Our main results are:
1. The impact of participation in training on income is significantly positive. Training comprises any of the following: courses and seminars, participation in trade fairs, lectures, on-the-job training, quality circles, special tasks, and reading of specialist literature. Correcting for the endogeneity bias, the average treatment effect increases from 0.10 to 0.15.
2. The effect of training on earnings differs for heterogeneous agents. High-skilled workers profit more from training than low-skilled workers, job entrants obtain a higher earnings increase after participation in training than workers with a long job tenure, and workers with a temporary contract profit less from training than those with a permanent job contract. If also the workers with no positive wage effects experience a productivity increase induced by training, the employers reap all the gains from training.
3. The increase in the income effects of training if endogeneity is taken into account, compared with the case where selection is assumed to be random, suggests that our instrumental variables reduce the measurement error in the OLS regression and capture heterogeneous training returns more properly. This is plausible because our dummy variable for training inadequately captures training intensity and training effort. The third possibility for this phenomenon, a negative selection into training, seems unlikely given previous empirical evidence that training is seldom remedial.
4. Without controlling for endogeneity, external training (i.e. participation at trade fairs, lectures, courses and seminars, and reading of specialist literature) has a sig-nificant positive impact on wages, while the wage effect of internal training (i.e. on the job training, quality circles, and special tasks) is insignificant. Taking endogene-ity into account and instrumenting the training decision, the coefficient of external training rises from 0.05 to 0.13, internal training stays insignificant. Hence, par-ticipation in internal training does not translate into higher earnings. Here again, only the employer seems to skim productivity increases from investments in human capital (again assuming that employees’ productivity is increased by the training).
Therefore, only external training has a significant and positive impact on earnings and drives the result derived with a dummy for training participation.
5. Our contribution can only present indirect evidence on who gains when workers train. We have been able to answer the question “who gains from training?” in the sense of which type of employees profits from higher wages after participation in training. With our data, we were not able to present evidence for rent sharing after investment in training between employer and employee. Nevertheless, using the indirect information of income increases and assuming that productivity increases after training, we can make inferences about whether also the employer profits from training. Possibly, employers reap all the gains from the internal training measures analyzed in the second part of the paper. This is also suggested by the empirical literature using firm data. In order to obtain clearer evidence, linked employer-employee panel data with detailed information on type, length and cost of training would be required, however.
References
Acemoglu, D., and J.-S. Pischke (1999): “Beyond Becker: Training in Imperfect Labour Markets,”The Economic Journal, 109, 112—142.
Barrett, A., and P. J. O’Connell (2001): “Does Training Generally Work? The Returns to In-Company Training,”Industrial and Labor Relations Review, 54(3), 647—
662.
Bartel, A. P. (1995): “Training, Wage Growth, and Job Performance: Evidence from a Company Database,”Journal of Labor Economics, 13(3), 401—425.
(2000): “Measuring the Employer’s Return on Investments in Training: Evidence from the Literature,”Industrial Relations, 39(3), 502—524.
Becker, G.(1964): Human Capital. Chicago: University of Chicago Press.
Black, S. E., and L. M. Lynch (1996): “Human-Capital Investments and Produc-tivity,” American Economic Review, 86(2), 263—267, Papers and Proceedings of the Hundredth and Eighth Annual Meeting of the American Economic Association San Francisco, CA, January 5-7, 1996.
Blundell, R., L. Dearden, andC. Meghir(1996): The Determinants and Effects of Work-Related Training in Britain. Institute for Fiscal Studies, London.
Blundell, R., L. Dearden, C. Meghir, and B. Sianesi (1999): “Human Capital Investment: The Returns from Education and Training to the Individual, the Firm and the Economy,”Fiscal Studies, 20(1), 1—23.
Booth, A. L., M. Francesconi,andG. Zoega(2003): “Unions, Work-Related Train-ing, and Wages: Evidence for British Men,”IZA Discussion Paper, No. 737.
Booth, A. L., and D. Snower (1996): Acquiring Skills. Market Failures, their Symp-toms and Policy Responses.Cambridge University Press, Cambridge.
Card, D. (1999): “The Causal Effect of Education on Earnings,” in Handbook of Labor Economics, ed. by O. Ashenfelter, and D. Card, vol. 3A, chap. 30, pp. 1801—1863.
Elsevier, Amsterdam et al.
Dearden, L., H. Reed,and J. V. Reenen(2000): “Who Gains When Workers Train?
Training and Corporate Productivity in a Panel of British Industries,”CEPR Discussion Paper, No. 2486.
Fitzenberger, B., andH. Prey(1997): “Assessing the Impact of Training on Employ-ment - The Case of East Germany,”ifo Studien, 43(1), 71—116.
