This PDF is a selection from a published volume from the National Bureau of Economic Research

Volume Title: Improving the Measurement of Consumer Expenditures

Volume Author/Editor: Christopher D. Carroll, Thomas F. Crossley, and John Sabelhaus, editors

Series: Studies in Income and Wealth, volume 74

Volume Publisher: University of Chicago Press

Volume ISBN: 0-226-12665-X, 978-0-226-12665-4

Volume URL: http://www.nber.org/books/carr11-1

Conference Date: December 2-3, 2011

Publication Date: May 2015

Chapter Title: List of contributors, indexes

Chapter Author(s): Christopher D. Carroll, Thomas F. Crossley, John Sabelhaus

Chapter URL: http://www.nber.org/chapters/c13884

Chapter pages in book: (p. 493 – 504) Contributors

Marco Angrisani Caitlin Blair Center for Economic and Social US Department of Commerce Research 1401 Constitution Avenue, NW University of Southern California Washington, DC 20230 635 Downey Way Los Angeles, CA 90089- 3331 Laura Blow Institute for Fiscal Studies Stephen Ash 7 Ridgmount Street US Census Bureau London WC1E 7AE England 4600 Silver Hill Road Washington, DC 20233 Christopher D. Carroll Consumer Financial Protection Bureau Orazio Attanasio 1700 G Street, NW Department of Economics Washington, DC 20552 University College London Gower Street Thomas F. Crossley London WC1E 6BT England Department of Economics University of Essex Garry Barrett Wivenhoe Park School of Economics Colchester, UK, C04 3SQ England H04- Merewether The University of Sydney Scott Fricker Sydney NSW 2006 Australia Bureau of Labor Statistics Office of Survey Methods Research, Adam Bee PSB Suite 1950 US Census Bureau 2 Massachusetts Avenue, NE 4600 Silver Hill Road Washington, DC 20212- 0001 Washington, DC 20233 Thesia I. Garner Bureau of Labor Statistics 2 Massachusetts Avenue, NE Washington, DC 20212

493 494 Contributors

John Greenlees David Dreyer Lassen Bureau of Labor Statistics Department of Economics 2 Massachusetts Avenue, NE University of Copenhagen Washington, DC 20212 Øster Farimagsgade 5, building 26 DK- 1353 Copenhagen, Denmark Steve Henderson Bureau of Labor Statistics Valérie Lechene 2 Massachusetts Avenue, NE Department of Economics Washington, DC 20212 University College London Gower Street Michael D. Hurd London WC1E 6BT England RAND Corporation 1776 Main Street Andrew Leicester Santa Monica, CA 90407 Frontier Economics 71 High Holborn Erik Hurst London WC1V 6DA England Booth School of Business University of Chicago Søren Leth- Petersen Harper Center Department of Economics Chicago, IL 60637 University of Copenhagen Øster Farimagsgade 5, building 26 David Johnson DK- 1353 Copenhagen, Denmark Bureau of Economic Analysis 1441 L Street NW Peter Levell Washington, DC 20230 Institute for Fiscal Studies 7 Ridgmount Street Arie Kapteyn London WC1E 7AE England Center for Economic and Social Research Clinton McCully University of Southern California Bureau of Economic Analysis 635 Downey Way 1441 L Street NW Los Angeles, CA 90089- 3331 Washington, DC 20230

Ralph Koijen Bruce D. Meyer London Business School Harris School of Public Policy Studies Regent’s Park University of Chicago London NW1 4SA England 1155 E. 60th Street Chicago, IL 60637 Brandon Kopp Bureau of Labor Statistics Kevin Milligan 2 Massachusetts Avenue, NE Department of Economics Washington, DC 20212 University of British Columbia #997- 1873 East Mall Claus Thustrup Kreiner Vancouver, BC V6T 1Z1 Canada Department of Economics University of Copenhagen Jonathan A. Parker Øster Farimagsgade 5, building 26 MIT Sloan School of Management DK- 1353 Copenhagen, Denmark 100 Main Street, E62- 642 Cambridge, MA 02142- 1347 Contributors 495

William Passero James X. Sullivan Bureau of Labor Statistics Department of Economics 2 Massachusetts Avenue, NE 447 Flanner Hall Washington, DC 20212 University of Notre Dame Notre Dame, IN 46556 Luigi Pistaferri Department of Economics David Swanson 579 Serra Mall Bureau of Labor Statistics Stanford University 2 Massachusetts Avenue, NE Stanford, CA 94305- 6072 Washington, DC 20212

