Home Bias: Investigating the Impact of State Borders on Internal Migration

Last registered on January 18, 2023

View Trial History

Pre-Trial

Trial Information

General Information

Title

Home Bias: Investigating the Impact of State Borders on Internal Migration

RCT ID

AEARCTR-0009590

Initial registration date

June 15, 2022

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

June 17, 2022, 4:16 PM EDT

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

Last updated

January 18, 2023, 1:51 PM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Country

United States of America

Region

Primary Investigator

Name

Riley Wilson

Affiliation

Brigham Young University

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2022-06-20

End date

2023-08-31

Keywords

Labor

Additional Keywords

Migration, Mobility

JEL code(s)

J6, R1

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

Observational data suggests that human mobility (migration and commuting) drops off discretely at state borders. This online survey experiment will test if state borders have a causal effect on people's stated preference to move, holding other features of the potential destination constant and separate from the effect of maintaining/severing social ties to friends and family. In addition, by experimentally manipulating income differences associated with the move, I can back out people's willingness to pay to avoid moving across state lines and determine the economic cost of state borders.

External Link(s)

Registration Citation

Citation

Wilson, Riley. 2023. "Home Bias: Investigating the Impact of State Borders on Internal Migration." AEA RCT Registry. January 18. https://doi.org/10.1257/rct.9590-1.2

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

In the survey, participants will view scenarios that involve an increase in income, but require a move, of about 100 miles. I will intervene by randomly assigning participants to a scenario that does/does not include a move across state lines. I will also intervene by randomly assigning participants to a scenario that does/does not include family and friends nearby.

Intervention Start Date

2022-06-20

Intervention End Date

2023-01-31

Primary Outcomes

Primary Outcomes (end points)

Reported percent chance of moving, Difference in probability of moving between two scenarios.

Primary Outcomes (explanation)

This is measure is reported by the individual. The difference will be constructed as the probability in the first experiment minus the probability in the second reverse experiment.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

In the survey, participants will view scenarios that involve an increase in income, but require a move, of about 100 miles. They will then be asked to report the percent chance that they would move and the percent chance that they would stay. Participants will be randomized so that they view a scenario that involves either a within state or a cross-state move. They will also be independently randomized whether or not the new location has family and current friends living nearby.

Experimental Design Details

In the survey, participants will view scenarios that involve an increase in income, but require a move, of about 100 miles. Depending on the treatment arm, the scenario will specify whether or not this requires a cross-state move and whether or not family and current friends will be nearby. The survey will have 12 treatment arms that participants will enter with equal probability. First, participants will be randomized as to whether the scenario they are shown involved a within state or cross-state move. Second, participants will be independently randomized whether or not there is family or current friends that live near the potential destination. Third, participants will be independently randomized to view scenarios that include a 10%, 20%, or 50% increase in income relative to their current income. They will then be asked to report the percent chance that they would move to the destination and the percent chance that they would stay. These must sum to 100.

Prior to the experimental scenarios, I will ask about the state where the individual currently lives, the state they were born in, and if they moved as a child. After the experimental scenario, I will ask which state the individual calls their home state. I can then explore heterogenous responses based on these responses. For example, is the effect of moving across state lines stronger for people living in their state of birth or the state they call their home state?

Randomization Method

Randomization will be done by Qualtrics in the online survey.

Randomization Unit

All treatment randomization will be done at the individual level.

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

1,200 individuals.

Sample size: planned number of observations

1,200 individuals.

Sample size (or number of clusters) by treatment arms

Planned sample sizes:
Same state, social ties nearby, 10% income: 100 individuals
Same state, no social ties nearby, 10% income: 100 individuals
Different state, social ties nearby, 10% income: 100 individuals
Different state, no social ties nearby, 10% income: 100 individuals
Same state, social ties nearby, 20% income: 100 individuals
Same state, no social ties nearby, 20% income: 100 individuals
Different state, social ties nearby, 20% income: 100 individuals
Different state, no social ties nearby, 20% income: 100 individuals
Same state, social ties nearby, 50% income: 100 individuals
Same state, no social ties nearby, 50% income: 100 individuals
Different state, social ties nearby, 50% income: 100 individuals
Different state, no social ties nearby, 50% income: 100 individuals

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

IRB