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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Biographical Sketches of Panel Members and Staff

ERIC A. HANUSHEK (Chair) is professor of economics and political science at the University of Rochester. During 1983-1985, he served as deputy director of the Congressional Budget Office. He previously held academic appointments at Yale University and the U.S. Air Force Academy and governmental appointments at the Cost of Living Council and the Council of Economic Advisers. He is a past president of the Association for Public Policy Analysis and Management. His primary academic interests have involved applied public finance and public policy analysis with special reference to schooling and aspects of income determination. He received a B.S. degree from the United States Air Force Academy and a Ph.D. degree in economics from the Massachusetts Institute of Technology.

DAVID M. BETSON is an associate professor in the Department of Economics at the University of Notre Dame. He was previously a research associate at the Institute for Research on Poverty at the University of Wisconsin and a staff economist at the U.S. Department of Health, Education, and Welfare. His research has dealt with the impact of federal tax and transfer programs on the economy and the distribution of income. He received a B.A. degree from Kalamazoo College and a Ph.D. degree from the University of Wisconsin.

LYNNE BILLARD is professor of statistics and associate to the dean of the Franklin College of Arts and Sciences at the University of Georgia. She was formerly head of the statistics and computer science department at the university and has held faculty positions and visiting positions at other U.S. universities and in England and Canada. Her current research interests include time series,

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

sequential analysis, stochastic processes, and AIDS. She is a fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. She has held many professional offices, including president of the Biometric Society, Eastern North American Region, and associate editor and associate book editor for the Journal of the American Statistical Association. She is currently a member of the International Council of the Biometric Society and the Council of the International Statistical Institute. She received a B.S. honors degree in mathematics and statistics and a Ph.D. degree in statistics from the University of New South Wales, Australia.

CONSTANCE F. CITRO (Study Director) is a member of the staff of the Committee on National Statistics. She is a former vice president and deputy director of Mathematica Policy Research, Inc., and was an American Statistical Association/National Science Foundation (NSF)/Census research fellow at the Bureau of the Census. For the Committee on National Statistics, she has served or is serving as study director for the Panel to Study the NSF Scientific and Technical Personnel Data System, the Panel on Decennial Census Methodology, the Panel on Statistics on Supply and Demand for Precollege Science and Mathematics Teachers, and the Panel to Evaluate the Survey of Income and Program Participation. Her research has focused on the usefulness and accessibility of large, complex microdata files, as well as analysis related to income measurement and demographic change. She is a fellow of the American Statistical Association. She received a B.A. degree from the University of Rochester and M.A. and Ph.D. degrees in political science from Yale University.

MICHAEL L. COHEN is an assistant professor in the School of Public Affairs at the University of Maryland. He was formerly a visiting lecturer at the Department of Statistics, Princeton University, and a research associate at the Committee on National Statistics. His general area of research is the use of statistics in public policy, and his current research concerns whether and how to adjust the census for undercoverage. He received a B.S. degree in mathematics from the University of Michigan and M.S. and Ph.D. degrees in statistics from Stanford University.

SHELDON DANZIGER is professor of social work and public policy and faculty associate at the Institute of Public Policy Studies at the University of Michigan, where he also directs the Research and Training Program on Poverty, the Underclass, and Public Policy. From 1983 to 1988 he was director of the Institute for Research on Poverty, professor of social work, and Romnes Faculty Fellow at the University of Wisconsin. He is the coeditor of several books on poverty and public policy and the author of numerous scholarly articles on poverty, income inequality, and social welfare programs and policies. He is a member of the Committee on Child Development Research and Public Policy

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

at the National Research Council and of the Social Science Research Council's Committee for Research on the Urban Underclass. He was a member of the Panel on Employment, Income, and Occupations for the National Research Council's Committee on the Status of Black Americans. He received a B.A. degree from Columbia University and a Ph.D. degree in economics from the Massachusetts Institute of Technology.

EUGENE P. ERICKSEN is a professor and chair of the Department of Sociology at Temple University. He is currently cochair of the Special Advisory Panel on the 1990 Census, which was convened by the U.S. Secretary of Commerce for advice on the possibility of adjusting the census results for the differential undercount. His research interests focus on the estimation of local-area characteristics from sample data, survey sampling, and problems of survey measurement in general. He received a B.S. degree in mathematics from the University of Chicago and an M.S. degree in statistics and a Ph.D. degree in sociology from the University of Michigan.

THOMAS J. ESPENSHADE is professor of sociology and faculty associate of the Office of Population Research at Princeton University. He was formerly director of the Program in Demographic Studies and senior fellow at the Urban Institute in Washington, D.C. His research interests have included the cost of raising children; changes in U.S. family structure; the demographic and economic consequences of slowing population growth in developed countries; and the demographic, economic, and social implications of immigration to the United States. He has written widely on contemporary U.S. immigration and immigrant policy and has testified before Congress on changes in U.S. immigration policy. His current research is related to developing models of undocumented migration to the United States; the role of undocumented migrants in California agriculture; determinants of public attitudes toward undocumented migrants and illegal migration; and proposed reforms of U.S. policy toward legal immigration. He received a B.A. degree in economics from the College of Wooster and a Ph.D. degree in economics and demography from Princeton University.

HARVEY GALPER is a principal in the Policy Economics Group of KPMG Peat Marwick in Washington, D.C. His prior positions include senior fellow at the Brookings Institution, senior public finance resident at the Advisory Commission on Intergovernmental Relations, and director of the Office of Tax Analysis of the U.S. Department of the Treasury. He has also served on the staffs of the Urban Institute and the Board of Governors of the Federal Reserve System and has taught at Dartmouth College, the University of California at Berkeley, Yale University, and the Georgetown University Law Center. He is a past member of the board of directors of the National Tax Association-Tax Institute of America and of the Advisory Group of the Commissioner of the

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Internal Revenue Service, and currently serves on the editorial board of the National Tax Journal. He received a B.A. degree from Dartmouth College and M.A. and Ph.D. degrees, both in economics, from Yale University.

LOUIS GORDON is professor of mathematics at the University of Southern California. Previously, he was statistician at the ALZA Corporation and at the Energy Information Administration of the U.S. Department of Energy. His interests are in the analysis of computation-intensive statistical algorithms. He is a member of the Committee on National Statistics at the National Research Council and a fellow of the Institute of Mathematical Statistics. He received a B.S. degree in mathematics from Michigan State University and a Ph.D. degree in statistics from Stanford University.

