Build-your-own fancharts in R

Andrew Blake

Central banks the world over calculate and plot forecast fancharts as a way of illustrating uncertainty. Explaining the details of how this is done in a single blog post is a big ask, but leveraging free software tools means showing how to go about it isn’t. Each necessary step (getting data, building a model, forecasting with it, creating a fanchart) is shown as R code. In this post, a simple data-coherent model (a vector auto-regression or VAR) is used to forecast US GDP growth and inflation and the resulting fanchart plotted, all in a few self-contained chunks of code.

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What does population ageing mean for net foreign asset positions?

Noëmie Lisack, Rana Sajedi and Gregory Thwaites

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.

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Perceiving risk wrong: what happens when markets misprice risk?

Kristina Bluwstein and Julieta Yung

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.

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Great Expectations: the economic power of news about the future

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.

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Houses are assets not goods: taking the theory to the UK data

John Lewis and Fergus Cumming

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.

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Houses are assets not goods: What the difference between bulbs and flowers tells us about the housing market

John Lewis and Fergus Cumming

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.

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How economic integration fuels macroeconomic imbalances

Sophie Piton

From the introduction of the Euro up to the 2008 global financial crisis, macroeconomic imbalances widened among Member States. These imbalances took the form of strong differences in the dynamics of unit labour costs, which increased much faster in ‘peripheral’ economies than in ‘core’ countries. At first, these imbalances were interpreted as reflecting a catch-up and convergence process within the Euro Area – and were supposed to fall as countries converged. But, more recently economists and policymakers have challenged this view, suggesting that imbalances reflected a broader competitiveness problem in the ‘periphery’ compared to the ‘core’ countries. This post, based on a recent Staff Working Paper, revisits the effect of economic integration on macroeconomic imbalances.

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Is there really a global decline in the (non-housing) labour share?

Germán Gutiérrez and Sophie Piton

Much has been written on the global decline of the corporate labour share (defined as the share of corporate value added going to wages, salaries and benefits). The IMF and OECD worry about this trend, linking it to decreasing wages and rising inequality. And economists are hard at work looking for an explanation: prominent hypotheses range from automation and ‘superstar’ firms to offshoring. But is there really a global decline in the non-housing/business labour share? Not if you properly exclude housing income and account for self-employment, as described in a recent Staff Working Paper. Adjusting for housing and self-employment, labour shares have remained stable across most advanced economies except in the US, where the labour share still declines by 6% since 1980 (Figure 1).

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Bitesize: How much did PPI subsidise personal loan rates pre-crisis?

David Seaward

The Payment Protection Insurance (PPI) mis-selling scandal has rumbled on for years. But how did PPI impact loan margins pre-crisis?

This post argues that income from cross-selling PPI substantially offset lenders’ margins on personal loans between 2004 and 2009, and compares the pre-crisis PPI-adjusted margin to loan spreads today.

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