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Effectiveness of Higher Education to Labor ProductivityJung, Dae Bum (Jinju Health College). Introduction Key words of current world trends Globalization Knowledge-based economy Communicopia post-information Ubiquitous-computing (mobile based network) Harbison & Myerss study Education - Economic development Human resource as the core factor for the economic development Limitation Use the cross-section data (1950s 1960s) Research methods : Correlation, Coefficient Direction of this study Long-term higher education rate Labor productivity Research method Variable control Regression formulation

Compared and contrasted various regression ModelExplain labor productivity Explain the contribution of higher education toLabor productivityFind Unobservable individual effect to labor productivity. Theoretical Background (Precedent Research)ResearcherAnalysis YearAnalysis TargetIndex for Educational Development Index for Economic DevelopmentAnalysis MethodHarbison & Myers195975 countries% of enrollment in SchoolsGNP / capitaEstimation of cross-sectional correlation coefficient% of public education feeBannett1955-195669 countries% of academic educationin secondary schoolGNP / capitaEstimation of cross-sectional correlation coefficient% of vocational educationin secondary schoolCurle195857 countries% of enrollment in secondary schoolRate of savingsEstimation of cross-sectional correlation coefficientGNP / capita% of investment in educationRate of economic growth% of enrollment in elementary schoolInfant mortality rateBowman1950-195583 countries% of literacyGNP / capitaEstimation of cross-sectional correlation coefficient. Research Methods Analysis Data Data from Korea Information Service-Financial Accounting Systems(KIS-FAS) Financial Information of Companies (1990-2009) Listed on Korea Stock Exchange

Population of Higher EducationEconomically Active populationLabor ProductivityItemVariablesDetails of VariablesDependent VariablesThe sales / person(lnSPP)the value after taking a natural logarithm to the total sales/the number of employees (1 million won)Explanatory VariablesQuality of human capital(LnEDU) the value after taking a natural logarithm to population with collegedegree available for economical activities (1 thousand people) Capital intensity / person(lnFCP)the value after taking a natural logarithm to {(intangible fixed asset-construction temporary account/the number of employees)} (1 million won) Training cost / person(lnEEP)the value after taking a natural logarithm to (the total cost for trainingthe number of employees) (1 thousand won)Employees(lnNOE)the value after taking a natural logarithm to the number of employees Proportion of incentives(INC)Proportion of the incentives per quarter (%) Research Variables

YearAverageStandard Deviation Minimum Maximum19904.4960.6742.7067.71919914.6340.7042.7107.88619924.7500.7012.8318.05719934.8490.7062.5928.08419945.0100.6792.9758.35219955.1460.6883.1388.61919965.2780.6913.4068.97219975.4370.7143.5089.52319985.5780.7733.4949.79419995.6900.7463.6669.74720005.7760.7433.8918.82720015.8330.7334.0388.87220025.9300.7604.1638.76520035.9570.7444.1998.58720046.0680.7614.4018.80920056.1210.7524.3948.78420066.1890.7784.4168.73220076.2540.7784.1668.761The average of the sales per person (N=216)VariablesAverage (Standard Deviation)199019911992199319941995199619971998199920002001200220032004200520062007LnEDU8.0748.1838.3108.4088.4568.5228.5848.6168.7638.8068.8588.9138.9699.0969.1459.1959.2439.293LnEEP3.787(1.357)4.024(1.376)4.135(1.401)4.1770(1.564)4.374(1.524)4.584(1.476)4.677(1.427)4.626(1.396)3.900(1.736) 4.092(1.575) 4.357(1.537)4.367(1.760)4.692(1.504)4.724(1.638) 4.880(1.449) 5.018(1.483) 5.166(1.513)5.190(1.542)LnFCP11.510(0.754)11.694(0.753)11.830(0.740)11.939(0.755)12.095(0.708)12.232(0.698)12.373(0.710)12.588(0.735)12.809(0.772)12.902(0.758)12.908(0.760)12.929(0.732)12.958(0.750)12.999(0.742)13.066(0.746)13.145(0.712) 13.230(0.744)13.310(0.741)LnNOE6.866(1.156)6.877(1.145) 6.852(1.144)6.827(1.150) 6.806(1.145)6.820(1.152) 6.811(1.158)6.759(1.156) 6.595(1.188)6.564(1.185)6.578(1.193) 6.551(1.175)6.505(1.154) 6.477(1.160) 6.450(1.187)6.421(1.217) 6.396(1.231)6.378(1.258)INC9.383(4.664)8.560(4.812) 7.602(4.976) 7.218(5.228) 7.780(5.557)7.903(5.848)7.664(5.991)5.652(6.922)5.958(8.035) 7.948(9.202)8.076(9.23) 8.135(9.197)9.882(10.500)10.851(13.464)12.124(16.765)13.285(23.274)12.573(17.189)14.277(25.122)N216216216216216216216216216216216216216216216216216216Explanatory variables technical statistics Research Model Basic statistics model