KEVIN M. HOLLENBECK is senior economist at the W.E. Upjohn Institute for Employment Research. He was formerly with Mathematica Policy Research, Inc., where he developed a number of components of a microsimulation model. He has also been a consultant to a number of federal agencies to conduct studies with and to evaluate specific microsimulation models. His current research interests are in analysis and evaluation of education and training programs. He received a B.S. degree in mathematics from Michigan State University and M.S. and Ph.D. degrees in economics from the University of Wisconsin.

GORDON H. LEWIS is associate professor of sociology at Carnegie Mellon University, with appointments in the School of Urban and Public Affairs and in the Department of Engineering and Public Policy. His major research interest involves income transfers, especially modeling of the interactions among transfer programs; his recent work has focused substantively on areas of child support, tax rebates, and marriage policy. Other research interests include organizational design, organizational management, and individual decision making. He received both undergraduate and graduate degrees in sociology from Stanford.

ROBERT MOFFITT is a professor of economics at Brown University. He is a fellow of the Institute for Research on Poverty at the University of Wisconsin and a research associate of the National Bureau of Economic Research. His research interests cover the economics of welfare and other government benefit programs, statistical methods for the evaluation of public policy programs, and the study of labor force and demographic trends of American women. He has served on a committee for the Social Science Research Council on the Survey of Income and Program Participation and on the U.S. Department of Labor's National Advisory Panel for the National Longitudinal Study, and has been a consultant to the National Research Council's Panel on the Evaluation of AIDS Programs. He is chief editor of the Journal of Human Resources. He received a B.A. degree from Rice University and M.A. and Ph.D. degrees from Brown University.

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

CHRISTINE M. ROSS, who served as research associate during the first year of the study, is currently an economist with Mathematica Policy Research, Inc., in Princeton, N.J. Before working with the panel, she was associate analyst with the Human Resources and Community Development Division of the Congressional Budget Office, where she worked with microsimulation models on food stamp and Aid to Families with Dependent Children program policy. She received a B.A. degree in economics from Williams College and M.A. and Ph.D. degrees in economics from the University of Wisconsin.

GAIL R. WILENSKY, who served as a member of the panel during 1989, is now administrator of the Health Care Financing Administration of the U.S. Department of Health and Human Services (HHS). Previously, she was vice president for the division of health affairs of Project Hope and a senior research manager at the HHS National Center for Health Services Research where she designed and directed the analysis of the National Medical Care Expenditure Survey. She has served on the faculties of the University of Michigan and George Washington University and held a senior research appointment at the Urban Institute. She has published extensively on health economics and health policy. She is a member of the Institute of Medicine, and was a member of the Physician Payment Review Commission and the Health Advisory Committee of the General Accounting Office. She received a Ph.D degree in economics from the University of Michigan.

MICHAEL C. WOLFSON is director general of the Analytical Studies Branch, Statistics Canada. At Statistics Canada he led the group that developed a personal computer-based public-use microsimulation model of Canada's income tax/transfer system, the Social Policy Simulation Database and Model (SPSD/M). More recently, he has been engaged in a fundamental review of the health statistics program. From 1974 to 1985 he held a variety of positions with the Canadian federal public service, including the Treasury Board Secretariat, Department of Finance, and Privy Council Office, with responsibilities in the areas of program evaluation and tax and pension policy. He is also an appointed fellow of the Canadian Institute for Advanced Research in the Program in Population Health. He received a B.Sc. degree in computer science and economics from the University of Toronto and a Ph.D. degree in economics from Cambridge University.

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Index

A

Access to data, see User accessibility

Actuarial Research Corporation, 198

Administrative data, 22, 37, 44, 69-70, 104, 124, 163, 169, 199, 244-245, 248

evaluation of, 14, 15, 71, 141-142

survey data links, 62, 66-69, 129, 131-133, 137, 141-147 (passim), 149, 151, 169, 216-217, 277

see also Matching

see also specific data file names

Agency for Health Care Policy and Research, 201, 208, 275

Aging, see Data aging;

Elderly persons

Aid to Families with Dependent Children (AFDC), 9, 21-22, 21-24, 42-51, 77, 78, 129, 142, 156, 233-241, 248-259, 279

aging of data, 167

baseline, 107, 256

behavioral response, 170, 176

benefit-calculator models, 141, 186, 234, 278

costs, 21, 22, 23, 45, 47, 168, 233, 234, 245, 248, 250

distributional analysis, 45, 234, 248, 254-255

minimum benefit standard, 3, 24, 74, 257

participation, 136-137, 235, 246-247

AIDS, 196

American Housing Survey, 61

Archiving, see Documentation and archiving

Assistant Secretary for Planning and Evaluation (DHHS), 2, 22, 23, 24, 25, 26, 37, 42, 45-49 (passim), 97, 107, 110-111, 112, 113, 114 , 119, 137, 142, 161, 166, 185, 186, 187, 199-200, 201, 209, 221, 233, 274, 278

B

BAFPLAN model, 108

Baseline simulation, 105, 107, 124, 163, 291-298 (passim)

TRIM2, 107, 124, 256

see also Eligibility data and modeling

Basic research, 13, 38, 107-108, 281-283

Behavioral research, 17-18, 164-165, 176, 177, 181, 201-203, 217-219, 276, 282, 283-289

