We are happy to invite you to the research seminar by the Department of Quantative Methods and Modeling. On November 30th Algirdas Bartkus will present the topic „The Estimation of Traditional Phillips Curve“ in TechHub Conference Room.
For a couple of decades, the majority of empirical Phillips curve-type assessments were performed using the New Keynesian Phillips curve with Calvo pricing as a benchmark for this type of relationship. The new Keynesian model has solid microeconomic foundations and has proved itself very well in the analysis of price stickiness; nevertheless, it is not without limitations. The main insufficiency of the New Keynesian model is that it has no direct links to the conditions and changes that occur in the labour market. The need to encompass the conditions in the labour market comes from the coincides that occur from 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, which in turn means that the pressure on inflation won’t drop, despite the fact that production levels have not increased as expected or even decreased. This article aims to fill this gap and presents alternative theoretical foundations for the Phillips curve that lead to a model with direct links to the labour market. Theoretical foundations are necessary, as they may help minimise the risk of missing some important details or omitting important factors. This article presents theoretical foundations for the 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.
Information on the seminar
- Time: November 30, 14:00-15:00
- Venue: 402 room and MS Teams here
- Presenter: Associate Pofessor Dr. Algirdas Bartkus, Head of Department of Quantative Methods and Modeling
- Topic: „The Estimation of Traditional Phillips Curve“.
- Working language: English
The seminar is open to all - students, teachers, researchers. We invite you to learn more!