政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/145954
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113656/144643 (79%)
造訪人次 : 51761564      線上人數 : 525
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/145954


    題名: 經濟學實證研究:市場訊息與廠商創新活動
    Essays on Market Information and R&D Activities
    作者: 戴瑋澍
    Tai, Wei-Shu
    貢獻者: 陳鎮洲
    Chen, Jennjou
    戴瑋澍
    Tai, Wei-Shu
    關鍵詞: 訊息量
    噪音交易者
    股價
    成交量
    中美貿易爭端
    創新因素
    創新
    傾向分數
    生產力
    處理效果
    Information volume
    Noise traders
    Stock prices
    Trading volume
    U.S.-China trade dispute
    Innovation
    Innovation determinants
    Propensity score
    Productivity
    Treatment effect
    日期: 2023
    上傳時間: 2023-07-10 11:51:33 (UTC+8)
    摘要: 本論文集由二篇研究組成,篇一為「盤後訊息效果的實證研究—以中美貿易爭端為例」,篇二為「廠商創新因素與其生產力」。
    篇一旨在研究中美貿易爭端期間,股票市場中包含股價、成交量與盤後訊息之關係。文獻研究訊息與市場關係,時而忽略自變數與應變數時間重疊情形,本研究提出控制變數時間落差方法,消減可能產生的因果性與同時性問題。進一步發現,臺灣股票市場成交量與訊息相關因素有關,而價格波動則與市場訊息本質有關,此結果支持相關文獻之論述;但與文獻不同的是,價格對市場訊息的搜尋程度關係不顯著,且市場對訊息面因素的反應較基本面因素明顯。研判可能係臺灣股票市場存在噪音交易者(noise traders),其主要由網路搜尋等方式獲得市場訊息以從事交易決策,且重視訊息面高於基本面,但無法由訊息有效判斷價格趨勢所致。
    篇二旨在研究廠商創新傾向,以及廠商創新對其生產力表現。本文以廠商創新對生產力處理效果分析創新效果,但與Crowley與McCann(2018)運用需以較強假設估計相反事實產出之方式不同,本研究以估計樣本傾向分數配對方式,觀察創新廠商的創新處理效果。另一方面,相關文獻多以調查資料進行創新議題研究,本研究以普查資料,更完整觀察產業經濟環境。結果方面,本研究陳示製造業及四大工業廠商創新因素,依技術情形、外部國際化情形、內部廠商特徵、無形能力、人員特徵五面向分述,並發現相對於資訊電子工業,傳統產業創新廠商較其未創新時生產力提升之效益明顯。
    The dissertations include two articles: “After-Hours Information, Stock Prices, and Trading Volume: Evidence from the U.S.-China Trade Dispute” and “Firm Innovation and Productivity”.
    The first study examines the relationship between after-hours information and stock prices and trading volume during the U.S.-China trade dispute period. Since the time overlap may cause simultaneity and causality issues, a method to control the time lag is proposed. Supporting the argument of the literature, the nature of the information will affect stock prices, and the information volume will affect trading volume. However, the finding that the information search volume does not affect the stock prices is different from the literature. Noise traders who are more influenced by information than fundamentals may exist and affect the Taiwan stock market.
    The second study examines the innovation tendency of manufacturing firms, exploring the innovation effect on productivity. As opposed to the methodology used by Crowley and McCann (2018), the propensity score matching and the coarsened exact matching are used to estimate the average treatment effect. Also, different from the literature that used survey data, census data is used. The results of this study discuss the five major dimensions of innovation factors (the technical conditions, external internationalization, internal manufacturer characteristics, invisible abilities, and employee characteristics) and the reasons for the high innovation effectiveness of traditional industries.
    參考文獻: 第一篇
    Beaver, W. H. (1968). The information content of annual earnings announcements. Journal of Accounting Research, 6, 67-92.
    Bijl, L., Kringhaug, G., Molnár, P., & Sandvik, E. (2016). Google searches and stock returns. International Review of Financial Analysis, 45, 150-156.
    Black, F. (1986). Noise. The Journal of Finance, 41(3), 528-543.
