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Price and Spatial Distribution of Office Rental in Madrid: A Decision Tree Analysis

Author

Listed:
  • Máximo Camacho

    (University of Murcia, Spain)

  • Salvador Ramallo

    (University of Murcia, Spain)

  • Manuel Ruiz

    (Technical University of Cartagena, Spain)

Abstract

n this paper, we assess the drivers of office rental prices in the municipality of Madrid with asample of 4,721 offices in March, 2020. The estimation was performed using the decision treeapproach, which was built with a random forest algorithm. This technique allows us to capturethe strong nonlinear component in the relation between price and its drivers, mainly geospatiallocation. Through a stratified analysis, we find out that the willingness to pay high rent in thecenter of Madrid is a feature of particular relevance to medium-sized offices. For different reasons, we also find out some office clusters located far from the city center with high rent for both largeand small offices.

Suggested Citation

  • Máximo Camacho & Salvador Ramallo & Manuel Ruiz, 2021. "Price and Spatial Distribution of Office Rental in Madrid: A Decision Tree Analysis," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 44(87), pages 20-40.
    • Handle: RePEc:pcp:pucrev:y:2021:i:87:p:20-40
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    More about this item

    Keywords

    Spatial economics; Random forest; Nonlinear; Offices;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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