Behavioral response, 17, 41, 50-51, 120, 282-289, 303

AFDC, 170, 176

cost factors, models, 175, 181

design for, 153, 154, 155, 156, 163, 164, 170-181

DYNASIM2, 170, 171, 179

health care policy, 201-203, 209, 211

individual, 17, 48

MATH, 170, 171, 172, 174-175

model descriptions, specific, 216, 290-298 (passim)

parameterization, 17-18, 75-76, 107, 163, 173-174, 177, 180, 211, 218, 229, 282

PRISM, 170, 171

retirement income policies, 215, 217-219 337

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

taxpayers, 170, 171-172, 176, 178, 179, 226, 228-229

TRIM2, 170, 171, 172

uncertainty, 17-18, 75-76, 107, 173, 177, 180, 211, 282

see also Participation data and modeling

Second-round effects

Benefit-calculator models, 47, 141, 186, 234, 278, 279

Bias, estimation, 92, 94, 237, 240

Black Americans, 71, 126

Bootstrap techniques, 12, 91, 239-240

Brookings Institution, 109, 110, 204, 209, 220, 222, 294

Budget Act, 22, 36

Budget analysis, general, 1-24, 36-37

history, 35-37, 234

OMB, 37, 38, 49, 62, 63, 83, 137

state-level, 83-84

statistical programs budget, 6, 37, 56-59

tax policy, 220

see also Congressional Budget Office

Bureau of Economic Analysis, 59, 129

Bureau of Labor Statistics, 59, 69, 146, 205, 274

C

Calibration, 136, 237, 291-298 (passim), 303-304

see also Weighting

Canada, see Statistics Canada

CANSIM, 287

Carter Administration, 111, 171, 185, 194-195

CASE, 11, 190

Cell-based models, 2, 43-45, 53, 79, 111, 116, 199-200, 204, 213, 215, 238, 286, 304

see also specific models

Census Bureau, 33, 49, 59, 70, 221

confidentiality, 66, 67-68, 135, 216, 227, 228

databases, general, 11, 12, 15-16, 70, 71, 123-152

errors and error analysis, 14, 69, 70, 71-72, 86, 129, 140, 141, 151, 152

expanded role, 11, 12, 15-16, 149-152

see also Current Population Survey

Survey of Income and Program Participation

Committee on National Statistics, 2, 25, 26-27, 64, 68, 210

Community, microsimulation modeling, see Organizational factors

Computable general equilibrium models, 179, 180, 304-305

Computing technology, 11-12, 18, 27, 83, 121, 148, 182-193, 276

cost factors, 10, 18, 45-46, 121, 148, 163, 164, 182, 183, 184, 186 , 188, 189, 191, 193, 284, 285

design issues, 156, 158, 159, 191

DYNASIM2, 182, 183-184, 185, 186, 192

efficiency, 121, 158, 159

historical perspectives, 1. 24, 31, 34, 37, 162, 182-185, 186, 189

MATH, 185, 192

model descriptions, specific, 290-298 (passim)

personal computers, 34, 54, 108, 121, 186-187, 190, 191-192, 279

SPSD/M, 187-188, 191

TRIM2, 185, 186, 187-189, 191-192

validation and, 18, 192-193

workstations, 188, 189, 190, 191

see also Matching;

Software

User accessibility

Conferences, 20, 282-283

Confidence intervals, 79-80, 86, 87, 88, 92, 93-96, 244

Confidentiality, 66-69, 135, 207, 216, 227, 228

Congressional Budget Office, 21-24, 36-37, 42, 45, 46, 48, 61, 112 , 187, 190, 199, 203, 206, 221, 234

Consumer Expenditure Survey, 60, 136

Consumer Price Index (CPI), 58, 196

Continuous Medicare History Sample, 207

Contracts and contractors, 19, 261-262

external validation by, 5, 12, 19, 235-236, 262-263, 279-280

model vendors, 278, 290-298 (passim)

Control files, 136-137

see also Matching

CORSIM, 186

Cost factors, 24, 25, 56, 63-64, 76, 81, 105, 211, 213, 232, 285

AFDC. 21, 22, 23, 45, 47, 168, 233, 234, 245, 248, 250

aging of data, 17, 18, 49, 105, 154, 170, 237

behavioral response modeling, 175, 181

computing technology, 10, 18, 45-46, 121, 148, 163, 164, 182, 183, 184, 186, 188, 189, 191, 193, 284, 285

cost-effectiveness, 1, 2, 10, 26, 54, 110, 117-118, 148, 160, 181, 189, 192, 193, 196-197, 211, 215, 259, 260, 261, 265, 275, 279

health care financing, 53, 61, 111, 195-212

historical perspectives, 1, 37-38, 53, 182

matching files, CPS-SSA, 7-8, 67, 136

model design, 9, 11, 54, 153, 154, 155, 156, 160, 175, 181, 208

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

model development and operation, 9, 14, 45-46, 99, 112, 117-118, 156, 164, 181, 184, 186, 188, 189, 191, 208

sensitivity analysis, 259

statistical programs budget, 6, 37, 56-59

validation, 259, 260, 261

see also Budget analysis

Coverage of population, 11, 14, 71-72, 126-127, 138, 140, 151-152, 249-252

Cross-sectional models, 47, 221

see also specific models

Current Beneficiary Survey, 207, 210

Current Population Survey (CPS), 44, 45-46, 60, 69, 71

databases, 11, 15-16, 70, 71

described in detail, 126, 298-299

income data, 145, 146, 151, 174

linkages with SIPP, 144, 145, 146, 147, 228

March supplement, 15, 44-45, 67, 104, 120, 123-152 (passim), 174, 185, 204, 205, 207, 217, 220, 222, 227, 228, 244, 245, 248, 250, 256, 259-260

matching files, CPS-IRS, 67-68, 104, 110, 124, 134, 220, 224, 226-227, 228, 299, 307

matching files, CPS-SSA, 7-8, 18, 67, 104, 123-124, 134-135, 136, 216-217, 245, 277, 299

Current services estimates, 35

D

Data aging, 17, 18, 49, 105, 154, 163, 164-170, 205, 276

cost factors, 17, 18, 49, 105, 154, 170, 237

defined, 165, 302-303

design for, 154, 163, 164-170

dynamic, 49, 105, 106, 164, 166, 167-169, 214, 291, 295, 296

health care policy models, 198-199

MATH, 167, 168, 169, 170, 245, 302

retirement income models, 105, 214-215

static, 49, 105, 163, 164, 165-167, 169, 170, 198-199, 214-215, 221 , 225-226, 228, 249-250, 292, 293, 298, 302-303

tax policy models, 221, 225-226, 228, 229

TRIM2, 49, 107, 163, 166-168, 169, 170, 233

Databases, 1, 8, 9-10, 11, 15-16, 70, 104, 123-152, 277

access to, 14, 16, 66-69, 158, 159

Census Bureau, general, 11, 12, 15-16, 70, 71, 123-152

Current Population Survey, 11, 15-16, 70, 71, 123-152 (passim)

