本文主要探討金融發展對二氧化碳排放量的影響。利用 117個國家自1989年至2013年的縱橫面資料，並以system-GMM之計量方法進行實證分析，本文發現如下:金融發展對於二氧化碳排放量的影響為非線性，其中，銀行體系的發展對於二氧化碳排放量有倒U型態的顯著影響，這說明了銀行體系的改善，在初步階段雖然會使二氧化碳排放量增加，但長期而言 ，在發展到某個程度後會對二氧化碳排放量有抑制效果；然而，證券市場的發展對二氧化碳排放量有著 U型態的顯著影響，因此，與銀行體系的影響相反，證券市場在初步發展段，會先使二氧化碳排放量降低，但長期而言，證券市場發展到某個水準後會開始導致二氧化碳排放量增加。

This study investigates the nonlinear relationship between financial development and CO2 emissions in 117 countries over the period 1989-2013 using system-GMM model. The empirical results indicate that the banking sector has a statistically significant inverted U relationship with carbon dioxide emissions while the relationship between the stock market and carbon dioxide emissions is statistically significant U shape. Moreover, the empirical results imply the improvement in different segments of financial sector has different effect on CO2 emissions, where banking system would mitigate CO2 emissions in the long run while stock market would worsen the emissions.

Contents
1.Introduction.............................................1
2.Literature review........................................3
3.Data and methodology....................................9
3.1.Data................................................. 9
3.2.Methodology.......................................... 11
4.Empirical results.......................................14
4.1.Fixed effect estimation ..............................14
4.1.1.Linear fixed effect model ..........................14
4.1.2.Nonlinear fixed effect model .......................17
4.1.3.Nonlinear IV fixed effect model ....................19
4.2.System GMM estimation.................................22
4.3.Subsample estimation..................................26
5.Conclusion..............................................29
References................................................31

List of table
Table 1: Linear fixed effect model........................15
Table 2: Non-linear fixed effect model emission...........18
Table 3: Non-linear IV fixed effect model.................20
Table 4: Non-linear dynamic system GMM model..............23
Table 5: Dynamic system GMM model with subsample..........27
Appendix A : Literature review............................33
Appendix B : Country list.................................34
Appendix C : Descriptive statistics.......................35

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