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Rediscovering the Role of Noncognitive Elements of Human Capital

Rediscovering the Role of Noncognitive Elements of Human Capital. Jerry Miner Seminar, Syracuse University 5 April 2012 Henry M. Levin. Non-Cognitive. Non-cognitive refers to: Attitudes and values. Social and emotional behavior. Cognitive refers to: Knowledge and its application.

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Rediscovering the Role of Noncognitive Elements of Human Capital

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  1. Rediscovering the Role of Noncognitive Elements of Human Capital Jerry Miner Seminar, Syracuse University 5 April 2012 Henry M. Levin

  2. Non-Cognitive Non-cognitive refers to: • Attitudes and values. • Social and emotional behavior. Cognitive refers to: • Knowledge and its application. • Cognitive and non-cognitive may interact as in process of problem-solving.

  3. Dominance of Cognitive Skills in Economic Explanations • Nothing inherent in G Becker or T W Schultz that limits human capital to cognitive skills. • Becker highlights the influence of families on the “knowledge, skills, values, and habits” of children. Human Capital (1964):21. • Can capitalize the income stream of any human attribute (even physical characteristics) into a measure of human capital as implied by Irving Fisher’s broader framework in The Theory of Interest (1930).

  4. Economists Ignore Noncognitive View • Human Capital interpretation of link between education and earnings developed in early 1960’s as contained in educational attainment. • Rate of return on educational attainment as an unopened black box. • Opening of black box led to estimation of Educational Production Functions.

  5. 50 Years of Educational Production Functions • Virtually all production functions assumed that test scores are the objective function of schools. • All used cognitive measures of outcome with notable exception of Card and Krueger 1992 who used income and found “right signs” for school effects on income. • Cognitive exclusivity is summarized by the many articles showing league tables of educational production function results limited only to student achievement (Hanushek summaries).

  6. James Heckman Influence • In the last decade or so, Heckman has introduced non-cognitive variables into explanation of educational outcomes and income. • Psychologists and economists are working jointly to discover specific non-cognitive variables that are important for educational success and earnings.

  7. Purpose of Presentation • Emphasize importance of non-cognitive influences on school outcomes and life outcomes. • Urge greater balance in assessments between cognitive and non-cognitive outcome measures. • Rationale. • Evidence. • Next steps.

  8. Inkeles on Socialization of Competence • “Effective participation in a modern industrial and urban society requires certain levels of skill in the manipulation of language and other symbol systems, such as arithmetic and time; the ability to comprehend and complete forms; information as to when and where to go for what; skills in interpersonal relations which permit negotiation, insure protection of one’s interests, and provide maintenance of stable and satisfying relations with intimates, peers, and authorities; motives to achieve, to master, to persevere; defenses to control and channel acceptably the impulses to aggression, to sexual expression, to extreme dependency, a cognitive style which permits thinking in concrete terms while still permitting reasonable handling of abstractions and general concepts; a mind which does not insist on excessively premature closure, is tolerant of diversity, and has some components of flexibility; a conative style which facilitates reasonably regular, steady, and persistent effort, relieved by rest and relaxation but not requiring long periods of total withdrawal or depressive psychic slump; and a style of expressing affect which encourages stable and enduring relationships without excessive narcissistic dependence or explosive aggression in the face of petty frustration. This is already a long list and surely much more could be added (Inkeles 1966: 280-1).

  9. Inkeles and Smith • Index of Modern Attitudes • Six countries (Argentina, Bangladesh, Chile, India, Israel, and Nigeria) n = almost 6.000 • Explanatory variables: education, work experience, mass media, consumer goods, father’s education, urbanization, skill level, length of urban residence, modernity of workplace, home and school; and schooling. • Explained 32-62 percent of variance in modernism. • Education was most powerful influence—2-3 times more powerful than any other. (standard regression coefficients).

