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Housing Market Spillovers

  • School: Nottingham Business School
  • Starting: 2021
  • Funding: UK student / EU student (non-UK) / International student (non-EU) / Self-funded


The housing market has been argued as the main driving force of the 2008-2009 financial crisis. In U.S., the past decade initially saw a rapid growth in housing prices and residential investment, followed by the collapse of housing market and frozen credit market. This led many economists to raise the issue that housing market is not only a passive reaction of other economic and financial activities but the causing factor of business fluctuations. Therefore, we wish to expand this study further by undertaking empirical research, firstly by modelling housing market either in a dynamic stochastic general equilibrium (DSGE) framework or a reduced form VAR model. Secondly, we will examine the sources and consequences of housing market.

The earlier literature attempts to incorporate the housing market are Iacoviello (2005) and Iacoviello and Neri (2010). Building a dynamic stochastic general equilibrium (DSGE) model, they found that housing market spillovers cannot be ignored. Over the business cycle, housing demand and housing technology shocks explain one-quarter each of the volatility of housing market. Similar versions of this model have been used in different central banks and economic organisations, such as Riksbank (Sellin and Walentin, 2015), European Commission (Roeger and in ’t Veld, 2009), Bank of Canada (Christensen, et al., 2009), and IMF (Kannan, Rabanal and Scott, 2009).

Proposed Methods

The method can be two directions. If we focus on the reduced form model, we need to build a VAR model based on the DSGE framework of Iacoviello (2005). The impulse response functions can explain the housing market responses after a shock. The variance decomposition allows us to see how much each shock contributes to the volatility of the housing market. If we need to build a DSGE framework, we can use Bayesian estimation method. All the analysis will be based on these estimation results.


Iacoviello, M., and Neri, S., 2010. Housing Market Spillovers: Evidence from an Estimated DSGE Model. American Economic Journal: Macroeconomics, 2(2), 125-64.

Iacoviello, M., 2005. House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle. American Economic Review, 95(3): 739-764.

Sterk, V., 2015. Home Equity, Mobility, and Macroeconomic Fluctuations, Journal of Monetary Economics, 74, 16-32.

Roeger, W., and in ’t Veld, J., 2009. Fiscal Policy with Credit Constrained Households, European Commission, DG ECFIN, Working paper.

Christensen, I., et al., 2009. Consumption, Housing Collateral, and the Canadian Business Cycle, Bank of Canada, Working Papers, 09-26.

Kannan, et al., 2009. Monetary and Macroprudential Policy Rules in a Model with House Price Booms, IMF, Working paper.


Dr Chunping Liu

Entry qualifications

An applicant for admission to read for a PhD should normally hold a first or upper second class honours degree of a UK university or an equivalent qualification, or a lower second class honours degree with a Master's degree at Merit level of a UK university or an equivalent qualification.

International students will also need to meet the English language requirements - IELTS 6.5 (with minimum sub-scores of 6.0). Applicants who have taken a higher degree at a UK university are normally exempt from the English language requirements. A research proposal (between 1,000 and a maximum of 2,000 words) must be submitted as part of the application.

For more information please visit the NTU Doctoral School – Research Degrees webpages.

How to apply

Applications are accepted all year round.

Please visit our how to apply page for a step-by-step guide and make an application.

Fees and funding

This is a self-funded PhD opportunity. Find out more about fees and funding here.

Guidance and support

Further information on guidance and support can be found on this page.

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Chunping Liu