Fitzenberger, B., and S. Speckesser (2000): “Zur Wissenschaftlichen Evaluation der Aktiven Arbeitsmarktpolitik in Deutschland: Ein ¨Uberblick,”Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, 33(3), 357—370.
Franz, W.(2003): Arbeitsmarkt¨okonomik. Springer-Verlag, Berlin, Heidelberg, 5th edn.
Gang, I. N.,andM.-S. Yun(2002): “Decomposing Inequality Change in East Germany During Transition,”IZA Discussion Paper, No. 579.
Georgellis, Y.,andT. Lange(1997): “The Effect of Further Training on Wage Growth in West Germany, 1984-1992,”Scottish Journal of Political Economy, 44(2), 165—181.
Gerlach, K., and U. Jirjahn(1998): “Determinanten betrieblicher Weiterbildungsak-tivit¨aten: Eine empirische Untersuchung mit Daten des Hannoveraner Firmenpan-els,” in Qualifikation, Weiterbildung und Arbeitsmarkterfolg, ed. by F. Pfeiffer, and W. Pohlmeier, no. 31 in ZEW-Wirtschaftsanalysen, pp. 311—338. Nomos Verlagsge-sellschaft.
Goux, D., andE. Maurin(2000): “Returns to Firm Provided Training: Evidence from French Worker-Firm Matched Data,”Labor Economics, 7, 1—19.
Griliches, Z., and J. Hausman (1986): “Errors in Variables in Panel Data,” Journal of Econometrics, 31, 93—118.
Griliches, Z., andJ. Mairesse(1998): “Production Functions: The Search for
Identi-fication,” inEconometrics and Economic Theory in the 20th Century, ed. by S. Stroem,
pp. 169—203. Cambridge University Press, Cambridge.
Harmon, C., H. Oosterbeek, and I. Walker (2003): “The Returns to Education:
Microeconomics,”Journal of Economic Surveys, 17(2), 115—155.
Heckman, J. (1999): “Policies to Foster Human Capital,” NBER Working Paper, No.
7288.
Heckman, J., L. Lochner, and P. Todd (2003): “Fifty Years of Mincer Earnings Regressions,”IZA Discussion Paper, No. 775.
Hempell, T. (2003): “Do Computers Call for Training? Firm-Level Evidence on Com-plementarities Between ICT and Human Capital Investments,”ZEW Discussion Paper, No. 03-20.
Kuwan, H., F. Thebis, D. Gnahs, E. Sandau, and S. Seidel (April 2003):
Berichtssystem Weiterbildung 2000 - Integrierter Gesamtbericht zur Weiterbildungssit-uation in Deutschland. Bundesministerium f¨ur Bildung und Forschung, Bonn.
Lazear, E. P.(1979): “Why Is There Mandatory Retirement?,”The Journal of Political Economy, 87(6), 1261—1284.
(2002): “Firm-Specific Human Capital: A Skill-Weights Approach,” NBER Working Paper, No. 9679.
Leuven, E., and H. Oosterbeek (2002): “A New Approach to Estimate the Wage Returns to Work-Related Training,”IZA Discussion Paper, No. 526.
Loewenstein, M. A., and J. R. Spletzer (1997): “General and Specific Training:
Evidence and Implications,”The Journal of Human Resources, 34(4), 710—733.
Lynch, L. M. (1992): “Private-Sector Training and the Earnings of Young Workers,”
The American Economic Review, 82(1), 299—312.
Lynch, L. M., and S. E. Black (1998): “Beyond the Incidence of Employer-Provided Training,”Industrial and Labor Relations Review, 52(1), 64—81.
Maier, M., F. Pfeiffer, and W. Pohlmeier (2003): “Overeducation and Individual Heterogeneity,” Diskussionspapier der DFG-Forschergruppe ”Heterogene Arbeit”, No.
03/01.
Mincer, J. (1974): Schooling, Experience, and Earnings. National Bureau of Economic Research, New York.
(1991): “Job Training: Costs, Returns, and Wage Profiles,” in New Ecomomic Analysis and Evidence on Training of Adult Employee, pp. 15—39. David Stern.
Muysken, J., and T. Zwick (2003): “Credentialism by Members of Licensed Pro-fessions,” in Overeducation in Europe: Current Issues in Theory and Policy, ed. by F. B¨uchel, A. de Grip, andA. Mertens. Edward Elgar, Cheltenham, forthcoming.
Pannenberg, M. (1997): “Financing On-The-Job Training: Shared Investment or Pro-motion Based System? Evidence from Germany,”Zeitschrift f¨ur Wirtschafts- u. Sozial-wissenschaften, 117, 525—543.
