Sinem Hacioglu Hoke and Kerem Tuzcuoglu
We economists want to have our cake and eat it. We have far more data series at our disposal now than ever before. But using all of them in regressions would lead to wild “over-fitting” – finding random correlations in the data rather than explaining the true underlying relationships. Researchers using large data sets have historically experienced this dilemma – you can either throw away some of the information and retain clean, interpretable models; or keep most of the information but lose interpretability. This trade-off is particularly frustrating in a policy environment where understanding the identified relationships is crucial. However, in a recent working paper we show how to sidestep this trade-off by estimating a factor model with intuitive results.
Sebastian J A de-Ramon and Michael Straughan.
The landscape for competition between UK deposit takers (retail banks and building societies) was reset in the 1980s with the removal of the bank “corset” (1981), the Big Bang reforms and the Building Societies Act (both in 1986). These reforms facilitated entry and expansion of different business models into markets that had previously been off-limits. What followed was a significant restructuring of the deposit taking sector in the UK. In a new paper, we show that competition between UK deposit takers weakened substantially in the years leading up to the financial crisis.
Frank Eich and Jumana Saleheen.
Despite the fact that the financial crisis erupted nearly a decade ago, its legacy is still being felt today. Disappointingly weak growth and low interest rates are arguably part of that legacy (though other developments also matter), and policy makers are increasingly worried that these are no longer temporary phenomena but instead have become permanent features. This blog assesses what a prolonged period of weak growth and low interest rates (sometimes also referred to by “secular stagnation” or “low for long”) might mean for the viability of defined-benefit (DB) occupational pension schemes in the UK and what financial stability risks might arise as a result of a changing business environment.
Ian Billett and Patrick Schneider.
As time goes to infinity, the probability that a productivity analyst will wonder ‘which sectors are driving these trends?’ goes to one. We present an interactive sectoral productivity tool to help you explore this question without any fuss.
“Unlimited wants, scarce resources”. This is the economic problem. But once basic needs are met, how much should scarcity – having “enough” – be understood as a psychological problem? Is it possible to cultivate an “abundance mindset”? And what does all of this mean for how economics is taught?
Alastair Cunningham, David Bradnum and Alastair Firrell.
Uncertainty is a hot topic for economists at the moment. Have business leaders become more uncertain as a result of the EU referendum? If so, has that uncertainty had any effect on their plans? The Bank’s analysts look at lots of measures of economic uncertainty, from complex financial market metrics to how often newspaper articles mention it. But few of those measures are sourced directly from the trading businesses up and down the country whose investment and employment plans affect the UK economy. This blog reports on recent efforts to draw out what the Bank’s wide network of business contacts are telling us about uncertainty – comparing what we’re hearing now to trends seen in recent years.
Equity prices reflect the market value of public companies, making them an important indicator of the economy. In practice, stocks by firms listed on the local stock exchange serve as the ‘domestic’ equity benchmark but this might be misleading as an indicator of the national economy: stock markets track the performance of individual firms, including their international business. This makes it particularly challenging to extract a signal for the UK economy from UK equity prices, as the universe of UK-listed firms tends to be very global – for instance, around 2/3 of sales represented on the FTSE All-Share are generated abroad. So for a better read of the UK economy, I’ll look at a subset of more UK-focused stocks and other more domestically-focused UK equity indices.
Much has been written about the productivity puzzle. But there are actually two puzzles apparent in the data – one in the level that hit at the crisis and the other in the growth rate, which is a more recent phenomenon – and they could be driven by completely different sources. Distinguishing between the two puzzles is important precisely because of these potential differences – if anyone analyses the puzzle as a whole looking for the force driving it, the actual underlying variety will confound our estimates of the relative importance of these drivers.
In this post I discuss:
- what people mean by the productivity puzzle, usually a percent deviation from the pre-crisis trend;
- how I think of it as actually two puzzles: one in the level and the other in the growth rate; and
- why this distinction can be important, using the example of a simple growth accounting decomposition of productivity growth into capital deepening and technological advancement.
Christopher Hackworth, Nicola Shadbolt and David Seaward.
While official housing market statistics are relatively timely and high frequency, they usually come with a lag of at least one month. So indicators that lead official estimates are helpful for identifying turning points, or any ‘shocks’ to the economy.
Jeremy Chiu and Sinem Hacioglu Hoke.
When shocks cause trouble
Small shocks can lead to big crises. At the heart of this issue is that economic dynamics might play out very differently against different backdrops: the same shock would have a very different effect if it hit the economy at the heights of the Great Recession than if it hit during more benign times. It might knock the economy into a more severe and persistent recession or financial stress if it hits already turbulent periods. It seems reasonable, therefore, that we would want to take into account the economic backdrop when we estimate our models.