• http://dx.doi.org/10.18235/0011707

Libertun de Duren, Nora Ruth, et al. (2016). Replication Data for: Growing Resources for Growing Cities: Density and the Cost of Municipal Public Services in Brazil, Chile, and Mexico. IDB Open Data. https://doi.org/10.60966/kyqvaojp

1. English

What countries and municipalities are included in this dataset?

The dataset includes all municipalities in Brazil, Chile, and Mexico, covering both large metropolitan areas and smaller towns.

What years are covered by the dataset?

Two census waves are included: 2000 and 2010, allowing for comparisons over a decade.

What types of municipal services are covered?

The dataset provides indicators on water, sewerage, and trash collection coverage, as well as other key public service measures.

Can I analyze urban population density and municipal service delivery?

Yes. The dataset contains population, land area, and service coverage indicators that can be combined to study urban population density and municipal service outcomes.

Does the dataset allow analysis of urban growth and municipal expenditure?

Yes. By linking population changes to municipal budget data, researchers can evaluate the relationship between urban growth and municipal expenditure over time.

Is there evidence of scale economies in urban public service delivery?

The dataset is structured to test for economies of scale in urban public service delivery, enabling comparisons of costs and efficiency across municipalities of varying sizes.

Does the dataset include geographic or spatial information?

Yes. Geographic coordinates are provided for most municipalities, enabling spatial analysis of urban services and expenditures.

What socioeconomic indicators are included?

Beyond service coverage, the dataset includes measures such as consumer price index, population projections, and density-related indicators that support broader municipal analysis.

Can I compare metro areas versus rural municipalities?

Yes. The dataset flags whether municipalities are part of a metro area, are state capitals, or are considered primate cities, enabling urban–rural and hierarchical comparisons.

How can policymakers and researchers use this dataset?

The data can inform research on urban infrastructure, fiscal policy, efficiency of public service delivery, and equity in access to municipal services, supporting policy design in Latin America.

How does urban population increase affect municipal budgets?

This dataset suggests that larger urban populations are associated with larger municipal budgets, but the relationship is not one‑for‑one. The file includes municipality‑level population, municipal expenditures, municipal revenue, and public service spending for Brazil, Chile, and Mexico in 2000 and 2010.

In this dataset, municipalities with larger populations generally have higher total expenditures and revenues, as well as higher spending on services such as water, sanitation, trash collection, electricity, and green area conservation.

At the same time, the relationship appears sublinear rather than proportional. In practical terms, that means budgets tend to rise as population rises, but not at the exact same pace as population growth. This is consistent with some economies of scale in service delivery.

Based on this file alone, the safest conclusion is that urban population increase tends to expand municipal budgets and service spending, while also changing the scale and mix of local fiscal demands.

What is the relationship between urban sprawl and local government costs?

This dataset partially answers the question. It does not explicitly define or tag “urban sprawl,” but it does include variables that can serve as proxies for urban form, including population density, urban density, urban area share, and growth in covered urban density. It also includes total municipal expenditures and municipal public service spending.

Using those fields, the dataset supports a cautious conclusion that spatial form is related to local government costs. Municipalities with varying densities and urban coverage profiles exhibit distinct spending patterns, especially for public services.

However, because the file does not directly measure sprawl through zoning patterns, road network expansion, leapfrog development, or service-extension distances, it relies on a proxy‑based relationship rather than a complete sprawl cost model.

What are the econometric models of municipal expenditure elasticity?

This dataset supports basic econometric analysis of municipal expenditure elasticity, but it does not contain a prewritten econometric model. Because it includes municipality‑level expenditures, revenues, population, density, and urbanization measures, it can be used to estimate expenditure elasticity with respect to population or urban form.

A reasonable use of this dataset would be a log‑log model in which municipal expenditures are regressed on population, with optional controls for density, urban area share, country, and year.

Using the fields in this file, the broad pattern is that expenditures increase with population, but not in a proportional manner. That implies expenditure elasticity below 1 in a simple interpretation.

However, the dataset itself does not provide a published model specification, causal identification strategy, or robustness framework, so it supports estimation rather than delivering a finished econometric answer.