    Capaul, C., Rowley, I., & Sharpe, W. F. (1993). International value and growth stock returns. Financial Analysts Journal, 49(1), 27-36.
    Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461-1499.
    De Groot, C. G., & Verschoor, W. F. (2002). Further evidence on Asian stock return behavior. Emerging Markets Review, 3(2), 179-193.
    De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of Political Economy, 98(4), 703-738.
    Dimpfl, T., & Jank, S. (2016). Can internet search queries help to predict stock market volatility? European Financial Management, 22(2), 171-192.
    Fama, E. F., & French, K. R. (1992). The cross‐section of expected stock returns. The Journal of Finance, 47(2), 427-465.
    Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56.
    Hasan, M. B., Alam, M. N., Amin, M. R., & Rahaman, M. A. (2015). The size and value effect to explain cross-section of expected stock returns in Dhaka stock exchange. International Journal of Economics and Finance, 7(1), 14-23.
    Hu, S. Y. (1998). The effect of turnover on stock returns in Taiwan. Journal of Financial Studies, 5(4), 1-19.
    Hu, C., & Wang, Y. (2013). Noise trading and stock returns: evidence from China. China Finance Review International.
    Joseph, K., Wintoki, M. B., & Zhang, Z. (2011). Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search. International Journal of Forecasting, 27(4), 1116-1127.
    Kim, O., & Verrecchia, R. E. (1991). Trading volume and price reactions to public announcements. Journal of Accounting Research, 29(2), 302-321.
    Lakonishok, J., Shleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. The Journal of Finance, 49(5), 1541-1578.
    Li, Y. L., Tu, Y. C., & Wang, W. H. (2017). Google search volume index and its effects on stock return and trading volume of Taiwan stock market. Journal of Management and Systems, 24(4), 565-590.
    Merton, R. C. (1973). An intertemporal capital asset pricing model. Econometrica, 41(5), 867-887.
    Moussa, F., Delhoumi, E., & Ouda, O. B. (2017a). Stock return and volatility reactions to information demand and supply. Research in International Business and Finance, 39, 54-67.
    Moussa, F., BenOuda, O., & Delhoumi, E. (2017b). The use of open source internet to analysis and predict stock market trading volume. Research in International Business and Finance, 41, 399-411.
    Pae, J., Thornton, D. B., & Welker, M. (2005). The link between earnings conservatism and the price‐to‐book ratio. Contemporary Accounting Research, 22(3), 693-717.
    Peress, J., & Schmidt, D. (2021). Noise traders incarnate: Describing a realistic noise trading process. Journal of Financial Markets, 54, 100618.
    Shleifer, A., & Summers, L. H. (1990). The noise trader approach to finance. Journal of Economic Perspectives, 4(2), 19-33.
    Vlastakis, N., & Markellos, R. N. (2012). Information demand and stock market volatility. Journal of Banking & Finance, 36(6), 1808-1821.
    Wang, George Y., Chang, J., & Dai, H. L. (2011). Style investing - Evidence from Taiwan stock markets. Tunghai Management Review, 13(1), 1-46.
    Xu, J., & Zhang, S. (2014). The fama-french three factors in the Chinese stock market. China Accounting and Finance Review, 16(2), 210-227.

