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Introducing TIGC’s economic and population growth indexes (yawn)

As a kid, about the only sport I was halfway decent at was baseball (fair glove, no stick).  But one summer I had a health problem that kept me from playing and the coach (also my dad) stuck me in the press box (another formative moment) and made me keep the box score.  As part of that experience I wound up cobbling together crude statistical and performance reports on the team players (Jolly went two for three and fielded three grounders at second for outs at first; Studdard struck out five batters and walked one, drove in two runs … ).

During that same period, I was a rabid St. Louis Cardinals fan and went over all their performance stats in both the daily paper and the old Sporting News; I could tell you that the Cardinals would win 9 of 10 games if Bob Gibson struck out XX hitters and Musial and Boyer got YY hits between them.  Now, I tell you all that to make it abundantly clear (if it hasn’t been already) that you’re dealing here with a frustrated sports statistician.  I’m still a little annoyed that Bill James beat me to Sabermetrics.

I also tell you all this to serve notice that this post is going to be even more data-intensive, tedious and boring than most of my stuff.  Only serious geeks should sally forth.

Our subject matter today is county rankings.  I did an initial post back in October summarizing available economic, health and education rankings, but said at the time I wasn’t satisfied with that first pass and would loop back for a second take after wallowing around in the data for a bit.  Among the main things I’m looking for are how to gauge growth, directionality (are things getting better or worse?), and the magnitude of the quantitative and qualitative differences among Georgia’s 159 counties (don’t say I didn’t warn you).

You can think of this as TIGC’s crude answer for pro football’s quarterback rating system (QBR) or ESPN’s football power index (FPI).  It’s an effort to synthesize a lot of different data points into a single number, or maybe a couple of numbers.  It’s also a work in progress.

(Indeed, let me pause here to invite any actual statisticians or data geeks who have stumbled onto this page to make suggestions as to how I can improve the approach you’ll find below.)

Why, you might ask, would I or anybody else care about that kind of data?  Good question.  Part of the answer is that I may have too much time on my hands.  But the more serious answer is that I think it could be helpful in deciding how to attack different types of development problems throughout the state.

I have long thought the state should be triaging its rural counties and sorting them into different groups depending on what kind of shape they’re in.  Some may be too far gone for traditional community and economic development initiatives to work.  Others may still have a pulse and might be revived with the right kind of support and assistance.

To aid in that effort, I am hereby introducing the Trouble in God’s Country Population Growth Index (TIGC PGI) and the Trouble in God’s Country Economic Growth Index (TIGC EGI).  To concoct these indexes, I spent more time than I ought to admit thinking about which time frames to use and finally settled on a combination of 10-year, five-year and one-year growth rates.  I figured the longer-term growth rate was the most important and assigned the 10-year rate 60 percent of the total value of my indexes.  The five-year growth rates were weighted at 30 percent and the one-year rates got the final 10 percent.

I warned you.  If your eyes are glazing over, feel free to skip the next part and go straight to the growth indexes and rankings below.

If you’re still with me, the basic formula looks like this:

TIGC Index = ((10yr Growth Rate x 6)+(5yr Growth Rate x 3)+(1yr Growth Rate x 1))

The bigger the number, the better.

Still missing from my equation is a recognition of the size differences – of both local populations and economies.   I’m still noodling with different approaches to that and (as indicated above) would welcome suggestions from data geeks who are more statistically literate than I am.

To complicate matters further, I’ve combined two county-level economic metrics – gross domestic product (GDP) and total personal income (TPI).  This is part of what I spent way too much time fiddling with, but in the end I decided both were important.  As an example, Forsyth County, which is at or near the top in every economic, education and health category I’ve studied, ranked 19th for GDP growth but 1st for TPI growth.  As another example, tiny Randolph County, which is near the bottom in every category, ranked an unbelievable 1st in GDP growth but 154th in TPI growth.

So, to figure the overall TIGC Economic Growth Index I calculated the GDP and TPI indexes separately and then simply added them together, assigning each equal weight.  The TIGC Population Growth Index was calculated using the same split described above.

I’ll follow up shortly with a post with some thoughts on what all this means, or at least suggests.

For now, though, here’s a data dump with the economic and population indexes for each county.  The sort is by the Economic Growth Rank.

