Wall Street Journal Economic Forecast Survey January 2016 – Notable Aspects

The January Wall Street Journal Economic Forecast Survey was published on January 14, 2016.  The headline is “Economists See Continued U.S. Expansion, Heightened Global Risk.”  As indicated in the article, 76 economists were surveyed, although not every economist answered every question.

I found numerous items to be notable – although I don’t necessarily agree with them – both within the article and in the “Economist Q&A” section.

An excerpt:

Most economists think the American economy will continue to expand, but weakness abroad is heightening their concern about U.S. growth. Forecasters in The Wall Street Journal’s latest survey of economists say there is a 17% chance the U.S. will enter recession in the next year, the highest risk in three years. And 80% of forecasters said they see risks to the economy to the downside.

As seen in the “Recession Probability” section – and mentioned above – the average response as to the odds of another recession starting within the next 12 months was 16.93%; the average response in December’s survey was 15.00%.

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The current average forecasts among economists polled include the following:

GDP:

full-year 2015:  2.0%

full-year 2016:  2.5%

full-year 2017:  2.4%

full-year 2017:  2.3%

Unemployment Rate:

December 2016: 4.7%

December 2017: 4.6%

December 2018: 4.8%

10-Year Treasury Yield:

December 2016: 2.79%

December 2017: 3.26%

December 2018: 3.62%

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Please Note – The above is excerpted from the EconomicGreenfield.com (published by RevSD, LLC) post of January 14, 2016, titled “The January 2016 Wall Street Journal Economic Forecast Survey”

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RevSD, LLC offers the above commentary for informational purposes only, and does not necessarily agree with the views expressed by these outside parties.

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RevSD, LLC is a management consulting firm and strategic advisory that focuses on the analysis of current and future weak(ening) economic conditions, and offers businesses and other entities advice, strategies, and actionable methods on how to optimally adapt to such challenging, complex conditions.