Taylor Rule Estimation by OLS

Carlos Carvalho, Fernanda Nechio and Tiago Tristao

No 2018-11, Working Paper Series from Federal Reserve Bank of San Francisco

Abstract: Ordinary Least Squares (OLS) estimation of monetary policy rules produces potentially inconsistent estimates of policy parameters. The reason is that central banks react to variables, such as inflation and the output gap, that are endogenous to monetary policy shocks. Endogeneity implies a correlation between regressors and the error term – hence, an asymptotic bias. In principle, Instrumental Variables (IV) estimation can solve this endogeneity problem. In practice, however, IV estimation poses challenges, as the validity of potential instruments depends on various unobserved features of the economic environment. We argue in favor of OLS estimation of monetary policy rules. To that end, we show analytically in the three-equation New Keynesian model that the asymptotic OLS bias is proportional to the fraction of the variance of regressors due to monetary policy shocks. Using Monte Carlo simulations, we then show that this relationship also holds in a quantitative model of the U.S. economy. Since monetary policy shocks explain only a small fraction of the variance of regressors typically included in monetary policy rules, the endogeneity bias tends to be small. For realistic sample sizes, OLS outperforms IV. Finally, we estimate a standard Taylor rule on different subsamples of U.S. data and find that OLS and IV estimates are quite similar.

Keywords: Taylor Rule; Ordinary Least Squares (OLS); GMM; endogeneity; bias; weak instruments; New Keynesian models (search for similar items in EconPapers)
JEL-codes: E47 E50 E52 E58 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2021-09-01
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-mac, nep-mon and nep-ore
Note: The first version of this paper was September 6, 2018.
References: Add references at CitEc
Citations: View citations in EconPapers (30)

Downloads: (external link)
https://www.frbsf.org/economic-research/files/wp2018-11.pdf Full text - article PDF (application/pdf)

Related works:
Journal Article: Taylor rule estimation by OLS (2021)
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:fip:fedfwp:2018-11

Ordering information: This working paper can be ordered from

DOI: 10.24148/wp2018-11

Access Statistics for this paper

More papers in Working Paper Series from Federal Reserve Bank of San Francisco Contact information at EDIRC.
Bibliographic data for series maintained by Federal Reserve Bank of San Francisco Research Library ().