County TIGC GDP Growth Index TIGC TPI Growth Index TIGC Economic Growth Index TIGC Economic Growth Rank TIGC Population Growth Index TIGC Population Growth Rank
Forsyth 3.15 6.91 10.06 1 3.23 2
Oconee 3.80 6.25 10.05 2 1.92 5
Jackson 4.25 5.56 9.81 3 1.60 9
Bryan 4.03 4.91 8.94 4 2.33 3
Randolph 7.66 1.21 8.87 5 -0.81 151
Cherokee 3.29 5.26 8.54 6 1.75 7
Burke 5.71 2.54 8.25 7 -0.23 115
Dawson 3.32 4.87 8.18 8 1.20 15
Greene 2.04 5.99 8.02 9 0.99 24
Twiggs 5.26 2.74 8.00 10 -0.92 157
Fulton 2.83 5.07 7.90 11 1.31 14
Effingham 2.81 4.49 7.30 12 1.82 6
Barrow 2.56 4.60 7.16 13 1.63 8
Hall 2.34 4.77 7.11 14 1.11 18
Columbia 2.25 4.75 7.01 15 2.29 4
Long 1.64 5.38 7.01 15 3.42 1
Paulding 2.59 4.30 6.89 17 1.56 10
Walton 2.71 4.11 6.82 18 1.08 21
Hart 3.44 3.36 6.80 19 0.32 65
Clinch 2.35 4.40 6.76 20 -0.31 124
Pickens 2.55 3.99 6.54 21 0.77 34
Morgan 2.19 4.30 6.49 22 0.52 50
Fannin 2.11 4.38 6.48 23 0.95 26
Banks 2.91 3.48 6.39 24 0.49 53
Franklin 3.40 2.98 6.37 25 0.35 62
Coweta 1.92 4.33 6.26 26 1.47 11
Cobb 2.46 3.79 6.25 27 0.86 31
Gwinnett 2.45 3.66 6.11 28 1.40 13
Henry 2.46 3.62 6.08 29 1.40 12
Taliaferro 3.36 2.72 6.08 29 -0.85 156
Fayette 2.09 3.83 5.92 31 0.63 42
White 2.13 3.67 5.81 32 1.00 22
Lumpkin 1.52 4.27 5.79 33 0.99 23
Warren 4.00 1.63 5.63 34 -0.85 155
DeKalb 1.56 4.07 5.63 35 0.79 33
Peach 2.82 2.75 5.57 36 0.06 91
Lanier 2.26 3.30 5.56 37 0.46 55
Talbot 3.34 2.07 5.41 38 -0.67 144
Madison 2.20 3.20 5.40 39 0.56 47
Pike 1.83 3.52 5.35 40 0.51 51
Chatham 2.09 3.22 5.31 41 0.92 29
Telfair 3.77 1.54 5.31 41 -0.27 121
Dade 2.19 2.88 5.07 43 -0.20 112
Gordon 1.55 3.51 5.07 43 0.46 56
Brantley 2.40 2.63 5.03 45 0.56 48
Bulloch 1.56 3.44 5.00 46 1.16 16
Appling 1.87 3.08 4.95 47 0.15 81
Bacon 1.70 3.17 4.88 48 0.11 84
Clarke 1.16 3.65 4.81 49 0.76 35
Clayton 2.33 2.47 4.80 50 0.94 27
Heard 2.22 2.57 4.79 51 0.13 83
Newton 1.63 3.08 4.71 52 0.92 28
Jasper 1.00 3.69 4.69 53 0.23 72
Douglas 1.99 2.69 4.68 54 0.95 25
Oglethorpe 1.95 2.72 4.67 55 0.30 66
Glascock 1.89 2.71 4.60 56 -0.11 107
Whitfield 1.10 3.50 4.60 56 0.25 69
Webster 1.55 3.03 4.58 58 -0.28 122
Towns 0.37 4.18 4.55 59 1.11 19
Harris 1.04 3.42 4.46 60 0.91 30
Atkinson 1.76 2.68 4.44 61 -0.03 97
Butts 1.45 2.97 4.42 62 0.24 71
Carroll 1.20 3.22 4.42 63 0.59 44
Bartow 1.04 3.37 4.41 64 0.66 40
Troup 2.04 2.34 4.38 65 0.43 59
Union 0.80 3.56 4.36 66 1.15 17
Tift 1.28 2.88 4.16 67 0.15 82
Gilmer 0.49 3.64 4.13 68 0.79 32
Stewart 2.28 1.77 4.05 69 0.75 37
Wheeler 0.80 3.25 4.05 69 0.71 38
Lee 0.64 3.40 4.04 71 0.44 58
Polk 1.53 2.43 3.96 72 0.28 68
Lowndes 0.77 3.18 3.95 73 0.75 36
Pierce 0.65 3.27 3.92 74 0.46 57
Rockdale 1.54 2.38 3.92 74 0.66 41
Stephens 0.70 3.23 3.92 74 0.07 87
Camden 1.09 2.82 3.91 77 0.62 43
Haralson 0.90 2.99 3.90 78 0.32 64
Coffee 1.15 2.74 3.89 79 0.19 74
Wilkes 0.64 3.25 3.89 79 -0.44 135
Quitman 1.49 2.34 3.82 81 -0.77 149
