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研究生:馬元凱
研究生(外文):馬元凱
論文名稱:EXPLORING THE IMPACT OF POLITICALINSTABILITY ON ECONOMIC GROWTH
論文名稱(外文):EXPLORING THE IMPACT OF POLITICALINSTABILITY ON ECONOMIC GROWTH
指導教授:黃峰蕙黃峰蕙引用關係
指導教授(外文):黃峰蕙
學位類別:碩士
校院名稱:南台科技大學
系所名稱:商管專業學院
學門:商業及管理學門
學類:其他商業及管理學類
論文種類:學術論文
論文出版年:103
畢業學年度:102
語文別:英文
論文頁數:54
中文關鍵詞:Political Instability, Economic growth, hierarchical linear modeling (HLM),
外文關鍵詞:Political Instability, Economic growth, hierarchical linear modeling (HLM),
相關次數:
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ABSTRACT
This study explored the relationship between political instability and economic
growth, using hierarchical linear modeling (HLM). The major episodes of political
violence (MEPV) from Marshall (2011) were used as proxy variables for political
instability; GDP deflator, government spending, exchange rate and interest rates were
put in the first-level regression as a control variables individually
Based on the analysis of panel data for 159 countries from 1961 to 2010, the
study uses hierarchical linear modeling (HLM) as innovative methodology not yet
widely applied in the analysis of economic growth. The results appear to be mixed
(robust with some and inconsistent in other situations). The different MEPVs behave
differently to predict economic growth when input into the models with different control
variables under different scaling approaches (i.e., no centering (raw metric) and
centering around the group mean, with fixed or random slope for MEPV). HLM
appears to be an innovative method in predicting simultaneously, the short-term and
long term effect of economic growth in the same model.
Further investigation would be highly recommended for this study due to the
inconsistences shown by the results.
ABSTRACT
This study explored the relationship between political instability and economic
growth, using hierarchical linear modeling (HLM). The major episodes of political
violence (MEPV) from Marshall (2011) were used as proxy variables for political
instability; GDP deflator, government spending, exchange rate and interest rates were
put in the first-level regression as a control variables individually
Based on the analysis of panel data for 159 countries from 1961 to 2010, the
study uses hierarchical linear modeling (HLM) as innovative methodology not yet
widely applied in the analysis of economic growth. The results appear to be mixed
(robust with some and inconsistent in other situations). The different MEPVs behave
differently to predict economic growth when input into the models with different control
variables under different scaling approaches (i.e., no centering (raw metric) and
centering around the group mean, with fixed or random slope for MEPV). HLM
appears to be an innovative method in predicting simultaneously, the short-term and
long term effect of economic growth in the same model.
Further investigation would be highly recommended for this study due to the
inconsistences shown by the results.
TABLE OF CONTENTS
ABSTRACT .................................................................................................................... i
ACKNOWLEDGEMENTS ............................................................................................ ii
TABLE OF CONTENTS ................................................................................................ iii
LIST OF TABLES .......................................................................................................... v
LIST OF FIGURES ........................................................................................................ vi
1. INTRODUCTION .................................................................................................. 1
1.1. Research background ............................................................................................... 1
1.2. Problem definition .................................................................................................. 1
1.3. Purpose of the study ................................................................................................ 2
1.4. Significance of the study .......................................................................................... 2
1.5. Content of the study ................................................................................................. ..3
2. LITERATURE REVIEW ....................................................................................... ..4
2.1 Relationship between political instability and economic growth ............................. ..4
2.2 Measurement of political instability ............................................................................... ..6
2.3 Other determinants of economic growth: used as control variables ......................... ..7
2.3.1 GDP Deflator (inflation) as a determinant for economic growth .......................... ..8
2.3.2 Government spending as a determinant for economic growth .............................. ..8
2.3.3 Exchange rate as a determinant for economic growth ........................................... 10
2.3.4 Interest rate as a determinant for economic growth ............................................... 11
3. METHODOLOGY .................................................................................................... 14
3.1 Data ........................................................................................................................... 14
3.2. Statistical methods ................................................................................................... 18
3.2.1 Assessing multilevel relationships using Hierarchical linear modeling (HLM) .... 18
3.2.2. Hierarchical linear modeling and economic growth ............................................. 18
3.2.3 Comments on HLM outputs and non-normality problem ..................................... 19
3.3. Theoretical framework ............................................................................................. 19
iv
3.4. Exploratory factor analysis (EFA) of political instability ....................................... 20
4. EMPIRICAL RESULTS............................................................................................. 24
4.1 The two-level approach to cross-level investigation ................................................ 24
4.2 One-way ANCOVA with Random Effects .............................................................. 24
4.3 Random coefficient regression for MEPV 1 ............................................................. 27
4.4 Random coefficient regression for MEPV 2 ............................................................. 20
4.5 Random coefficient regression for MEPV 3 ............................................................. 32
4.6 Random coefficient regression for MEPV 4 ............................................................. 34
4.7 Summary of results .................................................................................................. 36
5. DISCUSSIONS……………………………………………………………………...39
5.1 Discusions ................................................................................................................. 39
5.2 Major contributions of this research ......................................................................... 40
6. CONCLUSIONS AND RECOMMENDATIONS ..................................................... 42
6.1 conclusions ................................................................................................................ 42
6.2 Limitations of the study ............................................................................................ 42
6.3 Recommendations for future research ...................................................................... 42
REFERENCES ...............................................................................................................44
APPENDIX A – LIST OF COUNTRIES USED ........................................................... 54
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