(1998): “Weiterbildung, Betriebszugeh¨origkeit und L¨ohne: ¨Okonomische Ef-fekte des ”Timings” von Investitionen in die Berufliche Weiterbildung,” inQualifikation, Weiterbildung und Arbeitsmarkterfolg, ed. by F. Pfeiffer, and W. Pohlmeier, no. 31 in ZEW-Wirtschaftsanalysen, pp. 257—279. Nomos, Berlin.
Pfeiffer, F., andJ. Brade(1995): “Weiterbildung, Arbeitszeit und Lohneinkommen,”
inMikro¨okonomik Des Arbeitsmarktes, ed. by V. Steiner, and L. Bellmann, no. 95-14, pp. 289—326. IAB, N¨urnberg.
Pfeiffer, F., and F. Reize(2001): “Formelle und Informelle Berufliche Weiterbildung und Verdienst bei Arbeitnehmern und Selbstst¨andigen,” inBildung und Besch¨aftigung, ed. by R. K. Weizs¨acker, no. 284 in Schriften des Vereins f¨ur Socialpolitik, pp. 215—274.
Duncker und Humboldt, Berlin.
Pischke, J.-S. (2001): “Continuous Training in Germany,” Journal of Population Eco-nomics, 14, 523—548.
Riphahn, R. T. (2001): Employment Policy in Transition: The Lessons of German Integration for the Labor Market. Springer, Heidelberg.
Shields, M.(1998): “Changes in the Determinants of Employer-Funded Training for Full-Time Employees in Britain, 1984-1994,” Oxford Bulletin of Economics and Statistics, 60, 189—214.
Wooldridge, J. M. (2002): Econometric Analysis of Cross Section and Panel Data.
MIT Press, Cambridge, Mass.
Zwick, T. (2002): “Continuous Training and Firm Productivity in Germany,” ZEW Discussion Paper, No. 02-50.
(2004): “Training - A Strategic Enterprises Decision?,” inModern Concepts of the Theory of the Firm - Managing Enterprises of the New Economy, ed. by G. Fandel, U. Backes-Gellner, M. Schl¨uter,and J. Stufenbiel, pp. 355—366. Springer, Heidelberg.
7 Appendix
Table A1 List of Variables Used
Variable Share / Average Notes
Less than 600 DM 0.07%
Between 600 and 1000 DM 0.16%
Between 1000 and 1500 DM 0.56%
Between 1500 and 2000 DM 1.25%
Between 2000 and 2500 DM 4.31%
Between 2500 and 3000 DM 7.69%
Between 3000 and 3500 DM 11.87%
Between 3500 and 4000 DM 14.87%
Between 4000 and 4500 DM 14.48%
Between 4500 and 5000 DM 12.28%
Between 5000 and 5500 DM 7.59%
Between 5500 and 6000 DM 6.93%
Between 6000 and 7000 DM 7.58%
Between 7000 and 8000 DM 4.10%
Between 8000 and 9000 DM 2.52%
Between 9000 and 10000 DM 1.37%
Between 10000 and 15000 DM 1.73%
15000 DM and more 0.64%
Without School Leaving
Full-Time Vocational School 2.22% Several years of professional training in school Dual Apprenticeship 60.17% Several years of professional training in school and
on the job
Master Craftman 11.34%
University of Applied Sciences 5.79%
University 7.85%
Courses and Seminars 26.72%
Trade Fair 18.09% Participation in trade fairs
Lecture 25.9% Participation in lectures
On-The-Job 16.70% Initial training on the job
Quality Circle 14.07% Participation in quality circles
Special Tasks 12.86% Tasks aiming at extending skills
Specialist Literature 26.11% Study of work-related literature Professional Experience 22.69 years Years from first job until today
Company Tenure 13.86 years Years from starting to work for a company until today
Unemployment 27.43% Dummy = 1 if a person was ever unemployed,
otherwise 0
Table A1 continued
Variable Share / Average Notes
Unskilled Blue-Collar Worker 15.63% Worker without professional degree
Skilled Blue-Collar Worker 27.18% Worker with degree from dual apprenticeship system or full-time vocational school
Assistant Foreman 3.60%
Master/Foreman 3.25%
Unskilled White-Collar Worker 2.22% White-Collar worker with basic tasks White-Collar Worker with Simple
Tasks
Civil Servant in Clerical Grade 4.55%
Civil Servant in Higher Service 3.93%
Civil Servant in Senior Service 2.07%
Computer Work Station 48.21% Work routine includes using the computer
Temporary Work 4.87%
Good Economic Situation 59.04% Dummy = 1 if the company is in a good economic situation, otherwise 0