Susann Rohwedder Nhien To RAND Corporation Bureau of Labor Statistics 1776 Main Street 2 Massachusetts Avenue, NE PO Box 2138 Washington, DC 20212 Santa Monica, CA 90407 Stijn Van Nieuwerburgh John Sabelhaus Stern School of Business Board of Governors of the Federal New York University Reserve System 44 West 4th Street, Suite 9- 120 20th and C Streets, NW New York, NY 10012 Washington, DC 20551 Roine Vestman Scott Schuh Department of Economics Federal Reserve Bank of Boston Stockholm University 600 Atlantic Avenue, T- 9 SE- 106 91 Stockholm, Sweden Boston, MA 02210 Joachim K. Winter Nicholas S. Souleles Department of Economics The Wharton School LMU Munich University of Pennsylvania Ludwigstr. 33 2300 Steinberg Hall- Dietrich Hall D- 80539 Munich Germany Philadelphia, PA 19104- 6367

Author Index

Aaronson, D., 96 Bollinger, C. R., 78n7 Adler, H. J., 264n3 Bonke, J., 26, 38, 41 Agarwal, S., 96 Bosworth, B., 182, 348 Aguiar, M. A., 14, 82n16, 101, 103, 103n2, Bound, J., 45, 290, 292, 303n8, 309, 328n9 108, 108n5, 114n9, 115, 125, 126, Bradburn, N. M., 27, 38, 43n6, 44 134n16, 257n29, 317, 441 Branch, E. R., 208, 211 Ahmed, N., 28, 30, 221, 309, 328n9, 449 Bray, I., 32 Altug, S., 365n1 Brewer, M., 442n3 Alvaredo, F., 275 Broda, C., 84, 441 Atkinson, A. B., 272 Brooks, K., 449 Attanasio, O., 23, 82n16, 82n18, 95, 96, 102, Brown, C., 45, 303n8, 309, 328n9 121, 123, 129n14, 133, 153, 182, 208, Browning, M., 23, 25, 33n4, 35, 36, 37, 38, 211, 235, 244n9, 264, 442n3, 450 101, 103n2, 108, 142, 155, 212n9, 290, Autor, D. H., 102n1 295, 309n3, 311n5, 317, 318, 324, 343, 366, 366n2, 390 Baddeley, A. D., 27 Brumberg, R., 81n14, 390 Banks, J., 96, 142, 147, 155 Brzozowski, M., 28, 30, 42, 221, 266, 267n9, Barten, A. P., 142 309, 328n9, 348, 350, 351, 371, 449 Battistin, E., 23, 30, 35, 45, 82n16, 82n18, 102, Bucks, B. K., 224, 246n12 121, 123, 182, 182n2, 208, 211, 212n9, Burtless, G., 182, 348 235, 264, 309n3, 328n9, 442n3, 450 Bee, A., 182, 212, 213, 222, 229, 232 Calvet, L. E., 310n4 Bennett, C., 33 Cameron, A. C., 427n6 Biemer, P., 182n2 Campbell, J. Y., 310n4 Bils, M., 14, 82n16, 101, 103, 103n2, 108, Carroll, C. D., 81n14, 94, 309 108n5, 125, 126, 257n29, 317 Cesarini, D. ., 310n4 Björklund, A., 310n4 Champion, H., 28, 29, 39, 44 Blake, M., 25, 34, 36, 37 Chang, L., 39, 415 Block, R. A., 358 Cho, M. J., 78n8 Blow, L., 450 Christensen, L. R., 142 Blundell, R., 35, 85, 102, 113, 114, 142, 147, Citro, C. F., 78n7 155, 309n2 Clark, T. E., 57

