State-level Taylor rule and monetary policy stress

• Authors: Hasan Engin Duran , Pawel Gajewski

Abstracts

EN

Research background: Taylor rule is a widely adopted approach to follow monetary policy and investigate various mechanisms related to or triggered by monetary policy. To date, no in-depth examination of scale, determinants and spillovers of state-level monetary policy stress, stemming from the Federal Reserve Board?s (Fed?s) policy has been performed. Purpose of the article: This paper aims to investigate the nature of monetary policy stress on US States delivered by the single monetary policy by using a quarterly dataset spanning the years between 1989 and 2017. Methods: We apply a wide array of time series and panel regressions, such as unit root tests, co-integration tests, co-integrating FMOLS and DOLS regressions, and Spatial Panel SAR and SEM models. Findings & value added: When average stress imposed on states is calculated, it is observed that the level of stress is moderate, but the distribution across states is asymmetric. The cross-state determinants behind the average stress show that states with a higher percentage of working-age and highly educated population, as well as those with higher population density and more  export-oriented are negatively stressed (i.e. they experience excessively low interest rates), whereas higher unemployment rate contributes to a positive stress (too high interest rates). To the best of our knowledge, the contribution of this paper lies in estimating monetary policy stress at the state level and unveiling some of the determinants of this stress. Moreover, the paper makes the first attempt to empirically test spatial spillovers of the stress, which are indeed found significant and negative.

Keywords

EN

Taylor Rule; states; monetary stress; spatial panel regression; FMOLS; DOLS

• Publisher: Instytut Badań Gospodarczych
• Journal: Equilibrium. Quarterly Journal of Economics and Economic Policy
• Year: 2023
• Volume: 18
• Issue: 1
• Pages: 89-120

Dates

published

2023

Contributors

author

Hasan Engin Duran

• Izmir Institute of Technology

• https://orcid.org/0000000207439943

author

Pawel Gajewski

• University of Lodz

• https://orcid.org/0000000282202081

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Identifiers

DOI

10.24136/eq.2023.003

Biblioteka Nauki

22443107