Policymaking is invariably uncertain. I created a new index of ‘policymaker’s uncertainty’ based on a textual search of the minutes of the MPC meetings since 1997. The index is constructed by simply calculating the number of references to the word ‘uncertainty’ (and its derivatives, including ‘not certain’ and ‘far from certain’) as a share of the total word count. To avoid double-counting, it also excludes the Monetary Policy Summary that was introduced in 2015. One caveat of this approach is that it doesn’t distinguish instances of low or falling uncertainty from those where uncertainty was high. That aside, this measure can offer a new insight into uncertainty compared to indicators based on media references or business surveys.
Around the world, central banks have a number of different ownership structures. At one end of the spectrum are central banks, like the Bank of England, that are wholly owned by the public sector. At the other end are central banks, like the Banca d’Italia, whose shareholders are wholly private sector entities. And there are central banks, like the Bank of Japan, that lie in-between. But do these differences matter?
In this blog post, we explore the variety of central bank ownership structures, both historically and globally. We also suggest areas for future research on the topic.
When moving house, people often don’t move too far away. Many will be commuting to the same job or don’t want their kids to move school. But many people move long-distance when they sell one house and buy another.
How sound is the argument that current account balances are driven by demographics? Our multi-country lifecycle model explains 20% of the variation in observed net foreign asset positions among advanced economies through differences in population age structure. These positions should expand further as countries continue to age at varying speeds.
Financial markets provide insightful information about the level of risk in the economy. However, sometimes market participants might be driven more by their perception rather than any fundamental changes in risk. In a recent Staff Working Paper we study the effect of changes in risk perceptions that can lead to a mispricing of risk. We find that when agents over-price risk, banks adjust their bank lending policies, which can lead to depressed investment and output. On the other hand, when agents under-price risk, excessive lending creates a ‘bad’ credit boom that can lead to a severe recession once sentiment is reversed.
When choosing a mortgage, a key question is whether to choose a fixed or variable-rate contract. By choosing the former, households are unaffected by official interest-rate decisions for the length of the fixation period. We can use transaction data on residential mortgages to get a sense of how long it takes interest-rate decisions to filter through to people’s finances.
This guest post is the second of an occasional series of guest posts by external researchers who have used the Bank of England’s archives for their work on subjects outside traditional central banking topics.
What can the Bank of England Archive tell us about cyber security? The answer is almost certainly more than you might expect. For my PhD thesis Computer Security in the UK Financial Sector, 1960-1990, I visited the Bank Archives in the interests of being thorough, fully expecting to have exhausted relevant folders within a matter of hours. How wrong I was. They turned out to be a treasure trove of detail on historical computer security and informed a key part of my research. One particular piece of fragmentary evidence offered a window into a particularly secretive and little-known surveillance mechanism which the Bank and intelligence agencies feared and which was known only by its NATO codename, TEMPEST.
Silvia Miranda-Agrippino, Sinem Hacioglu Hoke and Kristina Bluwstein
Can shifts in beliefs about the future alter the macroeconomic present? This post summarizes our recent working paper where we have combined data on patent applications and survey forecasts to isolate news of potential future technological progress, and studied how macroeconomic aggregates respond to them. We have found news-induced changes in beliefs to be powerful enough to enable economic expansions even if different economic agents process these types of news in very different ways. A change in expectations about future improvements in technology can account for about 20% of the variation in current unemployment and aggregate consumption.
In yesterday’s post we argued that housing is an asset, whose value should be determined by the expected future value of rents, rather than a textbook demand and supply for physical dwellings. In this post we develop a simple asset-pricing model, and combine it with data for England and Wales. We find that the rise in real house prices since 2000 can be explained almost entirely by lower interest rates. Increasing scarcity of housing, evidenced by real rental prices and their expected growth, has played a negligible role at the national level.
A tulip bulb produces flowers. Those flowers are what people actually enjoy consuming, not the bulb. Whilst that’s blindingly obvious for tulips, the equivalent is also true for housing. The physical dwelling is the asset, but it’s the actual living there (aka “housing services”) that people consume. The two things sound very similar and are often lumped together as “housing”. But in today’s post, we argue they are as different as bulbs and flowers. Sketching out a simplified framework of houses as assets we show how this can radically change how one views the “housing market”. Tomorrow, we use this to develop a toy model and bring it to the data to shed light on house price growth in England and Wales.