Productivity Change in Health Care

Economic

Are Medical Prices Declining?

We address long-standing problems in measuring health care prices by estimating two medical care price indices. The first, a Service Price Index, prices specific medical services, as does the current CPI. The second, a Cost of Living Index, measures the net valuation of treating a health problem. We apply these indices to heart attack treatment between 1983 and 1994. Because of technological change and increasing price discounts, the current CPI overstates a chain-weighted price index by three percentage points annually. For plausible values of an additional life-year, the real Cost of Living Index fell about 1 percent annually.

Pricing Heart Attack Treatments

In this paper, we estimate price indices for heart attack treatments, demonstrating the techniques that are currently used in official price indices and presenting some alternatives. We consider two types of price indices, a Service Price Index, which prices specific treatments provided, and a Cost of Living Index, which prices the health outcomes of patients. Both indices are complicated by price measurement issues: list prices and transactions prices are fundamentally different in the medical care field. The development of new or modified medical treatments further complicates the comparison of like' goods over time. And the Cost of Living Index is hampered by the need to determine how much of health improvement results from medical treatments in comparison to other factors. We describe methods to address each of these obstacles. We conclude that whereas traditional price indices when applied to heart attack treatments are rising at roughly 3 percent per year above general inflation, a corrected service price index is rising at perhaps 1 to 2 percent per year above general inflation, and the cost of living index is falling by 1 to 2 percent per year relative to general inflation. We discuss the implications of these results for official price index calculations.

Analysis and Control of a Variable-Pitch Quadrotor for Agile Flight

Fixed-pitch quadrotors are popular research and hobby platforms largely due to their mechanical simplicity relative to other hovering aircraft. This simplicity, however, places fundamental limits on the achievable actuator bandwidth and the possible flight maneuvers. This paper shows that many of these limitations can be overcome by utilizing variable-pitch propellers on a quadrotor. A detailed analysis of the potential benefits of variable-pitch propellers over fixed-pitch propellers for a quadrotor is presented. This analysis is supported with experimental testing to show that variable-pitch propellers, in addition to allowing for generation of reverse thrust, substantially increase the maximum rate of thrust change. A nonlinear, quaternion-based control algorithm for controlling the quadrotor is also presented with an accompanying trajectory generation method that finds polynomial minimum-time paths based on actuator saturation levels. The control law and trajectory generation algorithms are implemented on a custom variable-pitch quadrotor. Several flight tests are shown, which highlight the benefits of a variable-pitch quadrotor over a standard fixed-pitch quadrotor for performing aggressive and aerobatic maneuvers.National Science Foundation (U.S.) (0645960

Efficient reinforcement learning for robots using informative simulated priors

Autonomous learning through interaction with the physical world is a promising approach to designing controllers and decision-making policies for robots. Unfortunately, learning on robots is often difficult due to the large number of samples needed for many learning algorithms. Simulators are one way to decrease the samples needed from the robot by incorporating prior knowledge of the dynamics into the learning algorithm. In this paper we present a novel method for transferring data from a simulator to a robot, using simulated data as a prior for real-world learning. A Bayesian nonparametric prior is learned from a potentially black-box simulator. The mean of this function is used as a prior for the Probabilistic Inference for Learning Control (PILCO) algorithm. The simulated prior improves the convergence rate and performance of PILCO by directing the policy search in areas of the state-space that have not yet been observed by the robot. Simulated and hardware results show the benefits of using the prior knowledge in the learning framework

Strategic Surrogates or Sad Sinners: U.S. Taxation of Bartering in Digital Services

The COVID-19 pandemic caused both a surge in technology use and a deterioration in government finances. At the same time, big tech companies are under scrutiny by lawmakers for tax avoidance, antitrust issues, and other concerns. These realities call for governments to reassess tax policy toward tech companies and for tech companies to reassess legal strategy toward taxes. State and federal governments\u27 tax bases are eroding because of the noncash, barter nature of modern transactions. When a taxpayer uses “free” digital services such as e-mail, social media, or search engines, she pays via access to her personal data or attention. From a legal and policy standpoint, these barter transactions should be taxed just as if cash had changed hands, but because it is not practicable to identify, value, and tax the data and time of each user, they have escaped taxation, giving many tech companies an unintended tax advantage. To address this unfairness, this article proposes a surrogate tax, through which the tech company acts as a proxy to pay the tax that is technically the liability of its users. In contrast to Digital Services Taxes (DSTs), which have been the main focus of policy makers and the extant literature, surrogate taxes adhere closely to standards of good tax policy, providing an administrable means of capturing untaxed digital barter while advancing fairness across the industry\u27s business models. From a legal strategy standpoint, this article argues that tech companies themselves should support surrogate taxes, to avoid facing more onerous, “sin”-like taxes, such as DSTs

Lightweight infrared sensing for relative navigation of quadrotors

A lightweight solution for estimating position and velocity relative to a known marker is presented. The marker consists of three infrared (IR) LEDs in a fixed pattern. Using an IR camera with a 100 Hz update rate, the range and bearing to the marker are calculated. This information is then fused with inertial sensor information to produce state estimates at 1 kHz using a sigma point Kalman filter. The computation takes place on a 14 gram custom autopilot, yielding a lightweight system for generating high-rate relative state information. The estimation scheme is compared to data recorded with a motion capture system.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant No. 0645960