MICHIGAN’S INDUSTRIAL STRUCTURE

AND COMPETITIVE ADVANTAGE:

HOW DID WE GET INTO THIS PICKLE

AND WHERE DO WE GO FROM HERE?

Prepared by George A. Fulton Donald R. Grimes

Institute of Labor and Industrial Relations Research Seminar in Quantitative Economics

University of Michigan

Prepared for “Where Do We Go From Here?”

An Agenda-Setting Conference for the Economic Issues Facing Michigan

March 14, 2006

Table of Contents

Introduction......................................................................................................................................1

The Cyclical Behavior of the Michigan Economy, 1956–2005 ......................................................3

How Did We Get into This Pickle? .................................................................................................5

Michigan’s Dependence on the Auto Industry............................................................................6 The Price-Cost Squeeze ..............................................................................................................9

Where Do We Go from Here? .......................................................................................................14

The Framework .........................................................................................................................14 Industry Prospects Based on the Framework ............................................................................16 Industry Detail: Knowledge-Based Industries .........................................................................21 Industry Detail: High-Tech Industries .....................................................................................24 Industry Detail: Tourist-Oriented Industries............................................................................27 Michigan’s Assets .....................................................................................................................28

Higher-education system......................................................................................................30 Natural environment.............................................................................................................30 Financial capital ...................................................................................................................33 Linkage between assets and industries.................................................................................35

Conclusion .....................................................................................................................................39

References......................................................................................................................................41

Michigan’s Industrial Structure and Competitive Advantage: How Did We Get into This Pickle and Where Do We Go From Here?1

By GEORGE A. FULTON, research professor, Institute of Labor and Industrial Relations and Research Seminar in Quantitative Economics; and DONALD R. GRIMES, senior research specialist, Institute of Labor and Industrial Relations; University of Michigan

Introduction

During the festivities of Super Bowl week in Detroit last month, a hall-of-fame football

player was asked in a radio interview whether he was happy to be there. “Not really,” he replied.

“It’s too cold and there are no good beaches or other stuff I like to do.” He was then asked about

his impressions of Detroit and Michigan. “You’ve got to show a lot of respect there; every car in

the United States is built here, and they’ve got good workers. Besides, you have to give Mr. Ford

lots of credit for bringing the game here and building such a magnificent stadium.” We mention

this conversation here only because these casual observations from an outsider do touch on

issues that are key to the Michigan economy.

First, and there’s no debate about this, we are in a pickle. As we will confirm in this

paper, the state of Michigan is in the midst of serious structural economic trouble, probably its

worst crisis in our lifetime. Since 2001, the state has lost one-quarter of its automotive work

force and is in its sixth consecutive year of job loss, a period of decline unequaled in the fifty

years for which we have data. Our football player was a little off the mark when he observed

that every car in the country is made here—it’s actually more like 25 percent—but his

1 Many people kindly offered their time and expertise to us in putting this study together, either by gathering and compiling data or by discussing their ideas with us. We are very grateful to (in alphabetical order): Paul Courant, Joan Crary, Abel Feinstein, Louis Glazer, Saul Hymans, Sean McAlinden, David Macpherson, Neviana Petkova, Lawrence Root, and Steven Szakaly. We would like to single out Jacqueline Murray for her usual superb job in editing the text and providing graphics. The authors are solely responsible, though, for the interpretations and any errors of omission or commission in this study.

2

impression is valid in that Detroit, Michigan, is a metaphor for the auto industry. Michigan is

much more than just where they make cars, but there’s clearly a great deal about the state’s

society and economy that derives from the pervasive importance of the motor vehicle industry in

Michigan.

That dominance is highly concentrated in the Big Three domestic automakers and their

suppliers—many of whom are currently dealing with such severe problems that there is serious

concern about their longer-term viability. The structural problems of the domestic auto industry

have rippled through the state’s economy. We surely do have other economic problems in the

state, but they are dwarfed by the structural problems in the domestic auto industry (defined

throughout this paper to be the Big Three automakers and their suppliers).

Second, the logical follow-up to the question of how we got into this predicament is: how

do we get out of it, or to rephrase with the theme of this conference, where do we go from here?

In this paper, we offer a framework for thinking about this question based on the state’s

industrial structure and competitive advantage.2 This approach is in response to the charge that

we were given for this conference: We were asked to study Michigan’s industrial structure with

a view to identifying sectors that will promote economic growth in the future. We assess some

of the possibilities suggested by the framework that we have created.

Our visiting football celebrity intuitively identified some of the assets that lay the

groundwork for economic success. The quality of the labor force, the natural environment and

area amenities, entrepreneurship and the climate for investment, are all fundamental elements

that underlie why things happen in some communities and not in others. Promoting certain

2 Economists usually refer to an area’s comparative advantage when identifying which products an area should trade. We are intentionally using a different phrase, “competitive advantage,” which we define as referring to an activity in which the state could develop a sizable concentration and which has value to economies outside of Michigan, either nationally or internationally.

3

sectors of the economy as engines that can propel the Michigan economy forward is an exercise

that only makes sense in the context of the basic resources that the state has or can more fully

develop. (If you go prospecting in Alaska, you might strike gold. That won’t happen in

Michigan.)

Our football player also reminds us that judgments can be based on both perception and

reality, and that at times perception can shape reality. In this paper we attempt to make an

objective assessment of Michigan’s strengths, and from there, suggest where the economy could

profitably be pointed.

In the next section, we establish that our current economic problems are indeed structural

and not cyclical. The following section of the paper elaborates on how we got into this dire

situation, focusing on our auto dependency and evaluating the prospects for that sector as a

future economic engine. We then provide a framework for assessing alternate economic engines.

Subsequently, we identify sectors that pass through our filter, and take a closer look at those

sectors and economic units that hold the most promise for enhancing Michigan’s future

economy. We evaluate Michigan’s assets, which we view as fundamental to the state’s future

opportunities, and relate these to the sectors that show promise as economic engines. We close

with a brief concluding section on our findings.

The Cyclical Behavior of the Michigan Economy, 1956–2005

In the introductory literature for this conference, it was suggested that Michigan’s

economic troubles were perhaps the worst since the Great Depression, and that they were

structural in nature. Before the conference membership searches diligently for structural

remedies to address Michigan’s problems, it would be informative initially to assess how severe

4

Michigan’s current problems are compared with history, and to confirm that they are indeed

structural in nature.

To do this, we address the question of how the current experience, including our

Michigan forecast generated quarterly through 2008 [2], compares with previous recessions and

recoveries in Michigan, both in terms of job loss and duration of job recovery. The answers are

shown in table 1. We have data on payroll employment for Michigan back to 1956.3 We

identified six periods of peak employment followed by downturns since the mid-1950s,

including the current episode. As can be seen in the second column, which identifies the number

of quarters from peak employment needed to achieve full recovery of jobs, the current period

would rank as the longest duration to full job recovery from a recession in the past fifty years.

By the end of 2005, 22 quarters had passed since our peak employment levels in mid-2000.

Table 1

Comparison of Recessions and Recoveries in Michigan

Quarter of Peak Jobs

before

Number of

Quarters from Peak

Jobs Lost from Peak to Trough

Recession to Regain Jobs Thousands % 1960.2 9 174.1 7.3 1969.4 12 230.7 7.4 1973.4 12 216.6 6.5 1979.2 30 533.7 14.6 1990.3 11 109.4 2.7 2000.2 >34* 339.9** 7.3**

*Forecast: Current data at 22 quarters. **Forecast: Trough quarter is 2006.4. Source: Research Seminar in Quantitative Economics, University of Michigan, March 2006.

3 Although the early data are not strictly comparable with more recent estimates, we judge the series to be sufficiently compatible to make the summary comparisons documented in the table.

5

Within the horizon of our current forecast, we will reach 34 quarters by the end of 2008,

exceeding the 30-quarter duration of the 1979-82 recession, the longest on record to date.

But the news gets worse. If we assume that the economy grows at the same pace in the

five years following 2008 as it did during the 1996–2000 period, the economy would not achieve

full recovery of jobs until the first quarter of 2013, 51 quarters or almost 13 years after the

previous peak. And this is based on an optimistic assumption.

