406,202 research outputs found
An Agency Theory of Dividend Taxation
Recent empirical studies of dividend taxation have found that: (1) dividend tax cuts cause large, immediate increases in dividend payouts, and (2) the increases are driven by firms with high levels of shareownership among top executives or the board of directors. These findings are inconsistent with existing "old view" and "new view" theories of dividend taxation. We propose a simple alternative theory of dividend taxation in which managers and shareholders have conflicting interests, and show that it can explain the evidence. Using this agency model, we develop an empirically implementable formula for the efficiency cost of dividend taxation. The key determinant of the efficiency cost is the nature of private contracting. If the contract between shareholders and the manager is second-best efficient, deadweight burden follows the standard Harberger formula and is second-order (small) despite the pre-existing distortion of over-investment by the manager. If the contract is second-best inefficient -- as is likely when firms are owned by diffuse shareholders because of incentives to free-ride when monitoring managers -- dividend taxation generates a first-order (large) efficiency cost. An illustrative calibration of the formula using empirical estimates from the 2003 dividend tax reform in the U.S. suggests that the efficiency cost of raising the dividend tax rate could be close to the amount of revenue raised.
A systematic approach for monitoring and evaluating the construction project progress
A persistent problem in construction is to document changes which occur in the field and to prepare the as-built schedule. In current practice, deviations from planned performance can only be reported after significant time has elapsed and manual monitoring of the construction activities are costly and error prone. Availability of advanced portable computing, multimedia and wireless communication allows, even encourages fundamental changes in many jobsite processes. However a recent investigation indicated that there is a lack of systematic and automated evaluation and monitoring in construction projects. The aim of this study is to identifytechniques that can be used in the construction industry for monitoring and evaluating the
physical progress, and also to establish how current computer technology can be utilised for monitoring the actual physical progress at the construction site. This study discusses the results of questionnaire survey conducted within Malaysian Construction Industry and suggests a prototype system, namely Digitalising Construction Monitoring (DCM). DCM prototype system
integrates the information from construction drawings, digital images of construction site progress and planned schedule of work. Using emerging technologies and information system the DCM re-engineer the traditional practice for monitoring the project progress. This system can automatically interpret CAD drawings of buildings and extract data on its structural components and store in database. It can also extract the engineering information from digital images and when these two databases are simulated the percentage of progress can be calculated and viewed in Microsoft Project automatically. The application of DCM system for monitoring the project progress enables project management teams to better track and controls the productivity and quality of construction projects. The use of the DCM can help resident engineer, construction manager and site engineer in monitoring and evaluating project performance. This model will improve decision-making process and provides better mechanism for advanced project management
Great Bay Estuary Water Quality Monitoring Program: Quality Assurance Project Plan 2019 - 2023
Fair Labor Association 2006 Annual Public Report
Introduction concerns effects of globalization. Examines changes from 2005-2006 as companies are encouraged to move towards self compliance, with a concentration on corporate responsibility. Data is broken down by company
Great Bay Estuary Tidal Tributary Monitoring Program (GBETTMP): Quality Assurance Project Plan 2019 - 2023
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