Internal Revenue Service

About: Internal Revenue Service is a based out in . It is known for research contribution in the topics: Taxpayer & Tax credit. The organization has 171 authors who have published 185 publications receiving 3338 citations. The organization is also known as: IRS & Agenzia delle Entrate – Ministero dell’Economia e delle Finanze.

Reminders and Recidivism: Using Administrative Data to Characterize Nonfilers and Conduct EITC Outreach

Abstract: This project uses third-party information reporting and population-level administrative tax data to identify the population of nonfilers This population consists of individuals who do not file a tax return despite having income reported by third parties to the United States Internal Revenue Service After identifying and characterizing this population, we identified nonfilers who may have been eligible for Earned Income Tax Credit (EITC) benefits Using an experimental sample drawn from this population of potentially EITC-eligible nonfilers, we conducted two randomized controlled trials to test multiple hypotheses regarding inattention and recency effects in these low-income earners' tax filing decisions

Elderly Asset Management and Health: An Empirical Analysis

Abstract: We present models of asset management by the elderly. We focus on saving, spend-down of assets, and gift-giving, and the influence of health on these precesses. We also study the evolution of elderly health and the impact of economic variables on health outcomes. We present results from estimating our models using data from waves one and two of the AHEAD dataset. Our model of asset management links elderly decisions about saving, spend-down of assets, and gift-giving in a system of equations. We divide households for which head and partner (if present) are in poor health and those for which head and partner are in good health; our specification allows for differences in health to affect both the average level of economic outcomes and the marginal effects of income and wealth on the outcomes. We also include in our model a set of sociodemographic control variables. Our model of health outcomes links health in the preceding period to health in the current period, allowing for three outcomes good health, poor health, or death. In our models of health outcomes we include variables measuring health in the previous period, wealth, age, education, and control variables. Our main results are the following. First, results for gift-giving suggest that at least some elderly do plan their estate transfer - those that have established trust funds or for which households assets exceed the estate tax filling threshold have a significantly greater propensity to give gifts. Second, the average level of gift-giving is lower for those in poor health, but the marginal effect of increasing wealth on gift-giving is much greater. This result is important in showing the ways in which health can interact with economic variables in influencing economic decision-making. Third, income is an important determinant of saving and spend-down. Fourth, other things equal, households that save are also more likely to give gifts. Fifth, sudden changes in family structure and health are associated with changing patters of economic behavior - most especially, becoming a widow or widower is associated with a significant increase in the likelihood both of spending out of assets and of making gifts. Finally, variables related to children have less effect on propensity to give gifts than expected - the only variable that has a significant effect is the number of children for which parents cannot provide income information, suggesting that the quality of the relationship between parents and children is important for gift-giving.

Projections of health care expenditures as a share of the GDP: actuarial and macroeconomic approaches.

Abstract: STUDY QUESTION. Can the steady increases in health care expenditures as a share of GDP projected by widely cited actuarial models be rationalized by a macroeconomic model with sensible parameters and specification? DATA SOURCES. National Income and Product Accounts, and Social Security and Health Care Financing Administration are the data sources used in parameters estimates. STUDY DESIGN. Health care expenditures as a share of gross domestic product (GDP) are projected using two methodological approaches--actuarial and macroeconomic--and under various assumptions. The general equilibrium macroeconomic approach has the advantage of allowing an investigation of the causes of growth in the health care sector and its consequences for the overall economy. DATA COLLECTION METHODS. Simulations are used. PRINCIPAL FINDINGS. Both models unanimously project a continued increase in the ratio of health care expenditures to GDP. Under the most conservative assumptions, that is, robust economic growth, improved demographic trends, or a significant moderation in the rate of health care price inflation, the health care sector will consume more than a quarter of national output by 2065. Under other (perhaps more realistic) assumptions, including a continuation of current trends, both approaches predict that health care expenditures will comprise between a third and a half of national output. In the macroeconomic model, the increasing use of capital goods in the health care sector explains the observed rise in relative prices. Moreover, this "capital deepening" implies that a relatively modest fraction of the labor force is employed in health care and that the rest of the economy is increasingly starved for capital, resulting in a declining standard of living.

A dual-mode evolutionary algorithm for designing optimized refrigerant circuitries for finned-tube heat exchangers

Abstract: Heat exchanger performance is strongly influenced by the refrigerant circuitry, ie, the connection sequence of the tubes This article describes an evolutionary computation-based approach for designing an optimized refrigerant circuitry used in an intelligent system for heat exchanger design The technique used in this design employs two methods to generate designs implemented separately in two modules: the knowledge-based evolutionary computation module and the symbolic-learning-based evolutionary computation module The optimization example presented in this article employed each module independently and used the combined approach to demonstrate the performance of each module and the power of the combined module approach The best circuitry designs determined through these optimization runs yielded substantial capacity improvements over the original design; the symbolic-learning- and knowledge-based modules returned circuitry designs that improved the heat exchanger capacity by 26% and 48%, respecti