Obviously, this cannot be viewed as a cyclical downturn. Looking from here to as far

back as the data will take us, the current situation appears to be the most severe structural

problem we have yet encountered.

Actually, based on magnitude of job loss, the current period is not the most severe

downturn we have suffered through. That honor goes to the 1979–82 recession, when Michigan

lost 14.6 percent of its work force before the economy started turning around, compared with our

forecast of 7.3 percent in the current episode. Indeed, the current situation is not remarkably

different in this regard from most of the other recent recessions, excluding the severe one of

1979–82 and the mild one of the early 1990s. What is so unusual about the labor market in

Michigan recently is not the severity of the job losses, but the lack of a rebound. It’s not that our

current winter has been colder than normal; it’s just that it never ends.

How Did We Get into This Pickle?

Our evidence to this point is that we are indeed in a serious economic pickle in Michigan,

and that the problem is structural. A frequent claim is that this reflects the severe structural

difficulties faced by the automotive industry these days, and more to the point, by the Big Three

automakers. Although this may seem self-evident, verifying the claim and understanding the

underlying problems is key to pointing the state in the right direction. So we focus first on our

6

pickle, interpreted here as a structural problem in the auto industry that permeates the Michigan

economy, before we consider how to get out of it.

Michigan’s Dependence on the Auto Industry

The travails of the industry would not matter as much to Michigan if the state were not so

dominated by its activities. The magnitude of the industry’s dominance in the state can be

established by a single statistical measure, the location quotient, as shown in table 2. A location

quotient is the ratio of Michigan’s employment share to the nation’s employment share for an

industry. Stated in another way, the location quotient is a measure of the concentration of an

industry category in Michigan compared with its concentration in the United States. A location

quotient of more than one means that the industry claims a greater percentage share of

employment locally than nationally. A location quotient of less than one signifies a lesser

concentration locally; a location quotient of one indicates that the industry shares are equivalent.

Thus, the 7.88 location quotient for automobile, light truck, and parts manufacturing shown in

the table indicates that Michigan’s employment share in the industry was 7.88 times the nation in

2004—an astounding concentration. The concentration in the rest of manufacturing, in

comparison, was only 2 percent higher in Michigan than it was in the United States.

Table 2

Employment Location Quotients by Industry Michigan, 2004

Industry Location Quotient

Automobile, light truck, & parts manufacturing 7.88 Manufacturing except autos & parts 1.02 Natural resources, mining, construction 0.77 Service-providing sector 0.96

Source: U.S. Bureau of Labor Statistics; calculations by the authors, March 2006.

7

Does this ultra-concentration in autos, particularly Big Three autos, have a significant

effect on the economic performance and health of the overall Michigan economy? The

information in figure 1 says it does. Total payroll employment in Michigan is shown from 1979

through 2005 by the solid line, and the sales of vehicles produced in North America by the Big

Three are represented by the dotted line. (Why not just show vehicles produced in Michigan?

Because many Michigan firms supply Big Three facilities elsewhere, and support and

headquarters facilities are located here.) Total vehicle sales are included as reference in the

background bars.

2,500

3,000

3,500

4,000

4,500

5,000

’79 ’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03 ’05’80 ’82 ’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’02 ’04

MichiganEmployment

TotalVehicle Sales

Big ThreeSales

Figure 1

Michigan Employment, Big Three Sales, and Total Vehicle Sales1979–2005

0

5

10

15

20

Source: Research Seminar in Quantitative Economics, Department of Economics, University of Michigan,March 2006.

Thousands of jobs Millions of units

2,500

3,000

3,500

4,000

4,500

5,000

’79 ’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03 ’05’80 ’82 ’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’02 ’04

MichiganEmployment

TotalVehicle Sales

Big ThreeSales

Figure 1

Michigan Employment, Big Three Sales, and Total Vehicle Sales1979–2005

0

5

10

15

20

2,500

3,000

3,500

4,000

4,500

5,000

2,500

3,000

3,500

4,000

4,500

5,000

’79 ’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03 ’05’79 ’81 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’01 ’03 ’05’80 ’82 ’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’02 ’04’80 ’82 ’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’02 ’04

MichiganEmployment

MichiganEmployment

TotalVehicle Sales

TotalVehicle Sales

Big ThreeSales

Big ThreeSales

Figure 1

Michigan Employment, Big Three Sales, and Total Vehicle Sales1979–2005

0

5

10

15

20

0

5

10

15

20

Source: Research Seminar in Quantitative Economics, Department of Economics, University of Michigan,March 2006.

Thousands of jobs Millions of units

8

It is apparent that, although not perfectly correlated, the two lines do track fairly closely.4

This would be less remarkable if the employment line represented motor vehicle employment, or

even manufacturing. What is so telling is that the employment line represents total jobs in the

state. Focusing on the years after 1990 as being the most relevant, we highlight three periods.

The first is the early 1990s, when sales recovered rapidly following the 1990–91 recession and

Michigan employment picked up as well. The second period is from 1994 to 1998, when Big

Three sales held fairly steady while employment grew by a healthy 2¼ percent yearly.

Apparently, holding our own in Big Three sales is sufficient for positive employment growth in

the state overall, or at least it was during this episode.

After employment continued to grow in 1999 and 2000, tracking an upswing in Big

Three sales, we come to the third period, 2001 to 2005, when the state’s economy unraveled.

Big Three sales tumbled through 2003 and so did Michigan employment. The losses moderated

in 2004 and 2005, but a downward drift persisted in both Big Three sales and Michigan

employment. And according to our forecast, Big Three sales will continue to slide at least

through 2008 [2]. While total vehicle sales are expected to move up gradually over the next

three years, the Big Three market share is projected to shrink. And our view of the short-term

prospects for the industry seems to line up with others whose job it is to think about these

matters. A number of independent auto industry analysts predict that total light vehicle sales will

grow only 0.5 percent to one percent per year through 2010. We have been stuck on a sales

plateau for the past several years, with about 97.5 percent of purchases made for vehicle

replacement. These forecasts for total vehicle sales also come with a consensus opinion that Big

Three market share will continue to fall over the next few years. Indeed, GM and Ford are in the

process of reducing capacity. In sum, it appears very unlikely that Big Three sales can revive 4 The Pearson correlation coefficient is 0.50, significant at better than the one percent significance level.

9

sufficiently, at least in the next several years, to stimulate sustained and significant job growth in

Michigan.

The Price-Cost Squeeze

The cost side of the Big Three business model is even more troublesome. Total costs are

the sum of fixed costs and variable costs. In the jargon of the economist, General Motors and

Ford are currently pricing their vehicles between average per-vehicle variable cost and average

per-vehicle total cost, the latter including fixed costs (cost and revenue subcomponents are listed

in the footnote below).5 The following revenue and cost estimates for GM vehicle production in

2005 [4] illustrate the point, which is also repeated in figure 2:6

(1) Revenue per vehicle: $18,861

(2) Variable cost per vehicle $11,394

(3) Difference: (1) – (2) $7,467

(4) Fixed cost per vehicle $8,551

(5) Pre-tax profit per vehicle: (3) – (4) –$1,084

Economic theory suggests that as long as a firm can cover its variable costs, it will

continue to produce. The margins made in excess of covering variable costs can be applied to

cover part of the fixed-cost obligations, but in the long run revenue needs to cover fixed costs

and provide a reasonable profit. If a firm cannot make its interest and debt payments, then it is

bankrupt and subject to reorganization. The fear of this outcome for GM and Ford is growing.

Figure 2 suggests two strategies to cover costs, at least conceptually. The first is to raise

price, say from price 1 to price 2 in the figure. This doesn’t work in the new world of fierce

global competition, where pricing power is much more limited. This is apparent in figure 3, 5 Variable costs are those costs incurred in producing the product, and can be avoided by not producing; materials (parts and components) that go into the vehicle are the major item. Fixed costs are those costs that the company has to incur regardless of volume These include health care costs for active workers, pension and other costs for retirees, advertising, research and development costs, and capital costs. For this industry, it also includes labor costs (to be explained below). Price, or revenue per vehicle, is net of incentives and dealers’ margins. 6 Deutsche Bank estimates for calendar year 2005, based on data for the first nine months of 2005.

