I would encourage you to have a read of the 2014 Baltimore Business Review.  Produced by the CFA Institute  — Baltimore, and Towson University, it  is a great example of how academics and practitioners can work together.  Here is my article, reformatted so that it looks better on my blog:

Differences in US States’ Unemployment over the Last 36 Years

Unemployment is often treated as a national issue, but unemployment is often driven by regional or industry sector issues. This article pries apart the causes of unemployment since 1976, state-by-state.

Though there is a national component to every US state’s unemployment level, it is notable that local factors often dominate national trends. Here are some examples:

  • North Dakota has an energy boom amid increasing unemployment following the housing bust in 2008.
  • Texas had increasing unemployment in the mid-1980s as energy prices fell dramatically, in the midst of an economic boom.
  • Coastal economies benefited during the housing boom (pre-2008), and were punished in the bust – this is parallel to the US economy as a whole, but more severe.
  • The Rust Belt prospered slowly in the early 1980s as the rest of the nation began to prosper rapidly.

The rest of this article will explain the causes of unemployment over the last 36 years, related to how connected a state is to the rest of the US economy, and how well the industry mix in a given state is doing.

Data & Method

Unemployment data for each state and the US as a whole was obtained from the St. Louis Federal Reserve’s Federal Reserve Economic Data (FRED) database. The data covers the period from 1976 to August 2013. Ordinary least squares regression was used to calculate how sensitive unemployment rates were in each state relative to overall US unemployment rates. The equation looks like this:

Ustate,t = ?state + ?stateUUS,t + ?state,t

The intuition behind this equation is that the unemployment rate of a given state can be explained by the amount that it varies in proportion to the unemployment rate for the US as a whole (the beta term), a fixed difference (the alpha term), and the error term. Here were the results by State:

State Alpha Beta Alpha SD Beta SD R-squared Alpha T-stat Beta T-Stat Correlation Group
Michigan      (2.50)  1.67         0.25       0.04

81.46%

           (9.98)          17.82

3

Nevada      (2.44)  1.42         0.22       0.03

80.77%

         (11.22)          12.80

2

Indiana      (2.47)  1.35         0.20       0.03

81.90%

         (12.42)          11.63

3

Alabama      (1.80)  1.32         0.23       0.03

75.95%

           (7.72)           9.06

6

West Virginia       0.28  1.24         0.48       0.07

40.15%

            0.59*           3.42

6

Ohio      (1.10)  1.23         0.17       0.03

83.93%

           (6.49)           9.21

3

Rhode Island      (1.03)  1.17         0.26       0.04

65.95%

           (3.88)           4.33

5

Illinois      (0.51)  1.17         0.14       0.02

87.48%

           (3.64)           8.08

3

Tennessee      (0.86)  1.17         0.15       0.02

85.25%

           (5.65)           7.29

3

North Carolina      (1.44)  1.14         0.19       0.03

77.35%

           (7.40)           4.85

2

Oregon      (0.00)  1.13         0.17       0.03

80.95%

           (0.03)*           5.11

3

South Carolina      (0.72)  1.13         0.18       0.03

79.11%

           (3.94)           4.69

2

California       0.20  1.12         0.18       0.03

79.43%

            1.14*           4.61

5

Washington       0.07  1.09         0.15       0.02

83.84%

            0.49*           3.98

6

Florida      (0.53)  1.07         0.18       0.03

78.09%

           (2.93)           2.80

5

Pennsylvania      (0.33)  1.07         0.14       0.02

85.43%

           (2.40)           3.52

6

Wisconsin      (1.30)  1.07         0.17       0.03

78.88%

           (7.49)           2.57

3

Arizona      (0.50)  1.06         0.18       0.03

77.62%

           (2.81)           2.28

2

Kentucky       0.20  1.05         0.20       0.03

72.97%

            1.00*           1.56*

3

New Jersey      (0.10)  1.01         0.21       0.03

68.87%

           (0.47)*           0.32*

5

Mississippi       1.57  0.99         0.27       0.04

57.37%

            5.86          (0.29)*

3

Missouri      (0.28)  0.97         0.12       0.02

86.47%

           (2.35)          (1.54)*

4

Georgia      (0.22)  0.96         0.16       0.02

78.07%

           (1.37)*          (1.81)*

2

Delaware      (0.83)  0.95         0.20       0.03

67.93%

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