Why This Book?

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

Chapter Chapter 1 in Machine-learning Techniques in Economics, 2017, pp 1-6 from Springer

Abstract: Abstract In this chapter, we lay out our plan for the book and the argument for the advantages of machine learning. ML algorithms use out of sample validation to identify which variables matter most for economic growth and recessions without making any heroic assumptions about the underlying distribution of the variables. Thus, it avoids problems of endogeneity. It also helps with the missing data problem by imputing missing data with validated algorithms. However, most of all, these algorithms can eliminate variables that are unlikely to be causal. Policy makers can therefore get a sense of the most important policy levers to change the path of growth.

Keywords: Policy Levers; Machine Learning Framework; Standard Econometric Techniques; Parameter Point Estimates; Growth Affect (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spbchp:978-3-319-69014-8_1

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DOI: 10.1007/978-3-319-69014-8_1

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