10

Price(Revenue/vehicle)

price 2(>$19,945)

price 1($18,861)

Total cost per vehicle ($19,945)

Fixed cost per vehicle ($8,551)

Variable cost per vehicle ($11,394)

Figure 2

Illustration of the Price-Cost Squeeze at General Motors, 2005

Source: Deutsche Bank Securities Inc. [4]; calculations by the authors, March 2006.

Price(Revenue/vehicle)

price 2(>$19,945)

price 1($18,861)

Total cost per vehicle ($19,945)

Fixed cost per vehicle ($8,551)

Variable cost per vehicle ($11,394)

Figure 2

Illustration of the Price-Cost Squeeze at General Motors, 2005

Source: Deutsche Bank Securities Inc. [4]; calculations by the authors, March 2006.

PCE deflator

40

60

80

100

120

Figure 3

Prices of New Motor Vehiclesvs. Overall Consumer Expenditures

1979–2005Index

(2000 = 100)

’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’03’01 ’05’81’79’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’04’02’82’80

PCE deflator new MV

Source: U.S. Bureau of Economic Analysis, National and Income and Product Accounts, February 2006.

PCE deflator

40

60

80

100

120

40

60

80

100

120

Figure 3

Prices of New Motor Vehiclesvs. Overall Consumer Expenditures

1979–2005Index

(2000 = 100)

’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’03’01 ’05’81’79 ’83 ’85 ’87 ’89 ’91 ’93 ’95 ’97 ’99 ’03’01 ’05’81’79’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’04’02’82’80 ’84 ’86 ’88 ’90 ’92 ’94 ’96 ’98 ’00 ’04’02’82’80

PCE deflator new MV

Source: U.S. Bureau of Economic Analysis, National and Income and Product Accounts, February 2006.

11

which shows the path of prices for new motor vehicles from 1979 to 2005 compared with the

path of prices for all consumer expenditures.7 A dramatic change in vehicle pricing behavior has

occurred since the mid-1990s. Historically, when vehicle sales rose, prices would also rise.

There has been a departure from this pattern, however, since the mid-1990s. Although vehicle

sales grew from 1996 to 2000, there was no corresponding increase in vehicle prices. When

sales flattened out after 2000, prices for new vehicles drifted down while overall consumer prices

kept trending up.

There are other ways to raise average price, such as changing the mix of vehicles toward

higher revenue vehicles; or reducing the share of fleet and employee vehicles, which are priced

well below normal sales to consumers; but they don’t involve regaining pricing power.8 Pricing

strategies seem to have little potential to turn around the price-cost squeeze.

As is apparent in figure 2, the other conceptual strategy is to lower average total cost

below price. The options are to reduce materials costs or some category of fixed costs. The

largest fixed cost items are labor, pension and other benefits, and capital costs. Labor, the largest

single item, is regarded in these statistics as a fixed cost because of the Jobs Bank program.

Under this program, negotiated in the 1980s between the United Auto Workers union and the Big

Three automakers, laid-off workers are entitled to receive full-time pay, excluding overtime and

shift premiums, even though they are not currently involved in the production process.9

7 Both price concepts are based on the personal consumption expenditures deflator from the National Income and Product Accounts. 8 If fewer vehicles are sold, there could be more flexibility in raising prices for those remaining consumers with high brand loyalty, who would have been willing to pay more previously but were given a discounted price along with others who were only willing to purchase at the lower price (what economists refer to as capturing consumer surplus). 9 For the first 48 weeks of layoff, workers are eligible for supplemental unemployment benefits (SUB) as well as unemployment insurance when applicable. This amounts to about 70 percent of their take-home pay. After 48 weeks, they are eligible for the Jobs Bank program, at full straight-time pay.

12

The price-cost squeeze is hitting the Michigan-based auto industry more severely than the

industry in the rest of the country. Since 2001, Michigan has suffered approximately 60 percent

of all job losses nationally in motor vehicle and parts manufacturing, despite accounting for only

one-quarter of total jobs in the industry.

Michigan’s wage premium in the motor vehicle and parts industry is dramatic, as can be

seen in table 3. (Fringe benefit costs are not included; if they were, the cost disadvantages for

Michigan would be even greater.) Across every major category of the industry, Michigan’s

wage premium is in double-digit percentages, ranging from 11.7 percent higher in automobile

and light truck manufacturing to 46.6 percent higher in brake systems. Some of this differential

arises from a much higher concentration of skilled-trade workers in Michigan, who are more

highly compensated. The chief difference, though, is the higher wages that have been negotiated

by unions in the state.

Table 3

Auto Industry Employment and Wages

Annual Averages, 2004

Change in Michigan Wages

Employment Wages to Match Balance Balance Balance of U.S. Michigan of U.S. Michigan of U.S. $ % Autos & light trucks (33611) 70,234 151,273 $81,474 $71,971 –9,503 –11.7 Motor vehicle parts (3363) 168,955 521,766 65,599 46,793 –18,806 –28.7 Gas engines & parts (33631) 18,072 62,111 76,081 50,347 –25,734 –33.8 Electric equipment (33632) 11,073 88,459 59,159 46,762 –12,397 –21.0 Steering & suspension (33633) 10,199 32,553 78,910 52,383 –26,527 –33.6 Brake system (33634) 11,266 33,222 75,140 40,157 –34,983 –46.6 Power train (33635) 22,714 61,936 85,458 60,817 –24,641 –28.8 Seating & interior trim (33636) 22,760 43,771 56,461 37,270 –19,191 –34.0 Metal stampings (33637) 41,121 59,367 57,609 49,796 –7,813 –13.6 Other MV parts (33639) 31,750 140,347 56,907 41,026 –15,881 –27.9

Source: U.S. Bureau of Labor Statistics; computations by the authors, March 2006.

13

Clearly, the companies will be seeking some significant concessions in the scheduled

2007 contract negotiations with the union to ease their price-cost squeeze, and the outcomes of

these talks will determine the future prospects for the Big Three.

The situation for the Chrysler Group has not been as dire as for General Motors and Ford,

in part because much of their restructuring has already taken place. Also, their smaller size

allows them to be more nimble, and they have been more successful at fixing product problems

quickly. It is hard to come up with a scenario, though, where the Big Three collectively do not

become smaller. In fact, the process is already under way. GM and Ford have announced a total

of 50,000 U.S. hourly job cuts and 7,000 salaried worker reductions through 2010; there could be

more. The market is too competitive now to have companies with 25 percent market shares.

Even if downsizing and restructuring turn these companies into profitable enterprises again, the

analysis in this section does suggest that Michigan should no longer rely on domestic automotive

production to propel economic growth. This is not to say that automotive production will not

continue to be a major factor in the Michigan economic picture; all we are saying is that it cannot

be relied upon to provide new job growth in the state. For that, we have to look elsewhere.

Elsewhere could include what many view as a component of the auto industry: white-

collar workers in pre-production, including research, development, design, and other engineering

functions. In our data from the federal government, these workers are counted in another

category. In fact, they are included in our knowledge-based service industry designation

discussed in the next section. In that discussion, we observe that economic prospects for that

category are much different from the prospects for manufacturing production.

In the next section, we suggest a framework for guiding our search for prospective

economic engines, and we subsequently propose some activities that make sense in the context

of our framework and Michigan’s existing assets.

14

Where Do We Go from Here?

The Framework

In deciding where we go from here, we need a framework to identify those activities with

economic promise, why we should go in certain directions and not in others. To formulate a

measure, we have posited some characteristics of activities that contribute to a region’s economic

development and future prosperity. Those characteristics are:

• long-term growth potential

• a substantial export component

• above-average wages and salaries

• regional advantage in providing products or services

That the best regional economic engines are the ones with favorable prospects for growth

is self-evident. In practice, of course, growth potential cannot be anticipated with perfect

foresight. We do have our tools, though, both formal and informal, to bring some insight into the

process. We will take advantage of these tools in the next section of the paper when we are

evaluating specific industry groups.

