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題名 模型具內生性之工具變數選擇：ETF持有比率對股票波動性與流動性的影響
Instrumental Variable Selection under Endogeneity: The Impact of ETF Ownership on Stock Volatility and Liquidity
作者 林慈恩
Lin, Tzu-En
貢獻者 鄭宗記
Cheng, Tsung-Chi
林慈恩
Lin, Tzu-En
關鍵詞 指數股票型基金
波動性
流動性
內生性
工具變數選取
二階段最小平方法
ETF
Stock Volatility
Market Liquidity
Instrumental Variable Selection
Endogeneity
Two-Stage Least Squares
日期 2025
上傳時間 4-Aug-2025 15:11:46 (UTC+8)
摘要 本研究利用2014年至2024年臺灣上市公司之季度縱向數據，探討ETF持有比率對個股波動性與流動性的因果影響，並聚焦於內生性問題下有效工具變數的選取方法。為解決潛在內生性問題，本文採用二階段最小平方法，並輔以F檢定、Sargan過度識別檢定，以及Windmeijer等人（2021）所提出的信賴區間法，以評估並篩選最具效力的工具變數組合。實證結果顯示，ETF持有顯著影響部分波動性指標，並顯著降低個股的流動性與交易活躍度。本文不僅提供ETF持有對市場微觀結構的影響，也提出一套系統性的工具變數選擇架構，對處理內生性問題的實證研究具參考價值。
This study investigates the causal effects of exchange-traded fund (ETF) ownership on stock-level volatility and liquidity using quarterly panel data from Taiwan’s stock market between 2014 and 2024. To address potential endogeneity concerns, the analysis employs the two-stage least squares (2SLS) method, supplemented by the first-stage F-test, the Sargan overidentification test, and the confidence interval method proposed by Windmeijer et al. (2021) to evaluate and select valid instrumental variable sets. Empirical results show that ETF ownership significantly affects certain measures of volatility and is associated with a notable decline in individual stock liquidity and trading activity. This study not only provides new empirical evidence on the microstructural impacts of ETF ownership but also introduces a systematic framework for instrumental variable selection, offering methodological contributions for future research dealing with endogeneity.
參考文獻 Abad, D., Nieto, B., Pascual, R., & Rubio, G. (2023). Market-wide illiquidity and the distribution of non-parametric stochastic discount factors. International Review of Financial Analysis, 87, 102650. Acharya, V. V., & Pedersen, L. H. (2005). Asset pricing with liquidity risk. Journal of financial Economics, 77(2), 375-410. Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of financial markets, 5(1), 31-56. Amihud, Y., Hameed, A., Kang, W., & Zhang, H. (2015). The illiquidity premium: International evidence. Journal of financial economics, 117(2), 350-368. Andrews, I., Stock, J. H., & Sun, L. (2019). Weak instruments in instrumental variables regression: Theory and practice. Annual Review of Economics, 11(1), 727-753. Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist's companion. Princeton university press. Apfel, N., & Windmeijer, F. (2022). The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction. arXiv preprint arXiv:2212.04814. Armstrong, T. B., & Kolesár, M. (2021). Supplement to ‘Sensitivity analysis using approximate moment condition models’. Quantitative Economics Supplemental Material, 12. Bae, K., & Kim, D. (2020). Liquidity risk and exchange-traded fund returns, variances, and tracking errors. Journal of Financial Economics, 138(1), 222-253. Barndorff-Nielsen, O. E., & Shephard, N. (2002). Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society Series B: Statistical Methodology, 64(2), 253-280. Ben‐David, I., Franzoni, F., & Moussawi, R. (2018). Do ETFs increase volatility?. The Journal of Finance, 73(6), 2471-2535. Berger, A. N., & Di Patti, E. B. (2006). Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry. Journal of Banking & Finance, 30(4), 1065-1102. Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates?. The Quarterly journal of economics, 119(1), 249-275. Bollerslev, T., Patton, A. J., & Quaedvlieg, R. (2020). Multivariate leverage effects and realized semicovariance GARCH models. Journal of Econometrics, 217(2), 411-430. Bound, J., Jaeger, D. A., & Baker, R. M. (1995). Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. Journal of the American statistical association, 90(430), 443-450. Callaway, B., & Sant’Anna, P. H. (2021). Difference-in-differences with multiple time periods. Journal of econometrics, 225(2), 200-230. Campello, M. (2003). Capital structure and product markets interactions: evidence from business cycles. Journal of financial economics, 68(3), 353-378. Chen, J., & Xu, L. (2023). Do exchange-traded fund activities destabilize the stock market? Evidence from the China securities index 300 stocks. Economic Modelling, 127, 106450. Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of business, 59(3), 383-403. Chordia, T., Roll, R., & Subrahmanyam, A. (2001). Market liquidity and trading activity. The journal of finance, 56(2), 501-530. Conley, T. G., Hansen, C. B., & Rossi, P. E. (2012). Plausibly exogenous. Review of Economics and Statistics, 94(1), 260-272. Cont, R. (2007). Volatility clustering in financial markets: empirical facts and agent-based models. In Long memory in economics (pp. 289-309). Berlin, Heidelberg: Springer Berlin Heidelberg. Da, Z., & Shive, S. (2018). Exchange traded funds and asset return correlations. European Financial Management, 24(1), 136-168. Datar, V. T., Naik, N. Y., & Radcliffe, R. (1998). Liquidity and stock returns: An alternative test. Journal of financial markets, 1(2), 203-219. Demsetz, H. (1968). The cost of transacting. The Quarterly Journal of Economics, 82(1), 33-53. Durbin, J. (1954). Errors in variables. Revue de l'institut International de Statistique, 22(1/3), 23-32. El Kalak, I., Hudson, R., & Tosun, O. K. (2024). Engaged ETFs and firm performance. European Financial Management, 30(3), 1708-1756. Fama, E. F., & French, K. R. (2002). Testing trade-off and pecking order predictions about dividends and debt. Review of financial studies, 15(1), 1-33. Florackis, C., Gregoriou, A., & Kostakis, A. (2011). Trading frequency and asset pricing on the London Stock Exchange: Evidence from a new price impact ratio. Journal of Banking & Finance, 35(12), 3335-3350. Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. Journal of Business,53(1), 67-78. Glosten, L., Nallareddy, S., & Zou, Y. (2021). ETF activity and informational efficiency of underlying securities. Management Science, 67(1), 22-47. Gompers, P., Ishii, J., & Metrick, A. (2003). Corporate governance and equity prices. The quarterly journal of economics, 118(1), 107-156. Hamm, S. J. (2010). The effect of ETFs on stock liquidity (Doctoral dissertation, University of Pennsylvania). Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the econometric society, 50(4), 1029-1054. Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the econometric society, 46(6), 1251-1271. Humpe, A., & Macmillan, P. (2009). Can macroeconomic variables explain long-term stock market movements? A comparison of the US and Japan. Applied financial economics, 19(2), 111-119. Israeli, D., Lee, C. M., & Sridharan, S. A. (2017). Is there a dark side to exchange traded funds? An information perspective. Review of Accounting Studies, 22, 1048-1083. Krause, T., Ehsani, S., & Lien, D. (2014). Exchange-traded funds, liquidity and volatility. Applied Financial Economics, 24(24), 1617-1630. Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 53(6), 1315-1335. Lettau, M., & Ludvigson, S. (2001). Consumption, aggregate wealth, and expected stock returns. the Journal of Finance, 56(3), 815-849. Liang, X. (2022). Methods for Selecting Valid Instrumental Variables (Doctoral dissertation, University of Bristol). Madhavan, A., & Sobczyk, A. (2016). Price dynamics and liquidity of exchange-traded funds. Journal of Investment Management, 14(2), 1-17. Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. Journal of business, 53(1), 61-65. Rakowski, D., & Yamani, E. (2021). Endogeneity in the mutual fund flow–performance relationship: An instrumental variables solution. Journal of Empirical Finance, 64, 247-271. Rogers, L. C. G., & Satchell, S. E. (1991). Estimating variance from high, low and closing prices. The Annals of Applied Probability, 1(4), 504-512. Rogers, L. C., Satchell, S. E., & Yoon, Y. (1994). Estimating the volatility of stock prices: a comparison of methods that use high and low prices. Applied Financial Economics, 4(3), 241-247. Sargan, J. D. (1958). The estimation of economic relationships using instrumental variables. Econometrica: Journal of the econometric society, 26(3), 393-415. Schwert, G. W. (1989). Why does stock market volatility change over time?. The journal of finance, 44(5), 1115-1153. Staiger, D., & Stock, J. (1997). to Econometrica. Econometrica, 65(3), 557-586. Wang, N., & Ma, Z. (2024). ETF ownership and stock liquidity: evidence from China. Asia-Pacific Journal of Accounting & Economics, 1-18. Windmeijer, F., Liang, X., Hartwig, F. P., & Bowden, J. (2021). The confidence interval method for selecting valid instrumental variables. Journal of the Royal Statistical Society Series B: Statistical Methodology, 83(4), 752-776. Wu, D. M. (1973). Alternative tests of independence between stochastic regressors and disturbances. Econometrica: journal of the Econometric Society, 41(4), 733-750.
