The Unassuming Economist

From VoxEU:

“The global economy is growing, but so is uncertainty. This column presents a new quarterly index of uncertainty for 143 countries. The World Uncertainty Index reveals how uncertainty in the world has evolved over time, whether it is synchronised across countries, and how it compares across income groups and political regimes.

The October 2018 edition of the World Economic Outlook predicts that global economic growth will remain steady between 2018 and 2020 at the 2017 growth rate of 3.7% (IMF 2018). This exceeds the growth rate in any year between 2012 and 2016.

So, the global economy is growing, but so is uncertainty. Headlines that have appeared in the Financial Times in 2018 include: “Stocks unsettled by global trade uncertainty”, “Counting the costs of Brexit uncertainty”, “Latin America faces up to growing uncertainties”, “Italian bonds under pressure from budget uncertainty”, and “Boeing deal with Embraer faces political uncertainty”.

A Google news search for “uncertainty” gives about 0.6 million results for the whole of 2017, but 2.5 million results for the first ten months of 2018. Can we measure ‘uncertainty’ more precisely? Or compare the amount of ‘uncertainty’ in the US to that in China, the UK, or Ireland?

Measurements of economic and political uncertainty have been made only for a set of mostly advanced economies (Baker et al. 2016). We have constructed a new index of uncertainty for 143 countries using Economist Intelligence Unit (EIU) country reports. To the best of our knowledge, this is the first effort to construct a panel index of uncertainty for a large set of developed and developing countries.

Constructing the World Uncertainty Index

We constructed the World Uncertainty Index (WUI) – a quarterly index of uncertainty – for 143 individual countries from 1996 onwards. The WUI is defined using the frequency of the word ‘uncertainty’ (and its variants) in the quarterly EIU country reports. To make the WUI comparable across countries, the raw count is scaled by the total number of words in each report.

In contrast to existing measure of economic policy uncertainty, two factors help improve the comparability of the WUI across countries:

• The WUI is based on a single source. This source has specific topic coverage – economic and political developments.
• Reports follow a standardised process and structure.

The process through which the EIU country reports are produced helps to mitigate concerns about the accuracy, ideological bias, and consistency of the WUI. But we only have one EIU report per country per quarter, meaning there is potentially quite large sampling noise.

Stylised facts

This dataset allows us to establish five key facts:

1. Global uncertainty has increased significantly since 2012. Figure 1 shows that average uncertainty has increased since 2012, well above its historical average (computed between 1996 Q1 and 2010 Q4). The index spikes near the 9/11 attacks, the SARS outbreak, the second Gulf War, the euro area debt crisis, El Niño, the Europe border-control crisis, the UK referendum vote for Brexit, and the US presidential elections.

Interestingly, while text-based measures of uncertainty have been rising since the early 2000s, financial market measures rose until about 2010, but have fallen back to low levels (Pastor and Veronesi 2017).

 

Continue reading here.

 

From a new post by Dave Giles:

“Anyone who’s undertaken empirical macroeconomic research relating to Canada will know that there are some serious data challenges that have to be surmounted.

In particular, getting access to long-term, continuous, time series isn’t as easy as you might expect.

Statistics Canada has been criticized frequently over the years by researchers who find that crucial economic series are suddenly “discontinued”, or are re-defined in ways that make it extremely difficult to splice the pieces together into one meaningful time-series.

In recognition of these issues, a number of efforts have been made to provide Canadian economic data in forms that researchers need. These include, for instance, Boivin et al. (2010), Bedock and Stevanovic (2107), and Stephen Gordon’s on-going “Project Link“.

Thanks to Olivier Fortin-Gagnon, Maxime Leroux, Dalibor Stevanovic, &and Stéphane Suprenant we now have an impressive addition to the available long-term Canadian time-series data. Their 2018 working paper, “A Large Canadian Database for Macroeconomic Analysis“, discusses their new database and illustrates its usefulness in a variety of ways.”

From a new post by Timothy Taylor:

“Robert Solow is a notable player in these disputes: in particular, in his 1960 paper with Paul Samuelson, “Analytical Aspects of Anti-Inflation Policy” (American Economic Review, 50:2, pp. 177-194). In an essay in the Winter 2000 issue of the Journal of Economic Perspectives, “Toward a Macroeconomics of the Medium Run,”  Solow addressed this question of thinking about macroeconomic policy in the short- and the long-run. He wrote:

I can easily imagine that there is a “true” macrodynamics, valid at every time scale. But it is fearfully complicated, and nobody has a very good grip on it. At short time scales, I think, something sort of “Keynesian” is a good approximation, and surely better than anything straight “neoclassical.” At very long time scales, the interesting questions are best studied in a neoclassical framework, and attention to the Keynesian side of things would be a minor distraction. At the five-to-ten-year time scale, we have to piece things together as best we can, and look for a hybrid model that will do the job.

In this most recent essay, “A Theory is a Sometime Thing,” Solow pushes this idea of medium-run thinking harder. He acknowledges that if a central bank can only cause the interest rate and unemployment rate to shift for a year or two, in the short-run before a rebound to what is determined in the long run, then when problems of lags in timing are included, macroeconomic policy might be dysfunctional. But if a central bank can affect the interest rate and the unemployment rate for a medium-run period of, say 5-7 years, then even with some uncertainty and lags, macroeocnomic policy may be quite relevant and possible. At one point, Solow writes: “The medium run is where we live.””

From a new AEI post:

“Watch the top ten largest economies in the world based on GDP, year-by-year from 1961 to 2017. A few interesting observations:

1. The global slowdown in the early 1980s.

2. China’s ranking in the world’s ten largest economies has sure bounced around a lot. It was the world’s fifth largest economy in 1962 and remained in the top ten economies until it dropped out in 1978 and 1979, before returning in 1980, dropping out again for a few years and returning to the top ten in 1982. In 1987, China fell out for a year, came back in 1988, dropped out again in 1989 before returning to the top ten for good in 1992. By 2000, China rose to the No. 6 position by passing Italy, then to No. 5 in 2005 when it surpassed France, to No. 4 in 2006 when it surpassed the UK, No. 3 in 2007 surpassing Germany, and finally rising to No. 2 in 2010 by surpassing Japan.

3. As of 2017, the US economy at $19.4 trillion was 58.4% larger than China’s GDP of $12.2 trillion.”

Watch the dynamic chart here.

From a new post by Timothy Taylor:

“I was hired back in 1986 to be the Managing Editor for a new academic economics journal, at the time unnamed, but which soon launched as the Journal of Economic Perspectives. The JEP is published by the American Economic Association, which back in 2011 decided–to my delight–that it would be freely available on-line, from the current issue back to the first issue. Here, I’ll start with Table of Contents for the just-released Fall 2018 issue, which in the Taylor household is known as issue #126. Below that are abstracts and direct links for all of the papers. I may blog more specifically about some of the papers in the next week or two, as well.”