Perhaps the least apparent of the industry characteristics listed is the one referring to the

export base. We distinguish here between two types of industries: those that sell a significant

share of their products or services to businesses and consumers outside the local geographic area

(“export-based industries”), and those that mainly serve local residents and businesses (“local-

based industries”). Export-based industries are crucial to the local economy because they bring

money in from the outside, while local industries tend to recirculate money among local

businesses. Autos are an obvious example of an export-based industry, while laundromats are

the classic example of a local-based industry. Some industries do not fall quite as neatly into

these categories, but again, we do have numbers to bring to the issue when we get there.

15

Conceptually, it is important to recognize that when we use the term “export” in this paper in

reference to Michigan, we include not only international markets, but also domestic markets

outside of the state. We don’t distinguish between Toledo in Spain and Toledo in Ohio.

The third characteristic listed refers to the level of pay. Obviously, higher-paid activities

have greater leverage in raising the overall economic welfare and prosperity of a region than do

lower-paying activities. We do not view this as an essential requirement to become an economic

engine in Michigan, but lower-paying activities will not have the same impact.

The final characteristic listed is regional competitive advantage in providing products or

services. We define competitive advantage more loosely than the phrase “comparative

advantage” used in the trade theory literature. We are simply referring to an economic activity

where Michigan has the potential to develop a sizable job base, and whose output is not

produced solely for local consumption. This does not mean that Michigan needs to have an

existing concentration in an activity. If the state has the right assets to attract the activity, the

potential is there to develop it. For example, Michigan is at present in the process of growing its

intellectual assets into a viable biotech industry.

If our concentration in an activity is too low, perhaps we are not pushing our advantages

sufficiently. Alternatively, it could mean that we shouldn’t go there because we have no

competitive advantage. And this highlights what does matter: identifying and targeting the

advantages in resources that Michigan does have over other locations, a reason why businesses

and people would come here rather than somewhere else.

16

Industry Prospects Based on the Framework

Before we elaborate further on Michigan’s individual assets, we first want to bring some

life to our framework by considering how particular industry sectors measure up as potential

economic engines for Michigan.

Long-term growth potential for industries is measured by the most recent U.S. Bureau of

Labor Statistics (BLS) forecast of employment for the nation, which runs from 2004 to 2014 [1].

We supplement this information with historical growth rates from the decade prior to the

forecast, 1994–2004. The export component for industries is represented empirically by a

measure showing the percentage of each industry’s production of goods and services that were

sold outside of Michigan in 2001.10 The average industry wage in Michigan in 2004 from BLS

is used as the metric for level of pay.

For the final characteristic, the location quotient (earlier defined as the relative

concentration of an industry in an area compared with the nation) is used as a measure of trade

flows. A location quotient greater than one indicates that a region is a net exporter of a given

product, and therefore that the region has a competitive advantage in producing that product.

In practice, a high location quotient for a given industry means that an area has—or used

to have—a strong competitive advantage in that industry. A low location quotient is more

ambiguous. It could represent an activity where some inherent advantage exists, but has not

been fully exploited. Alternatively, it could represent an activity where no advantage exists.

Critical to the question of advantage is the relative scarcity or abundance of assets necessary to

generate the good or service. Here assets include both natural endowments (e.g., the Great

10 Estimates are generated by the REMI model for the state of Michigan [9].

17

Lakes) and man-made assets (e.g., the higher-education system). Clearly, it is essential to have

some notion of the state’s assets when assessing regional advantage.11

It is widely accepted by economic development specialists that a high concentration of

activity in one industry will in itself attract additional activity to the region in that industry or in

support industries. Economists call this the clustering or “agglomeration” effect, the notion that

“like attracts like.” There are instances, though, where clustering becomes too much of a good

thing, creating costs rather than benefits [7].

The four attributes that represent our framework for evaluating a sector’s potential for

Michigan economic development are quantified for selected industries in table 4. We have

chosen the breakouts to cover the major export sectors in the state, and we have consolidated

certain industries into larger sectors.

Auto, light truck, and parts manufacturing ranks first in the table in three of our four

categories: 79 percent of its products are sold outside of Michigan; it pays well, with an average

wage in 2004 of $70,260 in Michigan, well above any other sector in the table, including the

knowledge-based sector; and as noted earlier, its location quotient is a stunning 7.88. According

to the BLS long-term forecast, it also has some growth prospects. We do take issue with this,

based on the auto industry problems identified earlier in the paper, and based also on industry

performance over the past ten years, when employment fell by 7.1 percent. Furthermore, to the

extent that this industry shows growth over the next decade, it likely will not be generated by the

Big Three but rather by foreign nameplate automakers, which are not expected to have a large

manufacturing presence in the state.

11 Another limitation of location quotients as a measure of competitive advantage is that their variation over time may simply reflect the performance of other industries in a region. The location quotient for industry A could rise simply because other industries are declining, thus raising industry A’s share of total activity (usually measured by employment). We see some of this in the data for Michigan over the past five years, as the sharp drop in motor vehicle manufacturing employment has caused the location quotient of other industries to increase.

18

Table 4

Potential Economic Engines for Michigan’s Economy Category

Employment

Share of revenue

Average wage

Location quotient

(Employment Michigan from outside U.S. employment growth Michigan Michigan excludes self-employed) 2004 Michigan 1994–2004 2004–2014 2004 2004 Auto, light truck, and parts manufacturing 239,189 79% –7.1% 5.1% $70,260 7.88

Manufacturing except autos and parts 456,340 61% –16.4% –6.2% $48,634 1.02

Natural resources and mining 30,844 71% –14.6% –6.3% $27,391 0.55

Air transportation, accommodations, arts and recreation

118,437 41% 18.3% 19.5% $27,580 0.78

Knowledge-based export industries 541,651 27% 22.2% 16.9% $62,747 0.92

All other industries 2,915,282 14% 20.9% 15.9% $33,128 0.96

U.S. household growth* High-income households aged 65 and older 125,836 Almost all NA 104.2%+ NA 0.90

*U.S. household growth; data for this category are available only for 2000–2030. Notes: High-income residents are those households with income of $60,000 or more in 2000.

Growth is Census projection of total population by age category, 2000 to 2030. Source: For exports, REMI model, 2001 [9]; for U.S. forecast employment growth, U.S. Bureau of Labor

Statistics [1]; for employment, average wage, and location quotients, U.S. Bureau of Labor Statistics and computations by the authors, March 2006.

Manufacturing outside of the auto industry is also predominantly an export industry in

Michigan: 61 percent of its products are sold outside of the state. As an aggregate industry

category, it is above average in pay ($48,634 versus $40,373 for all industries), and its

employment concentration is slightly higher in Michigan than in the United States. Again,

though, its longer-term growth prospects are not promising. The 6.2 percent decline in

19

employment forecast for the next ten years may even be optimistic, given the drop of 16.4

percent recorded over the past decade.

We did look at industry detail below this level of aggregation. Most of the individual

industries within this grouping are expected to see job losses over the next decade. There are

some industries, however, that show more growth potential, at least nationally, and that pay

reasonably well. These include chemicals, especially pharmaceuticals; some food

manufacturing; the manufacture of measuring and controlling instruments; and medical

equipment and supplies. A thorough examination of the potential role of these industries as

smaller engines for Michigan’s economy is beyond the scope of this study.

The third industry reported in the table is natural resources and mining. Included here is

forestry, fishing, agricultural workers on payrolls, and mining. The employment data do not

include self-employed workers, a category that covers about one-half of all farm workers. All of

the evidence indicates that employment is declining and that wages are relatively low except for

some parts of mining. Michigan may or may not have a competitive advantage in some narrow

segments of this industry group. Regardless, natural resources and mining is a relatively small

employer in Michigan and will not be a central focus of this analysis.

The next industry group in the table, air transportation, accommodations, arts, and

recreation, is our empirical proxy for the tourist-oriented industry. Some of this industry serves

the local community, of course. Overall, however, a solid 41 percent of the services provided by

this group are to out-of-state residents. Added to the money brought into the state by visitors is

income repatriated when local residents who had previously headed to out-of-state tourist sites

choose instead to vacation in-state. The repatriated income can be regarded as an export gain for

Michigan. The tourism industry group is projected to grow quite rapidly over the next ten years.

