Probability Of A Double Dip Increases
Most data since then have supported that case.
Data from the housing sector have been relatively bullish, with house prices, pending home sales and residential construction all increasing after years of decline. Given the fact that the housing sector is particularly cyclical, this is an argument for the bullish case.
However, housing has not always been very useful as a leading indicator, and particularly not during the latest decade. During the 2001 recession, it didn't contract at all, and while housing did contract before the 2007-09 recession started, it started to contract as early as late 2005 and early 2006, almost two years before the overall economy started to contract. This means that even if housing has bottomed, it could take a long time before the overall economy recovers in a significant and sustainable way.
Just about all other news about the economy have at the same time been negative:
-The ISM Manufacturing index fell back.
-Non-residential construction continued to drop.
-Car sales fell dramatically.
-Real disposable income, both excluding and including the effects of transfer payments and taxes, continues to decline.
-Jobless claims increased.
-The ADP survey showed continued private sector job losses.
-After having increased in the previous weeks after previous big declines, money supply dropped again.
Clearly, the numbers suggests a renewed downturn in all sectors except housing, something which in turn most likely means a renewed overall downturn.
Tomorrow's employment report may perhaps settle the case, or if it is unexpectedly strong increase uncertainty. Remember however, that contrary to what most financial journalists suggests, the most important number from a macroeconomic perspective is neither the unemployment rate nor the change in payrolls. The most important number will instead be something which is not formally presented, but which can be easily calculated using other numbers. The most important number is aggregate labor income. That is a function of two other numbers presented: namely the number of payrolls and average weekly earnings. The latter is in turn a function of two factors: average work week and average hourly earnings.