This blog is about economic development and regionalism, not politics. But, if you've been listening to the pundits parse the election results since last Tuesday, it's not difficult to see the connection, especially in states like North Carolina. The conventional wisdom goes something like this:

1. Technology-led economic development gives regions with large research universities a competitive advantage because they attract world-class talent. The Research Triangle Park has three--Duke, UNC, and N.C. State--within 20 minutes drive time.

2. Talent attracts companies. Talent also attracts more talent. Consult any "best of" list and you'll find Raleigh-Durham at the top of the rankings. Charlotte, Greensboro, and Winston-Salem are getting their fair share of attention lately as well. Regional branding efforts like the Piedmont Triad Partnership and Charlotte USA are clearly paying off. Pick any hot sector in economic development circles right now and there's at least one region in North Carolina with a legitimate shot at it. 

3. The Creative Class is gaining steam in our increasingly service-based economy, and picking economic development winners in the process. The joke growing up was that CARY, a small suburb west of Raleigh, stood for Containment Area for Relocated Yankees. Be that as it may, look no further for evidence of the region's popularity among the Creative Class. Cary has grown so fast that the federal government had to change the Metropolitan Statistical Area designation from Raleigh-Durham to Raleigh-Cary.

4. Population growth, fueled by in-migration of the Creative Class to these university-based regions, is changing the demographics of entire states like North Carolina, including how people vote.

5. The Creative Class participates in elections. Obama wins the majority of Creative Class votes.

6. Obama wins North Carolina.

I looked at returns from the North Carolina State Board of Elections and labor market data from the Employment Security Commission to see if I could find any evidence backing what the pundits have been saying. Here's what I came up with:

• Obama received more votes than McCain in 33 of North Carolina's 100 counties. As in other states, the largest margins of victory for Obama were in urban areas, such as Mecklenburg (Charlotte), Durham, and Wake (Raleigh).

• Perhaps the economy had something to do with the outcome, as the pundits suggest, but I couldn't find much evidence of that in North Carolina. The average unemployment rate as of September was higher in counties where Obama received more votes than McCain (7.2% vs. 6.8%), but the difference was not statistically significant.

• Similarly, looking at one-year changes from September 2007 to September 2008, the unemployment rate increased by an average of 2.2 percentage points in counties that Obama won, compared to 2.3 points in counties won by McCain.

• Recent employment figures based on place of work are not available yet at the county level. But metropolitan level data show that North Carolina regions voting for Obama added an estimated 31,400 jobs between September 2007 and September 2008 (1.3% growth rate), compared to 7,400 jobs (1.1%) in regions voting for McCain.

Of course, all of this says nothing about how voters perceived the economy and how that may have affected their choices. But I can't find any data pointing to actual differences in recent economic performance, at least as of September.

Finally, here's a chart showing the relationship between Obama's share of the total two-party vote and the Creative Class share of total employment (i.e. number of jobs in occupations classified by Richard Florida as Creative Class divided by total employment in all occupations) in each of the 14 federally-designated metro areas in North Carolina. Click on the chart to see a larger version.

Thoughts?

Thanks to Kim Didier at the Newton Development Corporation, Newton mayor Chaz Allen, and the 125 or so other stakeholders who helped create the RIG implementation plan, for showing us what effective regional collaboration can accomplish. I imagine you've been getting a few well-deserved phone calls today.

Marc is the Director of Applied Research in the Labor Market and Career Information Department of the Texas Workforce Commission, and he's recently published a discussion piece called Green Collar Workers and Other Mythical Creatures. The title speaks for itself, so I don't need to go into much detail here. However, I do want to point out a few choice quotes:

"Enthusiasm plus ambiguity may suffice to create the political will to promote green collar jobs but sound policy and effective strategies require clarity and prudence."

"Conferring the green title on the construction industry as a whole or on a specific firm says nothing about employment demand therein. It would be all too easy to let excessive exuberance for the greening of the industry color our judgment and misguide strategic planning for its workforce preparation."

Also make sure to check out the Green Collar Jobs 101 Pop Quiz on p. ii. If you don't have time to read the entire paper, then go straight to p. 20 for a succinct discussion of the major difficulties in measuring and responding to the "green" revolution, at least in terms of workforce development.

One of the attendees came up to me after the presentation and asked exactly the sort of question that speakers hope for: If we are going to focus on workforce training to increase wages for residents, which types of jobs should we be looking at?     