20

Wages in the industry are relatively low, however, and so is the location quotient. The low

location quotient may reflect a shortfall in the state’s exploitation of its natural advantages as a

tourist destination, including insufficient marketing.

The knowledge-based export industries are defined as information services, finance and

insurance, professional and technical services, and company management.12 This definition is

the one used in the study soon to be released by Michigan Future Inc. [8]. In Michigan, these

industries account for over twice as many jobs as do autos. Over one-quarter of the value of

their services is exported to residents and business establishments located in other states. These

industries have had some of the most rapid national employment growth in the past ten years,

and are forecast to continue to see above-average growth nationally through 2014. Furthermore,

these industries have some of the highest wages in the economy. The sector is currently less

concentrated in Michigan than in the nation, but it is not grossly under-represented (a location

quotient of 0.92), and it does have opportunities to expand. This industry grouping will be

examined in more detail below.

The all-other-industries category is included in the table for reference. These industries,

such as retail trade, restaurants, construction, and health care, export a relatively small proportion

of their goods and services outside of the state. Most of their output is destined to serve local

residents. Some of the industries in this category—for example, the University of Michigan

Health System—do export a relatively large share of their services to residents of other states

and countries, but that is the exception rather than the rule.

The last item shown in the table may seem unusual in this context, but we believe it to be

important. It represents high-income households headed by persons age 65 or older. We define

high-income households arbitrarily to be those with incomes of $60,000 or more in 2000, or, 12 These industries are defined by NAICS codes 51, 52, 54, and 55, respectively.

21

adjusting for inflation, roughly $65,000 in 2004. We focus on this group here for the same

reasons we suggest that some industry sectors show promise as economic engines. That is, this

household group is export-based and has high growth potential, as well as being highly paid.

The group has a high export content because the vast majority of post-retirement-age

income comes from sources outside of the local area, such as social security, pensions, or 401k

or 403b retirement savings. This income can be viewed as similar to income received from

selling a good or service to an out-of-state resident or business, as it brings money into the local

community. The U.S. Census Bureau is forecasting that the population age 65 and older will

more than double between 2000 and 2030. The number of households will increase even more,

if average household size continues to decline. Consequently, the aging of the baby boom

generation is, in effect if not in name, a very rapidly growing export-based industry.

The group is strong in all of our designated characteristics save one: the location quotient.

This is a consequence of high-income households over 65 in Michigan accounting for a smaller

share of all households over 65 than they account for nationwide (15.8 percent versus 17.6

percent, respectively). This is in contrast to high-income households headed by a person age 64

or younger, where Michigan has a higher proportion of high-income households than the nation

(40.5 percent versus 37.1 percent, respectively). This suggests that Michigan is losing a

disproportionate share of high-income households when they retire, a lost opportunity that is

likely to accelerate—unless the elderly stop wanting to live in a warmer climate.

Industry Detail: Knowledge-Based Industries

Two of the industry groupings mentioned, the knowledge-based economy and the tourist-

based economy, do seem to offer promise as economic engines for Michigan, at least based on

our criteria for success, so we take a little closer look at the detail underlying each of them. The

22

knowledge-based economy is broken down into finer industry categories in table 5. The export

share statistics were not available to us at this level of detail.

Growth prospects are favorable for most of these industries, particularly software

publishing, computer systems design, and management consulting, none of which is relatively

concentrated in the state. Michigan shows the least concentration in some of the finance

categories such as banking and insurance. Although Michigan is under-represented overall in

knowledge-based industries, it does have fairly high concentrations in certain segments, such as

testing laboratories (location quotient of 4.68), engineering services (1.45), scientific research

(1.23), and company management, including the Big Three headquarters (1.21). All of the

wages in the knowledge-based industries are well above average, and some of them are very

high.

Table 5

Employment in Selected Knowledge-Based Export Industries, 2004 U.S. Michigan Michigan Employment Average Wage, 2004 Location Employment Growth Balance Quotient

Industry (NAICS) 2004 2004–14 of U.S. Michigan 2004 Total employment 4,301,743 14.0% $39,319 $40,373 1.00 Software publishers (5112) 7,330 67.6% $95,924 $81,650 0.93 ISPs, data processing (518) 5,835 27.6% $69,724 $54,447 0.45 Credit intermediation (522) 86,597 5.3% $54,190 $47,496 0.92 Securities, investments (523) 11,057 15.8% $158,937 $92,368 0.43 Insurance (524) 56,943 9.5% $59,617 $52,825 0.80 Engineering services (54133) 40,787 15.8% $65,543 $64,004 1.45 Testing laboratories (54138) 22,159 15.8% $53,740 $94,272 4.68

Computer systems design (5415) 38,821 39.5% $77,791 $68,869 1.02

Management consulting (5416) 18,848 60.5% $67,991 $61,574 0.72 Scientific research (5417) 23,730 11.9% $76,581 $91,108 1.23 Company management (55) 68,003 10.6% $79,562 $91,847 1.21

Source: For U.S. forecast employment growth, U.S. Bureau of Labor Statistics [1]; for employment, average wage, and location quotients, U.S. Bureau of Labor Statistics and computations by the authors, March 2006.

23

The employment path for the knowledge-based export sector is plotted in figure 4 for

Michigan and the balance of the United States, with each series indexed to equal 100 in 1990.

For most of the 1990s, the industry in Michigan kept pace with the rest of the country, but started

losing ground in the late 1990s. The local industry turned down with the rest of the Michigan

economy after 2000, and has been losing ground since then. This is a disturbing pattern that

needs to be reversed if the knowledge-based economy is to be a reliable economic engine for the

state.

90

100

110

120

130

140

’90 ’91 ’92 ’93 ’94 ’95 ’96 ’97 ’98 ’00’99 ’03’01 ’02 ’04 ’05

Balance of U.S.

Michigan

Figure 4

Employment in Information, Finance and Insurance, Professional Services, HeadquartersMichigan and Balance of United States, 1990–2005

Index(1990 = 100)

Source: U.S. Bureau of Labor Statistics and computations by the authors, March 2006.

90

100

110

120

130

140

90

100

110

120

130

140

’90 ’91 ’92 ’93 ’94 ’95 ’96 ’97 ’98 ’00’99 ’03’01 ’02 ’04 ’05’90 ’91 ’92 ’93 ’94 ’95 ’96 ’97 ’98 ’00’99 ’03’01 ’02 ’04 ’05

Balance of U.S.

Michigan

Figure 4

Employment in Information, Finance and Insurance, Professional Services, HeadquartersMichigan and Balance of United States, 1990–2005

Index(1990 = 100)

Source: U.S. Bureau of Labor Statistics and computations by the authors, March 2006.

24

Industry Detail: High-Tech Industries

Our definition of the knowledge-based economy is much broader than the high-profile

high-technology sector. The economic development focus should be on the broader category,

but the technology sector is highly visible and is also important to Michigan and its future.

High technology cuts across so many industry categories that we resorted to occupational

data to build our series of this group. The methods are detailed elsewhere [6]; the data have been

updated for this study and are included in table 6. We have divided high tech into three

categories: industrial high tech (research, development, and engineering functions in the

industrial manufacturing economy); information technology (electronic engineers and

technicians, systems analysts and programmers); and biotechnology (life and medical scientists

and technicians). Data have been averaged for the 1987–91, 1999–2000, and 2004–05 time

periods. The employment measure used is private sector plus public university employment.

The high-tech sector is large in total in Michigan, with almost a quarter of a million

workers in 2004–05. Over half of them are in industrial high tech, many associated with

advanced manufacturing in the auto industry. We have a significant concentration in this high-

tech area, with a location quotient of 1.66, indicating that Michigan’s share of employment is

about one and two-thirds the U.S. share. Michigan is one of the national leaders in industrial

high tech. The sector grew very rapidly during the 1990s, but has turned down with the rest of

the economy since 2000.