描述 碩士
國立政治大學
統計學系
112354024
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112354024
資料類型 thesis
dc.contributor.advisor 鄭宗記zh_TW
dc.contributor.advisor Cheng, Tsung-Chien_US
dc.contributor.author (Authors) 林慈恩zh_TW
dc.contributor.author (Authors) Lin, Tzu-Enen_US
dc.creator (作者) 林慈恩zh_TW
dc.creator (作者) Lin, Tzu-Enen_US
dc.date (日期) 2025en_US
dc.date.accessioned 4-Aug-2025 15:11:46 (UTC+8)-
dc.date.available 4-Aug-2025 15:11:46 (UTC+8)-
dc.date.issued (上傳時間) 4-Aug-2025 15:11:46 (UTC+8)-
dc.identifier (Other Identifiers) G0112354024en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158715-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 112354024zh_TW
dc.description.abstract (摘要) 本研究利用2014年至2024年臺灣上市公司之季度縱向數據，探討ETF持有比率對個股波動性與流動性的因果影響，並聚焦於內生性問題下有效工具變數的選取方法。為解決潛在內生性問題，本文採用二階段最小平方法，並輔以F檢定、Sargan過度識別檢定，以及Windmeijer等人（2021）所提出的信賴區間法，以評估並篩選最具效力的工具變數組合。實證結果顯示，ETF持有顯著影響部分波動性指標，並顯著降低個股的流動性與交易活躍度。本文不僅提供ETF持有對市場微觀結構的影響，也提出一套系統性的工具變數選擇架構，對處理內生性問題的實證研究具參考價值。zh_TW
dc.description.abstract (摘要) This study investigates the causal effects of exchange-traded fund (ETF) ownership on stock-level volatility and liquidity using quarterly panel data from Taiwan’s stock market between 2014 and 2024. To address potential endogeneity concerns, the analysis employs the two-stage least squares (2SLS) method, supplemented by the first-stage F-test, the Sargan overidentification test, and the confidence interval method proposed by Windmeijer et al. (2021) to evaluate and select valid instrumental variable sets. Empirical results show that ETF ownership significantly affects certain measures of volatility and is associated with a notable decline in individual stock liquidity and trading activity. This study not only provides new empirical evidence on the microstructural impacts of ETF ownership but also introduces a systematic framework for instrumental variable selection, offering methodological contributions for future research dealing with endogeneity.en_US
dc.description.tableofcontents 摘要 I ABSTRACT II 目錄 III 表次 V 圖次 VI 第一章 緒論 7 第一節 研究背景與動機 7 第二節 研究目的 10 第二章 文獻探討 11 第一節 ETF股票市場 11 第二節 縱向數據 13 第三節 內生性問題 14 第四節 工具變數 16 第五節 工具變數選取之理論與依據 18 第三章 研究方法 20 第一節 研究設計 20 第二節 波動性變數 21 第三節 流動性變數 22 第四節 二階段最小平方法 24 第五節 工具變數檢驗 25 第六節 工具變數選取 28 第四章 實證分析 30 第一節 資料介紹 30 第二節 第一階段迴歸分析與工具變數評估 31 第三節 工具變數檢驗與選取 37 3.1 波動性變數的工具變數選擇 37 3.2 流動性變數的工具變數選擇 39 第四節 第二階段迴歸分析 46 4.1 波動性變數第二階段迴歸 46 4.2 流動性變數第二階段迴歸 48 第五章 結論 55 參考文獻 57 附錄 62zh_TW
dc.format.extent 2981323 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112354024en_US
dc.subject (關鍵詞) 指數股票型基金zh_TW
dc.subject (關鍵詞) 波動性zh_TW
dc.subject (關鍵詞) 流動性zh_TW
dc.subject (關鍵詞) 內生性zh_TW
dc.subject (關鍵詞) 工具變數選取zh_TW
dc.subject (關鍵詞) 二階段最小平方法zh_TW
dc.subject (關鍵詞) ETFen_US
dc.subject (關鍵詞) Stock Volatilityen_US
dc.subject (關鍵詞) Market Liquidityen_US
dc.subject (關鍵詞) Instrumental Variable Selectionen_US
dc.subject (關鍵詞) Endogeneityen_US
dc.subject (關鍵詞) Two-Stage Least Squaresen_US
dc.title (題名) 模型具內生性之工具變數選擇：ETF持有比率對股票波動性與流動性的影響zh_TW
dc.title (題名) Instrumental Variable Selection under Endogeneity: The Impact of ETF Ownership on Stock Volatility and Liquidityen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Abad, D., Nieto, B., Pascual, R., & Rubio, G. (2023). Market-wide illiquidity and the distribution of non-parametric stochastic discount factors. International Review of Financial Analysis, 87, 102650. Acharya, V. V., & Pedersen, L. H. (2005). Asset pricing with liquidity risk. Journal of financial Economics, 77(2), 375-410. Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of financial markets, 5(1), 31-56. Amihud, Y., Hameed, A., Kang, W., & Zhang, H. (2015). The illiquidity premium: International evidence. Journal of financial economics, 117(2), 350-368. Andrews, I., Stock, J. H., & Sun, L. (2019). Weak instruments in instrumental variables regression: Theory and practice. Annual Review of Economics, 11(1), 727-753. Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist's companion. Princeton university press. Apfel, N., & Windmeijer, F. (2022). The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction. arXiv preprint arXiv:2212.04814. Armstrong, T. B., & Kolesár, M. (2021). Supplement to ‘Sensitivity analysis using approximate moment condition models’. Quantitative Economics Supplemental Material, 12. Bae, K., & Kim, D. (2020). Liquidity risk and exchange-traded fund returns, variances, and tracking errors. Journal of Financial Economics, 138(1), 222-253. Barndorff-Nielsen, O. E., & Shephard, N. (2002). Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society Series B: Statistical Methodology, 64(2), 253-280. Ben‐David, I., Franzoni, F., & Moussawi, R. (2018). Do ETFs increase volatility?. The Journal of Finance, 73(6), 2471-2535. Berger, A. N., & Di Patti, E. B. (2006). Capital structure and firm performance: A new approach to testing agency theory and an application to the banking industry. Journal of Banking & Finance, 30(4), 1065-1102. Bertrand, M., Duflo, E., & Mullainathan, S. (2004). How much should we trust differences-in-differences estimates?. The Quarterly journal of economics, 119(1), 249-275. Bollerslev, T., Patton, A. J., & Quaedvlieg, R. (2020). Multivariate leverage effects and realized semicovariance GARCH models. Journal of Econometrics, 217(2), 411-430. Bound, J., Jaeger, D. A., & Baker, R. M. (1995). Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. Journal of the American statistical association, 90(430), 443-450. Callaway, B., & Sant’Anna, P. H. (2021). Difference-in-differences with multiple time periods. Journal of econometrics, 225(2), 200-230. Campello, M. (2003). Capital structure and product markets interactions: evidence from business cycles. Journal of financial economics, 68(3), 353-378. Chen, J., & Xu, L. (2023). Do exchange-traded fund activities destabilize the stock market? Evidence from the China securities index 300 stocks. Economic Modelling, 127, 106450. Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of business, 59(3), 383-403. Chordia, T., Roll, R., & Subrahmanyam, A. (2001). Market liquidity and trading activity. The journal of finance, 56(2), 501-530. Conley, T. G., Hansen, C. B., & Rossi, P. E. (2012). Plausibly exogenous. Review of Economics and Statistics, 94(1), 260-272. Cont, R. (2007). Volatility clustering in financial markets: empirical facts and agent-based models. In Long memory in economics (pp. 289-309). Berlin, Heidelberg: Springer Berlin Heidelberg. Da, Z., & Shive, S. (2018). Exchange traded funds and asset return correlations. European Financial Management, 24(1), 136-168. Datar, V. T., Naik, N. Y., & Radcliffe, R. (1998). Liquidity and stock returns: An alternative test. Journal of financial markets, 1(2), 203-219. Demsetz, H. (1968). The cost of transacting. The Quarterly Journal of Economics, 82(1), 33-53. Durbin, J. (1954). Errors in variables. Revue de l'institut International de Statistique, 22(1/3), 23-32. El Kalak, I., Hudson, R., & Tosun, O. K. (2024). Engaged ETFs and firm performance. European Financial Management, 30(3), 1708-1756. Fama, E. F., & French, K. R. (2002). Testing trade-off and pecking