497 498 Author Index

Clarke, P. M., 39 Gibson, J., 309n3 Comerford, D., 37 Giebig, D. G., 39 Conrad, F., 422 Gieseman, R., 30, 208, 209, 216n15 Coutts, E., 404n16 Goldenberg, K., 26, 37, 201, 268, 305n9 Creech, B. J., 210n6, 212n9 Goodman, A., 442n3 Crossley, T. F., 23, 25, 28, 30, 33n4, 35, 37, Gottschalk, P., 303, 304 42, 101, 103n2, 108, 212n9, 217, 221, Gourinchas, P.- O., 95 241n1, 266, 267n9, 270, 309, 309n3, Gray, P. G., 27 328n9, 348, 350, 351, 371, 449, 450 Griffith, R., 441, 446 Curtin, R., 367 Groen, J. A., 244n10, 259n31 Cutler, D. M., 102 Grooteart, C., 37 Grosh, M., 23, 24, 30, 44, 416 D’Alessio, G., 272n16 Grossman, S. J., 143 d’Ardenne, J., 25, 34, 36, 37 Groves, R. M., 44, 247n13 David, M. H., 78n7 Guvenen, F., 309n2 Davis, S. J., 95, 102, 133 Deaton, A., 23, 24, 37n5, 39, 40, 44, 85, Hall, R. E., 87, 365n1 85n20, 88, 142, 208n2, 264, 276, 416 Ham, J., 422 de Heer, W., 272n15 Harding, M., 442 Delaney, L., 37 Harmon, C., 37 de Leeuw, E., 272n15 Heathcote, J., 102, 121, 244n9 DiNardo, J., 88 Heitjan, D. F., 32 Domeij, D., 310n4 Herriot, R. A., 33 Dubreuil, G., 221, 264n2, 267 Holmes, M., 29 Dynan, K. E., 95 Horrigan, M., 84 Houthakker, H. S., 182, 209n5 Edgar, J., 40, 263n1 Hudomiet, P., 44n7 Einav, L., 448 Huffman, S., 447 Essig, L., 25 Hurd, M., 27, 32, 39, 42, 204n1, 310, 348, 350, 351, 366, 391n3, 412, 412n17 Faiella, I., 272n16 Hurst, E., 114n9, 115, 134n16, 441 Fallesen, P., 26, 41 Hussain, I., 142n1, 143, 144, 155, 156, 161 Feenberg, D. R., 404n16 Feenstra, R. C., 446 Ichimura, H., 23, 82n16, 82n18, 102, 121, Ferber, R., 27, 28, 33, 41 123, 235 Fernandez- Villaverde, J., 182 Ferraro, D. L., 258n30 Jacob, C. A., 38 Fitoussi, J. P., 1n1 Jacobs, E., 27, 348 Fixler, D., 56, 56n5, 57, 71n20 Jaditz, T., 56, 56n5, 57, 71n20 Flavin, M., 143 Jensen, H., 447 Floden, M., 310n4 Jin, W., 458n18 Foster, K., 418, 423 Johnson, D. S., 88, 92n24, 244n9 French, E., 96 Johnson, T. P., 26 Fricker, S., 371, 422 Joliffe, D., 34 Friedman, M. A., 81 Jorgenson, D. W., 142 Juster, F. T., 412n17 Garner, T. I., 53n1, 57, 57n7, 57n8, 58, 61, 67n18, 68, 103, 182, 193n10, 208, 210, Kalton, G., 78n7 211, 212, 212n10, 241n2, 242, 242n4, Katz, L. F., 102, 102n1 264n3 Kearney, M. S., 102n1 Gerdtham, U.- G., 39 Kemsley, W. F. F., 25, 28, 29, 37, 40 Gervais, M., 153 Kennedy, C., 442 Author Index 499

