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In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least‐squares operations of order \u003Cjats:italic>O\u003C\u002Fjats:italic>(\u003Cjats:italic>T\u003C\u002Fjats:italic>\u003Cjats:sup>2\u003C\u002Fjats:sup>) for any number of breaks. Our method can be applied to both pure and partial structural change models. Second, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. 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Một hàm tiện ích bao gồm các đặc điểm 'đồng nhất' và các hiệu ứng đặc trưng của hàng hóa được sử dụng như một liên kết cơ bản giữa không gian hàng hóa và không gian đặc điểm. Hình thức chức năng cho phương trình giá hedonic, các yêu cầu về dữ liệu và các vấn đề về lỗi đo lường khi ước tính nhu cầu và cung ứng các đặc điểm được thảo luận. Chúng tôi minh họa phương pháp luận bằng cách xem xét nhu cầu ô tô tại Mỹ dựa trên dữ liệu từ năm 1969 đến 1986 được biên soạn từ \u003Cjats:italic>Báo cáo Người tiêu dùng\u003C\u002Fjats:italic> và \u003Cjats:italic>Sách Niên giám Ô tô Ward\u003C\u002Fjats:italic>.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>This paper explores the possibility of using market data to identify consumer preferences. A utility function composed of ‘homogeneous’ characteristics and goods‐specific effects is used as a basic link between the goods space and the characteristics space. The functional form for the hedonic price equation, the data requirements and issues of measurement errors for estimating demand and supply of characteristics are discussed. We illustrate the methodology by considering the US automobile demand using 1969–86 data compiled from \u003Cjats:italic>Consumer Reports\u003C\u002Fjats:italic> and \u003Cjats:italic>Ward's Automotive\u003C\u002Fjats:italic> \u003Cjats:italic>Yearbook\u003C\u002Fjats:italic>.\u003C\u002Fjats:p>",{"EN":844,"VI":845},"Estimating consumer preferences using market data—an application to us automobile demand","Ước lượng sở thích của người tiêu dùng bằng cách sử dụng dữ liệu thị trường - Ứng dụng cho nhu cầu ô tô tại Mỹ",{"VI":847},"",{"VOID":849},"10.1002\u002Fjae.3950090102",[139],[141],"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1002\u002Fjae.3950090102",[854,871,888],{"id":855,"sortIndex":25,"researcher":24,"roles":856,"affiliations":857,"properties":866,"displayName":868,"givenName":24,"familyName":24},"4a617891-84d8-4471-8867-cfecf155c531",[],[858],{"id":859,"sortIndex":25,"affiliation":860,"properties":24},"b838e46f-fbc2-473a-83b3-4bba36ddc26e",{"id":859,"createTime":24,"updateTime":24,"relativeEntities":861,"slug":24,"properties":862,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":865,"statistic":24},[],{"title":863},{"EN":864},"Department of Finance and Economics, University of West Florida, Pensacola, FL 32514-5752, USA",[],{"title":867,"openalex":869},{"EN":868},"Nestor M. Arguea",{"VOID":870},"A5043264055",{"id":872,"sortIndex":97,"researcher":24,"roles":873,"affiliations":874,"properties":883,"displayName":885,"givenName":24,"familyName":24},"4b043b97-61ec-4c79-8bb1-79db28be62c1",[],[875],{"id":876,"sortIndex":25,"affiliation":877,"properties":24},"f567db30-3040-4578-8a64-a1048b43be48",{"id":876,"createTime":24,"updateTime":24,"relativeEntities":878,"slug":24,"properties":879,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":882,"statistic":24},[],{"title":880},{"VI":881},"Department of Economics, University of Southern California, Los Angeles, CA 90089-0253, USA",[],{"title":884,"openalex":886},{"EN":885},"Chêng Hsiao",{"VOID":887},"A5056373616",{"id":889,"sortIndex":621,"researcher":24,"roles":890,"affiliations":891,"properties":900,"displayName":902,"givenName":24,"familyName":24},"39357314-b8b1-4586-9856-1dc0ee827bb7",[],[892],{"id":893,"sortIndex":25,"affiliation":894,"properties":24},"a12cba78-06e7-4754-ace8-4420a1cd4b88",{"id":893,"createTime":24,"updateTime":24,"relativeEntities":895,"slug":24,"properties":896,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":899,"statistic":24},[],{"title":897},{"EN":898},"Department of Finance and Economics, Hong Kong University of Science and Technology, Clearwater Bay, Kowloon, Hong Kong",[],{"title":901,"openalex":903},{"EN":902},"G. 