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High Education, High Technology, and High Wages An Exploration into the Relationship between University Education and Economic Prosperity and Dynamism:

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Presentation on theme: "High Education, High Technology, and High Wages An Exploration into the Relationship between University Education and Economic Prosperity and Dynamism:"— Presentation transcript:

1 High Education, High Technology, and High Wages An Exploration into the Relationship between University Education and Economic Prosperity and Dynamism: A California Wake-Up Call

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3 Susan B. Carter Mathew Sobek Richard Sutch Center for Social and Economic Policy University of California Riverside

4 California is a High Wage State Opening Observation

5 196019651970197519801985199019952000 480 520 560 600 640 680 United States California Median Real Wage 1998 Dollars

6 1940194519501955196019651970197519801985199019952000 1.00 1.05 1.10 1.15 1.20 1.25 Index of Median Wages in California US = 1

7 California’s High-Wage Status is Due in Part to California’s Highly Educated Labor Force

8 California is a High Education State Due in part to its long history of public and private support for education, particularly higher education.

9 Educational Expenditures per FTE College Student, 1994-95 All Four-Year Institutions Public and Private Less than $14,000 $14,000 - $17,000 More than $17,000

10 196019651970197519801985199019952000 10 15 20 25 30 35 Percent of Full-Time Workers with a College Education United States California

11 But, California is Losing its Relative Advantage The proportion of college-educated is falling

12 196019651970197519801985199019952000 1.00 1.10 1.20 1.30 1.40 California with US=1 Index of Highly-Educated Workers College Degrees

13 The Proportion of High-School Drop-Outs in California has Ceased to Fall And California has fallen behind the rest of the country

14 196019651970197519801985199019952000 0 10 20 30 40 50 Percent of Full-Time Workers without a High School Education United States California

15 Something More than just the Educational Mix is Influencing the Wage Structure in California

16 How do we know? Wages are higher in California, even after correcting for educational attainment levels –Wages of college grads are higher –Wages of high school grads are higher –Until recently, wages of drop outs were higher Next Slide, please

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18 196019651970197519801985199019952000 1.00 1.04 1.08 1.12 1.16 1.20 Index of Median Wages High School Graduates in California US=1

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20 Taken together these trends imply... Inequality in California is becoming greater –both absolutely and relative to the US Inequality Measure: The ratio of the wages of full-time workers at the 90th percentile to those at the tenth percentile –AKA: The 90/10 Pay Ratio

21 1940194519501955196019651970197519801985199019952000 2.0 3.0 4.0 5.0 6.0 Wage Inequality 90/10 Pay Ratio United States California

22 Why is California a High Wage State?

23 California is Technologically Advanced Silicon Valley –computers and telecommunication Military Contracts –Aircraft and Space Petrochemicals Our Proxy?

24 1880190019201940196019802000 0 20 40 60 80 Patenting Intensity Patents per 100,000 United States California

25 194519551965197519851995 0 10 20 30 40 United States California Patenting Intensity Patents per 100,000

26 California’s High Patent Intensity is a reflection of (a Proxy for) its High-Tech, Entrepreneurial Environment … And a High-Tech Environment May lead to Higher Wages for All

27 Relative Patenting Intensity California with US = 100 194519551965197519851995 90 100 110 120 130 140 150

28 194519551965197519851995 0 10 20 30 40 50 60 70 80 90 100 Relative Patenting Intensity South with US = 100

29 Relative Patenting Intensity US = 100 Great North Heartland

30 Relative Patenting Intensity US = 100 New Jersey Southern New England New York

31 Relative Patenting Intensity West with US = 100

32 Relative Patenting Intensity US = 100 Rust Belt Minnesota Wisconsin

33 Universities Patents High Tech

34 Universities Patents High Tech Adam B. Jaffee. “Real Effects of Academic Research.” American Economic Review 79 (December 1989). Authority:

35 Universities Patents High Tech High Wages Own Education

36 Universities High Wages Alfred Marshall

37 Regression Model Data: CPS March 1994, ‘95, and ‘96 Sample: Full-Time Male Workers –Age18-65 –Born in the USA Dependent Variable: Log Weekly Wage Estimator: Weighted Least Squares

38 Own Education Four Separate Regressions –No High School Diploma: –High School Diploma: –College Degree: –Advanced Degree: –n = 4,642 –n = 36,343 –n = 11,831 –n = 6,087 n = 58,903

39 Independent Variables Constant and Dummies for 1994 and 1995 Third-Degree Polynomial in Age State-Level Externality Variables –Patents per capita, 1994-96 [Johnson] –Percent of all 19-21 year olds attending college [CPS] –Educational Structure of State [next slide]

40 Educational Structure of State Workers All Workers (three out of four) –Percent that are HS Drop Outs –Percent that have HS Diploma –Percent that have College Degree –Percent that have Advanced Degree IDEA: You are more productive, if those around you are highly educated.

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42 Age-Wage Profile, 1994-96 Full-Time Working Men, Born in the USA Drop Outs Advanced Degree College High School Age

43 All the Marshallian Variables have Powerful Effects We can demonstrate this with a few examples... Start with HS graduates in Arkansas and ask what the impact on wages in that State would be if it had: –high tech environment of Massachusetts –college enrollment of Massachusetts –educational attainment of Massachusetts

44 2030405060 200 300 400 500 600 700 800 900 1000 Age-Wage Profile High School Graduates, Arkansas vs Massachusetts Full-Time Working Men, Born in the USA Arkansas With Colleges With Patents Massachusetts Age With LF Mix

45 How Big Depends Upon the Example Start with High School Grads in North Dakota and ask what the impact on wages in that State would be if it had: –high tech environment of New York –college enrollment of New York –educational attainment of New York

46 2030405060 200 300 400 500 600 700 800 900 1000 Age-Wage Profile High School Graduates, North Dakota vs New York Full-Time Working Men, Born in the USA North Dakota With Colleges With Patents New York Age With LF Mix

47 2030405060 200 300 400 500 600 700 Age-Wage Profile High School Graduates, United States vs California Full-Time Working Men, Born in the USA United States California Age

48 Conclusion California’s Past Investments in Higher Education have fostered a High-Tech Environment and has supported a High Wage work force California is in danger of losing its edge More support of higher education would yield handsome dividends –to those educated –to others in the State

49 Dilemma Would not educating more Californians simply benefit the rest of the world at California Tax-Payers’ expense? –They could move to other States Test: Relative Retention of In-State College Degree Recipients –Measured by CS Method

50 C-S Method In-migration measured as the difference between –the number of 29 or 30 year-olds in the State with a college degree in 1990 and –the expected number of surviving 19 or 20 year- olds attending college in the State in 1980. Survival rates calculated for the cohort from the US totals [Census Survival Method]. –See Carter and Sutch [1996] for details.

51 California is home to more college-educated people than it has educated During the decade 1980-1990, California was a net importer of college-educated people born in 1961 or 1962.

52 States by Net Importation of College Graduates, 1980-1990 Net importers No net change Net exporters

53 But, California is a net importer of people of all educational levels When we control for California’s population growth over the decade, its status changes...

54 States by Net Importation of College Graduates, Controlling for Population Growth, 1980-1990 Net importer No net change Net exporter

55 In-migration is not improving California’s Educational mix Can California hold on to its High- Tech, High-Education, High-Wage Position?

56 A stronger commitment to Higher Education would help

57 End of Show Comments welcome send e-mail to: susan.carter@ucr.edu sobek@ucr.edu richard.sutch@ucr.edu


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