documentation and archiving, 12, 14, 19-20, 85-86

errors in, 78-79, 90-91, 119-120

evaluation, 15, 137

health care financing, 203-207

individual descriptions, 298-302

Integrated Quality Control System, 15, 43, 46, 131-132, 141, 142, 250, 253-255, 257, 299-300

models, specific descriptions, 290-298 (passim)

retirement income, 216-217

Survey of Income and Program Participation, 123, 137-152

tax policy, 223-226

see also Matching

Data collection, 7, 13-14, 63-65, 70, 141, 209, 211

see also Questionnaires

Surveys and survey data

Data quality, 3, 5-8, 13-14, 26-27, 55-72, 119-120, 123-152, 256

census statistics, 125-132, 139-152

existing data, value added, general, 69-72, 210, 277

health care financing, 203-208

input errors, 79, 90, 91

omissions, 131-137

quality profiles, 19, 51, 92, 140, 263-264

Decennial census, errors, 71-72, 86

Demography, see Population factors

Department of Agriculture, 2, 22, 25, 36, 97, 110

see also Food and Nutrition Service

Department of Health, Education, and Welfare, 35-36

Department of Health and Human Services, 2, 13, 18, 22, 37, 97, 110 , 201, 208, 209, 210, 211, 212, 274

see also specific agencies

Department of Labor, 111, 112, 198

Department of the Treasury, 3, 23, 35, 109, 110, 179, 220, 229

Office of Tax Analysis, 98, 110, 136, 220, 223-226, 274, 296

Treasury Individual Income Tax Simulation Model, 296-297

see also Internal Revenue Service

Design and development, models, 11, 16-18, 153-181

aging of data, 154, 163, 164-170

behavioral response, 153, 154, 155, 156, 163, 164, 170-181

computing technology and, 156, 158, 159, 191

cost factors, 9, 11, 54, 153, 154, 155, 156, 160, 175, 181, 208

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

cost factors, development and operation, 9, 14, 45-46, 99, 112, 117 -118, 156, 164, 181, 184, 186, 188, 189, 191, 208

Current Population Survey, March supplement, 126-129, 143

documentation and, 16, 157, 158, 159, 160, 190, 266, 267

health care policy models, 208-210

misspecification, 3, 79, 83, 87, 90, 91-92, 93, 94

modular, 16, 111, 155, 156-157, 157, 159, 161, 248

prototyping, 159, 160, 192-193, 199

second-round effects, 153, 154, 155, 163, 164, 178-181

SIPP, 138, 140, 146-148

standards, 16-17, 193, 276

validation and, 16, 157, 158, 159-160

Disaggregation, 61, 132-133, 179

Distributional analysis, 221, 237, 240, 305

AFDC, 45, 234, 248, 254-255

health care outlays, 198, 199

Documentation and archiving, 12, 14, 18, 19-20, 27, 140, 193, 157, 265-272

databases, 12, 14, 19-20, 85-86

design and, 16, 157, 158, 159, 160, 190, 266, 267

MATH, 26, 268, 269

social welfare models and data, 84-86

software, 12, 14, 17, 19, 85-86, 267-269, 270-271

standards, 12, 14, 19, 266-271

user accessibility and, 266, 267, 269, 270

validation and, 85, 157, 158, 266, 270, 271

DRI, 36, 307

Dynamic models, general, 18, 109, 51, 111-112, 123-124, 192-193, 213, 215, 284, 305

aging of data, 49, 105, 106, 164, 166, 167-169, 214, 291, 295, 296

see also specific models

Dynamic Simulation of Income Model (DYNASIM), 111-112, 183-184, 214 , 245-246

Dynamic Simulation of Income Model2 (DYNASIM2), 37, 98, 112, 123-124, 161, 169, 198, 213-218, 290-291

behavioral response, 170, 171, 179

computing requirements, 182, 183-184, 185, 186, 192

history, 111-112, 183-184, 214, 245-246

DYNASIM, see Dynamic Simulation of Income Model

E

Econometric models, general, 17, 35, 53, 92, 176

Economic factors

budget deficit, federal, 25, 37, 60, 61, 80, 163

statistical concepts and methods, changing, 58

see also Cost factors;

Funding

Economic indicators, see CPI

GNP

Elderly persons, 196, 201, 205

see also Medicare

Retirement income policies

Eligibility data and modeling, 45, 47, 105, 130, 131, 142, 205, 213 , 234, 256

filing units, 104, 229, 305-306

vs participation, 44, 64-65, 136-137, 151

Employee Benefit Survey, 205

Employment and unemployment, 43-45, 50, 65, 146, 170, 179, 202, 234

Errors and error analysis, 3, 14, 51, 55, 61, 74, 75, 76, 78-79, 83, 84, 90-91, 137, 142, 215, 247

bounds, 83, 86, 87, 88

census data, 14, 69, 70, 71-72, 86, 129, 140, 141, 151, 152

confidence intervals, 79-80, 86, 87, 88, 92, 93-96, 244

databases, 78-79, 90-91, 119-120

decennial census, 71-72, 86

internal validation and, 5, 78-79, 85

missing detail, 129-130, 132-137

see also Imputations

model misspecification, 3, 79, 83, 87, 90, 91-92, 93, 94

quality profiles, 19, 51, 92, 140, 141, 263-264

sampling, 3, 69, 78-79, 86, 88, 90, 91, 95, 129, 215, 244, 257

sensitivity analysis, 12, 18, 73, 78, 79-80, 82, 83, 91-92, 93, 94 , 99, 157, 158, 177, 192, 215, 218, 228, 229, 233, 235, 237-239, 242, 246, 248-261

see also Coverage of population

Data quality;

Uncertainty, Validation and evaluation

Estimation processes, 17, 26-27, 42-51, 70, 72-74, 78-79

bias, 92, 94, 237, 240

conditional/unconditional, 74-75, 76, 93-95 42-51

problems of, 48-51

see also Data aging;

Errors and error analysis;

Uncertainty, Variance estimation

Evaluation, see Validation and evaluation

Exact matches, see Matching

External validation, 5, 12, 19, 77-78, 82, 87-88, 94-95, 99, 233, 235-236, 238, 246, 262-263, 271, 279-280

