The Role of Accounting Conservatism in Firms' Financial Decisions.

摘要

This dissertation investigates whether financial reporting conservatism is related to firms' financial flexibility and their financial decisions. If conservatism facilitates monitoring and governance by capital providers, they should be more willing to extend financing and increase firms' access to capital. However, because conservatism leads to systematic understatement of net worth and weakens the appearance of firms' balance sheet strength, it could also reduce firms' access to capital. This study tests these two opposing views of the relationship between conservatism and financial flexibility and its effect on corporate financial activities. Results indicate that firms with greater reporting conservatism exhibit less financial flexibility in their corporate liquidity management, in their debt or equity issuance decisions, in the sensitivity of their investments to financing constraints and in their payout policies. Overall, results suggest that although firms enjoy lower debt contracting costs and mitigate agency conflicts by reporting conservatively, they forgo some financial flexibility in future access to capital, and this affects their financial decisions.;In the third chapter, I provide a critical evaluation of the primary measure of reporting conservatism employed in the second chapter. Although there is substantial interest in research on accounting conservatism, there is no consensus among researchers on the most appropriate measure of conservatism in empirical studies. Dichev and Tang (2008) introduce a new measure of conservatism, which they believe to be a "natural and practical measure of conservatism." However, the econometric properties of this measure have not been fully evaluated in prior work, and prior studies have not provided evidence of this measure's construct validity. Based on a parsimonious model of conservatism, I find that the Dichev and Tang (2008) measure is increasing in the conservatism parameter. However, although this measure produces well-specified test statistics that generate Type 1 errors according to researchers' specifications, it generates tests of low power that lead to relatively high Type 2 errors. Next, I use actual data to support the construct validity of this measure. Finally, I suggest an alternative measure using the reverse regression specification of the Dichev and Tang (2008) model.