Three Essays on Housing, Credit and Uncertainty
Creators: name: Finch, Ben
Publisher: name: Lancaster University
Year: 2022

description: This thesis comprises three essays in macroeconomics. The key aim of our work is to quantify the link between housing, credit and uncertainty. In the first chapter we investigate the propagation mechanism of a temporary uncertainty shock for the UK. We adopt a factor augmented VAR model which facilitates an examination of variables which have not been included in previous studies. Our empirical analysis establishes that while the ‘traditional’ channels generally hold; across different sectors there are asymmetric responses. For example, precautionary behaviour implies that agents cut back on consumption and increase saving in order to mitigate the risks associated with uncertainty. However, decomposing consumption, we provide evidence that for food and fuel markets the impact of an increase in uncertainty is close to zero. This follows because we do not capture the expected fall in demand given the consumption decision is a necessity. In terms of housing and credit we propose a new housing uncertainty channel which is closely linked to growth option theory. The idea is that a second moment uncertainty shock extends the tails of the distributions and thus increases the potential payoffs. This in turn leads to an increase in investment. For those who are able to access credit, we capture an increase in housing investment and a corresponding expansion in mortgage credit which contributes to a reduction in the negative impacts of uncertainty shocks. The second paper extends the discussion in Chapter 1, by examining the transmission of uncertainty shocks in the US. Specifically, we quantify the linear and non linear impacts of uncertainty. For the linear analysis, we estimate a proxy SVAR using narrative identification, net of first moment shocks, and provide supporting evidence of the housing uncertainty channel. The interaction between housing and credit is shown to be crucial, reinforcing the findings we present in Chapter 1. The intuition for our non linear analysis builds upon the idea that once uncertainty has reached a certain level, any additional increases in uncertainty are unlikely to have any impact on macroeconomic aggregates. In order to test this conjecture, we propose an instrument to identify uncertainty shocks, which is constructed by isolating the variation in the price of gold around events associated with uncertainty. We argue that the change in the price of gold accurately represents uncertainty, because it is perceived as a safe haven asset. When faced with the additional risk associated with uncertainty agents invest in gold. This reflects a flight to safety. We adopt a threshold VAR model which isolates responses dependant on regimes synoptic with high and low uncertainty. We show that in a low uncertainty regime, uncertainty propagates similarly to the linear case. In contrast, there is a clear distinction in a high uncertainty regime driven by impatient behaviour. In our final chapter, we propose a DSGE model which is consistent with the empirical evidence we provide in the previous chapters. We choose to order the chapters in such a way that we first establish the empirical facts of uncertainty shocks and then use these to inform our theoretical model. The key empirical takeaway following a shock to uncertainty is a co-movement between consumption and investment. We demonstrate that a vanilla housing real business cycle model is not consistent with these empirical facts. In order to match the theoretical model to the empirics, we extend the baseline model by including both banks and financial frictions. We document first a credit channel which limits access to external funds for the credit dependant sector of the economy. Second, we find a housing demand channel, which leads to tighter constraints for households and entrepreneurs and lowers the return on capital. Together, both channels amplify precautionary saving for household borrowers. The credit channel creates a real option channel for entrepreneurs, while the housing demand channel impacts households savers by amplifying their reduction in investment. In the absence of credit constraints, the housing uncertainty channel dominates behaviour. However, this channel is reversed when agents face difficulty in accessing credit consistent with Chapter 1.