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K.andB. T.Ratchford(1980) ‘Estimating demand functions for product characteristics: the case of automobiles’ Journal of Consumer Research 249–62.",{"doi":971},"10.1086\u002F208813",{"id":24,"text":973,"url":24,"identifiers":974},"Aigner D. J., 1984, Handook of Econometrics, 1322",{},{"id":24,"text":976,"url":24,"identifiers":977},"10.1016\u002F0304-4076(85)90001-6",{"doi":976},{"id":24,"text":979,"url":24,"identifiers":980},"10.1016\u002F0304-4076(93)90108-H",{"doi":979},{"id":24,"text":982,"url":24,"identifiers":983},"Bajic V.(1988) ‘Market shares and price–quality relationships: an econometric investigation of the U. S. automobile market’ Southern Economic Journal April 888–900.",{"doi":984},"10.2307\u002F1059524",{"id":24,"text":986,"url":24,"identifiers":987},"10.1002\u002F0471725153",{"doi":986},{"id":24,"text":989,"url":24,"identifiers":990},"10.2307\u002F2938323",{"doi":989},{"id":24,"text":992,"url":24,"identifiers":993},"Brown J. N., 1983, The Measurement of Labor Cost",{},{"id":24,"text":995,"url":24,"identifiers":996},"10.2307\u002F1912614",{"doi":995},{"id":24,"text":998,"url":24,"identifiers":999},"Court A. T., 1939, The Dynamics of Automobile Demand, 99",{},{"id":24,"text":1001,"url":24,"identifiers":1002},"Cropper M. L. L. B.Deck andK. E.McConnell(1988) ‘On the choice of functional form for hedonic price functions’ Review of Economics and Statistics 668–75.",{"doi":1003},"10.2307\u002F1935831",{"id":24,"text":1005,"url":24,"identifiers":1006},"10.1017\u002FCBO9780511805653",{"doi":1005},{"id":24,"text":1008,"url":24,"identifiers":1009},"10.2307\u002F3003097",{"doi":1008},{"id":24,"text":1011,"url":24,"identifiers":1012},"10.1086\u002F261441",{"doi":1011},{"id":24,"text":1014,"url":24,"identifiers":1015},"10.1016\u002F0095-0696(74)90018-7",{"doi":1014},{"id":24,"text":1017,"url":24,"identifiers":1018},"10.1016\u002F0304-4076(76)90037-3",{"doi":1017},{"id":24,"text":1020,"url":24,"identifiers":1021},"10.2307\u002F1914070",{"doi":1020},{"id":24,"text":1023,"url":24,"identifiers":1024},"10.2307\u002F2526124",{"doi":1023},{"id":24,"text":1026,"url":24,"identifiers":1027},"Gorman W. M., 1976, Essays in Economic Analysis",{},{"id":24,"text":1029,"url":24,"identifiers":1030},"10.2307\u002F2296916",{"doi":1029},{"id":24,"text":1032,"url":24,"identifiers":1033},"Griliches Z., 1971, Price Indexes and Quality Change. Studies in New Methods of Measurement, 10.4159\u002Fharvard.9780674592582",{"doi":1034},"10.4159\u002Fharvard.9780674592582",{"id":24,"text":1036,"url":24,"identifiers":1037},"10.1016\u002F0094-1190(81)90021-8",{"doi":1036},{"id":24,"text":1039,"url":24,"identifiers":1040},"10.2307\u002F2297514",{"doi":1039},{"id":24,"text":1042,"url":24,"identifiers":1043},"10.2307\u002F2525705",{"doi":1042},{"id":24,"text":1045,"url":24,"identifiers":1046},"10.2307\u002F2525776",{"doi":1045},{"id":24,"text":1048,"url":24,"identifiers":1049},"10.2307\u002F1914194",{"doi":1048},{"id":24,"text":1051,"url":24,"identifiers":1052},"10.1016\u002F0304-4076(89)90047-X",{"doi":1051},{"id":24,"text":1054,"url":24,"identifiers":1055},"10.2307\u002F2297829",{"doi":1054},{"id":24,"text":1057,"url":24,"identifiers":1058},"10.1007\u002F978-94-009-0375-3_12",{"doi":1057},{"id":24,"text":1060,"url":24,"identifiers":1061},"10.1016\u002F0165-1765(80)90024-5",{"doi":1060},{"id":24,"text":1063,"url":24,"identifiers":1064},"10.1086\u002F261551",{"doi":1063},{"id":24,"text":1066,"url":24,"identifiers":1067},"10.2307\u002F2285946",{"doi":1066},{"id":24,"text":1069,"url":24,"identifiers":1070},"10.2307\u002F2526815",{"doi":1069},{"id":24,"text":1072,"url":24,"identifiers":1073},"Krouse C. G., 1986, Capital Markets and Prices",{},{"id":24,"text":1075,"url":24,"identifiers":1076},"10.1086\u002F259131",{"doi":1075},{"id":24,"text":1078,"url":24,"identifiers":1079},"Lancaster K. J., 1971, Consumer Demand: A New Approach",{},{"id":24,"text":1081,"url":24,"identifiers":1082},"10.1086\u002F296096",{"doi":1081},{"id":24,"text":1084,"url":24,"identifiers":1085},"Malhotra N. K., 1986, An approach to the measurement of consumer preferences using limited information, Journal of Marketing Research, S37",{},{"id":24,"text":1087,"url":24,"identifiers":1088},"10.2307\u002F1935993",{"doi":1087},{"id":24,"text":1090,"url":24,"identifiers":1091},"Muellbauer J.