How should we estimate value-relevance models? Insights from European data
We study the consequences of unobserved heterogeneity when employing different econometric methods in the estimation of two major value-relevance models: the Price Regression Model (PRM) and the Return Regression Model (RRM). Leveraging a large panel data set of European listed companies, we first d...
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| Format: | Article |
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Elsevier
2017
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| Online Access: | https://eprints.nottingham.ac.uk/52467/ |
| _version_ | 1848798733288865792 |
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| author | Onali, Enrico Ginesti, Gianluca Vasilakis, Chrysovalantis |
| author_facet | Onali, Enrico Ginesti, Gianluca Vasilakis, Chrysovalantis |
| author_sort | Onali, Enrico |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | We study the consequences of unobserved heterogeneity when employing different econometric methods in the estimation of two major value-relevance models: the Price Regression Model (PRM) and the Return Regression Model (RRM). Leveraging a large panel data set of European listed companies, we first demonstrate that robust Hausman tests and Breusch-Pagan Lagrange Multiplier tests are of fundamental importance to choose correctly among a fixed-effects model, a random-effects model, or a pooled OLS model. Second, we provide evidence that replacing firm fixed-effects with country and industry fixed-effects can lead to large differences in the magnitude of the key coefficients, with serious consequences for the interpretation of the effect of changes in earnings and book values per share on firm value. Finally, we offer recommendations to applied researchers aiming to improve the robustness of their econometric strategy. |
| first_indexed | 2025-11-14T20:24:28Z |
| format | Article |
| id | nottingham-52467 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:24:28Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-524672020-05-04T19:09:59Z https://eprints.nottingham.ac.uk/52467/ How should we estimate value-relevance models? Insights from European data Onali, Enrico Ginesti, Gianluca Vasilakis, Chrysovalantis We study the consequences of unobserved heterogeneity when employing different econometric methods in the estimation of two major value-relevance models: the Price Regression Model (PRM) and the Return Regression Model (RRM). Leveraging a large panel data set of European listed companies, we first demonstrate that robust Hausman tests and Breusch-Pagan Lagrange Multiplier tests are of fundamental importance to choose correctly among a fixed-effects model, a random-effects model, or a pooled OLS model. Second, we provide evidence that replacing firm fixed-effects with country and industry fixed-effects can lead to large differences in the magnitude of the key coefficients, with serious consequences for the interpretation of the effect of changes in earnings and book values per share on firm value. Finally, we offer recommendations to applied researchers aiming to improve the robustness of their econometric strategy. Elsevier 2017-09-30 Article PeerReviewed Onali, Enrico, Ginesti, Gianluca and Vasilakis, Chrysovalantis (2017) How should we estimate value-relevance models? Insights from European data. British Accounting Review, 49 (5). pp. 460-473. ISSN 0890-8389 Value-relevance ; Linear information model ; IFRS ; Price regression model ; Return regression model ; Panel data https://www.sciencedirect.com/science/article/pii/S0890838917300306 doi:10.1016/j.bar.2017.05.006 doi:10.1016/j.bar.2017.05.006 |
| spellingShingle | Value-relevance ; Linear information model ; IFRS ; Price regression model ; Return regression model ; Panel data Onali, Enrico Ginesti, Gianluca Vasilakis, Chrysovalantis How should we estimate value-relevance models? Insights from European data |
| title | How should we estimate value-relevance models? Insights from European data |
| title_full | How should we estimate value-relevance models? Insights from European data |
| title_fullStr | How should we estimate value-relevance models? Insights from European data |
| title_full_unstemmed | How should we estimate value-relevance models? Insights from European data |
| title_short | How should we estimate value-relevance models? Insights from European data |
| title_sort | how should we estimate value-relevance models? insights from european data |
| topic | Value-relevance ; Linear information model ; IFRS ; Price regression model ; Return regression model ; Panel data |
| url | https://eprints.nottingham.ac.uk/52467/ https://eprints.nottingham.ac.uk/52467/ https://eprints.nottingham.ac.uk/52467/ |