Overtime 78.34% Dummy = 1 if a person works overtime, otherwise 0
Profit-Sharing 7.94%
Incentive Wage 21.62%
Job Content 13 Categories: training, testing, counseling,
supervising, repairing, procurement, organisiation, marketing, research, negotiating, developing, manufacturing, monitoring
Children 49.98% Dummy = 1 if a person has at least one child,
otherwise 0
Foreigner 5.43% Dummy = 1 if a person does not have a German
Nationality, otherwise 0
Demand for Specific Training 12 Categories: need for training in presentation techniques, foreign languages, logistics,
Management, Controlling, Mathematics, German, System Engineering, Computer Engineering, Other Engineering, Safety at Work, Medicine
Changes in the Workplace 2 Categories: Downsizing, Restructuring
Size of Firm 7 Categories: number of employees is 1-4, 5-9,
10-49, 50-99, 100-499, 500-999 and 1000 and above Residence Community 3 Categories: communities with 50 000 and above
inhabitants, hinterland of large cities and other communities with less than 50 000 inhabitants
Federal State 11 Categories: all Federal States of West Germany
Economic Sector 46 Categories
Table A2 Comparison: Interval Regression (INTREG) vs. Ordinary Least Squares (OLS) - Estimates of the Extended Earnings Equation
INTREG OLS INTREG OLS
Professional
Experience 0.01 (11.56) *** 0.01 (11.02) ***
Trade Fair 0.08 (9.95) *** 0.09 (9.86) *** Professional
Experience Squared -0.00 (-7.76) *** -0.00 (-7.35) ***
Lecture 0.06 (7.13) *** 0.06 (6.99) *** Company Tenure 0.00 (10.43) *** 0.00 (9.88) ***
On-The-Job -0.03 (-3.95) *** -0.03 (-3.83) *** Unemployment -0.03 (-4.35) *** -0.03 (-4.17) ***
Quality Circle 0.03 (3.32) *** 0.26 (3.15) ***
Special Tasks 0.02 (2.18) ** 0.02 (2.14) **
Specialist Literature 0.06 (8.12) *** 0.06 (7.89) *** Computer Work
Station 0.09 (12.41) *** 0.09 (11.97) ***
Temporary Work -0.07 (-4.42) *** -0.07 (-4.13) ***
Without School
Leaving Certificate -0.03 (-1.45) -0.03 (-1.43) Good Economic
Situation 0.05 (6.47) *** 0.05 (6.21) ***
Lower Secondary
School -0.05 (-6.13) *** -0.05 (-6.11) *** Overtime 0.06 (8.09) *** 0.06 (8.00) ***
Intermediate
Secondary School Reference Reference Profit-Sharing 0.10 (7.92) *** 0.10 (7.76) ***
Entrance Examination for University for Applied Sciences
0.09 (6.64) *** 0.14 (5.57) *** Incentive Wage 0.03 (3.71) *** 0.03 (3.62) ***
High School Diploma 0.11 (8.48) *** 0.11 (8.35) ***
Without Professional
Degree -0.08 (-3.61) *** -0.03 (-1.43) Children 0.07 (10.81) *** 0.07 (10.58) ***
Full-Time Vocational
School Reference Reference
Apprenticeship -0.00 (-0.03) -0.00 (-0.20) Number of
Observations 10003 10003
Master Craftman 0.08 (3.75) *** 0.08 (3.52) *** Chi-squared Stat. 8513.97 University for Applied
Sciences 0.14 (5.83) *** 0.14 (5.57) *** R-squared 0.4691
University 0.27 (10.31) *** 0.27 (10.01) ***
Individual Characteristics
Following control variables have been added: size of firm (6), federal state (10), residence community (2), economic sector (46), demand for specific training (5), job contents (13) and a constant.
*** (**, *) signals a level of significance of 1% (5%, 10%) (t-values and z-values in parentheses are based on heteroscedasticity robust standard errors)
Source: BIBB-IAB 1998/99, own calculations.
School Attainment
Table A3 Correlations* between Types of Training and Income
Trade Fair Lecture Specialist
Literature On The Job Quality Circle
Specialist Literature 0.41 0.49 1.00
On-The-Job 0.06 0.11 0.11 1.00
Quality Circle 0.13 0.20 0.21 0.16 1.00
Special Tasks 0.16 0.24 0.24 0.19 0.17 1.00
Courses and Seminars 0.26 0.50 0.36 0.12 0.28 0.24 1.00
Income 0.31 0.38 0.38 0.03 0.19 0.19 0.31 1.00
* correlations are all significant at 5 percent level Source: BIBB-IAB 1998/99, own calculations.
