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This study provides a history and an inventory and analysis of existing public sector accounting principles in India from the time of independence from the British in 1947 through the economic reforms of the nineties. It also analyses the factors that are affecting the current evolution in governmental accounting from an ineffective bureaucratic system to an informative decision making tool, utilizing Luder’s Contingency Model of Public Sector Accounting.

This study examines whether nonprofit hospitals (NPHs) use price increases to overstate reported charity care spending. Anecdotal evidence points to hospitals raising prices to maximize Medicare's supplemental reimbursement and to maximize collection from self-pay and uninsured patients. This study provides empirical evidence that NPHs raise prices in part to satisfy the state's charity care requirements and to substitute real care with price-valued charity care. The ratio of charges to costs (RCC), price standardized by cost - a measure for comparing revenues generated to estimate costs allocations, is used to test the association between price increases and charity care reporting by NPHs. We hypothesize and find evidence that NPHs facing financial and political pressures in addition to charity care regulations are more likely to report a higher value of charity care.

We examine the factors that associate with local government decisions to comply with Generally Accepted Accounting Principles (GAAP). GAAP non-compliance is surprisingly common among larger local governments, and that trend has important implications for public policy, financial management transparency, and government accountability. To examine the factors that drive GAAP compliance, we develop a conceptual framework based on the politico-economic perspective on accounting policy choice, and then test that model with data from a national survey of local government finance professionals. Our key contribution is that we incorporate accounting professionalism. The findings suggest that for many local governments the decision to adopt GAAP is a response to the pressures of professionalism rather than a rational response to political and economic motives.

This paper examines if country level corruption affects the size of a country’s stock market and its ability to raise equity capital. Using Transparency International’s ranking of countries based on corruption levels, we relate the corruption index to total market capitalization for a sample of 104 countries and also examine the number and volume of new equity issues in each country across time. Additionally, we examine if corruption affects the frequency of foreign firms’ raising capital in the U.S. We find that the corruption index is not highly correlated to either the number of issues or the total volume of issue. The correlation between the average volume of issue and the TI index suggests that there is no clear cut relation between the corruption index and the likelihood of the firm raising capital abroad.

This paper looks at the importance of forecasted information as a key input to investors decision models. The research design uses accounting variables suggested by financial accounting theory, industry variables and economic variables. Analysis of the data indicated that only return on investment yield and capital intensity were associated with earnings. In an environment of rapidly changing economic conditions and attendant uncertainty, the scrutiny of forecast accuracy has is crucial. For a firm, the allocation of resources is based upon forecasts of financial information that may affect its survival. Earnings and dividends forecast, and the growth rates in these forecast are key informational inputs in investor decision models (Chang and Most, 1980). In addition, Securities and Exchange Commission, recognizing the importance of this subjective and non‐verifiable information, permits and encourages firms to include financial forecasts in their annual reports by granting them a “safe harbor”. The accounting profession responded to this demand for forecasted information by producing audit guidelines for these forecasts. Accounting‐based financial forecasts are used in a variety of ways. Banks and non bank financial institutions use forecasts to evaluate credit. Earnings forecasts are useful to financial analysts who attempt to isolate a firm's intrinsic characteristics such as residual income after removing the effect of economy and industry conditions through the use of index models. Auditors use accounting forecasts as a basis for expectations concerning reported items to determine the extent of detailed tests (Stringer, 1975; Kinney, 1978). Lev (1980, p.525) stated that the “… crucial stage of the analytical review process is the generation of expected, or reasonable, values of financial statement items.” Managers use internally generated earnings forecasts for resource allocation decisions concerning present operations as well as future operations and expansions/contractions.

Earnings forecasts provide useful numerical information concerning the expectations of a firm's future prospects and indicate management's ability to anticipate a firm's changing internal structure and external environment. The reasons for studying the accuracy of earnings forecasts is due to the Securities and Exchange Commission's position on financial forecasts and the issuance of a Statement of Position by the AICPA. These statements are important since they, in part, have motivated researchers to the importance of forecasting financial information. Consequently, if the disclosure of earnings forecasts in financial reports is permissable, the improvement of financial forecasts should be one of the primary concerns of the AICPA, the SEC, and numerous other interested groups.

Accounting studies have attempted to forecast future attributes of firms' financial statements, primarily earnings. These studies typically adopt a cross‐sectional approach in estimating forecasting models, combining firms from different industries in the same model. This cross‐sectional approach implicitly assumes the relations between earnings and the explanatory variables are consistent across industries.