Essays on dynamic interactions between housing markets and the macroeconomy

Abstract

This thesis sheds new light on the complex interaction between housing prices and macroeconomic system by modelling three defining pillars on which the building block of the relationship edifice rest, viz., space, credit disaggregation, and memory of shocks.The thesis contains three main chapters. Apart from Chapter 1 (Introduction), Chapter 2 sets the tone of the first important contribution by introducing the role of space in analysing impacts of macroeconomic interventions on cross-country housing price dynamics. This chapter first builds a theoretical framework to model and explain housing market disequilibrium by identifying spatial frictions among a panel of spatially adjacent countries. A spatial-dynamic housing production function is introduced for the purpose. This chapter finds and identifies the presence of a significant overestimation bias of the effects of macroeconomic variables on housing price variations in a traditional non-spatial model. To overcome this problem and to lend consistent and unbiased estimates of effects relevant for policy, a dynamic spatial Durbin model is proposed. Robustness exercise under different scenarios lends credibility to the proposed strategy.

Chapter 3 focuses on solving a mystery surrounding the real effects of credit in cross country housing market. Since ‘credit’ lies at the core of housing demand and supply and is controlled stringently by macroeconomic policy, to understand its real effects one needs to go beyond convention. This chapter proposes disaggregation of credit into credit to the real economy and credit to the asset markets to exactly identify both housing demand and supply credit-circulation channels where each component of credit exerts distinct impacts on housing price determinations. A conceptual framework is first developed to justify the strategy of disaggregation. Moreover, business cycles fluctuations are removed to align individual countries interaction-effects at the same level as other target countries, while economic policy uncertainty is also introduced to control for information asymmetry. An estimation by a panel vector autoregressive (PVAR) methodology shows that the proposed disaggregation strategy serves as a better approach for policy exercise regarding the optimal allocation of credit to the real economy and to the asset markets. The chapter demonstrates that that (i) there is a mutually positive reinforcing relationship between credit to the real economy and housing prices, (ii) the impact of credit to the asset markets on housing prices is negative and negligible in the short-run and positive and significant in the long-run. In addition, only credit to the real economy is found to stimulate economic growth in contrast to the insignificant impact of credit to the asset markets.

Modelling possible slow-convergence of shocks within a complex interactive system is crucial as it provides a robust predictive power by quantifying the extent to which estimated macroeconomic effects are meaningful for a policy design. In this spirit,Chapter 4 introduces a long-memory cointegration approach to unravel distinct effect transmission channels through which housing market and macroeconomic system comove. By employing a fractionally cointegrated VAR model, we demonstrate that there is a gradual price adjustment towards the housing market clearing while the effects of shocks on equilibrium adjustments are inherently slow and non-linear. This identification strategy is able to not only gauge impacts of housing demand- or supply-exclusive variables, but also the ones that have dual roles through both demand and supply sides, respectively, in equilibrium housing price determinations and dis-equilibrium error corrections. Eventually, an overall equilibrium housing price determination function is derived by solving simultaneous housing demand and supply functions. Chapter5 summarises the main results of the thesis, points out limitations of the work and discusses future research directions.

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Identifiers

ORCID for Tapas Mishra: orcid.org/0000-0002-6902-2326

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