Data, Variables, and Their Sources

Atin Basuchoudhary, James Bang and Tinni Sen
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Tinni Sen: Virginia Military Institute

Chapter Chapter 2 in Machine-learning Techniques in Economics, 2017, pp 7-18 from Springer

Abstract: Abstract In this chapter we describe the data and how we prepare the data for analysis. We choose “usual suspect” variables that are widely known as the correlates of growth. Specifically, we look at Xavier Salaa I Martin’s work in identifying these variables. In the process, we include variables suggested by multiple theoretical growth models. We also show how non-parametric approaches can help create variables that capture the latent underlying factors that span multiple variables. This process also helps reduce unsystematic measurement errors.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spbchp:978-3-319-69014-8_2

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DOI: 10.1007/978-3-319-69014-8_2

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