EconPapers    
Economics at your fingertips  
 

Predicting Recessions: What We Learn from Widening the Goalposts

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

Chapter Chapter 6 in Machine-learning Techniques in Economics, 2017, pp 57-73 from Springer

Abstract: Abstract In this chapter, we move our focus from economic growth to trying to predict a related target—economic recessions. We continue to use the “usual suspect” growth variables to check whether these variables are better at predicting recessions. We show how prediction performance of algorithms differs widely depending on the type of prediction criteria. We can, however, identify some of the most salient predictors of recessions. These suggest that fiscal policy may generally be better at combating recessions. Moreover, these predictors have non-linear effects on the likelihood of recessions which suggests that there may be no silver bullet for combating recessions. Last, the sorts of variables that influence economic growth also influence the likelihood of a recession. This suggest that economic growth probably should not be studied separately from recessions.

Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spbchp:978-3-319-69014-8_6

Ordering information: This item can be ordered from
http://www.springer.com/9783319690148

DOI: 10.1007/978-3-319-69014-8_6

Access Statistics for this chapter

More chapters in SpringerBriefs in Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-01
Handle: RePEc:spr:spbchp:978-3-319-69014-8_6