I didn't have any answers for her at the time, but I came across a short article by Ben Cover at the Bureau of Labor Statistics called Beyond averages: Other ways to look at occupational wages that may help. In the article, Cover shows how analysts can use wage ranges to identify specific occupations as candidates for training programs, based on a worker's chances of advancing within the profession and earning higher wages. In Austin, for example, entry-level shampooers last year made $5.41 per hour on average. Experienced shampooers, by comparison, made only $7.33 per hour--not even close to a living wage in Austin, even at the top end of that occupation. Compare that to sales engineers, where the difference between entry-level ($17.97) and experienced ($63.29) is about $45 per hour.

Taking an inventory of occupations held by East Austin residents and assessing whether or not there's potential for increasing wages through training programs could be the first step in a workforce-driven strategy for that community. For people in jobs with little chance of upward mobility, perhaps their knowledge, skills, and abilities could be transferred into another occupation, where the likelihood of earning a living wage is greater. Looking at the distribution of wages at various levels of experience gives you more information to work with compared to only average or median wages, which is the traditional way of identifying target occupations for workforce development efforts.

You can download the wage data for occupations in your region on the Occupational Employment Statistics section of the Bureau of Labor Statistics website.

Millions of dollars are spent every year on cluster studies, so I'm glad to see more how-to manuals in the public domain. If you are new to economic development, I'd also encourage you to read about sector strategies, as you are deciding on your approach to regionalism. Differences between cluster strategies and sector strategies are worth noting.

So here's my question: are cluster strategies producing results? Practitioners for years have been using research by Michael Porter and others as the basis for creating regional strategies around targeted clusters. However, I'm wondering if somewhere along the way the practice of cluster-based economic development veered off course. Do a Google search for "life sciences" and "economic development" and you'll see what I mean. Is it possible that 100 or more regions across the U.S. could truly have a competitive advantage in life sciences?

Cluster and sector strategies provide much needed structure to economic development efforts, especially at the regional level. Just make sure that competitive advantage drives your strategy, as opposed to the other way around.

Of course, it's not really that simple. As long as economic developers are judged by how many jobs they "create" in their communities, incentives such as property tax abatement and sales tax rebates are here to stay. The bias toward short-term results trumps any concern about long-term implications of incentive deals in communities focused on corporate recruitment. It's far worse to be the politician or economic developer who lost the project to another state than to be the person responsible for giving away the farm. And calling a site selector's bluff when tax incentives are on the table is not a popular move so that's usually a moot point anyway. That said, read about the economic gardening program in Littleton, CO, and make up your own mind about what economic development means in an incentive-free world. 

Debating the merits of incentives should be encouraged. But asking whether you are "for" or "against" incentives is not the right question. Instead, we should be promoting rigorous evaluation of incentive proposals, proper oversight, and enforceable claw backs when commitments are broken. There are plenty of budget-friendly tools available to help, such as WebLOCI developed by Georgia Tech and Fiscal Impact Tool from the Federal Reserve Board. Many economic developers have created their own data-driven evaluation tools and we should share best practices whenever possible.

Play around for a few minutes (mapping where your neighbors work is a wonderfully nosy way to start) and you'll quickly appreciate its value for economic and workforce development. Here are just a few of the things I've used it for:

• Defining regions by showing how central cities are dependent on surrounding areas for workers. Here's an example showing the labor shed for the city of Denver, where I'll be teaching a seminar with Sam Leiken from the Council on Competitiveness this week at the EDA Denver and Seattle Regional Conference.

• Showing how commuters will be impacted by highway projects. Highway 290 East from Austin to Manor will soon be getting a makeover. Here's a map showing where Manor and Elgin residents work in Austin and a report describing how many commuters from those areas are likely to be affected by the construction.

• Documenting workforce availability. In July, Volkswagen announced that it will build a new assembly plant in Chattanooga. The facility, located at Enterprise South Industrial Park, is expected to need approximately 2,000 workers. Here's a map showing the proposed VW plant location in Chattanooga and where production workers live in a 15-mile area. The analysis reveals approximately 16,000 workers with production experience living in the 15-mile area, including 63% between the ages of 31 and 54 and 19% age 30 or younger.

The chair of the Emerging Technology Fund Advisory Committee, Bill Morrow, said something in his presentation that caught my attention. He mentioned that identifying investment opportunities outside of traditional markets in Austin, Dallas, Houston, and San Antonio will be a top priority for the ETF group in the upcoming year. Top research universities are a huge advantage for regions interested in pursuing an innovation-based economic development strategy. But I don't agree with people who suggest that they are a prerequisite. And I certainly don't agree with people who exclude rural areas from this conversation. See, for example, this map of U.S. patents in 2007. And here's a close-up of patents in Texas. It's no surprise that the vast majority of patent activity is concentrated in the major metro areas. However, it's a mistake to overlook what's going on in other areas. Opportunities for leveraging innovation assets can be found in large cities, rural communities, and virtually everywhere in-between.