order predictions about dividends and debt. Review of financial studies, 15(1), 1-33. Florackis, C., Gregoriou, A., & Kostakis, A. (2011). Trading frequency and asset pricing on the London Stock Exchange: Evidence from a new price impact ratio. Journal of Banking & Finance, 35(12), 3335-3350. Garman, M. B., & Klass, M. J. (1980). On the estimation of security price volatilities from historical data. Journal of Business,53(1), 67-78. Glosten, L., Nallareddy, S., & Zou, Y. (2021). ETF activity and informational efficiency of underlying securities. Management Science, 67(1), 22-47. Gompers, P., Ishii, J., & Metrick, A. (2003). Corporate governance and equity prices. The quarterly journal of economics, 118(1), 107-156. Hamm, S. J. (2010). The effect of ETFs on stock liquidity (Doctoral dissertation, University of Pennsylvania). Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the econometric society, 50(4), 1029-1054. Hausman, J. A. (1978). Specification tests in econometrics. Econometrica: Journal of the econometric society, 46(6), 1251-1271. Humpe, A., & Macmillan, P. (2009). Can macroeconomic variables explain long-term stock market movements? A comparison of the US and Japan. Applied financial economics, 19(2), 111-119. Israeli, D., Lee, C. M., & Sridharan, S. A. (2017). Is there a dark side to exchange traded funds? An information perspective. Review of Accounting Studies, 22, 1048-1083. Krause, T., Ehsani, S., & Lien, D. (2014). Exchange-traded funds, liquidity and volatility. Applied Financial Economics, 24(24), 1617-1630. Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society, 53(6), 1315-1335. Lettau, M., & Ludvigson, S. (2001). Consumption, aggregate wealth, and expected stock returns. the Journal of Finance, 56(3), 815-849. Liang, X. (2022). Methods for Selecting Valid Instrumental Variables (Doctoral dissertation, University of Bristol). Madhavan, A., & Sobczyk, A. (2016). Price dynamics and liquidity of exchange-traded funds. Journal of Investment Management, 14(2), 1-17. Parkinson, M. (1980). The extreme value method for estimating the variance of the rate of return. Journal of business, 53(1), 61-65. Rakowski, D., & Yamani, E. (2021). Endogeneity in the mutual fund flow–performance relationship: An instrumental variables solution. Journal of Empirical Finance, 64, 247-271. Rogers, L. C. G., & Satchell, S. E. (1991). Estimating variance from high, low and closing prices. The Annals of Applied Probability, 1(4), 504-512. Rogers, L. C., Satchell, S. E., & Yoon, Y. (1994). Estimating the volatility of stock prices: a comparison of methods that use high and low prices. Applied Financial Economics, 4(3), 241-247. Sargan, J. D. (1958). The estimation of economic relationships using instrumental variables. Econometrica: Journal of the econometric society, 26(3), 393-415. Schwert, G. W. (1989). Why does stock market volatility change over time?. The journal of finance, 44(5), 1115-1153. Staiger, D., & Stock, J. (1997). to Econometrica. Econometrica, 65(3), 557-586. Wang, N., & Ma, Z. (2024). ETF ownership and stock liquidity: evidence from China. Asia-Pacific Journal of Accounting & Economics, 1-18. Windmeijer, F., Liang, X., Hartwig, F. P., & Bowden, J. (2021). The confidence interval method for selecting valid instrumental variables. Journal of the Royal Statistical Society Series B: Statistical Methodology, 83(4), 752-776. Wu, D. M. (1973). Alternative tests of independence between stochastic regressors and disturbances. Econometrica: journal of the Econometric Society, 41(4), 733-750.zh_TW