计量经济分析 = Econometric analysis

1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Our article comprehensively reexamines the performance of variables that have been suggested by the academic literature to be good predictors of the equity premium. We find that by and large, these models have predicted poorly both in-sample (IS) and out-of-sample (OOS) for 30 years now; these models seem unstable, as diagnosed by their out-of-sample predictions and other statistics; and these models would not have helped an investor with access only to available information to profitably time the market.

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A Comprehensive Look at the Empirical Performance of Equity Premium Prediction

Goyal and Welch (2007) argue that the historical average excess stock return forecasts future excess stock returns better than regressions of excess returns on predictor variables. In this article, we show that many predictive regressions beat the historical average return, once weak restrictions are imposed on the signs of coefficients and return forecasts. The out-of-sample explanatory power is small, but nonetheless is economically meaningful for mean-variance investors. Even better results can be obtained by imposing the restrictions of steady-state valuation models, thereby removing the need to estimate the average from a short sample of volatile stock returns. (JEL G10, G11) Towards the end of the last century, academic finance economists came to take seriously the view that aggregate stock returns are predictable. During the 1980s, a number of papers studied valuation ratios, such as the dividend-price ratio, earnings-price ratio, or smoothed earnings-price ratio. Value-oriented investors in the tradition of Graham and Dodd (1934) had always asserted that high valuation ratios are an indication of an undervalued stock market and should predict high subsequent returns, but these ideas did not carry much weight in the academic literature until authors such as Rozeff (1984), Fama and French (1988), and Campbell and Shiller (1988a, 1988b) found that valuation ratios are positively correlated with subsequent returns and that the implied predictability of returns is substantial at longer horizons. Around the same time, several papers pointed out that yields on short- and long-term treasury and corporate bonds are correlated with subsequent stock returns (Fama and Schwert,1977;KeimandStambaugh,1986;Campbell,1987;FamaandFrench, 1989).

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Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?

Economics Of Discrimination

There is no consensus in the literature regarding the financial consequences of megamergers in part due to the difficulty in establishing a good counterfactual. By comparing the performance of these deals to the performance of synthetic mergers constructed using a novel matching procedure, we find no significant changes in return on assets after megamergers. This apparent non-result is driven by merged firms subsidizing their increased operating inefficiencies with higher markups. We show that this cross-subsidization effect is stronger in larger deals and in more concentrated industries, suggesting that our findings are driven by market power and quiet life considerations.

Alexander W. Butler

Papers

The Worst of Both Worlds: Megamergers are Anticompetitive and Inefficient

Financial Breakups