Indirect Effects of Access to Finance

Last registered on May 30, 2022

View Trial History

Pre-Trial

Trial Information

General Information

Title

Indirect Effects of Access to Finance

RCT ID

AEARCTR-0009506

Initial registration date

May 27, 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

May 30, 2022, 8:15 AM EDT

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

Locations

Country

China

Region

Primary Investigator

Name

Jing Cai

Affiliation

University of Maryland

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Adam Szeidl

PI Affiliation

Central European University

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2013-07-01

End date

2020-09-01

Keywords

Finance & Microfinance, Firms & Productivity

Additional Keywords

JEL code(s)

Secondary IDs

Prior work

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

Abstract

We created experimental variation across local markets in China in the share of firms having access to a new loan product, to measure the direct and indirect effects of access to finance. We find that: (1) Access to finance had a large positive direct effect on the performance of treated firms. (2) Access to finance had a similar-sized negative indirect effect on the performance of firms with treated competitors. Due to these opposing effects, we do not find detectable gains in aggregate producer surplus. (3) Access to finance had a positive direct effect on business practices, service quality, and consumer satisfaction, and a negative effect on price. None of these effects were offset by indirect effects, suggesting net gains in consumer surplus. (4) Two additional indirect effects were active: diffusion of borrowing to firms with treated peers, and diffusion of demand to firms with treated neighbors. (5) Combining several effects in a model- based evaluation, we estimate that the loan had a private return of 74%, most of which was offset by losses to competitors, and a social return of 60%, most of which was driven by gains to consumers.

External Link(s)

Registration Citation

Citation

Cai, Jing and Adam Szeidl. 2022. "Indirect Effects of Access to Finance." AEA RCT Registry. May 30. https://doi.org/10.1257/rct.9506-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

We created experimental variation across local markets in China in the share of firms having access to a new loan product, to measure the direct and indirect effects of access to finance.

Intervention Start Date

2013-08-01

Intervention End Date

2014-08-01

Primary Outcomes

Primary Outcomes (end points)

Firm revenue, profit, borrowing

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Firm management, employment, price

Secondary Outcomes (explanation)

Experimental Design

We introduced the treatment using a combination of a market-level and a firm-level randomization. Out of our 78 markets, we randomized 37 to have high treatment intensity, 10 markets to have medium treatment intensity, and 31 markets to pure control.5 In high treatment intensity markets we treated a randomly selected 80% of firms; in medium intensity markets we treated a randomly selected 50% of firms; and in pure control markets we treated no firms. Every treated firm was visited every month for a year by a loan officer who provided information about the new loan product, and if the firm decided to apply, provided help with the application process, including filling in the relevant forms.

Experimental Design Details

Randomization Method

randomization done in office by a computer

Randomization Unit

market and firms

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

78 markets

Sample size: planned number of observations

3173 firms

Sample size (or number of clusters) by treatment arms

Out of our 78 markets, we randomized 37 to have high treatment intensity, 10 markets to have medium treatment intensity, and 31 markets to pure control. Among the 3173 sample firms, 1436 were treated.

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

Supporting Documents and Materials

IRB