A group of hunters look at 11 deer hanging on a buck pole at Skip's Sporting Goods in Grayling, Mich., Sunday, Nov. 15, Motels and sports shops in northern Michigan are already reaping the benefits of the hunting season. The firearms deer season is Nov (AP Photo/Brad Coville) Northbound traffic slows on the 5- mile-long Mackinac Bridge Friday, Nov. 14, Deer hunters are heading to camps in Michigan's Upper Peninsula for the opening of the firearms season Saturday, the first to fall on a weekend since (AP Photo/Liz Raffaele) Tourists to Cabela's pose next to a sculpture of two grizzley bears in Dundee, Mich., Aug. 30, The 17,000 pound statue was created by Mark Hamby, a former defensive end for the Buffalo Bills. (AP Photo/Carlos Osorio) Source: Economic Benefits of Deer Hunting in Michigan: What do you count?

Source: About ARC History of ARC In the mid 1960s, at the urging of two U.S. presidents, Congress created legislation to address the persistent poverty and growing economic despair of the Appalachian Region.

Examples of ARC Projects by Goal Area GOAL 1—Education and Workforce Training Making Appalachia’s Wood Industry More Competitive Developing Teaching Skills: Extending a Professional Development Network GOAL 2—Physical Infrastructure Revitalizing a Downtown Business District Building Water and Sewer Systems through Self- Help GOAL 3—Civic Capacity and Leadership Training Grassroots Leaders for Community Development Creating Practical Models for Community Change GOAL 4—Dynamic Local Economies Expanding Microloan Programs to Generate Business Growth Growing Businesses and Jobs through Incubators GOAL 5—Health Care Expanding Appalachians’ Access to Dental Care Creating Healthier Lives through Local Outreach Source and more details:

Not all ARC counties fit the stereotype of a rural, isolated, distressed area. e.g., see the data on suburban Atlanta counties: Atlanta Regional Commission Counties in Appalachia Georgia: Banks, Barrow, Bartow, Carroll, Catoosa, Chattooga, Cherokee, Dade, Dawson, Douglas, Elbert, Fannin, Floyd, Forsyth, Franklin, Gilmer, Gordon, Gwinnett, Habersham, Hall, Haralson, Hart, Heard, Jackson, Lumpkin, Madison, Murray, Paulding, Pickens, Polk, Rabun, Stephens, Towns, Union, Walker, White, and Whitfield Other ARC maps (reference and thematic):

Or look at the the Cincinnati region Counties in Appalachia Ohio: Adams, Athens, Belmont, Brown, Carroll, Clermont, Columbiana, Coshocton, Gallia, Guernsey, Harrison, Highland, Hocking, Holmes, Jackson, Jefferson, Lawrence, Meigs, Monroe, Morgan, Muskingum, Noble, Perry, Pike, Ross, Scioto, Tuscarawas, Vinton, and Washington Kentucky: Adair, Bath, Bell, Boyd, Breathitt, Carter, Casey, Clark, Clay, Clinton, Cumberland, Edmonson, Elliott, Estill, Fleming, Floyd, Garrard, Green, Greenup, Harlan, Hart, Jackson, Johnson, Knott, Knox, Laurel, Lawrence, Lee, Leslie, Letcher, Lewis, Lincoln, McCreary, Madison, Magoffin, Martin, Menifee, Monroe, Montgomery, Morgan, Owsley, Perry, Pike, Powell, Pulaski, Rockcastle, Rowan, Russell, Wayne, Whitley, and Wolfe Other ARC maps (reference and thematic): Cincinnati-Middletown, OH-KY-IN Metropolitan Statistical Area Dearborn County, IN Franklin County, IN Ohio County, IN Boone County, KY Bracken County, KY Campbell County, KY Gallatin County, KY Grant County, KY Kenton County, KY Pendleton County, KY Brown County, OH Butler County, OH Clermont County, OH Hamilton County, OH Warren County, OH