Kennickell, A. B., 246n12 Meekins, B., 182n2 Kiel, K. A., 224 Meghir, C., 142, 155 King, S. L., 247n13 Meyer, B. D., 6, 82n16, 182, 208, 210n7, Klein, P., 153 211, 212, 213, 222, 224, 229, 232, 234, Kleven, H. J., 291 243n6, 257, 270, 271n14, 317 Kopczuk, W., 304 Micklewright, J., 33 Kopp, B., 371 Miller, R. A., 365n1 Kozel, V., 39, 40, 208n2, 416 Miniaci, R., 35, 309n3 Kreiner, C. T., 297n5, 311n5, 324 Mishkin, F. S., 365n1 Kreuter, F., 35 Modigliani, F., 81n14, 390 Krosnick, J. A., 39, 415 Moffitt, R., 303, 304 Krueger, A. B., 292 Mok, W. K. C., 243n6, 317 Krueger, D., 6, 102, 103, 121, 182, 244n9 Molinari, F., 42, 44, 78n7 Kunze, K., 196n13 Moore, B. C., 182 Moore, J., 422 Laroque, G., 178 Moyer, B. C., 56, 56n6, 57, 244n8 Lassen, D. D., 297n5, 311n5, 324 Muellbauer, J., 142 Lau, L. J., 142 Lawless, T., 40 Nakagawa, S., 143 Lebow, D. E., 56, 56n4, 67, 71n20 Neter, J., 27, 79 Leibtag, E., 441, 442, 448, 449 Nevo, A., 448, 449 Leicester, A., 182, 208, 211, 264, 442n3, 444, Nicholson, J. L., 37, 40 446, 447, 448, 449, 450, 455, 456, 466, 469, 469n25, 472n28, 474 O’Connell, M., 446 Leth- Petersen, S., 36, 290, 295, 297n5, O’Dea, C., 270, 450, 466 311n5, 317, 318, 324, 343 Oldfield, Z., 446, 447, 448, 449, 455, 469, Lewbel, A., 142, 147, 155 469n25, 472n28 Li, G., 204n1 Olson, K., 305n9, 442 Li, X., 422 Lindahl, M., 310n4 Padula, M., 30, 45, 112, 121, 123, 143, 144, Lindqvist, E., 310n4 182n2, 235 Love, D. A., 400 Palumbo, M. G., 14, 310, 400 Lovenheim, M., 442 Parker, J. A., 91, 92, 92n25, 93, 95, 102, Lusardi, A., 390 182 Lusk, J. L., 449 Passero, W., 182, 201, 208, 210, 211, 212, Lynch, J., 264n2 212n10, 242, 243, 258n30, 264n3 Paulin, G. D., 258n30 Madsen, E., 366, 366n2 Pavoni, N., 102 Mahalanobis, P. C., 416 Payson, S., 196n13 Maki, D. M., 14, 103, 182, 310 Pence, K., 224 Malani, A., 40 Perri, F., 6, 102, 103, 121, 244n9 Manski, C. F., 32, 42, 44, 78n7 Philipson, T., 40 Massa, .W, 310n4 Pickering, C. M., 78n8 Mathiowetz, N., 45, 303n8, 309, 328n9, 442 Piketty, T., 81n15, 272 McCall, R., 1n2 Pistaferri, L., 35, 85, 102, 113, 114, 129n14, McClelland, R., 182, 208, 210, 211, 212, 309n2 212n10, 242, 264n3 Plug, E., 310n4 McCulla, S. H., 196n13 Pradham, M., 34 McCully, C. P., 56, 56n6, 57, 182, 196n13, Presser, S., 367 209, 211, 244n8 Preston, I., 35, 85, 102, 113, 114, 182, McFadden, D., 45 309n2 McWhinney, I., 28, 29, 39, 44 Pudney, S., 31, 45, 309 500 Author Index

Rao, K., 26 Souleles, N. S., 86, 92 Rasinski, K., 25, 43 Steinberg, B., 210n6, 212n9 Reagan, B. B., 34 Stephens, M., Jr., 28, 217 Redpath, R., 29 Stewart, K. J., 56, 56n6, 57, 182, 244n8 Reyes- Morales, S. E., 80, 80n12 Stiglitz, J. E., 1n1 Rips, L. J., 25, 43, 422 Stone, R., 142 Rohwedder, S., 27, 39, 42, 204n1, 310, 348, Sudman, S., 27, 28, 33, 41, 43n6 350, 351, 366, 412 Sullivan, J. X., 6, 82n16, 182, 208, 210n7, Romalis, J., 84 211, 212, 213, 222, 224, 229, 232, 234, Rubin, D. B., 32 243n6, 257, 270, 271n14, 317 Rubin, D. C., 27 Rudd, J. B., 56, 56n4, 67, 71n20 Tamer, E., 32 Ruud, P. A., 32, 45 Tanner, S., 28, 96, 450 Ryan, J., 37, 201, 268 Taylor, L. D., 182, 209n5 Teensma, T. D., 196n13 Sabelhaus, J., 182, 244n10, 259n31, 348 Theil, H., 142 Saez, E., 81n15, 272, 304 To, N., 78, 80n10, 348, 371 Safir, A., 26, 77n6, 263n1, 305n9 Tourangeau, R., 25, 43, 272n15, 272n16 Schnepf, S. V., 33 Tremblay, J., 264n2 Schunk, D., 32, 45 Triplett, J. E., 57, 450 Schwarz, N., 27, 32, 43n6 Trivedi, P. K., 427n6 Scott, S., 25, 28, 29, 30, 31, 217 Tucker, C., 33, 182n2, 449 Sen, A., 1n1 Turner, R., 28 Sen, S. B., 416 Shapiro, M. D., 446 van Soest, A., 32 Shea, J., 365n1 Vestment, R., 310n4 Sheppard, L., 422 Violante, G. L., 102, 121, 244n9 Shields, J., 78, 80n10, 348 Vissing- Jorgensen, A., 95, 96, 102 Shin, E., 26 Shipp, S., 27, 244n9, 348 Waksberg, J., 27, 79 Short, K., 193n10, 242n4, 244n9 Weber. G., 23, 25, 33n4, 35, 37, 95, 182, Silberstein, A. R., 25, 28, 29, 30, 31, 33, 38, 212n9, 309n3 217 Weinstein, D. E., 441 Silver, N., 16n4 Winter, J., 25, 32, 34, 45, 217 Simonov, A., 310n4 Wolfson, M., 264n3 Singer, E., 367 Wood, H., 305n9 Slacalek, J., 94 Woodburn, L. R., 246n12 Slesnick, D. T., 102, 182, 208, 257, 264n3, Wright, D. E., 32 450 Smith, A., 309n2 Yaari, M. E., 388, 391 Smith, J. P., 412n17 Yamashita, T., 143 Smith, P. A., 400 Smith, Z., 450 Zabel, J. E., 224 Smyth, J., 305n9 Zeldes, S. P., 365n1 Sodini, P., 310n4 Zhen, C., 447, 449, 469n25, 473 Sommer, M., 94 Ziebarth, N. L., 102 Song, J., 304 Ziliak, J., 113 Subject Index

Active saving, 403–9 Cash- flow reconciliation, 371. See also Bal- Aggregate coverage rates: within expendi- ance edit approach ture categories, 280–83; international CentER panel (the Netherlands), 34 comparison of, 270–71; reasons for CE Survey. See Consumer Expenditure (CE) declining, 272–80 Survey Aggregate spending: CE Survey and, Closed- response formats, 31–33 241–45; reasons for low levels of, in CE Collection strategies, survey design and, 26–31 Survey, 256–59 Computer- assisted personal interviews American Life Panel (ALP), 350; eliciting (CAPI), 26; reliability and, 41 total household spending and, 370–71; Consumer Expenditure (CE) Survey, 2, 23, financial crisis surveys, 368–69; indica- 268–69, 365; about, 207–8; aggregate tors of data quality of, 371–77; over- spending in, 241–45; benefits of panel view, 367; spending trends, 377–81 data, 77–84; CAMS vs., 395–96; com- Australia, 265–66 parisons to National Income Accounts, 211–21; Consumer Price Index and, Balance edit approach, 42, 371; design ob- 54–55; coverages differences of, vs. jectives, 348–49; future research priori- PCE, 189–90; data, introduction to, ties, 363–64; gaps in existing research, 53–54; data validity of, introduction 351; introduction, 347–48; prior re- to, 204–7; definition differences of, vs. search, 349–51; study design and pro- PCE, 190–94; distinguishing features cedure, 351–54; study discussion, 362; of, 75–77; durables in, 221–24; early study limitations, 362–63; study objec- comparisons, 208–11; evaluation of tives, 348–49; study results, 354–62 existing, 7–11; future research sug- Bracketed questions, 32; follow- up, 32 gestions, 71–72; goals for redesign of, British Social Attitudes Survey, 33–34 4–7; implications for uses of current, for redesigning, 233–36; income distri- CAMS. See Consumption and Activities bution data in, vs. other data sources, Mail Survey (CAMS) 245–47; international comparison of, Canada, 263–64, 266–67, 349–50 269–70; measurement differences of, vs. Canadian Food Expenditure Survey, 29–30 PCE, 194–95; for modeling household Canadian National Budget Survey, 29 demand, 141–44; nondurable expen- Canadian survey, 42 ditures and, 120–23; panel data and

