Inflation dynamics and the output-inflation trade-off: international panel data evidence

Bakas, D. ORCID: 0000-0003-4771-4505 and Chortareas, G., 2018. Inflation dynamics and the output-inflation trade-off: international panel data evidence. London: King's Business School, King's College London.

[img]
Preview
Text
13176_Bakas.pdf - Published version

Download (3MB) | Preview

Abstract

We explore the impact of inflation and its variability on the output-inflation trade-off using a unified single-step approach in a panel data context. A limitation of earlier empirical approaches is that they focus on either cross-country or country-by-country time-series analyses. This paper employs a dynamic heterogeneous panel data specification and uses an all-encompassing estimation framework that accounts for parameter heterogeneity, cross-sectional dependence, dynamics, and non-stationarity. Our sample covers 60 countries from 1970 to 2010. While inflation variability reduces the trade-off for specific periods and country groups, an unambiguous and more pronounced negative relation emerges between the inflation rate and the responsiveness of real output to nominal shocks. The findings are in line with the New Keynesian view of a negative association between the rate of inflation and the output-inflation trade-off, as well as with the observed flattening of the Phillips curve over the past decades.

Item Type: Working paper
Description: Data Analytics for Finance & Macro (DAFM) Research Centre working paper series no. 2018/3
Creators: Bakas, D. and Chortareas, G.
Publisher: King's Business School, King's College London
Place of Publication: London
Date: December 2018
Rights: This work is licensed under a Creative Commons Attribution Non-Commercial Non-Derivative 4.0 International Public License.
Divisions: Schools > Nottingham Business School
Record created by: Jonathan Gallacher
Date Added: 05 Feb 2019 14:24
Last Modified: 05 Feb 2019 14:24
URI: http://irep.ntu.ac.uk/id/eprint/35766

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year