Table A4 Standard Earnings Equation & Extended Earnings Equation including Different Types of Training
log (Earnings)
Professional Experience 0.02 (17.50) *** 0.02 (15.56) ***
Professional Experience Squared -0.00 (-11.52) *** -0.00 (-9.95) ***
Without School Leaving Certificate -0.07 (-2.77) *** -0.05 (-1.80) * Lower Secondary School -0.10 (-10.84) *** -0.06 (-6.89) ***
Intermediate Secondary School Entrance Examination for University for Applied Sciences
0.15 (8.05) *** 0.11 (6.36) ***
High School Diploma 0.17 (9.87) *** 0.14 (8.70) ***
Without Professional Degree -0.15 (-5.46) *** -0.12 (-4.53) ***
Full-Time Vocational School
Apprenticeship -0.00 (-0.15) -0.01 (-0.56)
Master Craftman 0.17 (6.12) *** 0.10 (3.64) ***
University for Applied Sciences 0.22 (6.99) *** 0.14 (4.71) ***
University 0.33 (10.25) *** 0.25 (7.96) ***
Courses and Seminars 0.05 (5.80) ***
Trade Fair 0.10 (9.65) ***
Lecture 0.09 (8.62) ***
On-The-Job -0.01 (-0.92)
Quality Circle 0.07 (6.78) ***
Special Tasks 0.04 (4.20) ***
Specialist Literature 0.08 (8.04) ***
Number of Observations
***, (**,*) signals a level of significance of 1% (5%, 10%) (t-values in parentheses are based on heteroscedasticity robust standard errors)
Source: BIBB-IAB 1998/99, own calculations.
Table A5 Extended Earnings Equation with Control Variables - Different Types of Training included
Unskilled Blue-Collar Worker Reference Courses and Seminars 0.00 (0.37) Skilled Blue-Collar Worker 0.07 (4.92) ***
Trade Fair 0.05 (4.86) *** Assistant Foreman 0.08 (4.15) ***
Lecture 0.04 (4.26) *** Master/Foreman 0.16 (6.61) ***
On-The-Job -0.01 (-1.54) Unskilled White-Collar Worker 0.06 (2.98) ***
Quality Circle 0.02 (2.06) ** White-Collar Worker with
Simple Tasks 0.03 (1.56)
Special Tasks 0.01 (0.76) White-Collar Worker with
Difficult Tasks 0.1 (6.29) ***
Specialist Literature 0.04 (4.80) *** High-Skilled White-Collar
Worker 0.21 (12.14) ***
Executive White-Collar Worker 0.3 (12.22) ***
Without School Leaving Certificate -0.01 (-0.45) Civil Servant in Clerical Grade 0.06 (2.52) **
Lower Secondary School -0.02 (-2.37) ** Civil Servant in Higher Service 0.14 (5.43) ***
Intermediate Secondary School Reference Civil Servant in Senior Service 0.3 (10.29) ***
Entrance Examination for
University for Applied Sciences 0.05 (3.47) ***
High School Diploma 0.07 (4.81) ***
Computer Work Station 0.04 (4.41) ***
Without Professional Degree -0.06 (-2.30) ** Temporary Work -0.07 (-3.4) ***
Full-Time Vocational School Reference Good Economic Situation 0.04 (5.21) ***
Apprenticeship -0.01 (-0.43) Overtime 0.04 (5.49) ***
Master Craftman 0.03 (1.08) Profit-Sharing 0.07 (5.11) ***
University for Applied Sciences 0.09 (3.21) *** Incentive Wage 0.03 (3.54) ***
University 0.19 (6.36) ***
Children 0.07 (9.58) ***
Professional Experience 0.01 (8.92) *** Foreigner -0.04 (-2.33) **
Professional Experience Squared -0.00 (-6.49) ***
Company Tenure 0.01 (5.16) *** Number of Observations 8325
Company Tenure Squared -0.00 (-2.08) ** F(122, 8202) 71.57
Unemployment -0.03 (-3.75) *** R-squared 0.5021
Professional Status
***, (**,*) signals a level of significance of 1% (5%, 10%) (t-values in parentheses are based on heteroscedasticity robust standard errors).
Source: BIBB-IAB 1998/99, own calculations.
Education and Continuous Training Training
Following control variables have been added: size of firm (6), federal state (10), residence community (2), economic sector (46), demand for specific training (5), job contents (13) and a constant.
