High Frequency Engel and Supply Curves in General Equilibrium: Experimental Evidence from Large Universal Cash Transfers in Malawi

Last registered on January 16, 2024

Pre-Trial

General Information

Title

RCT ID

AEARCTR-0012550

Initial registration date

November 21, 2023

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

December 06, 2023, 7:43 AM EST

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

Last updated

January 16, 2024, 4:37 AM EST

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

Locations

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Primary Investigator

Name

Dennis Egger

Affiliation

Oxford University

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Other Primary Investigator(s)

PI Name

Philipp Kastrau

PI Affiliation

IDinsight

Contact Investigator

PI Name

Bilal Siddiqi

PI Affiliation

IDinsight

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PI Name

Daniel Stein

PI Affiliation

IDinsight

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Additional Trial Information

Status

On going

Start date

2023-10-13

End date

2025-11-30

Keywords

Finance & Microfinance, Firms & Productivity, Gender, Welfare

Additional Keywords

universal cash transfers, general equilibrium effects, inflation, supply curves, Engel curves, high frequency

JEL code(s)

Secondary IDs

Prior work

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

Abstract

Understanding how firms and markets shape local supply curves in general equilibrium, to which degree economies can absorb (and change in response to) large local demand shocks, and how consumers shopping patterns and competitive pressures respond is crucial for understanding long-term development and the effects of macroeconomic policies. We estimate the high-frequency causal impacts of universal USD 550 cash transfers to every adult in the Khongoni District in Malawi on expenditure, prices and market activity. The rollout of the 45 million in cash transfers by the NGO GiveDirectly is randomized across 34 Group Village Headman (GVHs), an administrative unit corresponding approximately to a market catchment area, will reach over 80,000 individuals over the course of 12 months, and correspond to 90% of baseline GDP. Using random variation in treatment timing, together with bi-weekly price data for over 100 products and monthly enterprise surveys in all markets within the study area and a matched sample of markets outside the study area, as well as monthly expenditure surveys with 2500 eligible households, we document high-frequency marginal propensities to consume by product (Engel curves), inflationary impacts, expenditure switching of households across markets, and changes in resulting market activity and the productive environment. This will allow us to trace out short- and medium run supply curves at the firm- and market level.

External Link(s)

Registration Citation

Citation

Egger, Dennis et al. 2024. "High Frequency Engel and Supply Curves in General Equilibrium: Experimental Evidence from Large Universal Cash Transfers in Malawi." AEA RCT Registry. January 16. https://doi.org/10.1257/rct.12550-1.1

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

Intervention Start Date

2023-11-13

Intervention End Date

2024-11-19

Primary Outcomes

Primary Outcomes (end points)

- household expenditure (by product group, by location/market)
- output price inflation (by product group)
- market activity (total revenue, profits, number of customers, labor supply)
- imports (intermediate input purchases from within vs. outside the study area)

Primary Outcomes (explanation)

for details, see the pre-analysis plan

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

The Khongoni District in Malawi is divided into 34 Group Village Headman (GVH) administrative units. GVHs have a population of 2000 adults, or approximately 800 households on average. Treatment is randomized at the level of the GVH. Prior to the start of this study, GiveDirectly (GD) had already worked in 9 GVHs, which were selected quasi-randomly. Treatment order among the remaining 25 GVHs (the 'experimental sample') was randomized. GD will sequentially target GVHs in this randomized order, and the actual rollout timing will depend on logistical constraints and rollout capacity. We anticipate an average of 2-3 GVHs will be treated each month, for an overall rollout window of approximabely 12 months.

Experimental Design Details

Not available

Randomization Method

The order was randomized by a random number generator on a computer (STATA)

Randomization Unit

The Khongoni District in Malawi is divided into Group Village Headman (GVH) administrative units. GVHs have a population of 2000 adults, or approximately 800 households on average. Treatment is randomized at the level of the GVH, and all households within a GVH. Enrolment for all GVH included in a treatment wave will happen within the same calendar month, and transfers will typically be initiated the last Tuesday of the month after enrolment which we term experimental start date (though there may be some delays due to verification, etc.)

Was the treatment clustered?

Yes

Experiment Characteristics

Sample size: planned number of clusters

25 clusters in the experimental sample. 9 additional clusters for quasi-random analyses.

Sample size: planned number of observations

Households: We will survey 2500 households (100 per GVH) for a total of 9 rounds, or a total of 22,500 hosuehold-by-month observations Prices: We will collect up to 2 price quotes for 82 goods and services at 51 markets for a total of 24 bi-weekly rounds, or a total of over 200,736 price quotes. Market sellers: We will survey 20 sellers at each of the 51 markets, monthly for a total of 12 rounds, or a total of 12,240 seller-by-month observations.

Sample size (or number of clusters) by treatment arms

Households: This is an event-study design. All GVHs within Khongoni will eventually be treated. We will have at least 1 (sometimes more) baseline/control observation before treatment occurs for each household, (t = - 1), 1 observation in the month where the small token transfer goes out (t = 0) , and 7 observations thereafter in months t = {1, 2, 4, 6, 8, 10, 12} after the small transfer.

Markets (prices and sellers): For markets (prices and seller activity), we will use baseline expenditure shares to determine treatment intensity. We will have 14 official and 24 unofficial markets within the study area. At baseline, we survey 42 official markets outside the stury area, of which we select 14 as a comparison group based on baseline matching. Our total analysis sample is therefore 51 markets.

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

Supporting Documents and Materials

IRB