Housing and labour market interactions

Masst, Oyvind (2025) Housing and labour market interactions. PhD thesis, University of Glasgow.

Abstract

As workers switch jobs, they also often choose to move residences to be closer to their new place of work. This thesis investigates the dynamic interactions between housing and labour markets, showing that when housing is scarce, it acts as a barrier to job market transitions and aggregate employment.

While previous research has explored these markets independently, this study contributes to the literature by developing a Dynamic Stochastic General Equilibrium (DSGE) model treating the markets jointly. Chapter 1 introduces the theoretical framework, demonstrating how search frictions and spillover effects between housing and labour markets allow the model to replicate key stylized facts.

The second chapter empirically estimates the model using Bayesian methods and UK timeseries data from 1971Q2 to 2020Q1. It quantifies spillover elasticities, monetary policy parameters, and shock decompositions, shedding light on the effects of major housing and labour policy interventions during the Thatcher era. Counterfactual simulations reveal how policy reforms shaped market flexibility and economic resilience. The third chapter extends the analysis to the US economy using data from 1965Q2 to 2020Q1. Comparative analysis highlights structural differences in labour market flexibility between the UK and the US. A counterfactual experiment explores the macroeconomic consequences of a more flexible labour market in the United Kingdom, drawing lessons from the experience of the United States.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Supported by funding from the College of Social Sciences, University of Glasgow.
• Subjects: H Social Sciences > HB Economic Theory; H Social Sciences > HD Industries. Land use. Labor
• Colleges/Schools: College of Social Sciences > Adam Smith Business School
• Funder's Name: College of Social Sciences
• Supervisor's Name: Nolan, Professor Charles and Kirsanova, Professor Tatiana
• Date of Award: 2025
• Depositing User: Theses Team
• Unique ID: glathesis:2025-85585
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 12 Nov 2025 11:24
• Last Modified: 12 Nov 2025 11:29
• Thesis DOI: 10.5525/gla.thesis.85585
• URI: https://theses.gla.ac.uk/id/eprint/85585