Kristina Bluwstein, Michal Brzoza-Brzezina, Paolo Gelain and Marcin Kolasa.
Mortgages matter. For the individual, borrowing to buy a house can be the biggest debt decision of a lifetime. For the economy, mortgages make up a large fraction of total debt and are a main driver of the financial cycle. Mortgage debt exceeds 80% of UK household debt (see Figure 1), so it is important to understand mortgage market trends, how they link to the macroeconomy and the implications for monetary policy. This post uses a novel model to do just that. In particular, it introduces a rich description of the housing sector into an otherwise standard ‘DSGE’ Model. It focusses on the role of fixed rate mortgages, the mortgage cycle, and how they affect monetary policy transmission.
Following the onset of the financial crisis, the Monetary Policy Committee (MPC) cut interest rates to historically low levels and launched a programme of quantitative easing (QE) to support the UK economy. How did this exceptional period of monetary policy affect different households in the UK? Did it increase or decrease inequality? Although existing differences in income and wealth means that the impact in cash terms varied substantially between households, in a recent staff working paper we find that monetary policy had very little impact on relative measures of inequality. Compared to what would have otherwise happened, younger households are estimated to have benefited most from higher income in cash terms, while older households gained more from higher wealth.
In the first age of financial globalisation, from around 1880 to 1913, many countries tied their currencies to the mast of gold. The Bank of England’s unparalleled influence over this period is depicted by the Lady of the Bank, seated on the globe with a shower of gold coins to one side, which is carved into the Bank’s pediment. There was an old saying in the City that the Bank’s rate could draw gold from the moon. But could it?
Ben Bernanke famously remarked that “the trouble with QE is that it works in practice but not in theory”. And ahead of its adoption, many academics were sceptical that QE would have any effects at all. Yet despite QE being a part of the monetary policy landscape for nearly a decade, the bulk of academic research on QE has been on its empirical effect, with relatively little on theory and less still on normative policy questions. In a recent Staff Working Paper I develop a model which can provide answers to questions such as: “How should monetary policymakers return their instruments to more normal levels?” and “Should QE be part of the regular monetary policy toolkit?”
Philip Bunn, Jeanne Le Roux, Kate Reinold and Paolo Surico.
If you unexpectedly received £1000 of extra income this year, how much of it would you spend? All? Half? None? Now, by how much would you cut your spending if it had been an unexpected fall in income? Standard economic theory (for example the ‘permanent income hypothesis’) suggests that your answers should be symmetric. But there are good reasons to think that they might not be, for example in the face of limits on borrowing or uncertainty about future income. That is backed up by new survey evidence, which finds that an unanticipated fall in income leads to consumption changes which are significantly larger than the consumption changes associated with an income rise of the same size.
Empirical identification of the effects of monetary policy requires isolating exogenous shifts in the policy instrument that are distinct from the systematic response of the central bank to actual or foreseen changes in the economic outlook. Because the same tools are used to both induce changes in the economy, and to react to them, distinguishing between cause and effect is a far from trivial matter. One popular way is to use surprises in financial markets to proxy for the shock. In a recent paper, we argue that markets are not able to distinguish the shocks from the systematic component of policy if their forecasts do not align with those of the central bank. We thus develop a new measure of monetary shocks, based on market surprises but free of anticipatory effects and unpredictable by past information.
A railway boom in America’s Midwest goes spectacularly bust. Sixty-two of New York’s commercial banks close – out of sixty-three. Meanwhile in Britain, a decade gilt-edged by gold discoveries in Australia and fuelled by the Crimean War was beginning to lose its lustre. Thus the scene was set for the first global financial crisis shaking markets in New York, London, Paris and across the world. A crisis so severe it forced the Bank of England to “break the law” to survive.