    第二篇
    中文部分
    江雅玲(2000),《臺灣製造業中小企業對外直接投資傾向影響因素之研究》,淡江大學產業經濟學系碩士論文。
    行政院主計總處編(2019),《105年工業及服務業普查報告》,臺北市:主計總處。
    佟家棟、彭支偉(2007),從“幹中學”到“加工中學”——經濟全球化背景下的國際分工、技術外溢與自主創新,《南開學報:哲學社會科學版》,(6),71-81。
    林麗貞(2008),創新外溢與台灣經濟成長之計量分析,《台灣經濟論衡》,6(3),52-72。
    金京、戴翔、張二震(2013),全球要素分工背景下的中國產業轉型升級,《中國工業經濟》,(11),57-69。
    張兆銘(2018),《技術創新與廠商績效之研究 - 台灣電子零組件製造業》,國立中央大學產業經濟研究所在職專班碩士論文。
    彭亦寗(2017),《主治醫師性別對病患住院死亡率與再住院率之影響-以內科為例》,國立成功大學經濟學系碩士。
    馮文娜(2010),高新技術企業研發投入與創新產出的關係研究——基於山東省高新技術企業的實證,《經濟問題》,(9),74-78。
    焦文娟(2022),《模特兒培訓個人工作室創新商業模式之研究》,國立臺灣師範大學國際時尚高階管理碩士在職專班碩士論文。
    游珮雯(2018),《研發、創新活動與廠商績效之研究》,國立中央大學產業經濟研究所碩士論文。
    楊桂菊(2009),本土代工企業自創國際品牌——演進路徑與能力構建,《管理科學》,(6),38-45。
    廖錦文、鄭博文、江耀宗、俞錚蓉、石宜正(2016),比較偏遠與一般地區學生數學表現之差異:傾向分數配對法的分析,《科學教育學刊》,24,549-572。
    劉云、石金濤(2010),組織創新氣氛對員工創新行為的影響過程研究,《中國軟科學》,(3),133-144。
    劉志彪(2005),中國沿海地區製造業發展:國際代工模式與創新,《南開經濟研究》,(5),37-44、58。
    劉穎馥(2015),《企業教育訓練對員工創新影響之探討》,中原大學國際經營與貿易研究所碩士論文。
    賴立瑋(2014),《家族企業與薪資酬勞對創新的影響-台灣半導體產業之實證研究》,中原大學國際經營與貿易研究所碩士論文。
    謝中興(2020),代工廠商的創新升級與產業動態,《經濟論文叢刊》,48(2),269-299。
    關秉寅、李敦義(2008),補習數學有用嗎?一個「反事實」的分析,《臺灣社會學刊》,41,97-148。
    龔軼、顧高翔、劉昌新、王錚(2013),技術創新推動下的中國產業結構進化,《科學學研究》,(8),1252-1259。
    英文部分
    Abimbola, T. (2001). Branding as a competitive strategy for demand management in SMEs. Journal of Research in Marketing and Entrepreneurship, 3(2), 97-106.
    Agostini, L., Galati, F., & Gastaldi, L. (2020). The digitalization of the innovation process: Challenges and opportunities from a management perspective. European Journal of Innovation Management, 23(1), 1-12.
    Allred, B. B., & Park, W. G. (2007). The influence of patent protection on firm innovation investment in manufacturing industries. Journal of International Management, 13(2), 91-109.
    Alsos, G. A., Hytti, U., & Ljunggren, E. (2016). Gender and innovation–an introduction. In Research Handbook on Gender and Innovation (pp. 3-16). Edward Elgar Publishing.
    Audretsch, D. B., & Belitski, M. (2022). The knowledge spillover of innovation. Industrial and Corporate Change, 31(6), 1329-1357.
    Balasubramanian, N., & Lee, J. (2008). Firm age and innovation. Industrial and Corporate Change, 17(5), 1019-1047.
    Becker, S. O., & Ichino, A. (2002). Estimation of average treatment effects based on propensity scores. The Stata Journal, 2(4), 358-377.
    Becker-Blease, J. R., Kaen, F. R., Etebari, A., & Baumann, H. (2010). Employees, firm size and profitability of U.S. manufacturing industries. Investment Management and Financial Innovations, 7(2).
    Blackwell, M., Iacus, S., King, G., & Porro, G. (2009). cem: Coarsened exact matching in Stata. The Stata Journal, 9(4), 524-546.
    Calder, B. J., & Calder, E. S. (2012). Brand‐led innovation. Kellogg on Marketing, 332-347.
    Coad, A., Holm, J. R., Krafft, J., & Quatraro, F. (2018). Firm age and performance. Journal of Evolutionary Economics, 28, 1-11.
    Coad, A., Segarra, A., & Teruel, M. (2016). Innovation and firm growth: does firm age play a role? Research Policy, 45(2), 387-400.
    Comanor, W. S., & Scherer, F. M. (1969). Patent statistics as a measure of technical change. Journal of Political Economy, 77(3), 392-398.