Michigan’s advantage in industrial high tech reflects the fact that it is the “capital” of the

U.S. auto industry. Because the Big Three are headquartered in

Michigan, their research, engineering, and design functions are also centered here. In addition,

many overseas auto producers have located their U.S. tech centers in Michigan, and are currently

25

expanding these operations. This results in a massive investment in technology resources in

Michigan and the creation of a large technology-related employment base.

Table 6

High-Tech Occupational Employment Trends Summary, Michigan Averages for 1987–91, 1999–2000, and 2004–05

Employment Location Quotient Occupation ’87–’91 ’99–’00 ’04–’05 ’87–’91 ’99–’00 ’04–’05 High-tech 170,017 253,894 246,232 1.12 1.15 1.25

Engineers 117,846 128,523 1.66 1.90 Engineering & related technologists & technicians 32,748 22,681 1.00 0.93

Mathematical & computer scientists 59,940 56,908 0.88 0.86 Natural scientists 12,906 13,834 0.79 0.89 Science technicians 8,879 5,315 0.91 0.79 Computer programmers 21,575 18,971 0.91 1.12

Industrial high-tech 108,485 142,038 126,244 1.44 1.70 1.66 Engineers ex. electrical & electronic 98,419 94,037 2.11 2.31 Engineering and related technologists & technicians ex. electrical & electronic

23,609 13,538 1.36 0.87

Mathematical & computer scientists ex. systems analysts 12,746 12,689 1.35 1.17

Natural scientists ex. chemists, agri- cultural & food scientists, biological & life scientists, & medical scientists

2,153 2,122 0.49 0.48

Science technicians 5,111 3,858 0.86 0.87

Information technology 52,377 97,335 106,819 0.79 0.80 0.99 Electrical & electronic engineers 19,427 34,486 0.80 1.29 Electrical & electronic technicians 9,139 9,143 0.60 1.05 Computer systems analysts 47,194 44,219 0.80 0.80 Computer programmers 21,575 18,971 0.91 1.12

Biotechnology 9,155 14,521 13,169 0.96 0.92 0.98 Agriculture & food scientists 678 857 0.48 0.69 Biological & life scientists 2,044 2,557 0.72 0.88 Biological tech 3,768 1,457 0.97 0.64 Chemists ex. biochemists 4,864 5,885 1.07 1.47 Medical scientists 3,167 2,413 1.05 0.82

Source: Michigan at the Millennium [6], Chapter 7, updated by David Macpherson, Abel Feinstein, and the authors, March 2006.

26

The motor vehicle industry is one of the top industries in the country for research and

development. Its R&D expenditures were $16.1 billion in 2001, 69 percent of which can be

attributed to Michigan. As we mentioned in our more detailed discussion of the auto industry

earlier, this pre-production part of the industry is considered separately in the data, and in our

analysis. Unlike the production part of the industry, the engineering component is treated in the

standard employment statistics as a service industry, and we have included it in our knowledge-

based service sector.

Information technology is smaller and not as concentrated, although it is becoming more

so, with a location quotient near one in 2004–05. It also continued growing over the past five

years. Michigan has its niches, particularly in industrial electronics.

The smallest high-tech group is in the still-emerging biotechnology category, with just

over 13,000 employees in 2004–05. The location quotient is a little below one, supporting the

notion that we are a little behind some of our regional competitors. On the other hand, it is a

field that is still in its infancy, and is widely recognized as having the potential for major

scientific advance. The importance of biotech lies more in its potential, both scientific and

economic, than in its current employment levels. And involvement by the higher-education

sector, particularly at the University of Michigan, is an asset in this area that could be further

cultivated.

High tech also means high wage, as shown in table 7. Nearly all high-tech occupations

shown in table 7 paid a wage premium compared with the average pay for all occupations. More

than half of the occupations shown had a wage premium above 50 percent, and at the high end,

chemists had a premium of 140 percent.

27

Table 7

Average Weekly Wage in High-Tech Occupations, 2004–05

Average Weekly Wage

2004–05

Ratio of High-Tech Wages to Wages in

All Occupations All occupations $ 730 1.00 Engineers 1,376 1.88 Mathematical and computer scientists 1,178 1.61 Natural scientists 1,334 1.83 Engineering and related technologists and technicians 846 1.16

Science technicians 592 0.81 Computer programmers 1,066 1.46 Electrical and electronic engineers 1,362 1.87 Computer systems analysts 1,132 1.55 Biological and life scientists 697 0.95 Designers 783 1.07 Electrical and electronic technicians 720 0.99 Chemists, except biochemists 1,751 2.40 Medical scientists 1,099 1.51 Chemical technicians 745 1.02

Source: Michigan at the Millennium [6], Chapter 7, updated by David Macpherson, Abel Feinstein, and the authors, March 2006.

Industry Detail: Tourist-Oriented Industries

We turn next to the tourist-oriented industry, which we break down into finer industry

categories in table 8. Again, the export share statistics were not available to us at this level of

detail. The growth prospects are greater than the all-industry average for every category listed

except air transportation, with many categories considerably greater. The wages are lower than

the all-industry average for most categories though, and also tend to be lower for comparable

industries in the rest of the country. The location quotients are well below one for all categories

except three: golf courses (1.28), marinas (1.23), and gambling (1.13). We do not seem to be

supplementing our natural assets with sufficient ancillary activities to be taking full advantage of

our opportunities in this sector.

28

Table 8

Employment in Selected Tourist-Oriented Industries, 2004

U.S. Michigan Michigan Employment Average Wage, 2004 Location Employment Growth Balance Quotient

Industry (NAICS) 2004 2004–14 of U.S. Michigan 2004 Total employment 4,301,743 14.0% $39,319 $40,373 1.00 Air transportation (481) 14,979 8.8% $53,857 $66,429 0.88 Performing arts companies (7111) 1,730 17.4% $34,326 $26,942 0.44

Spectator Sports (7112) 3,570 25.2% $83,854 $103,065 0.81 Museums, historical sites, zoos, parks (712) 3,742 19.6% $28,462 $20,218 0.55

Amusement parks & arcades (7131) 675 26.5% $20,919 $11,538 0.13

Gambling, except casino hotels (7132) 10,125 26.5% $26,964 $34,849 1.13

Golf courses and country clubs (71391) 13,915 26.5% $19,639 $16,699 1.28

Skiing facilities (71392) 839 26.5% $16,960 $11,535 0.74 Marinas (71393) 1,309 26.5% $26,695 $25,122 1.23 Casino hotels (72112) 5,213 16.9% $30,221 $25,038 0.51 Other accommodations (721 except 72112) 34,149 16.9% $21,303 $16,578 0.68

Source: For U.S. forecast employment growth, U.S. Bureau of Labor Statistics [1]; for employment, average wage, and location quotients, U.S. Bureau of Labor Statistics and computations by the authors, March 2006.

Michigan’s Assets

We have identified some promising industries for economic development in Michigan.

We must also consider whether Michigan has the underlying assets to promote and sustain these

industries. Too often, efforts at economic development are motivated solely, and perhaps

naively, by an infatuation with industries that are “hot” at the moment. Not enough thought is

given to whether the region has what it takes to nurture and develop those industries. In

29

economic jargon, if we think of the industries’ requirements as “demand,” the question that

needs to be asked is whether the region can “supply” the assets needed to satisfy that demand.

So what are our assets? Our jumping-off point for defining Michigan’s assets is the

standard economic concept of the factors of production: labor, land, capital, and the wherewithal

to put them together (entrepreneurship).

In the introduction to this paper, our football player recognized that quality of labor

matters. At the most fundamental level, labor quality derives from education and training, and

what increasingly matters in our transitioning economy is higher education. This should be an

advantage to Michigan, because one of Michigan’s strongest assets is a premier system of higher

education.

With respect to land, we have a natural asset: the Great Lakes and the surrounding

environment in the northern parts of Michigan. To reiterate, this is an asset that has not been

fully exploited, particularly in terms of amenities. We differ in this regard from the trade

theorists’ concept of endowments in that we allow the value of our assets either to be enhanced

or to deteriorate based on human intervention. And our focus should not be only on the

enhancement of assets; it is just as important to avoid the deterioration of our assets (for

example, pollution of the Great Lakes).

