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

Last registered on February 04, 2025
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Pre-Trial

Trial Information

General Information

Title
High Frequency Engel and Supply Curves in General Equilibrium: Experimental Evidence from Large Universal Cash Transfers in Malawi
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
February 04, 2025, 2:18 AM EST

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

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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
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PI Name
Bilal Siddiqi
PI Affiliation
IDinsight
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PI Name
Daniel Stein
PI Affiliation
IDinsight
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PI Name
Tilman Graff
PI Affiliation
Harvard University
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PI Name
John Walker
PI Affiliation
Oxford University
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PI Name
Winnie Mughogho
PI Affiliation
Queen Mary University London
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Additional Trial Information

Status
On going
Start date
2023-10-13
End date
2028-12-31
Keywords
Behavior, Education, Electoral, Finance & Microfinance, Firms & Productivity, Gender, Health, Labor, 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 (Phase I) and Chiradzulu Districts (Phase II) in Malawi on household outcomes, including expenditure, enterprise outcomes, and on market activity and prices. The rollout of the approx. 100 million in cash transfers to approx. 200,000 recipients by the NGO GiveDirectly is randomized, and treatment intensity varies across three geographical levels: a) the traditional authority, b) Group Village Headman (GVHs), an administrative unit corresponding approximately to a market catchment area, and c) villages.

Using random variation in treatment timing, together with high-frequency price data for over 100 products (monthly or bi-weekly), 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 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.

In Phase II, we additionally inform a random subset of traders in treated market ex-ante about upcoming demand increases (the IRFs estimated in Phase I). Predicted demand shocks naturally vary in size, and we additionally vary the salience of the temporary or permanent nature of the shock. This allows us to test whether demand predictability and variability affect firm and market-level supply dynamics, and draw inference on the competitive environment within which firms set prices.
External Link(s)

Registration Citation

Citation
Egger, Dennis et al. 2025. "High Frequency Engel and Supply Curves in General Equilibrium: Experimental Evidence from Large Universal Cash Transfers in Malawi." AEA RCT Registry. February 04. https://doi.org/10.1257/rct.12550-2.0
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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2023-11-13
Intervention End Date
2025-02-04

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)
- child mortality
- other household outcomes, including assets, labor supply, food security, mental health, female empowerment, etc.
Primary Outcomes (explanation)
for details, see the pre-analysis plan

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
not public until completion of the intervention to maintain the integrity of the study.
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
Phase I: Treatment is assigned at the GVH level, randomly across 25 GVHs (and 9 additional GVHs which were treated non-randomly before the start of the experiment).
Phase II: Treatment is assigned across 10 TAs, 113 GVHs, and approx. 900 villages as described above. Information treatments are randomized at the individual enterprise level (though for later expansions, we may consider clustering treatment intensity at the market-level).
Sample size: planned number of observations
Phase I: 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. Phase II: This is split into two stages, 344 villages in stage I, and approx. 600 villages in stage II. Households: We will census all households at baseline, and survey 8 households per village, 2752 in stage I, and approximately 8,000 households across both stages. Households will be surveyed in person at baseline, as well as 1-2 months after transfers, 5-6 months after transfers, and 11-12 months after transfers. Enterprises: We will census all enterprises operating in all approx. 80-100 weekly markets within Chiradzulu, monthly during the period of most intense transfers (approx. 2-3 months prior, and up to 6 months after the large transfers), and bi-monthly or less frequently thereafter. We will survey approx. 50 sellers per market in a panel of over 4,000 sellers to be followed over time.
Sample size (or number of clusters) by treatment arms
Phase I: Details in PAP
Phase II: Details in PAP
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 Oxford
IRB Approval Date
2023-09-14
IRB Approval Number
ECONCIA22-23-25
IRB Name
National Comission for Science & Technology
IRB Approval Date
2023-11-08
IRB Approval Number
P.10/23/808
IRB Name
University of Oxford
IRB Approval Date
2025-01-24
IRB Approval Number
DREC - 1107211
Analysis Plan

Analysis Plan Documents

Pre-Analysis Plan

MD5: 48dc423dc5c9fadf664a3c990a9eacc8

SHA1: de25ee859fd950515b0b357c0f4e7a137b3f871b

Uploaded At: January 16, 2024