TRIM2, 99, 233-239

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

F

Family Support Act, 3, 6, 21-24, 31, 41-51, 77, 176, 187, 195, 234 , 261, 279

Family Support Administration, 22, 49

Federal government, general, 1, 35

budget deficit, 25, 37, 60, 61, 80, 163

data quality, 6-7

interagency coordination, 6-7, 10, 12-13, 37, 62-63, 146, 149-150, 209, 210, 212, 274-277;

see also Matching

see also Laws, specific federal

Policy analysis agencies

Statistical agencies

specific departments and agencies

Filing units, 104, 229, 305-306

Food and Nutrition Service, 2, 22, 25, 26, 36, 97, 110, 113, 114, 142, 274, 278, 283

Food stamp program, 6, 23, 43, 46, 56, 110, 113, 123, 131, 133, 141-142 , 202, 244-245

Food Stamp Reform Act, 36, 110

Foreign countries, 108, 109, 193

see also specific countries

FOSTERS, 113, 143

Frankfurt model, 108

Funding, 19, 26, 59, 82, 278

research, 19, 39, 82

SIPP-CPS, 144, 146, 228

statistical agencies, general, 6, 37, 56-59, 61-62

G

General Accounting Office, 15, 77

Germany, Federal Republic, 108

Gramm-Rudman-Hollings Act, 37-38, 163, 219

Graphical interfaces, 121, 189, 190, 193

Gross National Product (GNP), 58, 60, 195, 196, 197

H

Health Benefits Simulation Model, 113, 205

Health Care Financing Administration, 22, 23, 190, 199, 201, 204, 207, 275

Health care policies, general, 18, 98, 111, 113, 124, 178, 194, 195-212, 274-275

cost, 53, 61, 111, 195-212

databases, 203-207

history, 197-200, 203-207, 208

long-term care, 202, 204, 209, 295-296

Medicaid, 65, 196, 198, 199, 201, 202-203, 204, 205, 207

Medicare, 61, 124, 178, 195, 199, 201, 202, 203, 207, 225

research, 201-203, 209, 211-212

see also Long-Term Care Financing Model;

Pension and Retirement Income Simulation Model

Health Financing Model, 111, 199-200

Health insurance, 196, 198, 199, 201, 202, 206, 209

Medigap policies, 201, 225

see also Medicaid;

Medicare

Health Interview Survey, 60, 200, 205, 207, 210

Health Resources Administration, 199

Historical perspectives, 1, 33, 154, 161-163, 269

aging of data, 166

budget analysis, 35-37, 234

computing technology, 1, 24, 31, 34, 37, 162, 182-185, 186, 189

cost factors, 1, 37-38, 53, 182

DYNASIM/DYNASIM2, 111-112, 183-184, 214, 245-246

health care models and surveys, 197-200, 203-207, 208

macroeconomic models, 35

MATH, 110, 111, 112, 114, 161, 162, 185

microsimulation modeling, general, 2, 9, 24, 25, 27, 31, 33-38, 97 , 107-114

quality profiles, 140

retirement income policy, 212-213

SIPP, 137

social science research, 283-284, 286-287

social welfare policy, 20-24, 34, 278

statistical agencies, 8, 57-62

tax policy, 75-76, 86-87, 108, 110, 212, 219-220, 278

TRIM/TRIM2, 16, 155, 156-157, 157, 159, 161, 248

validation studies. 241-259

HITSM, see Household Income and Tax Simulation Model

Hot deck, see Imputations

Household Income and Tax Simulation Model (HITSM), 98, 113-114, 136 , 268, 291-292

Human-computer interface, see User accessibility

Hungary, 109

I

Imputations, 90, 95, 124, 133-136, 145, 146, 149, 174, 204, 249

model descriptions, specific, 291-298 (passim)

tax policy models, 221, 223, 225, 226-227, 228, 229-230, 306

see also Matching

Income and income support models, 2, 61, 98, 109, 148, 274

CPS, 145, 146, 151, 174

HITSM, 98, 113-114, 136, 268, 291-292

ISDP, 132-133, 137

MRPIS, 98, 113, 161-162, 179, 180, 293-294

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

PENSIM, 183

PRISM, 98, 51, 112, 124, 162, 163, 167, 170, 171, 198, 204, 213-218, 245, 294-295

Reforms in Income Maintenance, 36, 109-110, 161

vs tax models, 221-222

TRIM, 110-111, 161, 184-185

see also Aid to Families with Dependent Children

Dynamic Simulation of Income Model 2

Eligibility data and modeling

Micro Analysis of Transfers to Households

Participation data and modeling

Retirement income policies

Statistics of Income;

Survey of Income and Program Participation data and modeling

Tax models and policy

Transfer Income Model 2

Income Survey Development Program (ISDP), 132-133, 137

Individual behavior, 17, 48

see also Behavioral response

Individual Retirement Accounts, 215, 217-219

Institute of Electrical and Electronics Engineers, 267-268, 269, 270

Integrated Quality Control System (IQCS), 15, 43, 46, 131-132, 141 , 142, 250, 253-255, 257, 299-300

Interagency Forum on Aging-Related Statistics, 210

Internal Revenue Service (IRS), 59, 67-67, 145

linkages with SIPP, 228

matching files, CPS-IRS, 67-68, 104, 110, 124, 134, 220, 224, 226-227, 228, 299, 307

see also Statistics of Income

Internal validation, 5, 78-80, 85

International perspectives, 108, 109, 193

see also specific countries

Investment, 52-55, 63

data production, 56, 57-64

validation, 80-81

see also Funding

J

Job Training Partnership Act, 30

Joint Committee on Taxation, 23, 24, 25, 136, 220, 222, 274

K

Kasten-Greenberg-Betson (KGB) model, 47-48, 111, 161, 170, 171

L

Laws, specific

federal Budget Act, 22, 36

Family Support Act, 3, 6, 21-22, 31, 41-51, 77, 176, 187, 195, 234 , 261, 279

Food Stamp Reform Act, 36, 110

Gramm-Rudman-Hollings Act, 37-38, 163, 219

Job Training Partnership Act, 30

Medicare Catastrophic Coverage Act, 6, 206-207, 225

Omnibus Budget Reconciliation Act, 42

Paperwork Reduction Act, 63

Privacy Act, 66

Social Security Act, 112

Tax Reform Act, 3, 23, 24, 66, 113, 176, 221, 225, 226, 229

Lewin/ICF, Inc., 112-113, 124, 200, 205, 213, 291, 294, 295

Linkages, 65, 157, 159, 216-217

administrative/survey data, 62, 66-69, 129, 131-133, 137, 141-147 (passim), 149, 151, 169, 216-217, 277