    Crépon, B., Duguet, E., & Mairessec, J. (1998). Research, innovation and productivity: an econometric analysis at the firm level. Economics of Innovation and New Technology, 7(2), 115-158.
    Criscuolo, C., Haskel, J. E., & Slaughter, M. J. (2010). Global engagement and the innovation activities of firms. International Journal of Industrial Organization, 28(2), 191-202.
    Crowley, F., & McCann, P. (2018). Firm innovation and productivity in Europe: evidence from innovation-driven and transition-driven economies. Applied Economics, 50(11), 1203-1221.
    De Bondt, R. (1997). Spillovers and innovative activities. International Journal of Industrial Organization, 15(1), 1-28.
    Encaoua, D., Guellec, D., & Martínez, C. (2006). Patent systems for encouraging innovation: Lessons from economic analysis. Research policy, 35(9), 1423-1440.
    Fang, X., Paez, N. R., & Zeng, B. (2021). The nonlinear effects of firm size on innovation: an empirical investigation. Economics of Innovation and New Technology, 30(1), 48-65.
    Heller, M. A., & Eisenberg, R. S. (1998). Can patents deter innovation? The anticommons in biomedical research. Science, 280(5364), 698-701.
    Huergo, E., & Jaumandreu, J. (2004). Firms` age, process innovation and productivity growth. International Journal of Industrial Organization, 22(4), 541-559.
    Khachoo, Q., & Sharma, R. (2016). FDI and innovation: An investigation into intra-and inter-industry effects. Global Economic Review, 45(4), 311-330.
    Leiponen, A. (2005). Skills and innovation. International Journal of Industrial Organization, 23(5-6), 303-323.
    Love, J. H., Roper, S., & Du, J. (2009). Innovation, ownership and profitability. International Journal of Industrial Organization, 27(3), 424-434.
    Lööf, H., & Heshmati, A. (2006). On the relationship between innovation and performance: A sensitivity analysis. Economics of Innovation and New Technology, 15(4-5), 317-344.
    Merrilees, B. (2007). A theory of brand‐led SME new venture development. Qualitative Market Research, 10 (4), 403-415.
    OECD/Eurostat (2018), Oslo Manual 2018: Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition, The Measurement of Scientific, Technological and Innovation Activities, OECD Publishing, Paris/Eurostat, Luxembourg
    Parrilli, M. D., Balavac, M., & Radicic, D. (2020). Business innovation modes and their impact on innovation outputs: Regional variations and the nature of innovation across EU regions. Research Policy, 49(8), 104047.
    Pecis, L. (2016). Doing and undoing gender in innovation: Femininities and masculinities in innovation processes. Human Relations, 69(11), 2117-2140.
    Rachinger, M., Rauter, R., Müller, C., Vorraber, W., & Schirgi, E. (2018). Digitalization and its influence on business model innovation. Journal of Manufacturing Technology Management, 30(8), 1143-1160.
    Roper, S., Du, J., & Love, J. H. (2008). Modelling the innovation value chain. Research Policy, 37(6-7), 961-977.
    Sharma, P., Davcik, N. S., & Pillai, K. G. (2016). Product innovation as a mediator in the impact of R&D expenditure and brand equity on marketing performance. Journal of Business Research, 69(12), 5662-5669.
    Shefer, D., & Frenkel, A. (2005). R&D, firm size and innovation: an empirical analysis. Technovation, 25(1), 25-32.
    Sinaga, O., Lis, M., & Razimi, M. S. A. (2019). Education and core skills in the performance with mediating role of employee innovation. Polish Journal of Management Studies, 19(2), 363-373.
    Yanadori, Y., & Cui, V. (2013). Creating incentives for innovation? The relationship between pay dispersion in R&D groups and firm innovation performance. Strategic Management Journal, 34(12), 1502-1511.
    描述: 博士
    國立政治大學
    經濟學系
    103258503
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0103258503
    資料類型: thesis
    顯示於類別:[經濟學系] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    850301.pdf1571KbAdobe PDF20檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