the relevance of the informational content of book-tax differences for predicting future income: evidence from latin american countries

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ID: 150626
2016
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Abstract
This study aims to investigate whether the different types of book-tax differences are useful for predicting the future income of publicly traded companies in five Latin American countries. This is possible since these differences convey information about transitory components of income, which can be used by investors for predicting future income. However, little is known about the relationship between tax variables and companies' future results. The sample analyzed here is composed of 580 publicly traded companies from five Latin American countries (Argentina, Brazil, Chile, Mexico, and Peru) with information available in the Economatica(r) database covering 2002 to 2013. In terms of methodology, regressions are employed in order to find a connection between the different types (total, permanent, temporary, and the negative and positive variations) of book-tax differences and companies' current and future earnings per share, as well as some control variables suggested by previous literature. The model's coefficients were estimated through panel data techniques: fixed effects. The results obtained suggest that the information gathered in the different types of book-tax differences (total, permanent, temporary, positive and negative variations) is relevant in predicting future income. Total, permanent and temporary differences contribute to the uncertainty in future income prediction, given that results are more transitory and less persistent in years with higher book-tax differences. Positive and negative variations, on the other hand, attribute higher income in coming years to greater variations in book-tax differences, representing increased timeliness of results and a reduction in off balance sheet funding for the publicly traded companies from these countries.
Reference Key
marques2016revistathe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Alessandra Vieira Cunha Marques;Patrícia de Souza Costa;Pablo Rogers Silva
Journal international journal of copd
Year 2016
DOI
10.1590/1808-057x201501570
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