Expensing Isn\u27t the Only Option: Alternatives to the FASB\u27s Stock Option Expensing Proposal

This paper reviews the arguments for and against the Financial Accounting Standard Board\u27s (FASB) proposal to require that corporations expense options. It identifies two major goals of the proposed rule -- 1) clarity in financial statements and 2) a reduction of corporate fraud by removing the incentive of options. To address these two goals, I adopt a framework of Information Reforms v. Rules of the Game Reforms. The article starts with a history of FASB Statement No. 123 Accounting for Stock-based Compensation and also analyzes the Congressional legislation that attempts to block the measure, the Stock Option Accounting Reform Act. I review the opinions of leading economists on the accuracy of the option valuation schemes advocated by the FASB and conclude that the models are too easily manipulated to advance the FASB goals of clarity in accounting. I conclude that neither the FASB proposed rule nor the Congressional legislation advances the goal of clarity in financial statements. The article suggests alternative measures that would better serve the interests of investors. I argue that a more accurate solution to the expense problem would be to adopt the IRS method for valuing stock options -- intrinsic value at date of exercise. This accounting method tracks the cash flow out of the corporation since it reflects either an actual repurchase of shares issued by the company or a lost opportunity cost. In addition, I propose that corporations be required to only use fully diluted, in-the-money capitalization when computing EPS. This measure would address the FASB\u27s concerns that the employee is given a valuable equity instrument at date of grant without there being a reflection in the company\u27s financials. Finally, I review the literature that analyzes the impact of the FASB proposal on companies and the economy as a whole. The data shows that the FASB measure will not result in a reduction of corporate accounting fraud and the measure will result in a loss of productivity among American firms that use options to incentivize workers. I argue that the FASB proposed rule should be considered independent of considerations such as a reduction in fraud. The measure should solely be considered as an Information Reform, which by its nature is meant to improve the clarity of information rather than modify behavior. Modifying the behavior of executives who commit fraud or boards of directors who make large option grants requires more fundamental Rules of the Game Reforms rather than Information Reforms. Typical Rules of the Game Reforms would shift the power from management and the Board of Directors to shareholders and might include restrictions on the sale of executive stock so as to better align the interests of shareholders and employees

Optimal language policy for the preservation of a minority language

We develop a dynamic language competition model with dynamic state intervention. Parents choose the language(s) to raise their children based on the communicational value of each language as well as on their emotional attachment to the languages at hand. Languages are thus conceptualized as tools for communication as well as carriers of cultural identity. The model includes a high and a low status language, and children can be brought up as monolinguals or bilinguals. Through investment into language policies, the status of the minority language can be increased. The aim of the intervention is to preserve the minority language in a bilingual subpopulation at low costs. We investigate the dynamic structure of the optimally controlled system as well as the optimal policy, identify stable equilibria and provide numerical case studies

AMST: Alignment to Median Smoothed Template for Focused Ion Beam Scanning Electron Microscopy Image Stacks

Alignment of stacks of serial images generated by focused ion Beam Scanning electron Microscopy (FIB-SEM) is generally performed using translations only, either through slice-by-slice alignments with SIFT or alignment by template matching. However, limitations of these methods are two-fold: the introduction of a bias along the dataset in the z-direction which seriously alters the morphology of observed organelles and a missing compensation for pixel size variations inherent to the image acquisition itself. These pixel size variations result in local misalignments and jumps of a few nanometers in the image data that can compromise downstream image analysis. We introduce a novel approach which enables affine transformations to overcome local misalignments while avoiding the danger of introducing a scaling, rotation or shearing trend along the dataset. Our method first computes a template dataset with an alignment method restricted to translations only. This pre-aligned dataset is then smoothed selectively along the z-axis with a median filter, creating a template to which the raw data is aligned using affine transformations. Our method was applied to FIB-SEM datasets and showed clear improvement of the alignment along the z-axis resulting in a significantly more accurate automatic boundary segmentation using a convolutional neural network