Macroprudential Policy and Housing Market Expectations

Last registered on October 25, 2022
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Pre-Trial

Trial Information

General Information

Title
Macroprudential Policy and Housing Market Expectations
RCT ID
AEARCTR-0010049
Initial registration date
October 25, 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
October 25, 2022, 2:49 PM EDT

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

Locations

Country
United Kingdom of Great Britain and Northern Ireland
Region

Primary Investigator

Name
Shihan Xie
Affiliation
University of Illinois at Urbana-Champaign
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Other Primary Investigator(s)

PI Name
Pei Kuang
PI Affiliation
University of Birmingham
Contact Investigator
PI Name
Li Tang
PI Affiliation
Middlesex University London
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PI Name
Kaushik Mitra
PI Affiliation
University of Birmingham
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Additional Trial Information

Status
Completed
Start date
2022-08-18
End date
2022-08-20
Keywords
Behavior
Additional Keywords
housing price expectation, macroprudential policies
JEL code(s)
E60, E70, E21
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We conduct a large sample survey in the UK to study the effects of various housing market policy changes on house price expectations using information treatment experiments.
External Link(s)

Registration Citation

Citation
Kuang, Pei et al. 2022. "Macroprudential Policy and Housing Market Expectations." AEA RCT Registry. October 25. https://doi.org/10.1257/rct.10049-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Respondents are randomly assigned into one of 7 groups (1 control and 6 treatment groups). We consider three macroprudential policies in the UK housing market, namely the mortgage loan-to-income (LTI) ratio, buy-to-let mortgage loan-to-value (LTV) ratio and owner-occupier mortgage loan-to-value ratio. For each policy, we consider 2 scenarios - a fall- and a rise-scenario.
Intervention Start Date
2022-08-18
Intervention End Date
2022-08-19

Primary Outcomes

Primary Outcomes (end points)
Housing price expectation revisions and other behavioral changes
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Pre-treatment: The survey starts with a brief instruction on how to answer each type of question and a few questions to collect information about respondents’ geographic location in the UK, home ownership, and type of mortgage if they are mortgage payers. We then elicit respondents’ point and probabilistic forecasts of house price growth at their local authority over the next 12 months. In addition, we collect a range of additional 12-months-ahead macroeconomic forecasts and directly ask for their intention of buying a house, plus the purpose
of the purchase.

Treatments: Respondents are randomly assigned into one of 7 groups (1 control and 6 treatment groups). We consider three macroprudential policies in the UK housing market, namely the mortgage loan-to-income (LTI) ratio, buy-to-let mortgage loan-to-value (LTV) ratio and owner-occupier mortgage loan-to-value ratio. For each policy, we consider 2 scenarios - a fall- and a rise-scenario.

Post-treatment: respondents are asked to complete questions based on the policy scenario they received as treatment. A series of
structured questions solicit if they believe under the treatment scenario conditions of the housing market would improve. Next, they are presented with a quantitative question and a series of structured questions to track their predictions of overall and several categorical non-housing spending changes, respectively. Then, we re-elicit their point house price growth forecasts over the next 12 months and 5 years, respectively, plus predicted change in rent expenses. An open-ended question is used to capture narratives of their 12-month house price change forecast.
Experimental Design Details
Randomization Method
Randomization is done by the survey platform Prolific
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
1 online wave
Sample size: planned number of observations
3500 individual participants
Sample size (or number of clusters) by treatment arms
700 individuals control, 2800 individuals treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Birmingham
IRB Approval Date
2022-06-27
IRB Approval Number
Details not available
Analysis Plan

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