia Schmidt and Martina Vecchi. 2020. "Local food in times of crisis: the impact of Covid-19." AEA RCT Registry. November 18. https://doi.org/10.1257/rct.6755-1.0
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Experimental Details

Interventions

Intervention(s)
Respondents are randomly divided in three groups, two treatment groups and one control. Initially, participants in the two treatment groups are asked about the impact of the pandemic on either (a) their personal life and personal health and financial concerns (Individual), or (b) their local community and concerns about the health and financial situation in their local community, including local farmers and food retailers (Community).
Next, participants are asked about their preferences for local food (both fruits and vegetables, and meat products). Then they are asked to make an incentivized donation decision to charities supporting farmers, supporting farmers markets, or a food relief program.
This experimental design allows us to study the impact of individual concerns versus community concerns on preferences for local food and on the amount donated. We also investigate sources of heterogeneity in participants’ reaction to priming.
Intervention Start Date
2020-11-20
Intervention End Date
2020-12-17

Primary Outcomes

Primary Outcomes (end points)
1. Price premium for local food
2. Donation to charity
Primary Outcomes (explanation)
1. Price premium for local food: average self-reported percentage price premium for local food, collected using the “unfolding brackets method”.
2. Donations to charity, measured as average of the amounts donated to the three charitable organisations on a scale from 0 to $25. We have selected a charity supporting farmers (Farm Aid), one supporting farmers market (Farmers Market Coalition) and one committed to bringing food to people in need (World Central Kitchen).

Secondary Outcomes

Secondary Outcomes (end points)
1.a. Average percentage price premium for local fruit or vegetables
1.b. Average percentage price premium for meat or poultry
2.a. Positive donation
2.b. Average donation to “Farm Aid”
2.c. Average donation to “Farmers Market Coalition”
2.d. Average donation to “World Central Kitchen”
Secondary Outcomes (explanation)
1.a. Average self-reported percentage price premium for local fruits and vegetables, collected using the “unfolding brackets method”.
1.b. Average self-reported percentage price premium for local meat and poultry, collected using the “unfolding brackets method”.
2.a. Positive donation, indicator equal to one if a positive donation is made

Experimental Design

Experimental Design
This online experiment will take place in November-December 2020. Each participant will be asked to complete a 10-15-minutes online survey. We aim to recruit approximately 1,000 respondents from the Mid-Atlantic Region in the U.S., with the help of the survey provider Dynata, LLC.
In the first stage of the study, we randomly assign respondents to three conditions
1. Individual
2. Community
3. Control
In the Individual condition, we ask respondents about the impact of the coronavirus pandemic on their personal life and their personal financial and health concerns, and then ask them to describe the most important ways in which the pandemic has impacted their life. In the Community condition, we ask respondents about the impact of the coronavirus pandemic on their local community and their concerns for their community, and then ask them to describe the most important ways in which the pandemic has impacted their community. Asking participants to think about the impact of Covid-19 places the crisis at the top of the respondents’ mind, creating the context in which they would then consider the following questions and decisions.

In the second stage, we firstly define local food as food that was grown, produced, or processed within 50 miles from the respondents. Participants are then asked about their preferences for local food through a series of choice-based questions meant to elicit a hypothetical price premium. We select this definition of local amongst many others as commonly supported by the literature (Chambers et al., 2007; Groves, 2005; La Trobe, 2001). Moreover, Darby et al. (2008) find that consumers assign the same value to different definitions of “local” and that willingness to pay for a local attribute is independent from other features. Also, in the study we are mainly interested in the difference between treatments and not on the exact definition of local foods.
We measure the price premium for local fruit or vegetables and the price premium for local meat or poultry products with two sets of questions. The questions are adapted from Carpio et al. (2009). We select food categories instead of specific food items to avoid food-specific aspects other than preference over the local attribute (as disliking the food selected, food allergies, religious prohibitions, and others) would drive responders answers (Cranfield et al., 2012). We collect the self-reported price premium for the local food using the “unfolding brackets method”. Participants are asked are asked to indicate what they would buy between local and non-local foods, at varying price premiums for local food. The unfolding brackets mechanism involves an adaptive questionnaire with binary choices presented to participants depending on their prior choices. The first choice of the titration is between non-local and local food products at equal prices. If participants choose the local food, then the next choice will be between non-local food and 50% more expensive local food. The alternatives adjust upwards or downwards to narrow in on the indifference point (accurate to a 5% interval).

We then measure participants’ donations to charitable organisations supporting farmers, farmers markets, or a food relief program. We notify participants that a randomly selected group of participants will receive a $25 bonus. We ask participants, should they be selected for the bonus, whether they want to donate part of the $25 to three charitable organisations or keep it all for themselves. To capture individual preferences for certain charitable organisations, we ask participants to make the allocation decisions between themselves and three charities. We have selected a charity supporting farmers (Farm Aid), one supporting farmers market (Farmers Market Coalition) and one committed to bringing food to people in need (World Central Kitchen).

Respondents are then asked about their sense of community belonging using a question by Carpiano et al. (2011), and to complete the six-item short-form state anxiety inventory developed by Marteau and Bekker (1992). Afterwards, we collect respondents’ shopping habits and their agreement with six attitudinal statements regarding personal motives for purchasing local food. These responses will help capture attitudinal factors that can play a role in explaining preferences for local foods. We select the questions based on their relevance in determining preference for local food (Chinnakonda et al. 2007; Grebitus et al. 2013) andbecause these attitudes are likely to be interact with our treatment in strengthening the impact of a change in price premium due to the priming. In particular, we might expect an interaction between safety concerns and the Individual prime, and an interaction between the support for local economy and the Community prime. We ask participants’ agreement with six sentences about motives for preferring local food using five-point scales ranging from 1 (strongly disagree) to 5 (strongly agree). In particular, we ask about support for the local economy (question 1 and 2), safety (question 3), environmental concerns (question 4), and freshness and taste (questions 5 and 6). We also ask respondents about their personal definition for local food, their self-reported altruism, their frequency of charitable giving, whether they themselves or anyone in their family got infected with COVID 19 or lost their job because of the pandemic, and several demographic variables.
Experimental Design Details
Randomization Method
Randomization done by Qualtrics
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
Around 1000 respondents
Sample size: planned number of observations
Around 1000 respondents
Sample size (or number of clusters) by treatment arms
Around 330 participants for each treatment arm (Control, Individual and Community)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Our estimations have 80% power to detect effect sizes of 0.229 standard deviations for the impact of the Individual and Community prime.
IRB

Institutional Review Boards (IRBs)

IRB Name
Penn State Institutional Review Board
IRB Approval Date
2020-07-16
IRB Approval Number
STUDY00015454
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials