Data Sparseness and Variance in Accounting Profitability
Organizational Research Methods , Volume 18 - Issue 4 p. 656- 678
A central question in strategic management is why some firms perform better than others. One approach to addressing this question empirically is to decompose the variance in firm-level profitability into firm, industry, location, and year components. Although it is well established that data sparseness in variance decomposition studies can lead to overestimating particular variance components, little attention has been paid to sample size requirements in strategic management studies that have examined the nature of differences in firm profitability. We conduct a meta-regression and variance decomposition study and conclude that the variation in the results from previous studies is driven—to a considerable extent—by the number of observations per group within a component. Based on these findings, we draw conclusions regarding the validity and reliability of previous variance decomposition studies and provide implications for current debates in the strategic management literature.
|data sparseness, firm profitability, meta-analysis, variance decomposition|
|ERIM Top-Core Articles|
|Organizational Research Methods|
|Organisation||Erasmus University Rotterdam|
Stavropoulos, S, Burger, M.J, & Skuras, D. (2015). Data Sparseness and Variance in Accounting Profitability. Organizational Research Methods, 18(4), 656–678. doi:10.1177/1094428115574517