Workplace Characteristics
Individual Characteristics School Attainment
Vocational Training
Professional Career
Table A6 Extended Earnings Equation with Control Variables - Training
Table A7 Extended Earnings Equation with Interaction Variables - Training included as a Dummy and in Interaction Variables
Training 0.06 (6.54) *** Children 0.06 (6.03) ***
Foreigner -0.05 (-2.77) ***
Without School Leaving
Certificate 0.01 (0.24)
Lower Secondary School -0.00 (-0.04)
Intermediate Secondary School Reference Professional Experience 0.01 (1.90) * Entrance Examination for
University for Applied Sciences 0.03 (0.77) Professional Experience Squared -0.00 (-0.50) College Entrance Exam 0.08 (2.75) *** Company Tenure -0.01 (-2.48) **
Company Tenure Squared 0.00 (1.35) Without Professional Degree -0.07 (-1.78) * Computer Work Station 0.03 (1.45) Full-Time Vocational School Reference Temporary Work -0.05 (-1.36) Apprenticeship -0.02 (-0.44) Good Economic Situation 0.02 (1.07)
Master Craftman 0.02 (0.46) Overtime -0.01 (-0.74)
University for Applied Sciences 0.09 (1.49) Profit-Sharing 0.02 (0.81)
University 0.15 (2.68) *** Incentive Wage -0.04 (-2.75) ***
Without School Leaving
Certificate -0.04 (-0.85)
Professional Experience 0.01 (4.85) *** Lower Secondary School -0.05 (-3.01) ***
Professional Experience Squared -0.00 (-4.16) *** Entrance Examination for
University for Applied Sciences 0.04 (1.04)
Company Tenure 0.01 (5.23) *** High School Diploma 0.00 (0.16)
Company Tenure Squared -0.00 (-2.26) **
Unemployment -0.02 (-1.80) * Skilled Blue-Collar Worker -0.02 (-0.68) Assistant Foreman -0.00 (-0.07)
Master/Foreman 0.43 (0.79)
Unskilled Blue-Collar Worker Reference Unskilled White-Collar Worker -0.04 (-0.98) Skilled Blue-Collar Worker 0.07 (4.36) *** White-Collar Worker with Simple
Tasks -0.03 (-0.86)
Assistant Foreman 0.07 (2.58) *** White-Collar Worker with Difficult
Tasks -0.07 (-2.06) **
Master/Foreman 0.13 (2.76) *** High-Skilled White-Collar Worker 0.02 (0.70) Unskilled White-Collar Worker 0.09 (3.29) *** Executive White-Collar Worker 0.02 (0.28) White-Collar Worker with Simple
Tasks 0.05 (2.02) ** Civil Servant in Clerical Grade -0.15 (-3.51) ***
White-Collar Worker with Difficult
Tasks 0.16 (6.50) *** Civil Servant in Higher Service -0.14 (-1.95) * High-Skilled White-Collar Worker 0.20 (7.60) *** Civil Servant in Senior Service -0.27 (-3.72) ***
Executive White-Collar Worker 0.30 (6.43) ***
Civil Servant in Clerical Grade 0.16 (4.68) *** Number of Observations 10003 Civil Servant in Higher Service 0.23 (3.55) *** F(220, 9781)
Civil Servant in Senior Service 0.55 (8.26) *** R-squared 0.5169
Computer Work Station 0.03 (1.82) *
Temporary Work -0.04 (-1.59)
Good Economic Situation 0.03 (2.34) **
Overtime 0.05 (4.25) ***
Profit-Sharing 0.06 (2.41) **
Incentive Wage 0.05 (3.95) ***
Following control variables have been added: size of firm (6), federal state (10), residence community (2), economic sector (46), demand for specific training (5), job contents (13) and a constant.
School Attainment
Professional Status Individual Characteristics
Interaction Variables
Professional Status
Workplace Characteristics ***, (**,*) signals a level of significance of 1% (5%, 10%) (t-values in parentheses are based on heteroscedasticity robust standard errors) Source: BIBB-IAB 1998/99, own calculations.
Education and Continuous Training School Attainment
Vocational Training
Professional Career
Table A8 Extended Earnings Equation with Internal and External Training
External Training 0.05 (6.93) *** Unskilled Blue-Collar Worker Reference Internal Training -0.01 (-1.75) * Skilled Blue-Collar Worker 0.04 (1.91) *
Assistant Foreman 0.04 (1.60)
Without School Leaving
Certificate -0.01 (-0.28) Master/Foreman 0.13 (4.43) ***