(1974) ‘Household production theory quality and the hedonic technique’ American Economic Review 977–94.",{},{"id":24,"text":1093,"url":24,"identifiers":1094},"10.2307\u002F1391318",{"doi":1093},{"id":24,"text":1096,"url":24,"identifiers":1097},"10.2307\u002F2297155",{"doi":1096},{"id":24,"text":1099,"url":24,"identifiers":1100},"Ramsey J. B., 1974, Frontiers in Econometrics, 13",{},{"id":24,"text":1102,"url":24,"identifiers":1103},"10.2307\u002F2525734",{"doi":1102},{"id":24,"text":1105,"url":24,"identifiers":1106},"10.1086\u002F260169",{"doi":1105},{"id":24,"text":1108,"url":24,"identifiers":1109},"Sargan J. D., 1964, Econometric Analysis for National Economic Planning",{},{"id":24,"text":1111,"url":24,"identifiers":1112},"10.1287\u002Fmnsc.20.6.921",{"doi":1111},{"id":24,"text":1114,"url":24,"identifiers":1115},"10.2307\u002F3150681",{"doi":1114},{"id":24,"text":1117,"url":24,"identifiers":1118},"Triplett J. E., 1987, The New Palgrave, 630",{},{"id":24,"text":1120,"url":24,"identifiers":1121},"10.2307\u002F1230278",{"doi":1120},{"id":24,"text":1123,"url":24,"identifiers":1124},"Whittlemore A. S., 1989, Approximations for regression with covariate measurement error, Journal of the American Statistical Association, 83, 1057, 10.1080\u002F01621459.1988.10478701",{"doi":1125},"10.1080\u002F01621459.1988.10478701",{"id":24,"text":1127,"url":24,"identifiers":1128},"Witte A. D. H.SumkaandJ.Erekson(1979) ‘An estimate of a structural hedonic price model of the housing market: an application of Rosen's theory of implicit marketing’ Econometrica 1151–72.",{"doi":1129},"10.2307\u002F1911956",{"id":24,"text":1131,"url":24,"identifiers":1132},"10.2307\u002F1883264",{"doi":1131},{"id":1134,"createTime":1135,"updateTime":1136,"relativeEntities":1137,"slug":1138,"properties":1139,"entityType":135,"verifyStatus":136,"verifyTime":1153,"verifyNote":137,"languages":1154,"translateLanguages":1155,"viewCount":25,"primaryUrl":1156,"fullTextUrl":24,"authors":1157,"publicationType":180,"publisherRelationship":1221,"citationCount":1275,"citationInfo":1276,"publishDate":1289,"publishYear":1277,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":1290,"openAccess":24,"references":1291,"isForceReanalyzing":319},"3da45247-7f1d-4b0f-871c-7d2db3b34752","2024-10-16T11:50:31.689+00:00","2025-01-08T20:48:51.907+00:00",[],"Macroeconomic-forecasting-and-structural-change",{"openalex":1140,"mag":1142,"abstract":1144,"title":1147,"keywords":1150,"doi":1151},{"VOID":1141},"W2119327830",{"VOID":1143},"2119327830",{"VI":1145,"EN":1146},"\u003Cjats:title>TÓM TẮT\u003C\u002Fjats:title>\u003Cjats:p>Mục tiêu của bài báo này là đánh giá xem việc mô hình hóa biến đổi cấu trúc có thể giúp cải thiện độ chính xác của các dự báo kinh tế vĩ mô hay không. Chúng tôi thực hiện một bài kiểm tra thực tế mô phỏng ngoài mẫu sử dụng một mô hình hồi quy vectơ với hệ số thay đổi theo thời gian (VAR) có độ biến động ngẫu nhiên để dự đoán tỷ lệ lạm phát, tỷ lệ thất nghiệp và lãi suất tại Hoa Kỳ. Mô hình này tạo ra các dự đoán chính xác cho cả ba biến. Đặc biệt, các dự báo về lạm phát chính xác hơn nhiều so với các mô hình cạnh tranh khác, bao gồm cả các mô hình VAR với hệ số cố định, hồi quy tự hồi quy thay đổi theo thời gian và mô hình đi ngẫu nhiên ngây thơ. Các kết quả này cũng đúng sau giữa những năm 1980, một giai đoạn mà việc dự đoán lạm phát là vô cùng khó khăn. Bản quyền © 2011 