Bill and the rest of the ETF folks will have their work cut out for them because the environment for turning an idea into a commercialized product or service is so much stronger in urban areas where resources are concentrated and support networks are in place. Yet, given this state's unique blend of agriculture, energy, and a strong tradition of rural entrepreneurship, this strategy is worth pursuing in all corners of Texas.

Kudos to Bill and the ETF team for making it a priority.

Here are a few rankings (of course) to provide answers. Jim asked specifically about Indiana, Iowa, Michigan, Ohio, and Vermont. So I'll include the top ten states under each category I looked at, as well as those states. All data reflects changes between 2000 and 2007 (latest available). I'm not really sure how we got so obsessed with rankings in this field, but I blame Forbes. And Richard Florida.

Which states are experiencing the largest nominal gains in population (average annual)?

1. Texas  (381,573)
   
2. California  (335,195)
   
3. Florida  (283,552)
   
4. Georgia  (169,742)
   
5. Arizona  (151,018)
   
6. North Carolina  (126,818)
   
7. Virginia  (79,133)
   
8. Washington  (71,786)
   
9. Nevada  (70,891)
   
10. Colorado  (69,937)
    

Which states are experiencing the fastest population growth rates (total 2000-07)?

1. Nevada  (27%)
2. Arizona (23%)
3. Utah  (18%)
4. Georgia  (16%)
5. Idaho  (15%)
6. Texas  (14%)
7. Florida  (14%)
8. Colorado  (12%)
9. North Carolina  (12%)
10. Delaware  (10%)

1. New York  (-181,146)
2. California  (-152,999)
3. Illinois  (-68,914)
4. New Jersey  (-47,145)
5. Michigan  (-44,970)
6. Louisiana  (-41,902)
7. Massachusetts  (-38,211)
8. Ohio  (-37,731)
9. Connecticut  (-9,758)
10. Kansas  (-8,414)

     20. Indiana  (-2,054)
     23. Vermont  (-47)

Finally, where are people going when they leave Ohio (number of people in 2006-07, per capita income)?

1. Florida  (21,079, $35,376)
2. Kentucky  (12,138, $22,497)
3. Indiana  (10,260, $23,449)
4. Texas  (10,190, $27,558)
5. North Carolina  (9,525, $27,192)
6. California  (9,355, $35,376)
7. Michigan  (8,457, $27,793)
8. Pennsylvania  (8,415, $25,657)
9. Georgia  (7,605, $23,543)
10. Illinois  (7,078, $35,023)

So, this is the first of likely a couple posts on what we can learn about population and migration trends in Ohio using data from the IRS and other federal sources. If there's interest, we can expand this analysis to include other regions since the IRS makes this data available for all counties in the U.S. and it's fairly easy to work with. We'll start here with an overview of migration in Ohio and later draw connections to economic development, regional planning, and perhaps other topics.

• Ohio has been losing an estimated 36,500 residents on average each year to other states since 2004. People leaving Ohio during 2004-07 took $14.7 billion in adjusted gross income with them. Factoring in people moving to Ohio from other states, the net impact of outmigration was a $4.4 billion decrease for the state.

• Between April 2006 and April 2007 (most recent available) the five counties in Ohio losing the most residents to other states included Franklin (-23,505), Cuyahoga (-18.637), Hamilton (-16,092), Montgomery (-10,009), and Lucas (-8,386). But, factoring in both inmigrants and outmigrants, the counties with the greatest net losses to other states were in this order: Cuyahoga (-5,326), Hamilton (-3,738), Franklin (-3,394), Summit (-2,918), and Lucas (-2,796). On the other end of the spectrum, six counties had net gains from out-of-state in 2006-07: Warren, Delaware, Lawrence, Knox, Monroe, and Belmont.

• Twenty-eight out of 88 counties in Ohio experienced a net gain in residents resulting from total migration in 2006-07 (in-state and out-of-state), with Delaware, Warren, and Butler leading the way with gains of at least 1,000 people each. Cuyahoga, Hamilton, Franklin, Montgomery, Lucas, Summit, Mahoning, and Trumbull experienced the greatest net losses. Cuyahoga had a total net loss of 12,910 residents, including a net loss of 5,326 residents to other states.

• To get at Jim's points about potential differences in incomes, per capita income for people moving to Ohio from other states in 2006-07 was $25,553, compared to $28,502 for people leaving Ohio. Using observations from all 88 counties, the difference in income was statistically significant at the .05 level. I could not find a statistically significant difference in incomes when including both in-state and out-of-state movers. This doesn't nearly address Jim's points fully, but it's a start.