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研究生:李其灃
研究生(外文):Chi-Feng Lee
論文名稱:人壽保險市場發展與經濟成長間之關係-動態追蹤資料模型分析
論文名稱(外文):The Relationship between Life Insurance Market Development and Economic Growth - The Analysis of Dynamic Panel Data Models
指導教授:李建強李建強引用關係
指導教授(外文):Chien-Chiang Lee
學位類別:碩士
校院名稱:國立中興大學
系所名稱:應用經濟學系所
學門:社會及行為科學學門
學類:經濟學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:英文
論文頁數:75
中文關鍵詞:
外文關鍵詞:life insurance market developmenteconomic growthtwo-step system GMMdynamic panel modelmarginal effectnon-linear model
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ABSTRACT
Generally, financial sector contains bank, stock and insurance markets. Although there is a plenty of research study on financial sector development, less literature focuses on insurance industry. However, life insurance market has become an increasingly important part of financial sector over the last two decades. In other words, the development of insurance markets has a great contribution to economic growth. Most importantly, life insurance market development plays an increasingly important role within the insurance industry. While there is a sea of research on the demand for life insurance or the relationship between life insurance market and economic growth, the impact on economic growth considering conditional variables has not received enough attention in this respect.
This article examines empirically the relationship between life insurance market development and economic growth by using the two-step system Generalized Method of Moments (GMM) for dynamic models of panel data for 60 countries and for 1976-2005. In this paper, we use three different proxies of life insurance market development: (a) Life Insurance Penetration (LIP) is defined as the ratio of premium volume to GDP, (b) Life Insurance Density (LID) is defined as premiums per capita, and (c) Life Insurance in Savings (LIS) is defined as the ratio of premium volume to gross savings. Specially, we further take different conditional variables into consideration to assess whether and how this relationship affected by conditional variables. Moreover, our conditional variables are divided into five sets as follows: (a) economic conditions, containing savings (SAVINGS), real interest rate (REALINT), and social security (SECURITY); (b) financial conditions, including private credit by deposit money banks to GDP (CREDIT), stock market total value traded to GDP (STOCKTRA), and stock market turnover ratio (TURNOVER); (c) demographic conditions consist of young dependency ratio (YDEP), life expectancy (LIFEXP), and urbanization (URBAN); (d) income level conditions, comprising middle-income (MIC) and low-income (LIC) level dummies; and (e) regional conditions, involving Europe (EUROPE), Latin America (LATIN) and Sub-Saharan AFRICA (S-S AFRICA) dummies.
What we find is an interesting evidence that life insurance market development robustly has a positive effect on economic growth in the basic model. Moreover, in the extended model, our results clearly show that the conditional variables of SAVINGS, SECURITY, STOCKTRA, TURNOVER, YDEP, MIC, and S-S AFRICA mitigate the positive impacts of LID on economic growth, while the conditional variable of LATIN enhances the positive impact of LID on economic growth. Next, the conditional variables of REALINT and SECURITY mitigate the positive impacts of LIP on economic growth, whereas the conditional variable of LIC enhances the positive impact of LIP on economic growth. Interestingly, the conditional variable of EUROPE alleviates the negative impact of LIP on economic growth. Last, the conditional variables of TURNOVER mitigate the positive impacts of LIS on economic growth. In conclusion, in the extended model, our results roughly show that the conditional variables of MIC, S-S AFRICA, SAVINGS, REALINT, and SECURITY, STOCKTRA, TURNOVER, and YDEP alleviate the positive impacts of life insurance market development on economic growth. Oppositely, the conditional variables of LIC and LATIN strengthen the positive impacts of life insurance market development on economic growth. As we consider the marginal effect by adding conditional variables, the relationship between life insurance market development and economic growth may become ambiguous. Therefore, we can validly demonstrate that why same life insurance market development has different economic growth. In conclusion, the conditional variables may affect the relationship between life insurance market development and economic growth. This paper offers several useful insights for policy-makers and researchers. Furthermore, we find that the relationship between life insurance market development and economic growth is better described as a weak inverse U-shape. Thus, life insurance market development and economic growth, in fact, be in a non-linear form.
CONTENTS
ABSTRACT...........................................................................................................I
CONTENTS........................................................................................................IV
LIST OF FIGURES.............................................................................................V
LIST OF TABLES..............................................................................................VI
1 INTRODUCTION........................................................................................1
2 LITERATURE REVIEW.............................................................................9
2.1 Relationship between Life Insurance and Economic Growth 9
2.2 The Conditions that affect Life Insurance and Economic Growth 11
2.3 Empirical Literature on the Dynamic Panel Data Model 16
3 EMPIRICAL MODEL AND METHODOLODGY.................................18
3.1 The Basic Model 18
3.2 The Extended Model 23
4 DATA DESCRIPTION...............................................................................28
5 EMPIRICAL RESULTS ANALYSIS........................................................31
5.1 The Basic Model 31
5.2 The Extended Model 32
5.3 The Marginal Effect 36
5.4 Summary of Empirical Results 38
5.5 Robustness 39
6 CONCLUSIONS AND SUGGESTIONS..................................................44
REFERENCE....................................................................................................48






LIST OF FIGURES
Figure 1. The Research Flow 54
Figure 2. The Scatter Plot of Life Insurance Penetration (LIP) and Economic Growth, 1976-2005 55
Figure 3. The Scatter Plot of Life Insurance Density (LID) and Economic Growth,
1976-2005 55
Figure 4. The Scatter Polt of Life Insurance In Savings (LIS) and Economic Growth, 1976-2005 55






















LIST OF TABLES
Table 1. Empirical Studies on the Relationship between Life Insurance and Economic Growth 56
Table 2. List of 60 Countries by the Regions. 57
Table 3. Definitions and Sources of Variables used in the Regression Analysis 58
Table 4. Country Groups by the Income Level 60
Table 5. Descriptive Statistics: GROWTH (%) 61
Table 6. Descriptive Statistics: LIP (%) 62
Table 7. Descriptive Statistics: LID (US$) 63
Table 8. Descriptive Statistics: LIS (%) 64
Table 9. Correlation Matrix 65
Table 10. The Basic Model 65
Table 11. The Extended Model: The Economic Conditions 66
Table 12. The Extended Model: The Financial Conditions 67
Table 13. The Extended Model: The Demographic Conditions 68
Table 14. The Extended Model: The Income level Conditions 69
Table 15. The Extended Model: The Regional Conditions 70
Table 16. The Signs of the Marginal Effects of Life Insurance Market Development on Economic Growth in the Extended Model 71
Table 17. The Degrees of the Marginal Effects of LIP on Economic Growth in the Extended Model 71
Table 18. The Degrees of the Marginal Effects of LID on Economic Growth in the Extended Model 72
Table 19. The Degrees of the Marginal Effects of LIS on Economic Growth in the Extended Model 72
Table 20. Five-Year Average Data: The Basic Model 73
Table 21. Non-Linear Model: Raw Data, The Basic Model 73
Table 22. Non-Linear Model: Five-Year Average Data, The Basic Model 74
Table 23. MAD: Raw Data, The Basic Model 74
Table 24. MAD: Five-Year Average Data, The Basic Model 75
Table 25. Drop Out Outliers: The Basic Model 75
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