501 502 Subject Index

Consumer Expenditure (CE) Survey (cont.) Expenditure categories: desegregation of, research, 84–95; panels, 76; precision 33–35; prediction of, 35–36; survey and frequency of reported purchases in, design and, 33–35 224–32; reasons for low levels of aggre- Expenditure data: future research priorities gate spending in, 256–59; reasons for for collection/analysis of, 42–46; recall vs. underrepresentation of highest income diary strategies for collection of, 26–27 households, 247–56; redesign goals for, Expenditure survey methodologies, 265–66 23–24; relationship of PCE data and, Expenditure surveys, design of, 24–42; 181–89; representativeness of, 232–33; approaches to reduce/correct response for studying income inequality, 100– errors, 41–42; data collection strategies, 101, 109–12; synthetic panel data vs. 26–31; defining response units, 36–38; true panel data, 95–96; use of, for study- expenditure categories, 34–35; predict- ing inequality, 109–12; use of incentives, ing aggregates, 35–36; reference peri- 41. See also Household expenditures; ods, 38–40; response formats, 31–33; Joint CE- to- PCE concordance; Per- role of incentives, 40–41; survey modes, sonal consumption expenditures (PCE) 24–26. See also Consumer Expenditure Consumer Price Index (CPI), 58n9; Con- (CE) Survey sumer Expenditure data and, 54–55; entry level items and, 58; hybrid index Family Expenditure Survey (United King- design and, 55–56; methodologies, dom), 142 58–63; previous comparisons, 56–58 Follow- up bracketed questions, 32 Consumption: after- tax income and, 390; income inequality vs., 104–5 Gemini Project, 24, 24n1, 263 Consumption and Activities Mail Survey (CAMS), 39, 366, 393–95; vs. Con- Health and Retirement Study (HRS), 389, sumer Expenditure (CE) Survey, 395–96 392–96 Consumption inequality, 120–23; income HES. See Household Expenditure Survey inequality and, 123–31. See also (HES, Australia) Income inequality; Leisure inequality Home scanner data approach, for data col- Consumption surveys, 308–9 lection, 27. See also In- home scanners CPI. See Consumer Price Index (CPI) Household demand: data and sample for, Cross- sectional surveys, 83 149–54; demand systems, 154–69; modeling, 144–49; using CE Survey for Danish Family Expenditure Survey, 289, 294 modeling, 141–44 Demand. See Household demand Household expenditures, 1–2; about, 23–24; Demand systems, 154–69 alternative approaches to data collec- Denmark: accuracy of survey day, 292–93; tion for, 11–20; current knowledge of, administrative register data, introduc- 3–4; personal expenditures vs., 36–38; tion, 289–91; income data, 297–304; survey design for, 24–42. See also matching administrative register data American Life Panel (ALP); Consumer with survey data, 291–92; suggestions Expenditure (CE) Survey for future work for survey data, 304–6; Household Expenditure Survey (HES, Aus- total expenditure data, 294–96 tralia), 265–66 Dependent interviewing, 78n7 Household expenditure survey data, inter- Diaries, design of, 33 national comparison of, 263–64. See Diary methods: disadvantages of, 28–29; also specific countries recall methods vs., 29–30 Household savings: challenges in empirical Durables, in CE Survey, 221–24 analysis of, 389–90; data, 392–96; introduction, 388–89; study results, Engel curves, 159 403–9; theoretical background, 391–92 Entry level items (ELIs), 58–59, 58n9, HRS. See Health and Retirement Study 59n11, 59n12 (HRS) Subject Index 503