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>","\u003Cjats:title>SUMMARY\u003C\u002Fjats:title>\u003Cjats:p>The aim of this paper is to assess whether modeling structural change can help improving the accuracy of macroeconomic forecasts. We conduct a simulated real‐time out‐of‐sample exercise using a time‐varying coefficients vector autoregression (VAR) with stochastic volatility to predict the inflation rate, unemployment rate and interest rate in the USA. The model generates accurate predictions for the three variables. In particular, the forecasts of inflation are much more accurate than those obtained with any other competing model, including fixed coefficients VARs, time‐varying autoregressions and the naïve random walk model. The results hold true also after the mid 1980s, a period in which forecasting inflation was particularly hard. Copyright © 2011 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>",{"EN":1148,"VI":1149},"Macroeconomic forecasting and structural change","Dự đoán kinh tế vĩ mô và biến đổi cấu trúc",{"VI":847},{"VOID":1152},"10.1002\u002Fjae.1257","2024-10-16T11:50:31.688+00:00",[139],[141],"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1002\u002Fjae.1257",[1158,1175,1194],{"id":1159,"sortIndex":25,"researcher":24,"roles":1160,"affiliations":1161,"properties":1170,"displayName":1172,"givenName":24,"familyName":24},"256e63ab-303d-4a21-8ea8-8ec47c98ac69",[],[1162],{"id":1163,"sortIndex":25,"affiliation":1164,"properties":24},"ca724145-89ce-419e-bd43-9a9857d004cc",{"id":1163,"createTime":24,"updateTime":24,"relativeEntities":1165,"slug":24,"properties":1166,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1169,"statistic":24},[],{"title":1167},{"EN":1168},"CBFSAI, European Central Bank, Frankfurt am Main, Germany",[],{"title":1171,"openalex":1173},{"EN":1172},"Antonello D’Agostino",{"VOID":1174},"A5022932066",{"id":1176,"sortIndex":97,"researcher":24,"roles":1177,"affiliations":1178,"properties":1187,"displayName":1191,"givenName":24,"familyName":24},"77902f79-70cd-4a7f-93ea-c1773fbf34f2",[],[1179],{"id":1180,"sortIndex":25,"affiliation":1181,"properties":24},"387eaa5c-a06f-4733-965b-868be791607e",{"id":1180,"createTime":24,"updateTime":24,"relativeEntities":1182,"slug":24,"properties":1183,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1186,"statistic":24},[],{"title":1184},{"VI":1185},"Departament d' Economia i Història Econòmica, Universitat Autònoma de Barcelona, Spain",[],{"orcid":1188,"title":1190,"openalex":1192},{"VOID":1189},"https:\u002F\u002Forcid.org\u002F0009-0002-5082-174X",{"EN":1191},"Luca 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GewekeJ.2007.Hierarchical Markov normal mixture models with applications to financial asset returns. Working Paper Series 831 European Central Bank.",{"doi":1295},"10.2139\u002Fssrn.1009589",{"id":24,"text":1297,"url":24,"identifiers":1298},"10.1198\u002F073500106000000332",{"doi":1297},{"id":24,"text":1300,"url":24,"identifiers":1301},"Atkeson A, 2001, Are Phillips curves useful for forecasting inflation?, Federal Reserve Bank of Minneapolis Quarterly Review, 2",{},{"id":24,"text":1303,"url":24,"identifiers":1304},"10.1198\u002F073500104000000271",{"doi":1303},{"id":24,"text":1306,"url":24,"identifiers":1307},"Bates J, 1968, The combination of forecasts, Operational Research Quarterly, 20, 451, 10.1057\u002Fjors.1969.103",{"doi":1308},"10.1057\u002Fjors.1969.103",{"id":24,"text":1310,"url":24,"identifiers":1311},"10.1111\u002Fj.1538-4616.2008.00106.x",{"doi":1310},{"id":24,"text":1313,"url":24,"identifiers":1314},"10.1017\u002FS136510050705033X",{"doi":1313},{"id":24,"text":1316,"url":24,"identifiers":1317},"10.1016\u002Fj.jedc.2008.05.010",{"doi":1316},{"id":24,"text":1319,"url":24,"identifiers":1320},"10.1093\u002Fbiomet\u002F81.3.541",{"doi":1319},{"id":24,"text":1322,"url":24,"identifiers":1323},"10.1162\u002F003355300554692",{"doi":1322},{"id":24,"text":1325,"url":24,"identifiers":1326},"ClarkTE.2011.Real‐time density forecasts from VARs with stochastic volatility.Journal