Lower Secondary School -0.03 (-2.97) *** Unskilled White-Collar Worker 0.06 (1.96) **
Intermediate Secondary
School Reference White-Collar Worker with
Simple Tasks 0.00 (0.12)
Entrance Examination for University for Applied Sciences
0.04 (2.21) ** White-Collar Worker with
Difficult Tasks 0.09 (4.03) ***
High School Diploma 0.07 (4.25) *** High-Skilled White-Collar
Worker 0.17 (7.45) ***
Executive White-Collar Worker 0.23 (7.39) ***
Without Professional Degree -0.07 (-2.11) ** Civil Servant in Clerical Grade 0.04 (1.52) Full-Time Vocational School Reference Civil Servant in Higher Service 0.12 (3.53) ***
Apprenticeship -0.02 (-0.88) Civil Servant in Senior Service 0.32 (7.81) ***
Master Craftman 0.02 (0.62)
University for Applied
Sciences 0.07 (2.02) ** Workplace Characteristics
University 0.15 (4.27) *** Computer Work Station 0.04 (4.53) ***
Temporary Work -0.08 (-3.59) ***
Good Economic Situation 0.04 (5.02) ***
Professional Experience 0.01 (9.39) *** Overtime 0.04 (4.79) ***
Professional Experience
Squared -0.00 (-6.70) *** Profit-Sharing 0.06 (4.33) ***
Company Tenure 0.01 (5.08) *** Incentive Wage 0.03 (3.37) ***
Company Tenure Squared -0.00 (-2.18) **
Unemployment -0.03 (-3.33) *** Number of Observations 8325
F(335, 7988)
R-squared 0.5245
Children 0.07 (9.43) ***
Foreigner -0.02 (-0.65)
Professional Status
Professional Career
Individual Characteristics Education and Continuous Training
School Attainment
Vocational Training
Table A8 continued
Professional Experience 0.00 (0.53) Professional Experience 0.00 (1.98) **
Professional Experience
Squared -0.00 (-0.87) Professional Experience
Squared -0.00 (-0.25)
Company Tenure 0.00 (1.68) * Company Tenure -0.01 (-4.42) ***
Computer Work Station 0.00 (0.27) Computer Work Station 0.01 (1.28)
Temporary Work -0.00 (-0.14) Temporary Work -0.04 (-1.40)
Good Economic Situation -0.01 (-1.22) Good Economic Situation 0.02 (2.10) **
Overtime -0.00 (-0.12) Overtime -0.01 (-1.25)
Profit-Sharing -0.00 (-0.38) Profit-Sharing 0.01 (0.84)
Incentive Wage 0.00 (0.02) Incentive Wage -0.02 (-2.44) **
Without School Leaving
Certificate -0.01 (-0.28) Without School Leaving
Certificate -0.01 (-0.43)
Lower Secondary School -0.03 (-2.99) *** Lower Secondary School -0.02 (-1.73) * Entrance Examination for High School Diploma -0.03 (-2.04) ** High School Diploma 0.02 (1.42) Skilled Blue-Collar Worker -0.03 (-1.87) * Skilled Blue-Collar Worker -0.01 (-0.54) Assistant Foreman -0.00 (-0.14) Assistant Foreman -0.04 (-1.38)
Master/Foreman -0.02 (-0.89) Master/Foreman 0.00 (0.06)
Unskilled White-Collar Worker 0.00 (0.12) Unskilled White-Collar Worker -0.03 (-0.78) White-Collar Worker with
Simple Tasks -0.01 (-0.66) White-Collar Worker with
Simple Tasks -0.04 (-1.22)
White-Collar Worker with
Difficult Tasks -0.03 (-1.62) White-Collar Worker with
Difficult Tasks -0.05 (-1.9) *
High-Skilled White-Collar
Worker -0.02 (-1.32) High-Skilled White-Collar
Worker -0.02 (-0.61)
Executive White-Collar
Worker -0.07 (-2.69) *** Executive White-Collar Worker -0.00 (-0.06) Civil Servant in Clerical Grade -0.03 (-1.40) Civil Servant in Clerical Grade -0.10 (-3.27) ***
Civil Servant in Higher
Service -0.02 (-0.83) Civil Servant in Higher Service -0.06 (-1.97) **
Civil Servant in Senior
Service -0.05 (-1.51) Civil Servant in Senior Service -0.09 (-2.48) **
School Attainment
Interaction Variables - External Training
Professional Status Professional Status
School Attainment Interaction Variables - Internal Training
Following control variables have been added: size of firm (6), federal state (10), residence community (2), economic sector (46), demand for specific training (5) and a constant.
***, (**,*) signals a level of significance of 1% (5%, 10%) (t-values in parentheses are based on heteroscedasticity robust standard errors)
Source: BIBB-IAB 1998/99, own calculations.
