How Important are Investment Indivisibilities for Development?

Last registered on June 01, 2023


Trial Information

General Information

How Important are Investment Indivisibilities for Development?
Initial registration date
June 20, 2017

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 21, 2017, 12:50 PM EDT

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

Last updated
June 01, 2023, 3:04 PM EDT

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


Primary Investigator

University of Virginia

Other Primary Investigator(s)

PI Affiliation
University of Notre Dame
PI Affiliation
PI Affiliation
Tufts University

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Theoretically, indivisible investments together with financial frictions can lower development, generate poverty traps, and lead agents to become risk-loving. Using experimental cash grants involving a choice between a safer, low payoff and a riskier, large payoff lottery, we find that 27 percent choose the riskier, larger lottery. Small grant winners invest in livestock and business inventory, while large grant winners invest in land, which exhibits high capital gains. Our quantitative model shows that the aggregate effects of financial deepening are sizable if the indivisible investment can be accumulated (e.g., capital) but not if it is in fixed supply (e.g., land).
External Link(s)

Registration Citation

Kaboski, Joseph et al. 2023. "How Important are Investment Indivisibilities for Development?." AEA RCT Registry. June 01.
Former Citation
Kaboski, Joseph et al. 2023. "How Important are Investment Indivisibilities for Development?." AEA RCT Registry. June 01.
Experimental Details


The intervention allowed primarily unbanked households in peri-urban and rural western Uganda to choose between a less risky and riskier lottery with a smaller and larger payout, respectively (50% chance of winning $100 versus a 10% chance of winning $485). Conditional on lottery choice, winning the payout was random. The control group, who did not win a lottery, received a $1 cash transfer. Both lottery winnings and the consolation transfer were allocated to study participants via mobile money.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Outcome categories: (1) investment, in aggregate as well as disaggregated between lumpy and divisible agriculture/livestock and business investments, (2) land investment, in terms of land value and land quantity, (3) land use and land productivity, (4) savings, (5) household income and labor provision, in aggregate as well as disaggregated between agriculture/livestock and business income, (6) returns to the cash grants, (7) household consumption, and (8) use of/engagement in financial services (including outstanding credit, as well as formal versus informal sources of credit and savings)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This study uses a randomized controlled trial design to understand how households react to an unanticipated (positive) shock to their wealth and how this relates to their time preferences and risk preferences. Households are given a choice between a lottery with a 50% probability of getting $100, or a 10% probability of getting $485. Moreover, they are given a choice between receiving the transfer tomorrow or receiving a somewhat larger amount one month later.
Experimental Design Details
Randomization Method
Computerized randomization via algorithm in survey software, done in real-time during the cash grant lottery
Randomization Unit
participant level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
1,048 households
Sample size: planned number of observations
1,048 households
Sample size (or number of clusters) by treatment arms
590 control households, 373 small ($100) grant winners, 85 large ($500) grant winners (over-sampled)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Notre Dame
IRB Approval Date
IRB Approval Number
IRB Name
University of Virginia
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials