Less is more: what does mindfulness mean for economics?

Dan Nixon.

Economic theory generally assumes that more consumption means greater happiness. This post puts forward an alternative, “less is more” perspective based around the concept of mindfulness. It argues that we may achieve greater happiness by seeking to simplify our desires, rather than satisfy them. The result – less consumption but greater wellbeing – could be especially important for debates around secular stagnation and ecological sustainability.

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Is sterling ever a fashionable currency?

Jihyoung Yi.

Despite the fact that the US dollar and the euro are the most traded currencies in terms of shares of average daily turnover (2013, BIS), my analysis suggests that foreign exchange rate (FX) market trends are usually driven by other currencies. Most notably, ‘commodity’ currencies (such as the Australian dollar and Mexican peso) and ‘carry-trade’ currencies (such as the Swiss franc and Japanese yen) tend to be the main drivers. In contrast, sterling typically does not often drive currency movements – FX strategists often consider that it is rare for sterling to be ‘the story’ amongst the speculative community in the FX market. But this is not always the case. This blog post zooms in on a selection of sub-periods to show when particular currencies, including sterling, became ‘focal’.

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When banks say ‘No’: how the credit crunch lowered UK productivity

Jeremy Franklin, May Rostom & Gregory Thwaites.

In the aftermath of the 2007/8 financial crisis bank lending to firms fell back sharply and investment plummeted. And at the same time, growth in labour productivity and wages fell, with neither fully recovering since (Chart 1). Are these facts causally linked, and if so, in which direction? Did firms stop borrowing because they had no good uses for the money, or did banks cut lending, making it harder for firms to do business? In a new paper, we find a way to distinguish between the two. We measure how changes in the amount firms were able to borrow affected how much they invested, how much their workers produced and earned, and how likely firms were to survive.

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Testing the test: How reliable are risk model backtesting results?

Emmanouil Karimalis, Paul Alexander & Fernando Cerezetti.

All models, including those which model financial risk, are in some sense “wrong” – they aim to “approximate” the real word but cannot possibly recreate it. Consequently, in a world in which risk models are used to calculate and exchange vast sums of capital and margin, the need for reliable tests is of paramount importance. The Kupiec-POF test represents the most widely-used test for assessing the reliability of these risk models (typically Value-at-Risk (VaR) models) – a process known as backtesting. As with all forms of testing, the Kupiec-POF test has a degree of error associated with its use and under certain circumstances these errors may be substantial.

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Extracting insight from complexity

John Hill and Jamie Coen.

The financial system is complex and highly interconnected. Indeed, interactions between agents are key to its functioning. But these interconnections have the potential to turn small shocks into systemic crises. Understanding the complex nature of these interconnections is important, but can also be difficult. In this post we introduce new tools designed to analyse the financial network and help analysts build a better understanding of risks posed by interconnectedness.

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On the benefits of reducing uncertainty about policy

Riccardo M Masolo and Francesca Monti.

Newspapers and other media outlets regularly speculate about what the Bank of England might do in response to current economic conditions. Curiously, however, most of the models we use to carry out our economic and policy analysis completely disregard this type of uncertainty. Many of them consider how people would behave when uncertain about the state of the economy, yet everyone is assumed to know for sure the variables that the central bank will respond to, how aggressively and why. To try and fill this gap between the models we typically use and the reality we actually face, in our paper we explore the effects of Knightian uncertainty about the behaviour of the policymaker in an otherwise standard macro model. Continue reading “On the benefits of reducing uncertainty about policy” →

Bringing together stress testing and capital models – a Bayesian approach

Dan Georgescu & Manuel Sales.

Capital requirements for financial institutions are typically calculated using a statistical model and a risk measure such as VaR, whereas stress tests designed by regulators and risk managers are often based on subjective scenarios with no associated probability level. The stress test cannot therefore be easily linked to the capital measure. Taking insurance as an example, we show how to establish the link using intuitive tools which (i) respect the stress test designer’s intuition about causal direction, (ii) can be calibrated to pre-determined parameters such as correlations between risks, and (iii) can be easily communicated to and challenged by non-technical audiences.

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Izzy Whizzy let’s get Vizzy – The magic of using visualisation to analyse and understand data.

Lyndsey Pereira-Brereton.

Like Sooty, the BBC’s yellow bear loved by generations of British children, central banks should wave the ‘magic wand’ of data visualisation over their large, granular or complex data sets, in order to gain further insight into the patterns and relationships contained within them. This blog draws on some examples to highlight how different visualisation techniques help not only the communication of data, but more importantly, how it can aid data exploration, analysis and understanding.

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Forecasting GDP in the presence of breaks: when is the past a good guide to the future?

George Kapetanios, Simon Price and Sophie Stone.

Structural breaks are a major source of forecast errors, and few come larger than the recent financial crisis and subsequent recession. After a break, formerly good models stop working. One way to cope is to discount the past in a data driven way. We try that, and find that shortly after the crash it was best to ignore almost all data older than three years – but now it is again time to take a longer view.
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