The Estimation of Traditional Phillips Curve
Articles
Algirdas Bartkus
Department of Quantitative Methods and Modelling, Faculty of Economics and Business Administration, Vilnius University
Published 2023-10-04
https://doi.org/10.15388/Ekon.2023.102.2.3
PDF
HTML

Keywords

inflation
unemployment
Phillips curve
nonlinear time series models

How to Cite

Bartkus, A. (2023) “The Estimation of Traditional Phillips Curve”, Ekonomika, 102(2), pp. 47–67. doi:10.15388/Ekon.2023.102.2.3.

Abstract

This article presents theoretical foundations for original Phillips curve formulation and an empirical investigation, where the structure of the theoretical model serves as a template for the creation of the empirical model.
For a couple of decades the majority of empirical Phillips curve type assessments are performed using the New Keynesian Phillips curve with Calvo pricing as a benchmark for this type of relationship. New Keynesian model has solid microeconomic foundations, has proved itself very well in the analysis of price stickiness; nevertheless, it is not without limitations. The main insufficiency of New Keynesian model is that it has no direct links to the conditions and the changes that occur in the labour market. The need to encompass the conditions in labour market comes from the coincides that occur time to time when the growth rates of aggregate production may diminish or even become negative, but the level of employment may stay the same, what in turn means that the pressure on inflation won’t drop, despite the fact that production level has not increased as expected or even has decreased. This article aims to fill this gap and presents alternative theoretical foundations for Phillips curve, that lead to the model with direct links to the labour market. Theoretical foundations are necessary as they may help to minimize the risks to miss some important details or to omit important factors. Although the empirical analysis in this paper is based on Lithuanian data, it is not country specific.

PDF
HTML
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Downloads

Download data is not yet available.