Upgrading Slum Infrastructure in Mexico

Last registered on December 02, 2016

Pre-Trial

Trial Information

General Information

Title
Upgrading Slum Infrastructure in Mexico
RCT ID
AEARCTR-0001640
Initial registration date
December 02, 2016
Last updated
December 02, 2016, 1:36 PM EST

Locations

Region

Primary Investigator

Affiliation
IRPS/UCSD

Other Primary Investigator(s)

PI Affiliation
UT San Antonio
PI Affiliation
El Colegio de la Frontera Norte
PI Affiliation
El Colegio de la Frontera Norte

Additional Trial Information

Status
Completed
Start date
2009-03-01
End date
2014-03-01
Secondary IDs
Abstract
This paper reports on the results of a large infrastructure investment experiment in which $68 million in spending was randomly allocated across a set of low-income urban neighborhoods in Mexico. We show that the program resulted in meaningful improvements in the access of the average household to numerous forms of infrastructure, such as electric lighting, street lights, sidewalks, medians, and road paving. We exploit the study’s randomized saturation design to understand how spillovers at the municipal level might work to undermine causal inference when multiple levels of government provide forms of investments that are close substitutes. Our results suggest that the strategic response of municipal governments to federal spending is muted. The program increased the aggregate real estate value in program neighborhoods by two dollars for every dollar invested.
External Link(s)

Registration Citation

Citation
, et al. 2016. "Upgrading Slum Infrastructure in Mexico." AEA RCT Registry. December 02. https://doi.org/10.1257/rct.1640-1.0
Former Citation
, et al. 2016. "Upgrading Slum Infrastructure in Mexico." AEA RCT Registry. December 02. https://www.socialscienceregistry.org/trials/1640/history/12222
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
The intervention was provision of a federal block grant with matching requirements to municipalities for infrastructure improvement in low-income urban areas. Primary expenditures were on heavy infrastructure such as roads, water, sewage, lighting, sidewalks; but funds were also used for community centers, parks, and sports facilities. Eligible neighborhoods were identified in every participating municipality, and a randomly selected fraction of eligible neighborhoods in each municipality receive the treatment.
Intervention Start Date
2009-03-01
Intervention End Date
2012-03-31

Primary Outcomes

Primary Outcomes (end points)
An index of basic infrastructure quality (e.g. road quality, water access, sewerage, street lighting, and sidewalks); change in municipal spending; real estate value of raw land; private investment in housing
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
All eligible neighborhoods in the municipalities participating in the program were part of the sample. A random fraction of eligible neighborhoods in each municipality were assigned to the treatment group. Treatment was a block grant to be spent on improving basic infrastructure in low-income urban neighborhoods. This included introducing or expanding things such as water access, sewerage, road pavement, street lights, community sports fields, etc. The researchers conducted a baseline and a follow up survey to create a panel dataset; however, panel-tracking was performed at the house-level, not the household level, as the researchers were interested in changes in structure attributes.

Since the level of treatment has an endogenous component due to the number of eligible neighborhoods in a city, the researchers instrument for the treatment with the randomly assigned fraction of eligible neighborhoods. The researchers then examined evidence of flypaper effects, the impact of the treatment at the neighborhood level, evidence for spillover effects, impacts of private investment, impacts on real estate values, and impacts on political behavior.
Experimental Design Details
Randomization Method
A random fraction between .1 and .9 of each municipality's eligible neighborhoods was selected for treatment.
Randomization Unit
Neighborhoods ("polygons")
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
370 neighborhoods ("polygons")
Sample size: planned number of observations
10,670 houses (structures)
Sample size (or number of clusters) by treatment arms
Treatment group: 176 neighborhoods
Control Group: 194 neighborhoods
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
March 31, 2013, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
March 31, 2012, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
342 polygons
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
9,702 houses (structures)
Final Sample Size (or Number of Clusters) by Treatment Arms
Treatment group: 155 polygons Control group: 187 polygons
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
This paper reports on the results of a large infrastructure investment experiment in which $68 million in spending was randomly allocated across a set of low-income urban neighborhoods in Mexico. We show that the program resulted in meaningful improvements in the access of the
average household to numerous forms of infrastructure, such as electric lighting, street lights,
sidewalks, medians, and road paving. We exploit the study’s randomized saturation design to
understand how spillovers at the municipal level might work to undermine causal inference when
multiple levels of government provide forms of investments that are close substitutes. Our results
suggest that the strategic response of municipal governments to federal spending is muted. The
program increased the aggregate real estate value in program neighborhoods by two dollars for every
dollar invested.
Citation
McIntosh, Craig; Alegría, Tito; Ordóñez, Gerardo; & Zenteno, René. (2014). INFRASTRUCTURE UPGRADING AND BUDGETING SPILLOVERS: MEXICO’S HÁBITAT EXPERIMENT. UC Berkeley: Center for Effective Global Action. Retrieved from: http://escholarship.org/uc/item/0gq587m0

Reports & Other Materials