of Business Economics and Statistics(forthcoming).",{},{"id":24,"text":1328,"url":24,"identifiers":1329},"10.1002\u002Fjae.1127",{"doi":1328},{"id":24,"text":1331,"url":24,"identifiers":1332},"Cogley T, 2001, Macroeconomics Annual, 331",{},{"id":24,"text":1334,"url":24,"identifiers":1335},"10.1016\u002Fj.red.2004.10.009",{"doi":1334},{"id":24,"text":1337,"url":24,"identifiers":1338},"10.1016\u002Fj.jedc.2005.06.005",{"doi":1337},{"id":24,"text":1340,"url":24,"identifiers":1341},"10.1257\u002Fmac.2.1.43",{"doi":1340},{"id":24,"text":1343,"url":24,"identifiers":1344},"D'AgostinoA GiannoneD SuricoP.2006.(Un)predictability and macroeconomic stability. Working Paper Series 605 European Central Bank.",{},{"id":24,"text":1346,"url":24,"identifiers":1347},"10.1080\u002F07474938408800053",{"doi":1346},{"id":24,"text":1349,"url":24,"identifiers":1350},"10.1257\u002Fmac.1.1.26",{"doi":1349},{"id":24,"text":1352,"url":24,"identifiers":1353},"10.1162\u002FJEEA.2008.6.2-3.621",{"doi":1352},{"id":24,"text":1355,"url":24,"identifiers":1356},"GiordaniP VillaniM.2009.Forecasting macroeconomic time series with locally adaptive signal extraction. Working Paper Series 234 Sveriges Riksbank (Central Bank of Sweden).",{"doi":1357},"10.2139\u002Fssrn.1551203",{"id":24,"text":1359,"url":24,"identifiers":1360},"10.1016\u002Fj.ijforecast.2009.10.007",{"doi":1359},{"id":24,"text":1362,"url":24,"identifiers":1363},"Huurman C, 2010, The power of weather, Computational Statistics and Data Analysis",{},{"id":24,"text":1365,"url":24,"identifiers":1366},"10.1002\u002Fjae.1162",{"doi":1365},{"id":24,"text":1368,"url":24,"identifiers":1369},"10.1111\u002F1467-937X.00050",{"doi":1368},{"id":24,"text":1371,"url":24,"identifiers":1372},"Mitchell J, 2010, Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness, Journal of Applied Econometrics",{},{"id":24,"text":1374,"url":24,"identifiers":1375},"10.1016\u002Fj.jedc.2006.05.001",{"doi":1374},{"id":24,"text":1377,"url":24,"identifiers":1378},"10.1111\u002Fj.1467-937X.2005.00353.x",{"doi":1377},{"id":24,"text":1380,"url":24,"identifiers":1381},"Roberts JM, 2006, Monetary policy and inflation dynamics, International Journal of Central Banking, 2, 193",{},{"id":24,"text":1383,"url":24,"identifiers":1384},"10.1257\u002Faer.90.3.429",{"doi":1383},{"id":24,"text":1386,"url":24,"identifiers":1387},"RossiB SekhposyanT.2008.Has models' forecasting performance for US output growth and inflation changed over time and when?Manuscript Duke University.",{},{"id":24,"text":1389,"url":24,"identifiers":1390},"10.3386\u002Fw8320",{"doi":1389},{"id":24,"text":1392,"url":24,"identifiers":1393},"10.2307\u002F1392096",{"doi":1392},{"id":24,"text":1395,"url":24,"identifiers":1396},"Stock JH, 2004, NBER Macroeconomics Annual 2003, 159",{},{"id":24,"text":1398,"url":24,"identifiers":1399},"10.1111\u002Fj.1538-4616.2007.00014.x",{"doi":1398},{"id":24,"text":1401,"url":24,"identifiers":1402},"StockJH WatsonMW.2008.Phillips curve inflation forecasts. NBER Working Paper 14322.",{"doi":1403},"10.3386\u002Fw14322",{"id":24,"text":1405,"url":24,"identifiers":1406},"StrachanRW van DijkH K.2008.Bayesian averaging over many dynamic model structures with evidence on the great ratios and liquidity trap risk. Tinbergen Institute Discussion Papers 08‐096\u002F4 Tinbergen Institute.",{"doi":1407},"10.2139\u002Fssrn.1283567",{"id":1409,"createTime":1410,"updateTime":1411,"relativeEntities":1412,"slug":1413,"properties":1414,"entityType":135,"verifyStatus":136,"verifyTime":1410,"verifyNote":137,"languages":1428,"translateLanguages":1429,"viewCount":25,"primaryUrl":1430,"fullTextUrl":24,"authors":1431,"publicationType":180,"publisherRelationship":1451,"citationCount":1506,"citationInfo":1507,"publishDate":1512,"publishYear":1508,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":1513,"openAccess":24,"references":1514,"isForceReanalyzing":319},"b714d443-e9c7-4ffc-adfd-0dd98bf70efd","2024-11-25T07:53:57.343+00:00","2025-01-08T20:47:56.658+00:00",[],"Doubly-Robust-Estimation-of-Causal-Effects-with-Multivalued-Treatments-An-Application-to-the-Returns-to-Schooling",{"openalex":1415,"mag":1417,"abstract":1419,"title":1422,"keywords":1425,"doi":1426},{"VOID":1416},"W2145490350",{"VOID":1418},"2145490350",{"VI":1420,"EN":1421},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\u003Cjats:p>Bài