see also Matching

interagency coordination, 6-7, 10, 12-13, 37, 62-63, 146, 149-150, 209, 210, 212, 274-277

see also Matching

of models, 16, 53, 112, 157, 159, 131, 190, 199

Longitudinal data, 47, 76, 147, 197, 291

CPS/SIPP, 15, 131, 145, 146, 147

Long-term approaches, 146-148

Long-term care, 202, 204, 209, 295-296

Long-Term Care Financing Model, 204-205, 209, 295-296

Loss functions, 240-241

M

Macroeconomic-Demographic Model, 200, 213, 215

Macroeconomic models, 2, 22, 31, 35, 49, 52, 56, 95-96, 109, 116, 178, 200, 213, 215, 238, 307

linkage with microsimulation models, 53, 112, 199

validation, 74-75, 76

Matching, files, 149, 163, 307-308

CPS-IRS, 67-68, 104, 110, 124, 134, 220, 224, 226-227, 228, 299, 307

CPS-SIPP, 144, 145, 146, 147, 228

CPS-SSA, 7-8, 18, 67, 104, 123-124, 134-135, 136, 216-217, 245, 277 , 299

exact, 7, 18, 67-68, 104, 134-135, 216-217, 228-229, 308

IRS-SIPP-CPS, 228

SIPP-SSA, 217

statistical, 104, 110, 127, 133, 135-136, 204, 222, 228, 307-308

MATH, see Micro Analysis of Transfers to Households

Mathematica Policy Research, Inc., 110, 292

Medicaid, 65, 196, 199, 201, 202-203, 205

TRIM2, 198, 204, 207

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Medicare, 61, 124, 178, 195, 199, 201, 202, 203, 207, 225

Medicare Catastrophic Coverage Act, 6, 206-207, 225

Medigap policies, 201, 225

MERGE files, 110, 220

Micro Analysis of Transfers to Households (MATH), 2, 36, 47-48, 104 , 132, 133, 162, 198, 244-245, 292-293

aging of data, 167, 168, 169, 170, 245, 302

behavioral response, 170, 171, 172, 174-175

computing requirements, 185, 192

documentation, 26, 268, 269

historical perspectives, 110, 111, 112, 114, 161, 162, 185

Microanalytic Simulation of Households, 183

Microcomputers, see Personal computers

Microsimulation models, general, 2, 8-9, 22, 42-51, 97-98, 101-109, 114-122, 284, 308

historical perspectives, 2, 9, 24, 25, 27, 31, 33-38, 97, 107-114

see also specific models

Minority groups, 71, 126

Models, general, 1-2, 89-90

defined, 34-35, 76-77, 89

see also specific models

MOSES, 108

MRPIS, see Multi-Regional Policy Impact Simulation

MS-DOS, 186, 188

Multiple imputation, see Imputation

Multi-Regional Policy Impact Simulation (MRPIS), 98, 113, 161-162, 179, 180, 293-294

N

National Ambulatory Medical Care Survey, 61

National Bureau of Economic Research, 222

National Center for Health Statistics, 59, 69, 201, 208, 210

National Health Insurance Experiment, 202

National Health Interview Survey, 60, 64, 206, 210

National Health and Nutrition Examination Survey, 60, 61, 129

National Income and Product Accounts, 61, 129

National Institute on Aging, 200, 201, 213, 219, 275

National Longitudinal Surveys of Labor Market Experience, 60, 285

National Long-Term Care Channeling Demonstration, 202

National Medical Care Expenditure Survey, 205, 206, 208, 211, 300-301

National Medical Care Utilization and Expenditure Survey, 113, 205 , 206, 208, 211, 300-301

National Medical Expenditure Survey, 205, 206, 208, 211, 300-301

National Nursing Home Survey, 61, 205, 211

National Science Foundation, 286-287

Near-term approaches, 12, 38, 54, 143-146, 277

Nonparametric techniques, 91

Nonresponse, household/person/item see Imputations;

Response rates

O

Office of Management and Budget (OMB), 37, 38, 49, 62, 63, 83, 137

Office of Tax Analysis, 98, 110, 136, 220, 223-226, 274, 296

Omnibus Budget Reconciliation Act, 42

Orcutt, Guy, 36, 109, 283-284, 287, 289

Organizational factors, 12-13, 62-63

interagency coordination, 6-7, 10, 12-13, 37, 62-63, 146, 149-150, 209, 210, 212, 274-277

see also Matching

microsimulation modeling community structure, 12-13, 20, 121-122, 273-289

validation of models, 260-263

Organization for Economic Cooperation and Development, 109, 193

P

Panel Study of Income Dynamics, 174, 218, 285

Panel techniques, general, 64, 144, 146, 147, 174, 219

Paperwork Reduction Act, 63

Parameterization, 107, 156, 185

behavioral, 17-18, 75-76, 107, 163, 173-174, 177, 180, 211, 218, 229, 282

policy-related, 74, 75, 107, 173

Participation data and modeling, 46-47, 51, 82, 171, 234, 246-247

AFDC, 136-137, 235, 246-247

vs eligibility data, 44, 64-65, 136-137, 151

see also Survey of Income and Program Participation

PENSIM, 183

Pension and Retirement Income Simulation Model (PRISM), 98, 51, 112 , 124, 162, 163, 167, 213-218, 294-295

behavioral response, 170, 171

health care financing, 198, 204

validation, 245-246

see also Long-Term Care Financing Model

Personal computers, 34, 54, 108, 121, 186-187, 190, 191-192, 279

Policy analysis, general, 8-13, 24-26, 29-31, 52-88

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Family Support Act, 20-24, 41-51, 187, 234, 261

model validation, 72-84, 86-88

vs policy research, 38, 281-283

social welfare, 34, 38-41,

Policy analysis agencies, 52-55, 148, 169, 274-276, 278-281

coordination with statistical agencies, 7, 70-71, 276-277

and decisionmaking staff, 4-5, 80-82, 280-281

interagency coordination, 6-7, 10, 12-13, 37, 62-63, 146, 149-150, 209, 210, 212, 274-277

