Wall Street Journal Economic Forecast Survey January 2013 – Notable Aspects

The January Wall Street Journal Economic Forecast Survey was published on January 10, 2013.  The headline is “‘Cliff’ Deal Seen Hitting Growth.”

Although I don’t agree with various aspects of the survey’s contents, I found numerous items to be notable, both within the article and in the Q&A found in the spreadsheet.

An excerpt from the article:

The economists expect the economy to expand at a tepid 2.3% pace in 2013, barely above the 2% rate they estimate for growth last year. That isn’t fast enough to bring down the unemployment rate quickly. On average, the economists still expect a 7.4% unemployment rate at year-end, compared with the current 7.8%. They don’t see unemployment falling below 7% until sometime in 2015.

Though the economists were largely unimpressed with the deal to avert the fiscal cliff, only 15 respondents said the agreement is actively bad for the economy. Indeed the average odds of a recession in the next 12 months tumbled to 19% from 24% last month, the first time they have been below 20% since last June.

The current average forecasts among economists polled include the following:


full-year 2012:  2.0%

full-year 2013:  2.3%

full-year 2014:  2.9%

full-year 2015:  3.0%

Unemployment Rate:

December 2013: 7.4%

December 2014: 7.0%

December 2015: 6.4%

10-Year Treasury Yield:

December 2013: 2.34%

December 2014: 2.97%

December 2015: 3.59%


Please Note – The above is excerpted from the EconomicGreenfield.com (published by StratX, LLC) post of January 14, 2013, titled “The January 2013 Wall Street Journal Economic Forecast Survey


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


StratX, 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.