báo này cung cấp các ước lượng gấp đôi cho các tham số hiệu ứng điều trị được định nghĩa trong khung hiệu ứng điều trị nhiều giá trị. Chúng tôi áp dụng phương pháp này vào tập dữ liệu độc nhất của Nghiên cứu Cohort Anh năm 1970 (BCS70) để ước lượng lợi nhuận từ các mức độ giáo dục khác nhau. Phân tích được thực hiện cho các mẫu nữ và nam riêng biệt để nắm bắt những khác biệt giới tính có thể xảy ra. Lợi nhuận trung bình được ước lượng cho toàn bộ dân số, cũng như có điều kiện dựa trên việc đạt được một thành quả giáo dục cụ thể. Đối với nam giới, so với không có bằng cấp, chúng tôi tìm thấy lợi nhuận trung bình vào cấp O là 6,3%, vào cấp A là 7,9% và vào giáo dục đại học là 25,4%. Lợi nhuận trung bình ước lượng vào cấp O và A so với không có bằng cấp là không đáng kể đối với nữ giới, trong khi lợi nhuận từ giáo dục đại học là 19,9%. Bản quyền © 2014 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>","\u003Cjats:title>Summary\u003C\u002Fjats:title>\u003Cjats:p>This paper provides doubly robust estimators for treatment effect parameters which are defined in a multivalued treatment effect framework. We apply this method to the unique dataset of the 1970 British Cohort Study (BCS70) to estimate returns to various levels of schooling. The analysis is carried out for female and male samples separately to capture possible gender differences. Average returns are estimated for the entire population, as well as conditional on having a specific educational achievement. For males, relative to no qualification, we find an average return to O‐levels of 6.3%, to A‐levels of 7.9% and to higher education of 25.4%. The estimated average returns to O‐level and A‐level relative to no qualification are insignificant for females, whereas the return to higher education is 19.9%.Copyright © 2014 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>",{"EN":1423,"VI":1424},"Doubly Robust Estimation of Causal Effects with Multivalued Treatments: An Application to the Returns to Schooling","Đánh Giá Nguyên Nhân Gấp Đôi Với Các Biện Pháp Đối Xử Nhiều Giá Trị: Ứng Dụng Vào Lợi Nhuận Từ Giáo Dục",{"VI":847},{"VOID":1427},"10.1002\u002Fjae.2386",[139],[141],"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1002\u002Fjae.2386",[1432],{"id":1433,"sortIndex":25,"researcher":24,"roles":1434,"affiliations":1435,"properties":1444,"displayName":1448,"givenName":24,"familyName":24},"0f699481-3543-4a5d-85a8-8a7f4ea7c7fb",[],[1436],{"id":1437,"sortIndex":25,"affiliation":1438,"properties":24},"89c080d1-0247-4174-a88b-69f3c6bcacce",{"id":1437,"createTime":24,"updateTime":24,"relativeEntities":1439,"slug":24,"properties":1440,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1443,"statistic":24},[],{"title":1441},{"VI":1442},"Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria",[],{"orcid":1445,"title":1447,"openalex":1449},{"VOID":1446},"https:\u002F\u002Forcid.org\u002F0000-0001-9670-2290",{"EN":1448},"S. 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R., 1965, Linear Statistical Inference and its Applications",{},{"id":24,"text":1873,"url":24,"identifiers":1874},"10.2307\u002F1911980",{"doi":1873},{"id":24,"text":1876,"url":24,"identifiers":1877},"10.2307\u002F2938337",{"doi":1876},{"id":24,"text":1879,"url":24,"identifiers":1880},"10.2307\u002F1913104",{"doi":1879},{"id":1882,"createTime":1883,"updateTime":1884,"relativeEntities":1885,"slug":1886,"properties":1887,"entityType":135,"verifyStatus":136,"verifyTime":1901,"verifyNote":137,"languages":1902,"translateLanguages":1903,"viewCount":25,"primaryUrl":1904,"fullTextUrl":24,"authors":1905,"publicationType":180,"publisherRelationship":1967,"citationCount":2022,"citationInfo":2023,"publishDate":2026,"publishYear":2024,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":2027,"openAccess":24,"references":2028,"isForceReanalyzing":319},"b78710c1-283f-4eba-bcd5-e083541dd600","2024-12-20T07:04:32.219+00:00","2025-01-08T20:46:05.120+00:00",[],"Efficiency-externalities-of-trade-and-alternative-forms-of-foreign-investment-in-OECD-countries",{"openalex":1888,"mag":1890,"abstract":1892,"title":1895,"keywords":1898,"doi":1899},{"VOID":1889},"W1989289937",{"VOID":1891},"1989289937",{"VI":1893,"EN":1894},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\u003Cjats:p>Tài liệu về các hiệu ứng bùng phát của thương mại và dòng vốn đầu tư trực tiếp nước ngoài (FDI) chủ yếu tập trung vào các ngoại tác công nghệ. Ít nỗ lực đã được thực hiện để xác định các ngoại tác về hiệu suất của chúng. Bài báo này đo lường các ngoại tác về hiệu suất của thương mại và nhiều hình thức đầu tư nước ngoài cho một mẫu gồm 20 quốc gia OECD trong giai đoạn từ 1982 đến 2000 bằng cách sử dụng phương pháp biên ngẫu nhiên. Thương mại và tất cả các dòng vốn đầu tư nước ngoài đều được phát hiện làm tăng hiệu suất, trong khi dòng vốn đầu tư trực tiếp nước ngoài ra nước ngoài làm trầm trọng thêm tình trạng không hiệu quả. Các ngoại tác về hiệu suất từ đầu tư nước ngoài phụ thuộc vào khả năng hấp thụ của các nền kinh tế tiếp nhận. Bản quyền © 2008 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>The literature on the spillover effects of trade and inflows of foreign direct investment (FDI) has concentrated on technological externalities. Little effort has been directed towards identifying their efficiency externalities. This paper measures the efficiency externalities of trade and various forms of foreign investment for a sample of 20 OECD countries between 1982 and 2000 using a stochastic frontier approach. Trade and all foreign investment inflows are found to enhance efficiency, whereas outflows of FDI are found to exacerbate inefficiency. The efficiency externalities from foreign investment are contingent on the absorptive capacity of the host economies. Copyright © 2008 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>",{"EN":1896,"VI":1897},"Efficiency externalities of trade and alternative forms of foreign investment in OECD countries","Các hiệu ứng bên ngoài về hiệu suất của thương mại và các hình thức đầu tư nước ngoài thay thế tại các quốc gia OECD",{"VI":847},{"VOID":1900},"10.1002\u002Fjae.1024","2024-12-20T07:04:32.218+00:00",[139],[141],"https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1002\u002Fjae.1024",[1906,1931,1950],{"id":1907,"sortIndex":25,"researcher":24,"roles":1908,"affiliations":1909,"properties":1926,"displayName":1928,"givenName":24,"familyName":24},"8fc1d5ea-956c-4d29-a4a4-d0420d073b6e",[],[1910,1918],{"id":1911,"sortIndex":25,"affiliation":1912,"properties":24},"580448b8-2c68-4130-9ec6-3e157ca9190a",{"id":1911,"createTime":24,"updateTime":24,"relativeEntities":1913,"slug":24,"properties":1914,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1917,"statistic":24},[],{"title":1915},{"VI":1916},"Department of Applied and International Economics, Massey University, Palmerston North, New Zealand",[],{"id":1919,"sortIndex":97,"affiliation":1920,"properties":24},"5601ccc0-6598-4e75-86a5-4ebd7b8ecb58",{"id":1919,"createTime":24,"updateTime":24,"relativeEntities":1921,"slug":24,"properties":1922,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1925,"statistic":24},[],{"title":1923},{"EN":1924},"This work was completed when the author was a PhD student in the School of Economics and the Centre for Efficiency and Productivity Analysis, University of Queensland, Australia",[],{"title":1927,"openalex":1929},{"EN":1928},"Krishna G. Iyer",{"VOID":1930},"A5024717096",{"id":1932,"sortIndex":97,"researcher":24,"roles":1933,"affiliations":1934,"properties":1943,"displayName":1947,"givenName":24,"familyName":24},"10424d30-465f-4373-af44-525eabbfc6e9",[],[1935],{"id":1936,"sortIndex":25,"affiliation":1937,"properties":24},"bd7911b4-bee8-4bc6-bb99-a14563af422e",{"id":1936,"createTime":24,"updateTime":24,"relativeEntities":1938,"slug":24,"properties":1939,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1942,"statistic":24},[],{"title":1940},{"EN":1941},"School