see also Matching

uncertainty, information on, 81-84, 86-87, 86-88

see also specific agencies

Political factors, 29, 30, 39-41, 60

POPSIM, 286

Population factors, 1, 21-22, 23, 24, 25, 27, 30, 115, 196, 218, 283-289

black Americans, 71, 126

elderly persons, 196, 201, 205

Macroeconomic-Demographic Model, 200, 213, 215

minorities, 71, 126

stochastic processes, 197

Poverty

CPS, 144

SIPP, 138, 147

see also Aid to Families with Dependent Children

Medicaid

Social welfare policy

PRISM, see Long-Term Care Financing Model

Pension and Retirement

Income Simulation Model Privacy, see Confidentiality

Privacy Act, 66

Private sector

health insurance, 196, 198, 199, 201, 202, 206, 209, 225

retirement pensions, 212, 216

Program for Better Jobs and Income, 111, 185, 194-195

Prototyping, 159, 160, 192-193, 199

Q

Quality of Employment Survey, 65

Quality profiles, 19, 51, 92, 140, 141, 263-264

Questionnaires

CPS, 143, 145, 146

duplication of items, 13, 63-64, 277

SIPP, 138, 147

R

Reagan administration, 195

Reforms in Income Maintenance (RIM), 36, 109-110, 161

Regression analysis, general, 78-79, 89-90, 91, 93-94, 116, 134, 159, 247, 249

Research, 38-41, 119, 120, 219 academic, 219, 281-282, 285-286

basic, 13, 38, 107-108, 281-283

behavioral, general, 17-18, 164-165, 176, 177, 181, 201-203, 217-219, 276, 282, 283-289

conferences, 20, 282-283

data quality, 69, 119-120

funding, 19, 39, 82

health care policies, 201-203, 209, 211-212

policy analysis vs policy research, 38, 281-283

social science microsimulation, 283-289

validation methods, 20, 241-263, 276, 282, 285-286

validation studies, grants and fellowships, 19, 263

Response rates, 61, 127, 129, 133-134, 137, 145

Retirement History Survey, 174, 218, 219

Retirement income policies, 18, 23, 67, 105, 170, 212-219

see also Dynamic Simulation of Income Model

Pension and Retirement Income Simulation Model

S

Sampling

error, 3, 69, 78-79, 86, 88, 90, 91, 95, 129, 215, 244, 257

reuse techniques, 12, 91, 93, 157, 158, 239-240

size, 56, 60, 112, 120, 138, 143, 144, 146, 183, 206, 223-224, 236

weighting, 138, 144, 147, 151

see also Response rates

Variance estimation

Second-round effects, 23, 53, 107, 113, 115, 178, 229

computable general equilibrium models, 179, 180, 304-305

design for, 153, 154, 155, 163, 164, 178-181

health care policy models, 202-203, 209

MRPIS, 98, 113, 161-162, 179, 180, 293-294

Self-contained modules, 16, 111, 155, 156-157, 157, 159, 161, 248

Sensitivity analysis, 12, 18, 73, 78, 79-80, 82, 83, 91-92, 93, 94 , 99, 157, 158, 177, 192, 215, 218, 228, 229, 233, 235, 237-239, 242, 246, 248-261

Simulated Tax and Transfer System (STATS), 110

Social Policy Simulation Database/Model (SPSD/M), 108, 186, 187-188, 191

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Social science, see Research

Social Security Act, 112

Social Security Actuary, 213

Social Security Administration (SSA), 23, 49, 145, 215

matching files, CPS-SSA, 7-8, 18, 67, 104, 123-124, 134-135, 136, 216-217, 216-217, 245, 277, 299

matching files, SIPP-SSA, 217

Social welfare policy, general, 2, 15, 21-24, 25-26, 29-96, 173

administrative data evaluation, 15, 216-217

eligibility, social welfare, 44, 45, 47, 64-65, 105, 136

historical perspectives, 20-24, 34, 278

participation data, 44, 46-47, 51, 64-65, 82, 136, 171

uncertainty, 72-96 (passim)

Social Welfare Research Institute, 293

SOCSIM, 286-287

Software, general, 186, 188, 189, 190, 193 CASE, 11, 190

documentation of, 12, 14, 17, 19, 85-86, 267-269, 270-271

graphical interfaces, 121, 189, 190, 193

MS-DOS, 186, 188

see also Documentation and archiving

Models

specific models

SPSD/M, see Social Policy Simulation Database/Model

Standards, 4, 158, 159-160

AFDC minimum benefit, 3, 24, 74, 257

design and development, 16-17, 193, 276

documentation, 12, 14, 19, 266-271

State-level factors, 48, 44, 46, 49-50, 83-84, 86, 142, 146, 196, 234

Static models, general, 18, 108, 109-111, 123, 162, 192, 308

aging of data, 49, 105, 163, 164, 165-167, 169, 170, 198-199 214-215, 221, 225-226, 228, 249-250, 292, 293, 298, 302-303

see also specific models

Statistical agencies, general

coordination with policy analysis agencies, 7, 70-71, 276-277

data quality, 69-72, 124

funding, 6, 37, 56-59, 61-60

historical perspective, 8, 57-62

interagency coordination, 6-7, 10, 12-13, 37, 62-63, 146, 149-150, 209, 210, 212, 274-277

see also Matching

social welfare, 59, 57-62

see also specific agencies

Statistical matching, 104, 110, 127, 133, 135-136, 204, 222, 307-308

Statistics Canada, 108, 136, 150, 186, 187-188

Statistics of Income, 15, 104, 124, 136, 141, 221, 222, 228, 274, 301

matching files, 67-68, 104, 110, 124, 134, 220, 224, 226-227, 228, 299, 307

STATS, see Simulated Tax and Transfer System

Stochastic processes, 197

''Sunset" provision, 17, 160

Supplemental Security Income, 56, 110

Survey of Consumer Finances, 205

Survey of Economic Opportunity, 220

Survey of Family Growth, 61

Survey of Income and Education, 198, 200

Survey of Income and Program Participation (SIPP), 11, 15-16, 58, 60, 64, 65, 68, 70, 71, 113, 120, 123, 125, 132-133, 137-152 (passim), 228, 285, 301-302

