| Summary: | 碩士 === 國立臺灣大學 === 農業經濟學研究所 === 107 === Supplementary tutoring has been the mainstream value of Taiwanese society. Even if the government had implemented a series of educational reforms in recent years, it has not reduced the trend of tutoring. All kinds of tutoring classes have been developed in a chain, and the subjects have been expanded to the writing of interview materials, the training of various language speaking skills and the training of special skills. Most of the researches on private tutoring expenditures in the past literature focused on the impact of individual or family characteristics. There is no research that combines the competition of supplementary tutoring industry, household tutoring expenditures and analyzes them by empirical methods. This study will use the Short-term Supplementary Tutoring Information Management System data to calculate the HHI index of the supplementary tutoring industry as the industrial concentration index, and combine The Survey of Family Income and Expenditure of Taiwan in 2015 to select household tutoring expenditure and household background information.
In the calculation of HHI, according to the different enrollment targets this study defines different relevant markets; divide the sample into mixed households, only elementary student households, only junior high school student households and only senior high school student households, to explicitly estimate the effect of the supplementary tutoring industrial concentration on the expenditure of tutoring. This study mainly uses the Tobit model for empirical analysis. However, because the tutoring industrial concentration and the household tutoring expenditure have interrelated and endogenous problems, this study uses the Instrumental Variable Method to solve the problem.
The main empirical results show that there is a negative relationship between the HHI of tutoring industry and the expenditure of tutoring for each student. In other words, the higher level of competition in the tutoring industry, the more tutoring expenditure will be spent per student. In addition, it can be found that the mixed households have the smallest estimated value; when the HHI increase by 0.1, the mixed households have the largest reduction in the amount of tutoring expenditure per student. The reason is that all the tutoring classes are taken into consideration when calculating the mixed HHI. Therefore, the increase in mixed HHI in counties is more difficult than others. When the HHI increase the same magnitude, the mixed households tutoring expenditures fluctuated significantly. The number of senior high school tutoring classes in all counties is the least so it is easier to increase the HHI. Therefore, the same magnitude of HHI is increased, the fluctuation of household tutoring expenditure is the smallest.
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