* = firm , * = year*L= the number of labor, *Q=gross sales *EDU= the level of education

* = firm , * = year Research Model*= the value after taking a natural logarithm to the sales per person*= the value after taking a natural logarithm to the percentage of people who completed middle school and high school out of all the people involved in economical activity*= the value after taking a natural logarithm to capital intensity per person*= the value after taking a natural logarithm to capital intensity per person*

Analysis of correlation [Labor productivity HER(Higher Education Ratio)]. Study Resultsthe sales per person (1990-2007)people with higher education among economically active population(1990-2007)Spearman's correlation coefficient0.96**N373Notes. * : p < 0.05, ** : p< 0.01 Change of labor productivity to HERYEAReconomically active populationwith more than college education(EDD)the sales per person(SPP)the average sales of company(SPPP)19903,211242,687484,30919913,583263,915531,40419924,068279,507559,92019934,487290,365586,85019944,704317,486644,10919955,025352,854736,86819965,350394,950815,06719975,520474,145880,50419986,399539,473821,89719996,679572,381909,22220007,031552,0991,016,294 20017,431556,4071,032,93520027,863606,3821,075,45920038,927582,1171,050,31020049,371642,5221,153,54220059,848657,2411,178,319200610,337698,7611,204,078200710,867730,7761,267,300unit: EDU=1,000 people, SPP=10,000 won, SPPP=1,000,000 won

Figure 1. The change of the rate of people with higher education among economically active population and the average sales of companies by yearNotes: SPPP= the average sales EDU= college graduates rate among economically active population

Figure 2. The change of the rate of people with higher education among economically active population and the sales per person by yearNotes:SPP= the sales per personEDU= college graduates rate among economically active population Analysis result of the panel dataFEPOLSRELnEDU0.710(33.56)**0.286(12.51)**0.672(20.86)**LnEEP0.051(11.83)**0.043(9.37)**0.055(12.44)**LnFCP0.486(36.00)**0.781(85.30)**0.515(38.79)**LnNOE-0.008(-0.53)-0.036(-5.91)-0.042(-3.79)**INC0.001(3.90)**0.002(5.13)**0.001(4.01)**Adj-R20.7560.7960.587N3888 (216 companies)38883888 (216 companies)Notes : 1. * : p < 0.05, ** : p< 0.012. The value in parenthesis is t.3. variables: LnEDU = the value taken natural logarithm into the number of economically active population with more than college educationLnEEP = the value taken natural logarithm into the education fee per personLnFCP = the value taken natural logarithm into capital intensity per personLnNOE = the value taken natural logarithm into the number of workersINC = incentive index Analysis result of the panel data (per size of companies)FEPOLSRELnEDU0.429(18.44)**0.665(23.93)**0.440(19.26)**LnEEP0.044(9.76)**0.030(5.08)**0.043(9.63)**LnFCP0.297(33.11)**0.538(53.88)**0.309(34.86)**INC0.002(5.08)**0.002(4.10)**0.002(5.03)**SSIZE-0.433(-12.40)**-1.616(-43.71)**-0.514(-14.95)**MSIZE-0.301(-11.02)**-1.166(-37.85)**-0.360(-13.34)**MLSIZE-0.184(-8.79)**-0.804(-29.37)**-0.221(-10.57)**Adj-R20.5730.6650.586N3888 (216 companies)38883888 (216 companies)Notes : 1. * : p < 0.05, ** : p< 0.012. The value in parenthesis is t.3. variables: SSIZE= number of workers