Hybrid index design, Consumer Price Index National Income and Product Accounts, 241 and, 55–56 National Sample Survey Organization (NSSO, India), 39 Incentives, role of, in survey design, 40–41 Netherlands, 34 Income inequality: consumption inequality Nondurable expenditures, CE Survey and, and, 123–31; consumption vs., 104–5; 120–23 dimensions of, 106–7, 131–34; evolu- Nonsampling error, 78–79 tion of, 115–20; introduction, 101–4; measurement error and, 107–9; mea- Omnibus survey (Office for National Statis- sures of, 105–6; use of CE Survey for tics, United Kingdom), 33–34 studying, 100–101; use of PSID for Open- ended response formats, 31–33 studying, 112–14. See also Consump- tion inequality; Leisure inequality Panel data: accuracy of expenditure mea- Index methodologies, 58–63 surement and, 77–81; measurement of India, 39 standard of living and, 81–84; research Inequality. See Consumption inequality; and, 84–95; synthetic vs. true, 95–96; Income inequality; Leisure inequality wealth change in, 389–90 “Infrequency of purchase” problem, 83 Panel Study of Income Dynamics (PSID), In- home scanners, 83; comparing data from, 35, 112–14, 365 to other expenditure data, 449–74; data Panel surveys, benefits of, 76–77 for study of, 443–46; prior research, Paper questionnaires, 24–25 446–49; surveys with, introduction, PCE. See Personal consumption expendi- 441–43; using data for prediction, tures (PCE) 474–80 “Permanent income hypothesis” (Fried- Internet surveys. See American Life Panel man), 81–82 (ALP) Personal consumption expenditures (PCE), Item representation, 63–67 65; coverage differences of, vs. CE Sur- vey, 189–90; definition differences of, Joint CE- to- PCE concordance: described, vs. CE Survey, 190–94; future research 196–200; future directions for, 200– suggestions, 71–72; index levels and 201; motivation, 195–96 change, 67–71; item representation, 63–67; measurement differences of, Kantar, 444–46 vs. CE Survey, 194–95; relationship of PCE data and, 181–89. See also Con- Leisure inequality, time- use surveys for sumer Expenditure (CE) Survey; Joint studying, 114–15, 134–38. See also CE- to- PCE concordance Consumption inequality; Income in- Personal expenditures: household expendi- equality tures vs., 36–38 Living Costs and Food Survey (LCFS, Personal interviews, 24; confidentiality United Kingdom), 267–68, 422, 443–44 and, 25 Longitudinal Individual Data (LINDA, Sweden), 311, 333 Questionnaires: paper, 24–25; self- administered, 24–25 Mail- mode designs, 26 Questions, survey: data set for study of, Measurement error, 45–46; accounting for, 417–18; descriptive statistics of study in income inequality, 107–9; in con- results, 423–26; experiment design for sumption data, 309 study of, 418–23; introduction, 414–17; Mixed data collection methods, 31 regression analysis of study results, Mixed- mode designs, 26, 31 426–38

National Income Accounts: comparisons of Recall methods: diary methods vs., 29–30; CE Survey data to, 211–21 disadvantages of, 27–28 504 Subject Index

Recall periods, 38–39 Survey modes: effect of, in household sur- Reference periods, survey design and, veys, 25–26; survey design and, 24–26 38–40 Survey of Consumer Payment Choice Registry- based consumption: constructing, (SCPC), 414–15 312–13; constructing, details, 339–42; Survey of Health, Ageing and Retirement in details, 333–39; external validation, Europe (SHARE), 365–66 car transactions, 328–31; properties, Survey of Household Spending (SHS, 313–28; sampling restrictions, 342–44 Canada), 263–64, 266–67, 349–50 Reliability, approaches to improve, in survey Sweden: constructing registry- based con- design, 41–42 sumption for, 312–13; data set for, Research, panel data and, 84–95 311–12; properties of registry- based Respondents, choosing, 36–38 consumption in, 313–28 Response formats, survey design and: open- Synthetic panel data, 95–96; wealth change ended vs. closed- response, 31–33 in, 390 Response units, defining, 36–38 Telephone interviews, 24 Sampling error, 80–81 Time frames, recall, 415–17; descriptive sta- Savings. See Household savings tistics results, 423–26; experiment, 418– Scanners, in- home. See In- home scanners 23; regression analysis results, 426–38; Self- administered questionnaires, 24–25 sample for experiment, 417–18 Specific past recall periods, defining, 422–23 Time- use surveys, for studying leisure Stiglitz- Sen- Fitoussi commission, 1 inequality, 114–15, 134–38 Survey costs, 44–45 Survey design: approaches to improve reli- Unfolding brackets, 32 ability, 41–42; collection strategies, United Kingdom, 267–68 26–31; expenditure categories, 33–34; measuring household vs. personal Wealth changes, 389–90; data, 392–96; re- expenditures and, 36–38; modes of, sults, 397–403; study conclusions, 410– 24–26; prediction and, 35–36; reference 13; theoretical background, 391–92 periods for, 38–40; response formats, Wealth paths, 409–10 31–33; role of incentives in, 40–41 Web- survey modes, 26