The 1929 stock market crash on Black Thursday, followed by the subsequent four-year period of extreme economic downturn, signifies an extremely profound piece of U.S. history. During this time, global economic productivity – measured by GDP – decreased while the U.S. unemployment rate increased staggeringly. Leveraging construction permits as a forward-looking measure of economic activity, I empirically evaluate the effect of construction permits – specifically, the lagged growth rate of monthly construction permits – and lagged monthly stock returns on monthly Standard & Poor's 500 (S&P 500) stock returns. Lagged construction permit returns and lagged stock returns provide early indications (i.e., stock returns) of the following Great Depression.

Using MSA level data, the paper shows, that geographic areas which experienced the largest housing bubble generally suffered a more serious subsequent economic downturn. More specifically, the paper establishes that MSAs with larger declines in housing permits had larger increases in unemployment. There also appears to be strong evidence of a correlation between the magnitude of a housing boom and the timing of the decline in housing permits. MSAs which experienced larger real housing inflation offered early indications of the subsequent Great Recession.

Southern California is the largest U.S. metropolitan area geographically, and demonstrates complex spatial relationships between county labor markets. This paper is interested in investigating the employment dependencies between the core city of Los Angeles its respective commuting sheds, such as San Bernardino and Riverside counties. Using time series data that includes labor demand shocks from the Great Recession, this analysis implements a vector autoregressive model to dissect the relationship between urban and suburban employment changes. The work finds a strong lagging-leading relationship between counties that varies by business cycle phase, and provides policy implications from this relationship.