Earnings Management and Measurement Error

In this paper I consider the impact of a noisy indicator regarding a manager’s manipulative behavior on optimal effort incentives and the extent of earnings management. The analysis in this paper extends a twotask, single performance measure LEN model by including a binary random variable. I show that contracting on the noisy indicator variable is not always useful. More specifically, the principal uses the indicator variable to prevent earnings management only under conditions where manipulative behavior is not excessive. Thus, under conditions of excessive earnings management, accounting adjustments that yield a more congruent overall performance measure can be more effective than an appraisal of the existence of earnings management to mitigate the earnings management problem.

Who has really paid for the Reconstruction of East Germany? Expected and Realized Returns on Real Estate Investments in East and West Germany in the 1990s

We evaluate the profitability of investments in residential property in Germany after unification with a focus on the comparison of East and West Germany. Calculations are carried out for (1) the after-tax return an investor might have expected at the beginning of the 1990s, and (2) the after-tax return that has been realized ten years after. We compare a set of statistical data for investments in fifty major cities by using complete financial budgeting. The results show that tax subsidies could not always protect investors from losing money, but they have boosted realized returns after tax considerably. Therefore, it was indeed the taxpayers, not the investors, who have borne the cost of reconstructing East Germany.

Economic Loan Loss Provision and Expected Loss

The intention of a loan loss provision is the anticipation of the loan's expected losses by adjusting the book value of the loan. Furthermore, this loan loss provision has to be compared to the expected loss according to Basel II and, in the case of a difference, liable equity has to be adjusted. This however assumes that the loan loss provision and the expected loss are based on a similar economic rationale, which is only valid conditionally in current loan loss provisioning methods according to IFRS. Therefore, differences between loan loss provisions and expected losses should only result from different approaches regarding the parameter estimation within each model and not due to different assumptions regarding the outcome of the model. The provisioning and accounting model developed in this paper overcomes the before-mentioned shortcomings and is consistent with an economic rationale of expected losses. Additionally, this model is based on a close-to-market valuation of the loan that is in favor of the basic idea of IFRS. Suggestions for changes in current accounting and capital requirement rules are provided.