Rabun 0.25 3.54 3.78 82 0.33 63
Grady 1.33 2.43 3.76 83 -0.04 98
Houston 0.53 3.21 3.74 84 1.09 20
Lamar 1.04 2.64 3.68 85 0.52 49
Thomas 0.71 2.86 3.57 86 -0.05 100
Crisp 0.75 2.80 3.55 87 -0.26 119
Habersham 0.84 2.66 3.49 88 0.57 46
Glynn 0.46 3.00 3.46 89 0.70 39
Laurens 1.33 2.11 3.45 90 -0.14 109
Jeff Davis 1.39 2.01 3.40 91 0.18 75
Murray 0.98 2.38 3.36 92 0.07 89
Richmond 0.84 2.52 3.36 92 0.10 85
Taylor 1.74 1.62 3.36 92 -0.74 146
Screven 0.22 3.13 3.35 95 -0.41 131
Walker 0.92 2.29 3.22 96 0.16 78
Catoosa 0.51 2.65 3.17 97 0.51 52
Emanuel 0.87 2.30 3.17 97 0.05 93
Early 1.56 1.60 3.16 99 -0.63 143
Muscogee 0.63 2.49 3.12 100 0.17 76
Lincoln 0.02 3.09 3.11 101 -0.10 106
Spalding 0.37 2.73 3.10 102 0.36 61
McIntosh 0.23 2.82 3.05 103 0.24 70
Monroe -0.37 3.34 2.97 104 0.47 54
Meriwether 0.83 2.08 2.91 105 -0.43 133
Hancock 1.03 1.83 2.86 106 -1.12 158
McDuffie 0.37 2.44 2.81 107 -0.07 102
Jones 0.39 2.33 2.73 108 0.02 96
Floyd 0.15 2.58 2.72 109 0.19 73
Macon 0.68 2.02 2.71 110 -0.75 147
Ware 0.38 2.31 2.69 111 -0.07 103
Bibb 0.74 1.92 2.66 112 -0.09 104
Cook 0.24 2.35 2.59 113 0.05 94
Candler 0.33 2.25 2.58 114 0.06 92
Chattooga 0.04 2.22 2.26 115 -0.34 126
Pulaski 0.67 1.53 2.20 116 -0.43 134
Upson 0.11 2.07 2.18 117 -0.27 120
Crawford 0.95 1.19 2.14 118 -0.35 128
Tattnall 0.58 1.52 2.09 119 0.37 60
Echols -0.92 2.98 2.07 120 0.09 86
Colquitt 0.00 2.00 2.01 121 0.06 90
Marion -0.62 2.52 1.90 122 -0.09 105
Miller 0.11 1.79 1.90 122 -0.59 142
Sumter 0.25 1.65 1.90 122 -0.75 148
Johnson -0.29 2.19 1.89 125 -0.31 125
Washington -0.21 2.02 1.82 126 -0.25 118
Wilkinson -0.30 2.12 1.82 126 -0.50 138
Dooly -0.55 2.35 1.80 128 -0.34 127
Evans -0.53 2.31 1.77 129 -0.19 111
Charlton -0.08 1.80 1.73 130 0.15 80
Ben Hill -0.19 1.88 1.69 131 -0.42 132
Jefferson -0.01 1.69 1.68 132 -0.69 145
Jenkins 0.09 1.57 1.66 133 0.07 88
Elbert -0.24 1.89 1.65 134 -0.45 136
Dougherty -0.01 1.47 1.46 135 -0.25 117
Baldwin -0.43 1.86 1.43 136 -0.47 137
Berrien -0.76 2.19 1.43 136 0.16 77
Toombs -0.49 1.92 1.43 136 -0.14 108
Liberty -0.56 1.97 1.41 139 -0.15 110
Wilcox -0.30 1.63 1.33 140 -0.21 113
Dodge -0.36 1.60 1.24 141 -0.30 123
Irwin -0.82 1.97 1.15 142 -0.24 116
Montgomery -0.83 1.95 1.12 143 0.15 79
Mitchell -0.90 1.96 1.06 144 -0.53 141
Seminole -1.01 2.04 1.03 145 -0.52 140
Decatur -0.46 1.47 1.02 146 -0.40 130
Schley -1.33 2.33 1.00 147 0.58 45
Treutlen -1.27 2.19 0.91 148 0.03 95
Brooks -0.70 1.54 0.84 149 -0.39 129
Clay -0.08 0.90 0.81 150 -0.79 150
Worth -0.78 1.52 0.74 151 -0.51 139
Turner -0.67 1.28 0.60 152 -0.85 154
Wayne -1.05 1.57 0.52 153 -0.06 101
Terrell -0.95 1.40 0.45 154 -0.84 153
Bleckley -1.13 1.29 0.16 155 -0.04 99
Putnam -2.98 3.13 0.16 155 0.29 67
Baker -1.16 0.60 -0.57 157 -1.28 159
Calhoun -1.65 0.76 -0.89 158 -0.21 114
Chattahoochee -2.39 -0.59 -2.98 159 -0.83 152

 

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