Prescription Drug Coverage and Elderly Medicare Spending

The introduction of Medicare Part D has generated interest in the cost of providing drug coverage to the elderly. Of paramount importance -- often unaccounted for in budget estimates -- are the salutary effects that increased prescription drug use might have on other Medicare spending. This paper uses longitudinal data from the Medicare Current Beneficiary Survey (MCBS) to estimate how prescription drug benefits affect Medicare spending. We compare spending and service use for Medigap enrollees with and without drug coverage. Because of concerns about selection, we use variation in supply-side regulations of the individual insurance market -- including guaranteed issue and community rating -- as instruments for prescription drug coverage. We employ a discrete factor model to control for individual-level heterogeneity that might induce bias in the effects of drug coverage. Medigap prescription drug coverage increases drug spending by $170 or 22$350 or 13% (in 2000 dollars). Medigap prescription drug coverage reduces Medicare Part B spending, but the estimates are not statistically significant. Overall, a $1 increase in prescription drug spending is associated with a$2.06 reduction in Medicare spending. Furthermore, the substitution effect decreases as income rises, and thus provides support for the low-income assistance program of Medicare Part D.

Policy Options to Improve the Performance of Low Income Subsidy Programs for Medicare Beneficiaries

Outlines options for establishing a unified annual Medicare deductible, uniform coinsurance, and limits on out-of-pocket spending and providing better protection to low-income beneficiaries and beneficiaries with the greatest health care needs

Energy Price Reform: A Guide for Policymakers

This essay reviews the conceptual and quantitative literature on the efficient system of fossil fuel energy prices in different countries for reflecting supply and environmental costs, as well as the environmental, fiscal, and economic benefits from energy price reform. Drawing on recent experiences in numerous countries, the ingredients for successful reform are then discussed (e.g., the need for a comprehensive reform strategy and for compensating vulnerable groups). Low energy prices, fiscal pressures, and momentum for climate action provide an especially conducive environment for price reform and much is happening rapidly on the ground, however there is a long way to go to reap the enormous benefits at stake (e.g., at the global level, over a 20 percent reduction in carbon emissions and revenues gains of 4 percent of GDP)

Evaluating Policies to Implement the Paris Agreement: A Toolkit with Application to China

This paper describes a model, implemented in an Excel spreadsheet, for evaluating a wide range of fiscal and regulatory instruments policymakers might consider for implementing their Paris mitigation pledges. Policies are evaluated against a range of metrics, including impacts on carbon dioxide (CO2) emissions, revenue, deaths from local air pollution, economic welfare benefits and costs, and incidence across household and industry groups. The model is applied to China, the world's largest emitter, but could be readily transferred to most other countries

Feature extraction of the weak periodic signal of rolling element bearing’ early fault based on shift invariant sparse coding

When fault such as pit failure arises in the rolling element bearing the vibration signal of which will take on periodic characteristics, and the abrupt failure of rotating machinery can be avoided effectively if the weak periodic characteristics of the early fault stage is extracted timely. However, the periodic characteristics of bearing’ early weak fault is hard to be extracted usually and the reasons can be boiled to as following: Firstly, the weak periodic signal of rolling element bearing’ early fault stage is buried by the strong background noise. Secondly, the weak fault cannot show the complete shock attenuation impulsive characteristic due to its weak energy, so the traditional wavelet transform would not work effectively if a proper wavelet basis function fitting for analyzing the impulsive characteristics is not selected. To solve the above two problems, a feature extraction method of the weak periodic signal of rolling element bearing’ early fault based on Shift Invariant Sparse Coding (SISC) originating from sparse representation is proposed in the paper. To capture the underlying structure of machinery fault signal, SICS provides an effective basis functions learning scheme by solving the flowing two convex optimization problems iteratively: 1) L1-regularized least squares problem. 2) L2-constrained least squares problem. The fault feature can be probably contained and extracted if optimal latent component is filtered among these basis functions. The feasibility and effectiveness of the proposed method are verified through the corresponding simulation and experiment