The Annals of Applied Statistics

Maximizing the information content of a balanced matched sample in a study of the economic performance of green buildings

Cinar Kilcioglu and José R. Zubizarreta

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Abstract

Buildings have a major impact on the environment through excessive use of resources, such as energy and water, and large carbon dioxide emissions. In this paper we revisit a previously published study about the economics of environmentally sustainable buildings and estimate the effect of green building practices on market rents. For this, we use new matching methods that take advantage of the clustered structure of the buildings data. We propose a general framework for matching in observational studies and specific matching methods within this framework that simultaneously achieve three goals: (i) maximize the information content of a matched sample (and, in some cases, also minimize the variance of a difference-in-means effect estimator); (ii) form the matches using a flexible matching structure (such as a one-to-many/many-to-one structure); and (iii) directly attain covariate balance as specified—before matching—by the investigator. To our knowledge, existing matching methods are only able to achieve, at most, two of these goals simultaneously. Also, unlike most matching methods, the proposed methods do not require estimation of the propensity score or other dimensionality reduction techniques, although with the proposed methods these can be used as additional balancing covariates in the context of (iii). Using these matching methods, we find that green buildings have 3.3% higher rental rates per square foot than otherwise similar buildings without green ratings—a moderately larger effect than the one found by the prior study.

Article information

Source
Ann. Appl. Stat., Volume 10, Number 4 (2016), 1997-2020.

Dates
Received: June 2015
Revised: June 2016
First available in Project Euclid: 5 January 2017

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1483606849

Digital Object Identifier
doi:10.1214/16-AOAS962

Mathematical Reviews number (MathSciNet)
MR3592046

Zentralblatt MATH identifier
06688766

Keywords
Causal inference matched sampling observational studies propensity score

Citation

Kilcioglu, Cinar; Zubizarreta, José R. Maximizing the information content of a balanced matched sample in a study of the economic performance of green buildings. Ann. Appl. Stat. 10 (2016), no. 4, 1997--2020. doi:10.1214/16-AOAS962. https://projecteuclid.org/euclid.aoas/1483606849


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Supplemental materials

  • Supplement to “Maximizing the information content of a balanced matched sample in a study of the economic performance of green buildings”. In this on-line supplement, we include the appendices to “Maximizing the information content of a balanced matched sample in a study of the economic performance of green buildings” by Kilcioglu and Zubizarreta (2016).