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Featured Column: Can Insight Come From Our Recent, Painful Past?

Published September 10, 2013

With the U.S. economy recovering, California seems on the verge of renewed prosperity. After years of economic stress, more Californians have jobs. Incomes are rising. Retail sales are expanding. The housing market continues to improve. State policy makers can turn their attention to other, more pressing matters.

Before the memory of the recession fades, however, now might be a good time to consider how State fiscal policy might be calibrated to mitigate the effects of the next cyclical downturn.

The State's economy is large and diverse, so its fiscal policy often defies facile one-size-fits-all solutions. Depending on the particular character of macroeconomic trends and local economies, a recession may affect one region in a very different way than it affects its neighbors. In the early 1990s for example, the recession hit the Los Angeles region much harder than it did the Bay Area -- in part because Los Angeles was more sensitive to changes in federal defense spending and the aerospace industry.

To study the regional effects of the Great Recession, researchers at the Milken Institute (including James R. Barth, Kevin Klowden, Donald Markwardt and Ross DeVol) have been looking at economic indicators across counties for the period 2011 and 2012. They researched broad economic indicators, including per-capita income, unemployment rates, poverty rates and the relative size of public-sector employment by county. Their preliminary work lends support for tentative conclusions about the impact of the recession and the nascent recovery. These conclusions, as listed below, might help inform future policy debates:

1. California evidences broad income disparities among counties. Figure 3 ranks counties by income, with the blue bars measuring per-capita income in each county. The graph shows that incomes, scaled on the top horizontal axis, varied from a high of about $85,000 per person in Marin County to a low of nearly $27,000 in Del Norte County. The mean per capita income by county was $40,000, and 24 counties were above the mean. Bay Area counties were the top six highest-income areas. Orange, San Diego and Los Angeles Counties were all above the mean. Central Valley, Inland Empire and most counties north of Sonoma County were below the mean. The income variations across counties, indeed regions, are substantial and suggest that local governments have equally broad variation in their ability to respond to economic downturns.
2. California’s unemployment rates vary across counties and regions, between a low of 6.9 % in Marin, San Francisco and San Mateo Counties, and a high of 28.3 % in Imperial County. Figure 1 displays the unemployment rate by county with red bars scaled on the bottom horizontal axis. Again, urban counties along the coast tended to have healthier economies than did the northern, rural and suburbanizing counties. The counties with higher incomes tended to have lower unemployment, at least in the period covered by the Milken study.

As displayed in the figure, differences among counties may affect how state and local governments shape their policy decisions and choose among alternatives in times of cyclical distress. For example:

1. Regional limitations on fiscal capacity. Income differences among counties may limit how much discretion poorer counties have in responding to cyclical downturns. The Bay Area counties, with their per capita incomes at least twice as high as the Central Valley counties, have greater income to cushion the effects of temporary economic downturns. They may also have greater fiscal capacity to finance counter-cyclical assistance. If the State were to provide assistance during recessions, it could rely on its relative advantage to construct, finance and manage income-transfer programs.
2. Not all counties recover at the same time. Smaller, rural or suburbanizing counties may have less diverse economies, so they may be prone to experience more acutely the impact of changes in economic conditions. This may mean that -- as perhaps in the last recession -- these counties are slower to recover and may need more sustained or targeted assistance. If in future recessions the State were to enact statewide assistance policies, it may want to monitor economic recovery patterns among counties so that those regions experiencing slower recoveries may continue receiving appropriately calibrated assistance.
3. State assistance may be cheaper in counties which lag in recovery. The Milken data show that the counties with lower income and higher unemployment rates tend to have lower population densities. Policy intervention to assist these counties may be cheaper to finance if the assistance was targeted to the most stressed — but less populous — counties.

Given the widespread — and often seemingly intractable — nature of the Great Recession, policy makers at all levels of government sometimes struggled to craft assistance measures with sufficient precision. The Milken data provide a perspective on the regional effects of the Great Recession. Regions seemed to experience the recession in broadly different ways. These differences suggest that future state policy may benefit from regionally calibrated responses to economic downturns.

Figure 3: Comparing Income and Unemployment Rate By County

Source:  Milken Institute

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