  10. Why favor cognitive? • Long history of cognitive testing with relatively clear constructs, measures, statistical properties. • Widespread adoption. • Skills logically assumed to be cognitive. • (At the time of HC development, economists did not associate with psychologists. That has changed today.)

  11. Non-cognitive Ambiguity • Distinction not clear—interacts with cognitive. • Constructs and measurement are contested. • Labels differ: Social and Emotional (SEL). Social and Behavioral Attitudes and Values

  12. Early non-cognitive Interest • Coleman (1966) included efficacy, motivation, and other non-cognitive variables—didn’t use them. • Bowles and Gintis (1976) and Gintis (1971) argued that schools mainly emphasize non-cognitive development. • Rejected by most economists.

  13. Cognitive Test Scores or Behavioral Socialization • If cognitive skills explain effect schooling effect on earnings in human capital equations, addition of test scores should deflate severely the earnings coefficient for schooling. • Schooling variable is highly errorful (no adjustment for quality, effort, area of study, retrospective errors). • 25 studies with 58 estimates over four decades. • School coefficient retains about 82 percent of its value after test scores are added to the equation.

  14. Has effect of cognitive test score increased? • Murnane, Willett, Levy (1995) compared test score impacts on earnings between 1978 & 1986 and found rise in hourly wages related to math scores. • Bowles, Gintis,Osborne (2001) reviewed 65 estimates from 24 studies over 30 years and found no rise. • UK study for 1995-2004 also finds no increase in returns to cognitive skills.

  15. Other evidence • Teenage cognitive skills in predicting later earnings (Murnane et al. 2000). • Murnane et al. equations including test scores explain no more than 17 percent of variance. • NRC study of supervisor ratings of worker productivity found that only about 6 percent of variance was explained.

  16. Employer Needs • NRC study of High School Graduates by Employer Panel (1984) • Examined Cognitive needs, but also behavioral and social. • Interacting in socially appropriate manner; respect for opinions, customs, and individual differences of others. • Handling conflict maturely; participation reaching group decisions.

  17. NRC study continued. • Positive attitude toward self. • Self-discipline. • Regular attendance, punctuality, dependability. • Ability to set goals and allocate time to achievement of them. • Capacity to accept responsibility.

  18. Employer Employment Survey (1995) U.S. Dept. Ed. • 4,000 employers • Recruitment characteristics for hiring. (1-5 high) • Applicant attitude (4.6); communication skills (4.2). • Test scores, academic grades, reputation of applicants school (2.4 or 2.5).

  19. Independent Effects of non-cognitive (Perry Preschool) • Perry preschool—initial test score advantage faded in early grades. • But assessment at age 40 showed: earnings advantage of one third; half the crime conviction rate. • Higher graduation rates and more positive attitudes towards schools. • Something other than academic achievement must explain.

  20. GED--Heckman • GED recipients had similar test results as regular high school graduates who do not enroll in college. • GED earnings well below high school graduates and even lower than dropouts with similar test scores. • Ultimate educational attainments lower than for dropouts who do not take GED. • Something else happening—lower non-cognitive skills that affect employment.

  21. Tennessee Class Size Experiment • Dramatic reductions in class size for 1-4 years, K-3. • Modest increases in achievement. • Dramatic increases in high school graduation rates. (disadvantaged from 70 percent (no reduction of class size to 88 percent for 4 years of early class size reductions). • Well beyond the impact of prediction from early achievement advantage.

  22. Can non-cognitive be taught? • Experimental study of teaching of executive function (self-regulation)—more important than cognitive measures for school readiness. • Experimental study of Tools of the Mind shows dramatic effects on EF. (Barnett 2011) • Bandura cites impressive data-base that shows self-efficacy can be taught.

  23. Early Childhood Education Summary • Nores and Barnett (2010)—38 studies reviewing 30 pre-school interventions in 23 countries RFT or quasi-experiments. Found both cognitive and non-cognitive benefits. • Camilli et al (2010) meta-analysi of 123 experimental preschool studies showed effects on cognitive skills, student social skills and school progress.