Table A9 Selection into Internal Training
Restructuring 0.24 (7.32) *** Unskilled Blue-Collar Worker Reference Skilled Blue-Collar Worker 0.06 (2.03) **
Mathematics -0.12 (-2.21) ** Assistant Foreman 0.34 (5.29) ***
German 0.08 (1.23) Master/Foreman 0.05 (0.84)
System Engineering 0.13 (1.85) * Unskilled White-Collar Worker -0.10 (-1.94) * Computer Engineering 0.06 (1.32) White-Collar Worker with Simple
Tasks -0.05 (-1.03)
Other Engineering 0.26 (6.04) *** White-Collar Worker with Difficult
Tasks 0.11 (2.58) ***
Safety at Work 0.11 (2.77) *** High-Skilled White-Collar Worker 0.07 (1.68) * Medicine 0.13 (1.66) * Executive White-Collar Worker -0.10 (-1.76) *
Civil Servant in Clerical Grade 0.22 (3.25) ***
Civil Servant in Higher Service 0.15 (2.05) **
School Attainment Civil Servant in Senior Service -0.02 (-0.19) Without School Leaving
Certificate 0.03 (0.44)
Lower Secondary School 0.00 (0.13)
Intermediate Secondary School Reference Computer Work Station 0.20 (7.55) ***
Entrance Examination for
University for Applied Sciences -0.03 (-0.63) Temporary Work -0.11 (-2.75) ***
High School Diploma -0.02 (-0.55) Overtime 0.09 (4.31) ***
Incentive Wage 0.17 (6.45) ***
Without Professional Degree -0.03 (-0.47) Full-Time Vocational School Reference
Apprenticeship -0.02 (-0.33) Foreigner -0.04 (-1.16)
Master Craftman -0.06 (-0.85)
University for Applied Sciences -0.08 (-0.94) Number of Observations 9723
University -0.15 (-1.77) * F(102, 9620) 17.92
R-squared 0.1714
Professional Experience 0.00 (0.64) Professional Experience Squared -0.00 (-2.51) **
Company Tenure 0.01 (-1.55)
Company Tenure Squared -0.00 (-1.59)
Unemployment -0.00 (-0.20)
Professional Career
Following control variables have been added: size of firm (6), federal state (10), residence community (2), economic sector (46), demand for specific training (5) and a constant.
***, (**,*) signals a level of significance of 1% (5%, 10%) (t-values in parentheses are based on heteroscedasticity robust standard errors) Source: BIBB-IAB 1998/99, own calculations
Professional Status
Table A10 Selection into External Training
Restructuring 0.07 (2.51) ** Unskilled Blue-Collar Worker Reference Skilled Blue-Collar Worker 0.07 (3.65) ***
Mathematics -0.13 (-2.77) *** Assistant Foreman 0.17 (3.69) ***
German -0.13 (-2.66) *** Master/Foreman 0.35 (6.04) ***
System Engineering 0.21 (3.62) *** Unskilled White-Collar Worker 0.05 (1.31) Computer Engineering 0.17 (4.44) *** White-Collar Worker with Simple
Tasks 0.04 (1.18)
Other Engineering 0.19 (5.88) *** White-Collar Worker with Difficult
Tasks 0.26 (8.02) ***
Safety at Work 0.15 (4.63) *** High-Skilled White-Collar Worker 0.66 (18.96) ***
Medicine 0.10 (1.45) Executive White-Collar Worker 0.72 (14.03) ***
Civil Servant in Clerical Grade 0.23 (4.52) ***
Civil Servant in Higher Service 0.54 (8.35) ***
Civil Servant in Senior Service 0.78 (9.78) ***
Without School Leaving -0.05 (-1.10) Lower Secondary School -0.05 (-2.55) **
Intermediate Secondary School Reference Computer Work Station 0.19 (8.87) ***
Entrance Examination for
University for Applied Sciences 0.16 (4.08) *** Temporary Work -0.12 (-4.15) ***
High School Diploma 0.06 (1.57) Overtime 0.11 (6.25) ***
Incentive Wage 0.03 (1.48)
Without Professional Degree -0.02 (-0.42) Full-Time Vocational School Reference
Apprenticeship 0.05 (0.91) Foreigner -0.11 (-4.73) ***
Master Craftman 0.29 (4.96) ***
University for Applied Sciences 0.31 (4.60) *** Number of Observations 9723
University 0.38 (5.24) *** F(112, 9610) 73.09
R-squared 0.4322
Professional Experience 0.01 (2.64) ***
Professional Experience Squared -0.00 (-3.40) ***
Company Tenure 0.02 (6.69) ***
Company Tenure Squared -0.00 (-4.70) ***
Unemployment -0.05 (-3.01) ***
Following control variables have been added: size of firm (6), federal state (10), residence community (2), economic sector (46), demand for specific training (5), job contents (13) and a constant.
***, (**,*) signals a level of significance of 1% (5%, 10%) (t-values in parentheses are based on heteroscedasticity robust standard errors)
Table A11 Translation of Selected Variables
without professional degree Ohne Ausbildung full-time vocational school Berufsfachschule
apprenticeship Lehre
master craftsman Meister
university for applied sciences Fachhochschule
university Universität
unskilled blue-collar worker Angelernter Arbeiter skilled blue-collar worker Facharbeiter
assistant foreman Vorarbeiter
master/foreman Meister
unskilled white-collar worker Ausführender Angestellter white-collar worker with simple
tasks
Angestellter mit einfacher Tätigkeit white-collar worker with difficult
tasks
Angestellter, der schwierige Aufgaben nach allgemeiner
Angestellter, der schwierige Aufgaben nach allgemeiner