1. Brandon Walcutt Hankuk University of Foreign Studies Seoul, Korea ALLIED ACADEMIES CONFERENCE April 2010 WAGE DISCRIMINATION IN KOREA’S ESL INDUSTRY 1

2. Contents Background and Problem Statement The Study ESL Industry of Korea Literature Review Methodology Data Results/Implications Future Research and Limitations 2

3. Background Anecdotally, native speaking foreign teachers in Korea’s English as a Second Language (ESL) industry are subject to a substantial amount of racial, sexual and age-based discrimination. Neoclassical economic theory suggests that “discrimination in economic life usually consists of sorting people according to traits rather than productivity” (Cooter, 1994). As this definition applies to ESL instructors with unexplained differential earnings, wage discrimination occurs when members of different groups possess equal net marginal productivity, but are paid unequal wages. 3

4. The Study This study was conducted with the specific goal of identifying unexplained wage gaps which could indicate wage discrimination against certain groups within Korea’s ESL instructor population.. Economic characteristics, such as education, certificates and years of experience should contribute to productivity and therefore should be associated with an instructor’s wages. Noneconomic characteristics include such data as race, age, nationality and other indicators that should not be associated with the quality or productivity of an instructor. 4

5. The Industry English as a 2 nd Language is a Huge industry in Korea, accounting for 1.9% or roughly $15 billion of Korea’s $797.8 billion 2005 nominal GDP. Instructors can be found teaching at public schools, universities or at private institutes. In 2008, there were at least 18,000 English language instructors employed in Korea. Potentially many more exist within other visa categories. The ESL system is changing as it attempts to improve the quality and depth of education provided. 5

6. Literature Review Wage discrimination exists if individuals with the same economic characteristics receive different wages and the differences are systematically correlated with certain noneconomic (i.e. racial, religious, etc.) characteristics of the individual. The study of work related discrimination takes 2 primary approaches: “Discrimination-Preference Trade” model  G.S. Becker / K. Arrow - encompasses a competitive equilibrium model in which some individuals from one group have a taste or preference for working with individuals of a particular group and are willing to sacrifice some income to satisfy their preference “Imperfect Employer Information” model.  Arrow / Phelps - based on employer perception of differences in the predictors of a worker’s job performance or their expected net marginal value of productivity. 6

7. Methodology and Data Questionnaires were circulated to ESL instructors in Korea. Primary data of interest were:  Personal Demographics: Nationality, race, sex and age  Educational Background: Degree, major, teaching certs, teaching experience  Primary/PT job info: Type, contract hours, average monthly/hourly salary Final Sample Size:  ESL Instructors: 193 7

8. Methodology and Data GLM and linear regression analysis was used on the questionnaire data to create a controlled productivity baseline for the instructors based on common economic and noneconomic characteristics. Tukey HSD was also used for post-hoc testing to address any Type 1 errors resulting from the multiple variance analyses in the GLM model. 8

9. Results An additive model was used to estimate and test the effects of various demographic, education, and experience factors on composite annual earnings. The results are below. 9

10. Results Tukey HSD post-hoc tests demonstrated only Filipino and European- other earnings were significantly different from other nationalities (see table 8). Where other European mean composite earnings were significantly higher in four comparisons, Filipino earnings were lower in all other nationality comparisons. 10

11. Results Linear Regression model: Filipino, Other-European, and all other composite nationalities were binary coded into 3 new variables and loaded with Education level and years of teaching experience were in a linear regression model to ascertain the predictive adjustment to composite annual earnings. 11

12. Results Wage Gaps: The previous regression model shows 4 factors determining wages. Education level and years teaching add to productivity and hence to wages so cannot be considered wage discrimination. Those gaps found in relation to Filipinos and Other Europeans, however, can certainly be considered as possible areas of wage discrimination as their nationality cannot be considered an economic characteristic. No unexplained wage gaps were found in the expected areas of sex, age and race. 12

13. Limitations / Future Research Potential Limitations : General sample size should be increased Sample sizes of Filipinos and Other Europeans, in particular, are not as large as they could be. Future Studies: Expand the Filipino sample size considerably and retest for further validation of depth/scope of wage discrimination Assess the employer activities and perceptions that contribute to nationality-based wage differences as well as the effects of work visa status on wage discrimination 13

14. Thank You 14 For additional information, questions, criticism, etc., please contact me at travelingman2@gmail.com.travelingman2@gmail.com