design, 138, 140, 146-148

linkages with CPS, 144, 145, 146, 147, 228

linkages with IRS, 228

matching files, SIPP-SSA, 217

Survey of Institutionalized Persons, 198, 200

Surveys and survey data, 8, 37, 60-61, 63-64

administrative data links, 62, 66-69, 129, 131-132, 137, 141-147 (passim), 149, 151, 169, 216-217, 277

see also Matching

census databases, 11, 12, 15-16, 70, 71, 123-152

duplication of items, 13, 63-64, 277

evaluation of, 14, 71, 139-141

health care financing, 203-208

household, 60, 61, 104, 120

see also Questionnaires

Response rates

specific surveys

Sweden, 108-109

T

TATSIM, 175

Tax models and policy, 3-4, 9, 23, 25, 34, 35, 53-54, 65, 75-76, 98, 219-230, 274

aging of data, 221, 225-226, 228, 229

behavioral response, 170, 171-172, 176, 178, 179, 226, 228-229

confidentiality, 67-68, 227, 228

databases, 223-226

historical perspectives, 75-76, 86-87, 108, 110, 212, 219-220, 278

HITSM, 98, 113-114, 136, 291-292

imputation, 221, 223, 225, 226-227, 228, 229-230, 306

MRPIS, 98, 113, 160-162, 179, 180, 293-294

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
×

Social Policy Simulation Database/Model, 108, 186, 187-188, 191

Treasury Individual Income Tax Simulation Model, 296-297

see also Department of the Treasury

Internal Revenue Service

Joint Committee on Taxation

Statistics of Income

Transfer Income Model 2

Tax Reform Act, 3, 23, 24, 66, 113, 176, 221, 225, 226, 229

Tune-series data and analysis, 2, 50, 52-53, 56, 60, 61, 83, 90, 147, 151

Transfer Income Model (TRIM), 110-111, 161, 184-185

Transfer Income Model 2 (TRIM2), 2, 24, 45, 46, 47, 36, 50, 98, 104 , 133, 136, 162, 187-188, 198, 222, 268, 297-298

aging of data, 49, 107, 163, 166-168, 169, 170, 233

baseline simulation, 107, 124, 256

behavioral response, 170, 171, 172

computing technology, 185, 186, 187-189, 191-192

history, 110-111, 112, 113, 114, 162, 182, 184-185, 221

Medicaid, 198, 204, 207

sensitivity analysis, 99, 233

validation, 3, 78, 99, 233-239, 246-247, 248-259

Treasury Individual Income Tax Simulation Model, 296-297

TRIM2, see Transfer Income Model 2

U

Uncertainty, 3, 4, 5, 14, 15, 55, 85, 118-119, 215

behavioral parameters, 17-18, 75-76, 107, 173, 177, 180, 211, 282

confidence intervals, 79-80, 86, 87, 88, 92, 93-96, 244

information on, general, 81-84, 86-87, 86-88

macroeconomic models, 74-75

policy parameters, 74, 75, 107

quality profiles, 19, 51, 92, 140, 141, 263-264

social welfare policy models, 72-96 (passim)

see also Errors and error analysis

Unemployment, see Employment and unemployment

United Kingdom, 193

UNIX, 188

Urban Institute, 110, 111, 112, 183, 184, 290, 297, 248, 259

User accessibility, 14, 16, 18, 158, 159, 279-280

computing innovations, 121, 148, 164, 183, 188, 189, 190, 193

confidentiality and, 66-69, 135, 207, 216, 227, 228

documentation, 266, 267, 269, 270

graphical interface, 121, 189, 190, 193

Utility issues, 2, 13, 25, 26, 54-55, 145, 279

V

Validation and evaluation, 2, 3-5, 6, 10, 12, 14-15, 19, 25, 27, 51, 55, 77, 98, 119, 137, 139-152, 192, 209, 215, 229, 231-264

computing technology, 18, 192-193

costs, 259, 260, 261

design and, 16, 157, 158, 159-160

documentation and, 85, 157, 158, 266, 270, 271

external, 5, 12, 19, 77-78, 82, 87-88, 94-95, 99, 233, 235-236, 238 , 246, 262-263, 271, 279-280

historical perspectives, 241-259

information concerning, 81-84, 86-87, 86-88

internal, 78-80, 85

loss functions, 240-241

macroeconomic models, 74-75, 76

organizational factors, 260-263

quality profiles, 19, 51, 92, 140, 141, 263-264

research, 20, 241-263, 276, 282, 285-286

sensitivity analysis, 12, 18, 73, 78, 79-80, 82, 83, 91-92, 93, 94 , 99, 157, 158, 177, 192, 215, 218, 228, 229, 233, 235, 237-239, 242, 246, 248-261

social welfare policy models, 72-84, 86-88

"sunset" provision, 17, 160

surveys, general, 13, 140-141

TRIM2, 3, 78, 99, 233-234, 237-238, 246-247, 248-259

see also Data quality, Errors and error analysis

Uncertainty

Variance estimation

Variance estimation, 18, 91, 92, 192, 239-240, 261-262

reuse techniques, 12, 91, 93, 157, 158, 239-240

W

Weighting, 50, 124, 129, 136, 151, 308-309

sample, 138, 144, 147, 151

see also Data aging

Wisconsin, 86

Workstations, 188, 189, 190, 191

Wohgeldmodell, 108

Z

Zero-based reviews, see "Sunset" provision

Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Suggested Citation:"Biographical Sketches of Panel Members and Staff." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations. Washington, DC: The National Academies Press. doi: 10.17226/1835.
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Page 346
Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume I, Review and Recommendations Get This Book
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This book reviews the uses and abuses of microsimulation models--large, complex models that produce estimates of the effects on program costs and who would gain and who would lose from proposed changes in government policies ranging from health care to welfare to taxes.

Volume 1 is designed to guide future investment in modeling and analysis capability on the part of government agencies that produce policy estimates. It will inform congressional and executive decision makers about the strengths and weaknesses of models and estimates and will interest social scientists in the potential of microsimulation techniques for basic and applied research as well as policy uses.

The book concludes that a "second revolution" is needed to improve the quality of microsimulation and other policy analysis models and the estimates they produce, with a special emphasis on systematic validation of models and communication of validation results to decision makers.

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