Unemployment Across Time and Space: Will the State Differences Stay Around Forever?

R.T. Young

R.T. Young, Ph.D. Business Economics

It is an often-heard discussion point: why do states such as California or New York have such high unemployment rates?

Observers have pointed to various causes, including high tax rates, generous welfare programs and high regulation. How big of an effect these factors have on state unemployment rates is not the point of discussion here. Rather, the discussion point is whether high unemployment rate states today will be low unemployment rate states five years from now (i.e., is there a reversion to the mean?).

The following is a look the average unemployment rate by state for 2012.

The state with the highest unemployment rate is Nevada at around 11 percent, followed by California at 10.5 percent, Rhode Island at 10.4 percent, New Jersey at 9.5 percent and North Carolina at 9.5 percent.

On the other end of the spectrum, North Dakota has the lowest unemployment rate at 3.1 percent, followed by Nebraska at 3.9 percent, South Dakota at 4.4 percent, Vermont at 5 percent and Oklahoma at 5.2 percent.

Graph 1

The above figure is a snapshot in time. The question here is how reliable of an indicator is the current snapshot of how things will be five and 10 years from now?

Here is a look at how unemployment rates have changed by state since 1976 in animated GIF format.

It’s tough to tell from the bar charts what exactly is happening. Perhaps a geographic look would provide a better perspective. The following plots the changes in unemployment rate by state by geographic area.

Although it’ still tough to see, there appears to be some staying power in the idea that certain high unemployment rate states may stay high unemployment rate states. At the same time, there also appears to be some shifting in overall ranking, meaning that some states shift from being high unemployment rate states to low unemployment rate states, and vice versa.

To inspect this further, the following plots the unemployment rate ranking by state by year in 10-year increments.

The first figure shows the unemployment rate by state in 1976 compared to the unemployment rate by state in 1986. The vertical axis is the state’s 1986 average unemployment rate and the horizontal axis is the state’s 1976 average unemployment rate. The gray horizontal line is the average of the states in 1986 and the vertical gray line is the average of the states in 1976.

The green line represents a linear regression line. If there was a relationship between the two, such as high unemployment rate states tending to stay high unemployment rate states, then the linear regression line would be upward sloping, indicating that the higher the state’s unemployment rate in 1976, the higher the anticipated unemployment rate in 1986. If the green line is downward sloping, then a high unemployment rate in 1976 would be associated with a low unemployment rate in 1986. As a note, the green line is not statistically significant.

Anything surprising?

Well, as represented by the green line, there’s really no relationship between the two. Essentially, high unemployment rate states in 1976 were not necessarily high unemployment rate states in 1986 and high unemployment rate states in 1976 were not necessarily low unemployment rate states in 1986.

The slope, however, is weakly downward sloping, which, if it were statistically significant, would be evidence in favor of the latter — that high unemployment rate states in 1976 tend to be low unemployment rate states in 1986 and vice versa.

With the broad conclusions addressed, the individual states’ figures are interesting. For example, California had a high unemployment rate in 1976 but shifted to having about an average unemployment rate in 1986. States with improvement in their unemployment rates from 1976 to 1986 are in the lower left quadrant.

In contrast, some states made no improvement. For example, Michigan was a high unemployment rate state in 1976 and stayed that way in 1986. The same story holds true for such states as New Mexico, Oregon, Washington, Ohio, Alaska and a few others (states with this story are the top right quadrant).

The poor-performing states are contrasted with states that stayed in good times throughout the entire ten years. The bottom left quadrant states had low unemployment rates in 1976 and low unemployment rates in 1986. Among these states are South Dakota, Nebraska and Kansas.

The last quadrant is the top left. These states had low unemployment rates in 1976 and deteriorated into high unemployment rate states in 1986. States with this experience include Kentucky, Wyoming and Idaho.

Graph 2

The following figure compares unemployment rates in 1986 to 1996. Interestingly, the slope of green line over this period is positive and statistically significant. The positive green line indicates that high unemployment rate states tended to stay that way and low unemployment rate states tended to stay that way.

Graph 3

Continuing, the following plots unemployment rates in 1996 against unemployment rates in 2006. Again, the relationship is positive and statistically significant (green line), indicative of staying power in state unemployment rates.

Graph 4

The last figure plots 2006 and 2012. Again, the relationship is positive — states that had low unemployment rates in 2006 also tended to have low unemployment rates in 2012 (bottom left quadrant) and states that had high unemployment rates in 2006 tended to have high unemployment rates in 2012. States that bucked this trend for the better are in the bottom right quadrant, which includes Alaska, Texas, Massachusetts and a few others. States that bucked the staying power trend for the worse (top left quadrant) include Florida and Colorado.

Graph 5

Overall, high unemployment rate states today probably will stay on the bottom rung of the employment picture in five or 10 years from now, but there’s certainly no guarantee. If there is any reversion to the mean phenomenon in the unemployment rate figures, there’s a reasonable chance that some high unemployment rate states, such as California or Nevada, may become low unemployment rate states in the near future. If you currently live in a low unemployment rate state you might want to pay attention to what businesses and policymakers are doing, because high unemployment rate states are certainly making changes to improve their labor market and it may come at the expense of jobs in your state. After all, who wants to be Michigan or California for too long? The invisible hand of the market has a way of punishing the unsuspecting or latent, akin to what it did to Michigan over the past 30 years.

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About R.T. Young

R.T. Young

R.T. Young, Ph.D. Business Economics

R.T. is a business economist and angel investor. R.T. spends his days doing advanced statistical analysis and writing for businesses and elected officials across the United States, Europe and Asia. In his off-time, R.T. enjoys basketball, football, baseball and most any other sport. R.T. holds a Ph.D. in business economics and a bachelor’s degree in physics.

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