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Counterfactual Spatial Distributions

Author

Listed:
  • Paul E. Carrillo

    () (Department of Economics/Institute for International Economic Policy, George Washington University)

  • Jonathan Rothbaum

    () (Development Research Group, The World Bank)

Abstract

The influential contributions of DiNardo, Fortin, and Lemieux (1996), Firpo, Fortin, and Lemieux (2009), Machado and Mata (2005), and Donald, Green, and Paarsch (2000) provide researchers with a useful toolbox to estimate counterfactual distributions of scalar random variables. These techniques have been widely applied in the literature. Typically, the dependent variable of interest has been a scalar and little consideration has been given to spatial factors. In this paper we propose a simple method to construct the counterfactual distribution of the location of a variable across space. We apply the spatial counterfactual technique to assess 1) how much changes in individual characteristics of Hispanics in the Washington, DC, area account for changes in the distribution of their residential location choices, and 2) how changes in the average characteristics of shareholders account for changes in the spatial distribution of new firms in Quito, Ecuador.

Suggested Citation

  • Paul E. Carrillo & Jonathan Rothbaum, 2014. "Counterfactual Spatial Distributions," Working Papers 2014-05, The George Washington University, Institute for International Economic Policy.
  • Handle: RePEc:gwi:wpaper:2014-05
    as

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    File URL: http://www.gwu.edu/~iiep/assets/docs/papers/Carrillo_IIEPWP_2014-5.pdf
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    References listed on IDEAS

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    Cited by:

    1. Baum-Snow, Nathaniel & Hartley, Daniel, 2016. "Accounting for Central Neighborhood Change, 1980-2010," Working Paper Series WP-2016-9, Federal Reserve Bank of Chicago.

    More about this item

    Keywords

    Decomposition; Non-parametric Estimation;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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