The other items among our factors of production relate to assets where we judge

Michigan to be deficient. If we think of capital as representing financial capital, rather than

machines and equipment, it seems that there is significant under-investment in Michigan

enterprises, certainly in terms of venture capital and also in private sector funding overall.

Finally, our sense is that we are also deficient in entrepreneurship and the entrepreneurial

spirit. Part of this relates to the relative timidity financial institutions have shown in risking

30

support for new ideas and ventures, but there are undoubtedly many more reasons why

entrepreneurs are not coming here or staying here. Our football player recognized the value of

entrepreneurship and capital investment in acquiring the Super Bowl game. Michigan’s

economic success in the first half of the 1900s was fueled in great part by the entrepreneurship

shown early in that century. We seem to be missing that spirit in the early years of this century.

Let’s now consider some detail on these assets, to more fully support our judgments.

Higher-education system

The claim is that we have a premier higher-education system in Michigan, and for many

or most, this is accepted as fact. Do we have any data to support the claim? In a very general

way, the information in table 9 does. For each of five measures of higher-education quality,

rankings are shown for the top 200 colleges and universities in the country. The five categories

include research spending, faculty status (national academy membership, faculty awards of

distinction), and student achievement at both the graduate and undergraduate level (doctorates

awarded, National Merit Scholars). Among universities across the nation, both public and

private, the University of Michigan ranks in the top ten nationally in three of the five categories,

and among the top twenty in another. Michigan State University ranks in the top fifty in four

categories. Some of the smaller institutions in the state also appear in the top 200, particularly in

the categories associated with student achievement.

Natural environment

The ability of any area to attract tourists or retirees is influenced both by natural

amenities and man-made amenities. Natural amenities include the climate, topography of the

land, and the presence or absence of large bodies of water for recreational use. Man-made

31

Table 9

National Rankings of Michigan Colleges and Universities Various Measures of Quality

(Ranked among top 200 institutions in each category)

National Rank Total Research Spending, 2002 (millions) University of Michigan, Ann Arbor $674 3 Michigan State University $290 34 Wayne State University $199 59 Michigan Technological University $ 30 187

National Academy Membership, 2003 University of Michigan, Ann Arbor 73 14 Michigan State University 8 74 Wayne State University 5 86 Michigan Technological University 2 115

Faculty Awards of Distinction, 2003 University of Michigan, Ann Arbor 39 6 Michigan State University 14 43 Wayne State University 7 85 Western Michigan University 3 146 Hope College 2 194

Doctorates Awarded, 2003 University of Michigan, Ann Arbor 617 5 Michigan State University 442 17 Wayne State University 188 72 Western Michigan University 86 146 Central Michigan University 57 198

National Merit Scholars, 2003 University of Michigan, Ann Arbor 66 31 Michigan State University 62 33 Hope College 15 124 Hillsdale College 12 144 Kalamazoo College 9 161 Michigan Technological University 8 166 Alma College 7 174

Source: The Center, University of Florida (http://thecenter.ufl.edu/index.html) Compiled by the authors, March 2006.

32

amenities include the quantity and quality of restaurants, cultural activities, and recreational

facilities such as Disney World or gaming casinos.

Natural amenities cannot be altered, by and large, although they can be enhanced and

more heavily promoted. The U.S. Department of Agriculture has developed a series of measures

on the natural amenities of every county in the continental United States [5]. The measures

include mean January temperature, mean hours of sunlight in January, mean temperature in July,

and mean humidity in July. The department has also developed a measure of the topography of

the land area and the water area of a county, including its coastline.

As one would expect, Michigan’s ranking is poor in terms of winter weather, but it does

much better for summer weather. Michigan is also relatively flat, and therefore is lacking in

interesting topography. Michigan fares much better with respect to access to recreational water

resources. In this category, thirteen counties in the state rank among the top 100 in the country.

Michigan has thirty-four of the top 200 recreational water resource counties, even more than

Florida.13

Thus, for the Great Lakes state, the Great Lakes appear to be an asset that is attractive to

outside tourists. The lakes are an asset that is potentially attractive to retirees, as well. Also

important to retirees, though, according to those who rate the attractiveness of locations to

seniors [10], is a vibrant arts and entertainment scene and quality restaurants. With a location

quotient of only 0.44 in the performing arts industry (see table 8), however, it is clear that some

of the enabling activities that would allow Michigan to take full advantage of its enormous

natural asset are not yet in place.

13 There are 3,111 counties in the continental United States, and 83 counties in Michigan.

33

Financial capital

As we mentioned earlier, we have a sense that there is significant under-investment in

Michigan enterprises in terms of private sector funding. If this is correct, one cause may be

Michigan’s under-representation as a regional financial center, which was apparent in some of

the statistics we presented earlier. There also seems to be a relative timidity among the financial

community to take risks in backing local enterprises. This is clearly the case for private venture

capital investment in new and emerging industries, and here we have numbers to support this

observation. Venture capital expenditures are provided largely to enterprises that are

developing new ideas, products, or processes. As shown in table 10, for a recent period of

healthy growth in the state, 1995–2001, Michigan’s ranking among the states for total venture

capital expenditures is a mediocre 25, and for venture capital expenditures per employee it is a

very weak 35.

High tech requires funding on a large scale, and Michigan appears to be significantly

under-subscribed in this strategic area. This is unfortunate, because according to one of our

recent studies [6], venture capital shows up as the single most important variable in explaining

employment movements in biotech and information tech among states.

34

Table 10

Total Venture Capital and Venture Capital per Worker, by State, 1995–2001

Venture Capital Total 1995-2001

($ millions)

Ranking of

Venture Capital

Venture Capital

Per Employee ($)

Ranking of Venture Capital Per Employee

United States 260,871.2 2,251 Alabama 662.0 26 372 32 Alaska 3.5 50 15 49 Arizona 1,798.2 21 923 22 Arkansas 49.8 46 50 46 California 108,296.3 1 7,873 3 Colorado 10,336.5 5 5,368 4 Connecticut 4,209.1 15 2,845 6 Delaware 313.2 34 923 21 D.C. 1,921.3 19 10,278 1 Florida 6,014.9 10 965 19 Georgia 5,424.4 11 1,604 13 Hawaii 272.3 36 578 25 Idaho 60.0 45 111 44 Illinois 5,074.3 12 956 20 Indiana 488.7 30 182 41 Iowa 106.5 42 78 45 Kansas 469.2 31 403 29 Kentucky 459.1 32 283 34 Louisiana 616.1 27 374 31 Maine 301.7 35 533 26 Maryland 4,995.9 13 2,356 9 Massachusetts 26,227.6 2 9,360 2 Michigan 1,224.2 25 280 35 Minnesota 3,394.9 16 1,460 15 Mississippi 329.4 33 315 33 Missouri 2,179.0 18 892 23 Montana 85.1 43 226 36 Nebraska 174.2 39 224 37 Nevada 139.1 40 172 42 New Hampshire 1,459.6 23 2,531 7 New Jersey 7,527.6 7 2,164 11 New Mexico 131.3 41 208 39 New York 16,182.5 3 2,291 10 North Carolina 4,248.7 14 1,286 17 North Dakota 6.9 48 24 48 Ohio 2,300.9 17 470 27 Oklahoma 201.2 37 150 43 Oregon 1,868.3 20 1,269 18 Pennsylvania 6,934.7 9 1,365 16 Rhode Island 189.5 38 445 28

35

Table 10 continued

Total Venture Capital and Venture Capital per Worker, by State, 1995–2001

Venture Capital Total 1995-2001

($ millions)

Ranking of

Venture Capital

Venture Capital

Per Employee ($)

Ranking of Venture Capital Per Employee

South Carolina 604.0 28 379 30 South Dakota 4.5 49 13 50 Tennessee 1,590.0 22 686 24 Texas 14,775.7 4 1,742 12 Utah 1,451.9 24 1,601 14 Vermont 62.6 44 219 38 Virginia 7,188.4 8 2,526 8 Washington 7,579.1 6 3,050 5 West Virginia 30.5 47 47 47 Wisconsin 525.6 29 208 40 Wyoming 0.0 51 0 51

Source: Calculated by Abel Feinstein and the authors using data from “Cyberstates 2002.” Washington, D.C.: American Electronics Association, 2002.

