Deciding Between Alternative Approaches In Macroeconomics

David Hendry

No 778, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: Abstract: Macroeconomic time-series data are aggregated, inaccurate, non-stationary, collinear and rarely match theoretical concepts. Macroeconomic theories are incomplete, incorrect and changeable: location shifts invalidate the law of iterated expectations and ‘rational expectations’ are then systematically biased. Empirical macro-econometric models are non-constant and mis-specified in numerous ways, so economic policy often has unexpected effects, and macroeconomic forecasts go awry. In place of using just one of the four main methods of deciding between alternative models, theory, empirical evidence, policy relevance and forecasting, we propose nesting ‘theory-driven’ and ‘datadriven’ approaches, where theory-models’ parameter estimates are unaffected by selection despite searching over rival candidate variables, longer lags, functional forms, and breaks.

Keywords: Model Selection; Theory Retention; Location Shifts; Indicator Saturation; Autometrics. (search for similar items in EconPapers)
JEL-codes: C22 C51 (search for similar items in EconPapers)
Date: 2016-01-27
New Economics Papers: this item is included in nep-ecm and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://ora.ox.ac.uk/objects/uuid:ee6fd7f0-83f6-4613-a403-7b65de4947ed (text/html)

Related works:
Journal Article: Deciding between alternative approaches in macroeconomics (2018)
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:oxf:wpaper:778

Access Statistics for this paper

More papers in Economics Series Working Papers from University of Oxford, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Anne Pouliquen ( this e-mail address is bad, please contact ).