This study investigates how religiosity (i.e., the strength of religion) differences across countries influence an important characteristic of financial reporting, accounting conservatism. Prior literature suggests that religious individuals are more risk averse and have higher ethical standards, while accounting conservatism has been shown to reduce various risks to the firm (e.g., bankruptcy and stock price crashes) at the expense of higher reported earnings. We find that managers in more religious societies report more conservatively. Specifically, our cross-country analysis reveals that firms headquartered in countries with higher levels of religiosity exhibit, on average, higher accounting conservatism in financial reporting. This positive association is stronger in countries following IFRS or U.S. GAAP, and weaker in countries with a high degree of uncertainty avoidance, strong legal enforcement, and countries with greater numbers of religions. JEL Classifications: G34; M41; Z12. Data Availability: Data are available from the public sources cited in the text.

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This paper examines whether aggregate conditional and unconditional conservatism are associated with economic growth. Prior studies find that conditional conservatism improves contracting efficiency, but that unconditional conservatism has either a neutral or detrimental impact on contracting. We therefore conjecture that country‐level conditional conservatism increases the efficiency of resource allocation in an economy, whereas country‐level unconditional conservatism is not similarly beneficial. Using a cross‐country sample, we construct country‐level estimates of conditional and unconditional conservatism. We find that conditional conservatism is associated with higher level of growth in Gross Domestic Product and Gross Domestic Product per Capita. By contrast, unconditional conservatism shows no or negative association. Our study contributes to the ongoing debate on the desirability of accounting conservatism and also extends the literature on the macroeconomic effects of aggregate financial reporting attributes.

Principal component analysis (PCA) and factor analysis (FA) are variable reduction techniques used to represent a set of observed variables in terms of a smaller number of variables. While PCA and FA are similar along several dimensions (e.g., extraction of common components/factors), researchers often fail to recognize that these techniques achieve different goals and can produce significantly different results. We conduct a comprehensive review of the use of PCA and FA in accounting research. We offer guidelines on programming PCA and FA in SAS/Stata and emphasize the importance of implementation techniques as well as the disclosure choices made when utilizing these methodologies. Furthermore, we present intuitive, practical examples highlighting the differences between the techniques and provide suggestions for researchers considering the use of these procedures. Finally, based on our review, we provide recommendations, observations, notes, and citations to the literature, regarding the implementation of PCA and FA in accounting.

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