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題名:經濟學實證研究:市場訊息與廠商創新活動
作者:戴瑋澍
作者(外文):Tai, Wei-Shu
校院名稱:國立政治大學
系所名稱:經濟學系
指導教授:陳鎮洲
學位類別:博士
出版日期:2023
主題關鍵詞: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 volumeNoise tradersStock pricesTrading volumeU.S.-China trade disputeInnovationInnovation determinantsPropensity scoreProductivityTreatment effect
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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.
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第二篇
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