方法对比

	Tobin's Q Firm Value Analysis	Event Study Methodology
领域	战略管理	战略管理
方法族	Regression model	Process / pipeline
起源年份	1981	1997
提出者	Eric B. Lindenberg & Stephen A. Ross; Kee H. Chung & Stephen W. Pruitt	A. Craig MacKinlay; Stephen J. Brown & Jerold B. Warner
类型	Market-valuation ratio used as a firm performance and rent measure	Abnormal-return estimation pipeline for valuing corporate events
开创性文献	Lindenberg, E. B., & Ross, S. A. (1981). Tobin's q Ratio and Industrial Organization. Journal of Business, 54(1), 1-32.	MacKinlay, A. C. (1997). Event Studies in Economics and Finance. Journal of Economic Literature, 35(1), 13-39.
别名	Tobin's Q Ratio Analysis, Market-to-Replacement-Cost Analysis, Q-Ratio Firm Performance Measure, Approximate Tobin's Q	Abnormal Returns Analysis, Cumulative Abnormal Return (CAR) Analysis, Stock-Market Event Study, Market-Model Event Study
相关	3	3
摘要	Tobin's q is the ratio of a firm's market value to the replacement cost of its assets, and it serves in strategy and industrial organization as a forward-looking measure of value creation and economic rent. A q above one means the market values the firm at more than it would cost to rebuild its assets, signaling that the firm earns rents -- from market power, brands, technology, or hard-to-replicate capabilities -- beyond the competitive return on capital. Lindenberg and Ross's 1981 study brought q into empirical industrial organization, developing an algorithm to estimate the replacement cost of assets and showing how q relates to monopoly power and barriers to entry. Because exact replacement costs are laborious, Chung and Pruitt's 1994 paper introduced a simple approximation built entirely from standard accounting and market data that tracks the exact measure closely, making q practical for large-sample research on firm performance.	Event study methodology measures the stock-market reaction to a discrete corporate event by isolating the portion of a firm's return that cannot be explained by normal market movements. Under semi-strong market efficiency, new information about an acquisition, earnings announcement, alliance, CEO change, or regulatory shock is impounded into prices almost immediately, so the abnormal return around the event date is a clean, forward-looking estimate of the event's value consequences. A. Craig MacKinlay's 1997 survey codified the canonical pipeline -- define the event and windows, estimate a normal-return benchmark, compute abnormal returns, accumulate them into a cumulative abnormal return (CAR), and test significance. Brown and Warner's 1985 study established the statistical properties of these procedures with daily data, showing when simple methods are well specified and how variance and clustering must be handled. The method is the workhorse for linking strategic decisions to shareholder value.