In the news.

The overuse of the word “Strong” in economic news.

The US economy added 228,000 new jobs in November of 2017 and analysts rush to assess the state of the economy as “STRONG.” Although the job reports are indeed good indicators of the performance of the US economy, one should not simplify the job report as the snapshot of the economy that allows for those “strong” conclusions by and in itself. In this post, I show that despite the existence of a cointegration vector between unemployment rate data and the word-count of the word “Strong” in the Beige Book, journalists indeed overuse the word “Strong” in headlines. Although interpreting cointegration as elasticity goes beyond the scope of this post, I think that by looking at the cointegration relation it is safe to conclude that the current word count does not reflect the “strong” picture showed by the media, but somewhat more moderate economic conditions.

To start, let me go back to the first week of December of 2017. Back then, news outlets had headlines abusing the word “strong.” Some examples came from major newspapers in the US such as the New York Times, Reuters, CNN and the Washington Post. The following excerpts are just a sample of the narrative seen those days:

“The American economy continues its strong performance” (CNN Money).

“The economy’s vital signs are stronger than they have been in years” (NY Times).

“Strong US job growth in November bolsters economy’s outlook” (Reuters).

“These are really strong numbers, which is pretty exciting…” (Washington Post).

Getting to know what is happening in the economy challenges economists’ wisdom. Researchers are constrained by epistemological limits of data and reality, and so are journalists. To understand economic conditions, researchers utilize both quantitative and qualitative data while journalists focus on qualitative most of the times. Regarding qualitative data, the Beige Book collects anecdotes and qualitative assessments from the twelve regional banks of the Federal Reserve system that may help news outlets to gauge news statements and headlines. The Fed studies business leaders, bank employees, among other economic agents to gather information about the current conditions of the US economy. As a Researcher, I counted the number of times the word “strong” shows up in the Beige Book starting back in 2006. The results are plotted as follow:

If I were going to identify a correlation between the word count of “strong” and its relation to the unemployment rate, it would be very hard to do so by plotting the two lines simultaneously. Most of the times, when simple correlations are plotted, the dots show any relation between the two variables. However, in this case, cointegration goes a little deeper into the explanation. The graph below shows how the logs of both variables behave contemporarily over time. They both decrease during the Great Recession as well as they increase right after the crisis started to end. However, more recently both variables began to divert from each other, which makes it difficult to interpret, at least in the short run.

Qualitative data hold some clues in this case. Indeed, the plot shows a decreasing trend in the use of the word within the Beige Book. In other terms, as journalists increase its use in headlines and news articles, economists at the Federal Reserve Bank decrease the use of the word “strong”. If I were going to state causality from one variable to the other, first I would link the word “strong” to some optimism for expected economic outcomes. Thereby, one should expect a decrease in the unemployment rate as the use of the word “strong” increases. This is a classic Keynesian perspective of the unemployment rate. Such relation of causality might constitute the cointegration equation that the cointegration test identifies in the output tables below. In other words, the more you read “strong,” the more employers hire. By running a cointegration test, I can show that both variables are cointegrated over time. That is, there is a long-term relationship between both variables (both are I(1)). The cointegration test shows that at least there exists one linear combination of the two variables over time.

The difficulty with the overuse of the word nowadays is that the word is not being used by economists in the Federal Reserve at the same pace as journalist economists do. In fact, the word-count has decreased drastically for the last two years from its peak since 2015. Such mismatch may create false expectations about economic growth, sales and economic performance that may lead to economic crisis.

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