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A precise measure of uncertainty?

The Economic Policy Uncertainty Index tries to quantify unpredictability

FREDcast, FRED’s forecasting game, asks players to forecast four major macroeconomic variables by the 20th of every month. Some players may be frustrated by the erratic behavior of some of these indicators as they attempt to make their guesses. Fair enough. Plenty of other data analysts are in the same boat. Well, a team of researchers has been trying to quantify this sense of uncertainty using the Economic Policy Uncertainty Index, graphed above for the world’s five largest economies.

And how, exactly, does one transform a feeling into a number? According to the researchers, articles from major newspapers are analyzed for mentions of uncertainty related to aspects of economic policy, including the decisionmakers themselves, the actions undertaken, and the effects of those policies. The number of articles expressing uncertainty is standardized to the total number of articles written by each source; the accuracy of the resulting index is then tested by making comparisons with relevant indexes constructed through other methods.

The index associates historical events with the economic data. For example, the first significant spike outside of a recession in the above graph shows up in the first quarter of 2003. The spike is highest for Europe and occurred when 10 European countries were in talks to join the European Union under the condition that they’d eventually join the eurozone. The media covered these discussions in a way that uncertainty regarding policymakers, policies, and their effects came across in the index.

In 2008, as the financial crisis was unraveling, there was still much debate on what policies should be adopted and how effective those policies might be. This translated into an elevated index. Soon after, in 2011, the index spiked again in all countries. It’s likely that the uncertainty surrounding the economic and political events at the time, such as the European sovereign debt crisis and the U.S. debt-ceiling discussions, was captured by the index in this case as well.

After 2011, many nations appear to have maintained high levels of economic policy uncertainty that well surpass levels before the Great Recession. The impact of Britain’s vote to leave the European Union, several significant elections around the world, and similar newsworthy events are plainly visible in the all-time highs of the index in the past two years. If you’re not doing too well on FREDcast, you can use the pretty good excuse that there’s certainly a lot of policy uncertainty out there.

How this graph was created: Search for “economic policy uncertainty” and check the boxes next to the monthly series for the United States, Europe, China, India, and Japan. Select “Add to Graph.” Adjust the time range to begin in 1990.

Suggested by Maria Hyrc and Christian Zimmermann.

View on FRED, series used in this post: CHIEPUINDXM, EUEPUINDXM, INDEPUINDXM, JPNEPUINDXM, USEPUINDXM

How much do we spend on new houses?

The highs and lows in the numbers and values of new construction

Do we spend more on new houses than we used to? It can feel like it, especially because houses have become larger and available land has become more scarce. For a quantitative answer to this question, we can use FRED’s data on the number of new houses being sold across the U.S. and the median value of those houses. Multiplying these two indicators yields the total value of all houses sold in a given period. (Well, at least approximately: The mean would give us a better measure, but if the price distribution of new houses doesn’t change too much, this method will do.) Now, prices and incomes have generally increased, so we want to divide the total value of all houses sold by nominal GDP. The result is the series that we display in the graph above, with data normalized to 100 for the start of the sample.

What do we learn? 1) We spend relatively less on houses now, but we’re getting back to the trend. 2) There are strong seasonal factors in the sales volume of new houses. 3) Recessions are really bad for new house sales. 4) The U.S. spent historically high amounts for new houses just before the previous recession and then they dropped to historical lows. 5) Although this recent drop was extraordinarily severe, from a value of 183 to a value of 28 in the matter of a few years, the movements are also very large in other years and some values have doubled within a business cycle. After all, construction is known to be a very volatile sector, and this is especially true for new construction.

How this graph was created: search for “new houses sold, select the series and open the graph. Click on “edit graph” and add a series to the line by searching for median value, then again by searching for “nominal GDP.” Apply formula a*b/c. Finally, change the units ate the very bottom of the form to “Index” setting 100 on 1963-01-01.

Suggested by Christian Zimmermann.

View on FRED, series used in this post: GDP, HSN1FNSA, MSPNHSUS

Take it easy!

The Ease of Doing Business Index ranks regulatory environments around the world

In an increasingly competitive global economy, many in the private sector wonder whether their businesses would be better off if they were located somewhere else. FRED has data that can help shed some light on which countries foster the best business conditions: The World Bank’s Ease of Doing Business Index ranks 190 countries according to a combination of 10 factors, including cross-border trade, tax payment, electricity access, property registration, construction permits, and other issues related to how well the rules and regulations benefit private enterprise.

Despite its appearance as a simple ranking, the Ease of Doing Business Index is fairly intricate. It provides overall rankings as well as rankings in several categories. For example, New Zealand was ranked 1st overall in 2016, but was 55th in terms of trading across borders. Afghanistan was ranked 183rd overall, but was 42nd in ease of starting a business. It also tries to measure how far each country is from the ideal, with minute changes sometimes causing large moves in the rankings.

At its core, the index is about administrative hurdles and costs and thus doesn’t capture some factors that are relevant to the private sector, such as market size, labor force quality, and corruption. But the index still reflects these factors indirectly, because of how closely they’re tied to the indicators that are measured. For example, although macroeconomic stability isn’t explicitly incorporated into a nation’s ranking, it still impacts the time and cost of getting credit or starting a business, which is part of the ranking process.

A final consideration is the fact that data can be collected only from the formal economy. Many nations have large informal sectors and thus can be ranked lower in the index than they might be otherwise: The data disproportionately represent the more easily measured transactions in the formal economies of developed nations without taking into account the similarly efficient transactions in the informal economies of other nations. But, of course, the size of a country’s informal sector is likely correlated with the (lack of) ease of doing business in its formal sector.

How this map was created: The original post referenced an interactive map from our now discontinued GeoFRED site. The revised post provides a replacement map from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Maria Hyrc and Christian Zimmermann.



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