  24. Durlak (2011) Social-Emotional Learning • 213 school based programs, experimental or quasi-experimental. 270,000 children 5-18. • Non-cognitive (SEL) interventions. • Effect sizes: social & emotional skills, .57; attitudes towards self and others, .23; positive social behaviors, .24; problems of conduct, .22; emotional distress, .24; and academic performance, .27, rising to .32 for longer term studies. • Raise student achievement by 11 percentiles. • Equivalent to closing the gap between U.S. and Canada and rise in rankings from 17th to 5th place.

  25. Heckman and Colleagues • Use longitudinal (NLSY) to analyze students educational investment on earnings and graduation. • Creates battery of non-cognitive scores from anti-social construct using student anxiety, headstrongness, hyperactivity, peer conflict along with cognitive test scores. • Models developmental path and impacts of investment in cognitive and non-cognitive skill on high school graduation and earnings. Impact of the two kinds of investments shift from cognitive at younger ages 6-9 to older ages 9-13.

  26. Swedish Study (Lindqvist, E. & Vestman, R. (2011) “The Labor Market Returns to Cognitive and Noncognitive Ability: Evidence from the Swedish Enlistment,” American Economic Review: Applied Economics, (3), 101-128 • Sample: 14703 men distributed evenly over 1965-74 birth. • Universal enlistment age 18 males. • Evaluation of cognitive ability (test) and noncognitive ability 70-80 item questionnaire and interview by psychologist. • Wages age 31-40.

  27. Swedish (cont.) • Non-cognitive effects on wages and earnings are higher than cognitive for a range of specifications. • Non-cognitive more important at wages and earnings below median and cognitive above median. • Change in 1 sd in predictor: • Non-cognitive ES = .33; Cognitive ES = .15 for wages. • Employment Status: 3.3% to 1.1%. • More measurement error in non-cognitive than cognitive measures.

  28. Five Factor Model • For last two decades considered as the “big five” on the basis of many studies. • Openness—inventive and curious as opposed to consistent and cautious. • Conscientiousness—efficient and organized as opposed to easy-going and careless. • Extraversion—outgoing and energetic as opposed to solitary and reserved. • Agreeableness—friendly and compassionate as opposed to cold and unkind. • Neuroticism—sensitive and nervous as opposed to secure and confident.

  29. Examples of big five findings. • Major study finds openness predicts SAT. • Agreeableness and conscientiousness predicted Peer ratings of team member performance beyond controls for specific skills and general cognitive ability. • Kyllonen and colleagues go well-beyond big five in their extensive study of noncognitive constructs and measures.

  30. Most Comprehensive Review • Almlund, M., Duckworth, A. L., Heckman, J. & Kautz, T. (2011) Personality Psychology and • Economics, (January 17, 2001 version) ¨IZA Workshop: Cognitive and Non-Cognitive • Skills¨, January 25-27, (Bonn, Germany). Available as: • http://iza.org/conference_files/CoNoCoSk2011/heckman_j130.pdf.

  31. Conclusions • Non-cognitive skills are important contributors to educational outcomes and life outcomes. • Can be altered by educational interventions. • Contribute to cognitive outcomes. • Impact of test scores is overstated if noncognitive measures are omitted from analysis (omitted variable bias).

  32. Implications • Ignoring role of non-cognitive skills as mediating and outcome variables leads to misleading educational policies. • NCLB with its focus on test scores only. • Basing school and teacher evaluations only on value-added in test scores provides only limited picture of school and teacher effects.

  33. Next Steps • Choose most promising non-cognitive constructs and measures. • Test these in structural models of learning outcomes and life outcomes. • Non-cognitive outcomes affect cognitive outcomes and possibly reverse—need to evaluate this. • Start to incorporate these into national and international assessments of learning and impacts of educational systems.

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