The roles of stock market in the finance-growth nexus: time series cointegration and causality evidence from Taiwan

Abstract

This article uses quarterly data from 1971 to 2007 to investigate the finance-growth nexus in Taiwan. We take into account the role of stock market into our examined model and revise the stock-flow problem when calculating financial related variables. The result supports the comovement phenomenon among financial intermediation, stock market and economic development based on the Johansen cointegration. The contribution of stock market capitalization to economic growth is substantially larger than that of banking in the long-term, highlighting the importance of stock market in Taiwan. Further, Granger causality based on Vector Error Correction Model (VECM) concludes the bi-directional causal relation between financial development and economic growth, suggesting the simultaneous interaction of supply-leading and demand-following phenomena addressed by Partick (1966).

Causal nexus between economic growth, banking sector development, stock market development, and other macroeconomic variables: The case of ASEAN countries

“…the feedback hypothesis (FBH). This is true for all four samples in our study and is consistent with the earlier findings of Pradhan, Arvin, Norman and Hall (2014), Cheng (2012), Hou and Cheng (2010), Beck and Levine (2004), and Levine and Zervos (1998).…”

“…By contrast, Kar et al (2011), Panopoulou (2009), Liu and Sinclair (2008, Odhiambo (2008) Ang and McKibbin (2007), Liang and Teng (2006), and Dritsaki and Dritsaki-bargiota (2005) present evidence in support of a "demand-following" hypothesis, where unidirectional causality from economic growth to stock market development is present. Finally, Cheng (2012), Hou and Cheng (2010), Rashid (2008), Darrat, Elkhal, and McCallum (2006), Caporale, Howells, and Soliman (2004), Hassapis and Kalyvitis (2002), Wongbangpo and Sharma (2002), Huang, Yang, and Hu (2000), Muradoglu, Taskin, and Bigan (2000), Masih and Masih (1999), and Nishat and Saghir (1991) demonstrate 1960Naceur and Ghazouani (2007 MENA region MVGC 1979Boulila and Trabelsi (2004 Tunisia BVGC 1962-1987Agbetsiafa (2003 Sub-Saharan Africa TVGC 1963-2001 Calderon and Liu (2003) 109 countries MVGC 1960-1994 Thornton (1994) Asian countries BVGC 1951-1990 that causation runs in both directions simultaneously. Once again, the existing literature does not provide a definitive answer as to the direction of causality.…”

“…Similarly, stock market development is defined as a process of improvements in the quantity, quality and efficiency of stock market services. It also involves the interaction of many activities and cannot be captured by a single measure (Caporale et al, 2004; Cheng, 2012; Cooray, 2010; Darrat et al, 2006; Hou & Cheng, 2010; Kar et al, 2011; Kolapo & Adaramola, 2012; Pradhan, Arvin et al, 2013; Rousseau, 2009; Rousseau & Wachtel, 1998; Rousseau & Xiao, 2007; Wongbangpo & Sharma, 2002; Zhu et al, 2004). The present study deploys four commonly‐used measures of stock market development, namely market capitalization (MAC), traded stocks (TRA), turnover ratio (TUR), and the number of listed companies (NLC).…”

The dynamics of banking sector and stock market maturity and the performance of Asian economies

“…By contrast, Ang and McKibbin (2007), Dritsaki and Dritsaki-Bargiota (2005), Kar et al (2011), Liang and Teng (2006), Liu and Sinclair (2008), Odhiambo (2008), and Panopoulou (2009) present evidence in support of a DFH, where unidirectional causality from economic growth to stock market maturity is present. Finally, Caporale et al (2004), Cheng (2012), Darrat et al (2006), Hassapis and Kalyvitis (2002), Hou and Cheng (2010), Huang et al (2000), Masih and Masih (1999),…”

The Relationship Between Macroeconomy and Asset Prices: Long Run Causality Evidence From Lithuania

“…La Paz & White, 2012;Galvao et al, 2011). ere is no consensus among researchers on how many macroeconomic variables should be included in econometric models: some authors use just 1 or 2 variables (Fama & Schwert, 1977;Hou & Cheng, 2010), others -over 100 indicators (Ludvigson & Ng, 2009), but mostly -from 4 to 6 variables (Chen, 1991;La Paz & White, 2012;Singh et al, 2013). In the case of this study, it was decided to choose ve most frequently analysed macroeconomic variables: Lithuanian gross domestic product, foreign direct investment, consumer price index, money supply M2 and 6 month Vilnius interbank o ered rate (the description of these variables is provided in Annex 1).…”