Strategy Research and Panel Data: Evidence and Implications
A number of studies in strategic management rely on panel (longitudinal) data to test theory. The advantages of panel data notwithstanding, such data introduce analytic problems (e.g., autocorrelation, heteroskedasticity, contemporaneous correlation) that make traditional estimators (e.g., ordinary...
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| Vydáno v: | Journal of management Ročník 32; číslo 3; s. 449 - 471 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Thousand Oaks, CA
Sage Publications
01.06.2006
Sage Publications Ltd |
| Témata: | |
| ISSN: | 0149-2063, 1557-1211 |
| On-line přístup: | Získat plný text |
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| Abstract | A number of studies in strategic management rely on panel (longitudinal) data to test theory. The advantages of panel data notwithstanding, such data introduce analytic problems (e.g., autocorrelation, heteroskedasticity, contemporaneous correlation) that make traditional estimators (e.g., ordinary least squares) inappropriate. This study highlights the influence of contemporaneous correlation, a statistical problem that affects the analysis of panel data. Using Monte Carlo simulations, the authors find that contemporaneous correlation is particularly problematic when analyzing data sets typically used in strategic management research. They suggest straightforward techniques to mitigate the harmful effects of contemporaneous correlation. |
|---|---|
| AbstractList | A number of studies in strategic management rely on panel (longitudinal) data to test theory. The advantages of panel data notwithstanding, such data introduce analytic problems (e.g., autocorrelation, heteroskedasticity, contemporaneous correlation) that make traditional estimators (e.g., ordinary least squares) inappropriate. This study highlights the influence of contemporaneous correlation, a statistical problem that affects the analysis of panel data. Using Monte Carlo simulations, the authors find that contemporaneous correlation is particularly problematic when analyzing data sets typically used in strategic management research. They suggest straightforward techniques to mitigate the harmful effects of contemporaneous correlation. A number of studies in strategic management rely on panel (longitudinal) data to test theory. The advantages of panel data notwithstanding, such data introduce analytic problems (e.g., autocorrelation, heteroskedasticity, contemporaneous correlation) that make traditional estimators (e.g., ordinary least squares) inappropriate. This study highlights the influence of contemporaneous correlation, a statistical problem that affects the analysis of panel data. Using Monte Carlo simulations, the authors find that contemporaneous correlation is particularly problematic when analyzing data sets typically used in strategic management research. They suggest straightforward techniques to mitigate the harmful effects of contemporaneous correlation. [PUBLICATION ABSTRACT] |
| Author | Certo, S. Trevis Semadeni, Matthew |
| Author_xml | – sequence: 1 givenname: S. Trevis surname: Certo fullname: Certo, S. Trevis email: tcerto@tamu.edu organization: Department of Management, Texas A&M University, College Station, TX 77845-4221 – sequence: 2 givenname: Matthew surname: Semadeni fullname: Semadeni, Matthew organization: Department of Management, University of South Carolina, Columbia, SC 29208 |
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| Keywords | heteroskedasticity contemporaneous correlation panel data research methodology autocorrelation longitudinal data |
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| SubjectTerms | Correlation analysis Data analysis Inappropriateness Monte Carlo simulation Panel data Research methodology Strategic management Studies |
| Title | Strategy Research and Panel Data: Evidence and Implications |
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