Abstract
Event studies generally seek to measure abnormal security performance associated with firm-specific events. In principle, estimators of and tests for abnormal performance should appropriately reflect cross-sectional dependence between abnormal returns to different se? curities. Joint generalized least squares provides a natural framework for developing such estimators and tests. This paper derives a joint generalized least squares estimator and related test statistic applicable in the typical event study context. Simulation techniques comparable to those of Brown and Warner [2] are used to assess the frequency distribution of the estimator and power of the test statistic. Several simpler procedures are simulated for comparison. The results provide no evidence that joint generalized least squares is superior to simpler procedures.
Keywords
Event (particle physics)Joint (building)Least-squares function approximationMathematicsStatisticsComputer scienceEconometricsStructural engineeringPhysicsEngineering
Related Publications
On the Validity of Econometric Techniques with Weak Instruments
Abstract We evaluate Angrist and Krueger (1991) and Bound, Jaeger, and Baker (1995) by constructing reliable confidence regions around the 2SLS and LIML estimators for returns-t...
An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
Abstract In this paper a method of estimating the parameters of a set of regression equations is reported which involves application of Aitken's generalized least-squares [1] to...
Applied Linear Regression
Preface.1 Scatterplots and Regression.1.1 Scatterplots.1.2 Mean Functions.1.3 Variance Functions.1.4 Summary Graph.1.5 Tools for Looking at Scatterplots.1.5.1 Size.1.5.2 Transfo...
On a Complete Class of Linear Unbiased Estimators for Randomized Factorial Experiments
Consider a factorial system of order $N = p^m$, which consists of $m$ factors each at $p$ levels. The factorial model relates the expected yield to the various treatment combina...
Dynamic panel estimation and homogeneity testing under cross section dependence *
This paper deals with cross section dependence, homogeneity restrictions and small sample bias issues in dynamic panel regressions. To address the bias problem we develop a pane...
Publication Info
- Year
- 1986
- Type
- article
- Volume
- 21
- Issue
- 1
- Pages
- 27-27
- Citations
- 144
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
144
OpenAlex
Cite This
Paul Malatesta
(1986).
Measuring Abnormal Performance: The Event Parameter Approach Using Joint Generalized Least Squares.
Journal of Financial and Quantitative Analysis
, 21
(1)
, 27-27.
https://doi.org/10.2307/2330988
Identifiers
- DOI
- 10.2307/2330988