Linkage between assets and industries

We now return to the question posed at the beginning of this section on assets, that is, is

there a linkage between the assets and industries we have identified? If so, the prospects for

success are more promising for the sectors identified, and cultivation of the assets is more

compelling.

First, the knowledge-based economy and higher education. Bill Gates, one of the most

prominent entrepreneurs of our generation, has made the observation that for knowledge-based

enterprises, educational attainment trumps everything when deciding where to invest. Can we

extend that statement to include the entire educational environment? One piece of information

that helps is summarized in table 11. Here we have identified the five states (counting the

District of Columbia as a state) that have the highest and lowest shares of employment in the

knowledge-based export-oriented service industries. The table also shows the proportion of total

employment in each state that is in four-year public and private colleges and universities

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Table 11

Employment Share, Knowledge-Based Export-Oriented Service Industries (NAICS 51, 52, 54, 55) and Colleges and Universities (NAICS 6113)

and Average Wage Rate, Colleges and Universities 2004

Employment Average Wage NAICS

51, 52, 54, 55 Colleges and Universities

Colleges and Universities

% Share

Rank

% Share

Rank

Wage

Rank

District of Columbia 22.3 1 5.9 1 $44,824 11 Delaware 20.7 2 2.0 28 $51,388 3 Virginia 17.8 3 1.8 38 $39,983 31 Massachusetts 17.8 4 3.2 2 $52,277 2 New York 17.3 5 2.6 7 $42,782 21 Michigan 12.6 22 2.0 22 $41,022 26 South Carolina 9.4 47 1.7 41 $38,533 35 Indiana 9.4 48 2.3 15 $36,376 40 West Virginia 9.0 49 2.4 8 $33,929 47 Mississippi 8.5 50 1.7 42 $37,579 37 Wyoming 8.3 51 2.0 26 $28,567 50

Note: Data include both private and public employees. Source: Bureau of Labor Statistics, Quarterly Census of Employment and Earnings.

Compiled by the authors, March 2006.

(community colleges are excluded), as well as the average wage received by all employees at

those institutions. Data on the state of Michigan are also included for reference.

In four of the five states with a high share of activity in the knowledge-based service

industries, there is also either a high share of employment in their institutions of

higher education, or the employees at those institutions are paid relatively well. The exception is

Virginia, which ranks thirty-eighth in employment share in higher education and thirty-first in

average pay in higher education.14

14 Virginia (particularly northern Virginia, which is driving the state’s economy) is undoubtedly taking advantage of the higher-education sector in the District of Columbia, since it is essentially part of the same metropolitan area.

37

All of the states with a low share of employment in the knowledge-based service

industries pay their employees at colleges and universities relatively poorly, and most tend to

have a relatively small share of employment in higher education as well. The Pearson

correlation coefficient is 0.67 between average wage at higher-education institutions and the

share of employment in the knowledge-based service economy, and is significant at the one

percent level. The correlation coefficient between the share of employment in higher-education

institutions versus the knowledge-based service economy is 0.38, also significant at the one

percent level.

Of course, these correlations do not suggest causation, only that there is some positive

relationship between the knowledge-based economy and higher education. Perhaps the

knowledge-based economy promotes higher education, or there are intervening variables not

identified. Regardless, it is difficult to believe that institutions of higher education do not play an

important role in the development of the knowledge-based economy. In that regard, it is

noteworthy that Michigan ranks twenty-second both in its employment share for the knowledge-

based industries and in its share for colleges and universities. It is twenty-sixth in average pay

for employees of colleges and universities. In comparison, Michigan ranks twelfth in average

pay over all industries. The numbers suggest that Michigan may be under-investing in higher

education, whether private or public.

Second, tourist-oriented industries. The linkages here between assets and industries are

obvious. One advantage to having more than one industry prospect as an engine for the state

economy is that the geographic concentration is different for the knowledge-based and tourist-

oriented economies.

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Third, high-income retirees. Earlier in the paper, we identified high-income retirees as a

potential economic development “industry” for Michigan. It would be good to know how to

implement a strategy for retaining (or even attracting) this demographic in the state. We do not

currently have such a strategy in hand. So why did we raise the issue if we don’t have a means

of addressing it? Because the coming wave of baby-boomer retirements is going to be one of the

most pervasive demographic trends in the nation, with the power to reshape the economy of

virtually every state. States that do a good job of retaining their retirees are in a much better

position than those that lose them in large numbers. Obviously, many of Michigan’s retirees will

continue to move to Florida or Arizona, but maybe we can do something to reduce the exodus.

We want to keep as many of these people as we can because they meet several of the criteria we

have established for economic engines. Most of their income flows in from outside the state,

which, strange as it may sound, qualifies them as an export-based industry. And their growth

potential exceeds that of any industry in the economy. That is why, although we can’t say

anything particularly definitive at this time, we feel this subject merits further research to

determine whether there are retention strategies applicable to this important demographic group.

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Conclusion

To summarize briefly, the main findings of the study can be consolidated into several key

points:

• Michigan is in the midst of serious economic trouble. The trouble is structural and not

just cyclical. The current stretch of employment decline will inevitably become the

longest in at least the past fifty years, and we don’t see the state returning to its previous

peak job levels of mid-2000 until at least 2013.

• The domestic auto industry is in severe distress, and the Michigan economy remains

highly dependent on this sector. The outlook for Big Three production employment is

negative, so this sector is unlikely to be a force for job growth in Michigan for the

foreseeable future—we have to look elsewhere.

• We propose that activities with the best prospects to be regional economic engines are

those that have long-term growth potential, a substantial out-of-state export component,

and some regional competitive advantage in providing products and services. We also

view above-average pay as a desirable characteristic.

• Three groupings passed through our evaluation filter and show some promise as

economic engines in Michigan: the knowledge-based export economy; the tourist-

oriented economy; and higher-income retirees.

• Michigan’s premier system of higher education is needed to sustain the knowledge-based

economy. The Great Lakes are our most compelling asset in regard to tourism.

• Michigan’s higher-education situation is reasonably good, but we could do better.

• We need to do much more with our tourism potential, including more extensive national

and international promotion of Michigan as a tourist destination.

40

• We should develop strategies to retain a greater number of retirees in the state. Their

growth potential exceeds that of any industry in the economy.

• Venture capital is a key ingredient in growing new and emerging industries. Michigan

does poorly in this area.

• Michigan appears to be lagging in entrepreneurship, but there are no statistics to confirm

this. This area merits further research.

Regardless of the strategies proposed by this conference to answer the question, “Where

do we go from here?” a few basic fundamentals should hold. First, image matters. Perception

can shape reality; if Michigan is perceived as a good place to work and play, the state becomes a

stronger magnet to attract investors, entrepreneurs, and visitors, and their presence in turn will

reinforce a positive image. Second, we need to take a longer-term view of our problems. Short-

term solutions and quick fixes have always been political favorites, but it’s time to stop playing

the immediate-gratification game. Changing a state’s economic structure is a brick-by-brick

project; it will take time and it must transcend political rivalries. We need to work together for

the common good, and start thinking about how we can be united in an effort to make our state

great again.

What is clear is that we need to be working effectively on planning and implementing a

new strategy. That is the spirit of this conference. Our outlook for the Michigan economy

underscores the writing on the wall: the old model is broken, a new one is needed, and the clock

is ticking.

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2. Crary, Joan P.; Fulton, George A.; and Hymans, Saul H. “The Michigan Economic Outlook for 2006–2007.” In The Economic Outlook for 2006. Proceedings of the 53rd Annual Economic and Social Outlook Conference, University of Michigan, Ann Arbor, November 17 and 18, 2005. Updated for the Consensus Revenue Estimating Conference, Lansing, Michigan, January 12, 2006.

3. Crary, Joan P.; Fulton, George A.; and Hymans, Saul H. “Overview of the Michigan Economy.” In Michigan at the Millennium, eds. Charles L. Ballard, Paul N. Courant, Douglas C. Drake, Ronald C. Fisher, and Elisabeth R. Gerber. East Lansing: Michigan State University Press, 2003.

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