經濟成長、收斂假說與金融發展之實證探討

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Title:	經濟成長、收斂假說與金融發展之實證探討
Other Titles:	An empirical investigation of economic growth, convergence hypothesis and financial development
Authors:	葉志權;Yeh, Chih-chuan
Contributors:	淡江大學財務金融學系博士班黃河泉;Huang, Ho-chuan
Keywords:	經濟成長;金融發展;股票市場;工具變數門檻模型;異質性變異數;economic growth;Stock Market;Instrument Variables;Identification Heteroskedasticity;Financial Development;Threshold regression
Date:	2007
Issue Date:	2010-01-11 00:59:44 (UTC+8)
Abstract:	本論文旨在財金計量模型的實證應用, 以金融發展與經濟成長為主題逐一探討既存文獻中尚未能有效解決的問題。包括金融發展在不同所得高低的國家, 是否仍具有促進成長收斂的效果? 再則, 為一般學術研究所詬病的內生性問題暨聯立性偏誤估計是否能有效改善? 除緒論外共分為兩章, 茲將摘要簡述如下: 第1 章主要應用Caner and Hansen (2004) 工具變數門檻模型(The Threshold Regression with Instrumental Variables) 實證探討金融發展之於經濟成長、收斂假說的檢定, 該模型修正了Hansen (2000) 未能有效處理工具變數的缺憾, 以更完整的迴歸方程詮釋金融發展與經濟成長間的關係。實證結果與Aghion et al. (2005) 提出的理論預期一致, 即金融發展確能俾益於經濟成長率的收斂, 實證結果指出高低所得樣本國家存在相異的收斂速度: 高於門檻值的樣本國家, 成長收斂的速度較為緩慢; 低於門檻值的樣本國家, 在金融發展的推昇下更能有效且快速地促進長期的經濟成長, 以縮短與富有國家間的成長差距, 實證結果支持收斂假設與內生成長理論。第2 章運用Rigobon (2003) 提出的異質性認定(Identification Heteroskedasticity,IH) 方法, 藉由結構干擾差異效果的探討取得結構參數的認定與估計, 以確切補捉股市發展與經濟成長間的動態交互效果。有別於傳統工具變數的分析方法, IH 方法並不需擔心迴歸結果會因主觀工具變數的選取而有所差異, 同時可以解決聯立方程架構中應變數與自變數彼此相互影響的內生性問題。根據93 國樣本及資料期間1976-1998 所構成的縱橫資料分析結果顯示, 經濟成長與各股票市場發展指標間確實存在顯著且正向影響的同期效果, 支持雙向因果關係的存在。換言之, 市場規模大且存在高流動性的有價證券市場將有效刺激經濟成長, 而快速且持續的經濟成長亦能提昇股票市場的發展。本章亦運用不同的股市發展代理變數, 並同時考慮不同控制變數的訊息集合以及固定效果與隨機效果的計量分析角色, 審慎檢視實證結果的一致性。本章實證結果盡皆符合理論研究的預期, 不僅發現股市發展對經濟成長的正向效果支持了既存文獻研究的論述, 同時也證實了經濟成長對股市發展的回饋因果關係。 This paper provides a survey and synthesis of novel econometric tools that have been employed to study economic growth, convergence hypothesis and financial development. This paper is organized as follows: Chapter 1 describes a set of stylized facts concerning economic growth, convergence hypothesis and financial development. Chapter 2 describes the relationship between stock market development and econometric frameworks for growth, with a primary focus on panel data growth regressions. Chapter 1 investigates empirically the impact of financial intermediary development on convergence and whether such an impact varies according to the stage of real development. We implement this analysis through the instrumentvariable threshold regressions approach proposed by Caner and Hansen (2004) to delve with endogeneity of financial development, so as to concentrate on the causal effects of the exogenous component of financial development and uncover income threshold effects on the convergence process. Utilizing the cross-country data consisting of 61 countries averaged over the period 1960-1995, our empirical evidence shows that financial intermediary development leads to convergent rates of growth. Moreover, such convergence-enhancing effects of financial intermediation are much stronger in developing economies than industrialized ones. In other words, the lack of financial intermediaries prevents poorer countries from catching up with the richer ones, and this divergence is more prevalent for developing countries than for advanced ones. These findings are robust to alternative conditioning information sets and measures of financial intermediary development. Chapter 2 reviews, appraises and critiques theoretical and empirical research on the connections between the operation of the financial system and economic growth. Efforts to estimate the interrelationship between stock markets development and economic growth have been plagued by the reverse causation and endogeneity problem. This paper employs a simultaneous equations system to empirically investigate the causal inter-linkage between these two important variables. Identification and estimation of the structural parameters are relied on a novel identification through heteroskedasticity methodology. Using unbalanced panel data for 93 countries over the 1976-1998 period, we find a positive, bidirectional connection between economic growth and stock markets development as predicted by recent theories. Particularly, better developed stock markets induce faster economic growth and, in turn, higher economic growth facilitates the development of stock markets. The results are robust to different measures of stock markets development used, to alternative information sets conditioned, and to different econometric methods employed.
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