County Economic Status in Appalachia, FY 2003 Subregions in Appalachia Source: Percent Population Change in Appalachia, 1990–2000

§How do you determine the counterfactual? Several approaches: Regression analysis Matched pair before and after. However, this can be unreliable. Random assignment: control and experimental groups (Role of placebos -- to separate psychological and physical effects) Quasi-experiments (using the logic of experimental design, even though no control; use a pre-existing division of subjects into several groups. Example later in the presentation: the Gautreaux case in Chicago) beforeafter Matched pairs control experim ental Random assignment Identical in all but one characteristic (variable)

Matched pairs: criteria Estimating the counterfactual: find counties outside Appalachia that are otherwise similar

Matched pairs: the results

the start of the “treatment”

treatment

Conclusion Between 1969 and 1991 the counties of Appalachia grew faster than did their control-group twins. They averaged 48 percent more growth in income, 5 percent more in population, and 17 percent more in per capita income. These findings suggest that the Appalachian region has done relatively well since the Appalachian Regional Commission began its programs. Translated into dollar terms, the income growth differences between Appalachian counties and their twins meant $8.4 billion more income for Appalachia in 1991.

Are the ARC programs responsible for this progress? Did the $13 billion dollars in expenditures on ARC programs since 1965 produce a handsome return-$ 8.4 billion in additional income in one year alone? The two questions cannot be answered yes with certainty. As already mentioned, control group research ultimately requires a leap of faith. Some skeptics still insist that cigarette smoking has not been proven to cause higher incidence of lung cancer, and that perhaps some unknown factor, a gene maybe, causes some people both to smoke and to be more susceptible to lung cancer. Likewise, a skeptic might propose an alternative to the ARC to explain the findings of this study.

The role of research is to make the leap of faith as small as possible by systematically eliminating alternative explanations. For example, this analysis did not consider racial composition when matching counties. Arguably, ignoring factors associated with race in the U.S. might have caused the positive Appalachian finding. If predominantly white Appalachian counties were matched to predominantly black counties and the latter grew more slowly because of economic consequences of their racial composition, then the Appalachian growth effect might have been caused by the consequences of racial composition, not by the ARC. Racial composition can affect county growth rates through the historical legacy of segregated school systems, firms' biases against locating in places with large African-American populations, and an unequal distribution of public infrastructure, including roads and sewage facilities. If Appalachian counties do not suffer from similar legacies, biases, and inequitable distributions, ignoring race could have caused this study to find larger Appalachian growth differences than are warranted.

This possibility can be evaluated by adding percent black to the variables used to make county matches and then repeating the growth rate measurements. When doing so, new twins whose racial compositions better match those of the Appalachian counties replace the original twins for some counties. Fewer twins are drawn from Mississippi, Alabama, Georgia, and South Carolina. The mean growth rate differences using the new twins, however, contradict the racial composition hypothesis. The Appalachian counties outgrew their new twins by even more than they did the original ones. Therefore, ignoring racial composition did not cause the results reported here. In this manner, control group research narrows the leap of faith by considering and eliminating competing explanations.

The primary conclusion still stands. The counties served by ARC programs grew faster than their twins did. Exactly why some counties grew faster than their twins while others did not, and why some growth rate differences are large and others small remain beyond the scope of this study. To push the analogy with smoking studies further, control group research on that problem does not tell us precisely why some smokers died sooner than others. In both the smoking research and this Appalachian research, the crucial first step was the discovery that statistically significant differences exist. Now more research is needed to identify which ARC programs have been particularly successful and which ones ought to be adopted elsewhere under what conditions. The results presented here argue regional development planning has been successful in Appalachia. The next step is to learn more about why and how.

Source of images:

Why is 2.4 income multiplier < 4.3 employment multiplier?

From “break bulk” to containerization

From center city to peripheral, deep-water ports

“land bridge” “from intra-regional to inter-regional port competition

“land bridge” “from intra-regional to inter-regional port competition Dispersed economic benefits well into the hinterlands

(last slide)