of Economics, Centre for Efficiency and Productivity Analysis, University of Queensland, Brisbane, Australia",[],{"orcid":1944,"title":1946,"openalex":1948},{"VOID":1945},"https:\u002F\u002Forcid.org\u002F0000-0001-6438-8954",{"EN":1947},"Alicia N. Rambaldi",{"VOID":1949},"A5050225010",{"id":1951,"sortIndex":621,"researcher":24,"roles":1952,"affiliations":1953,"properties":1960,"displayName":1964,"givenName":24,"familyName":24},"905dcf0c-a4cb-4e92-9681-c667a9ed4179",[],[1954],{"id":1936,"sortIndex":25,"affiliation":1955,"properties":24},{"id":1936,"createTime":24,"updateTime":24,"relativeEntities":1956,"slug":24,"properties":1957,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1959,"statistic":24},[],{"title":1958},{"EN":1941},[],{"orcid":1961,"title":1963,"openalex":1965},{"VOID":1962},"https:\u002F\u002Forcid.org\u002F0000-0001-7282-8112",{"EN":1964},"Kam Ki Tang",{"VOID":1966},"A5008435016",{"url":24,"publisher":1968,"properties":2015},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1969,"slug":10,"properties":1970,"entityType":22,"verifyStatus":23,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":25,"subjectFields":1975,"manageAffiliations":1984,"indexDatabases":1995,"url":91,"thumbnailPath":24,"statistic":2010,"gsStatistic":24,"type":24,"analyzePriority":24},[],{"country":1971,"eissn":1972,"issn":1973,"title":1974},{"VOID":13},{"VOID":15},{"VOID":17},{"EN":19},[1976,1980],{"id":28,"createTime":24,"updateTime":24,"relativeEntities":1977,"label":1978,"description":1979,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":31},{},{"id":34,"createTime":24,"updateTime":24,"relativeEntities":1981,"label":1982,"description":1983,"parentId":24,"standard":24,"scholarHubFieldId":24},[],{"EN":37},{},[1985,1990],{"id":41,"createTime":24,"updateTime":24,"relativeEntities":1986,"slug":24,"properties":1987,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1989,"statistic":24},[],{"title":1988},{"EN":45},[],{"id":48,"createTime":24,"updateTime":24,"relativeEntities":1991,"slug":24,"properties":1992,"entityType":24,"verifyStatus":24,"verifyTime":24,"verifyNote":24,"languages":24,"translateLanguages":24,"viewCount":24,"url":24,"parentIds":1994,"statistic":24},[],{"title":1993},{"EN":52},[],[1996,2003],{"id":56,"indexDatabase":1997,"url":67,"indexYears":68,"academicFieldIds":2002,"indexDatabaseRanking":72},{"id":58,"createTime":24,"updateTime":24,"relativeEntities":1998,"label":1999,"description":2000,"key":64,"publicationTags":2001,"standard":24},[],{"EN":61,"VI":61},{"EN":61,"VI":63},[66],[70,71],{"id":74,"indexDatabase":2004,"url":87,"indexYears":24,"academicFieldIds":2009,"indexDatabaseRanking":24},{"id":76,"createTime":24,"updateTime":24,"relativeEntities":2005,"label":2006,"description":2007,"key":83,"publicationTags":2008,"standard":24},[],{"EN":79,"VI":79},{"EN":81,"VI":82},[85,86],[89,90],{"impactFactor":25,"impactFactorByYear":2011,"i10Index":100,"i10IndexLast5Year":25,"totalPublication":100,"totalPublicationByYear":2012,"totalCitation":102,"totalCitationByYear":2013,"totalCitationPerPublication":111,"totalCitationPerPublicationByYear":2014,"hindexLast5Year":100,"hindex":100},{"2014":94,"2015":95,"2016":96,"2017":97,"2018":98,"2019":99},{"2001":97,"2006":97,"2007":97,"2013":97,"2014":97,"2016":97,"2017":97},{"2001":104,"2006":105,"2007":106,"2013":107,"2014":108,"2016":109,"2017":110},{"2001":104,"2006":105,"2007":106,"2013":107,"2014":108,"2016":109,"2017":110},{"issue":2016,"pages":2018,"volume":2020},{"VOID":2017},"6",{"VOID":2019},"749-766",{"VOID":2021},"23",36,{"total":2022,"publishYear":2024,"statisticByYear":2025},2008,{"2012":1780,"2013":99,"2014":964,"2015":963,"2016":621,"2017":963,"2018":97,"2019":97,"2021":621,"2022":97,"2024":621},"2008-09-01",[85,72],[2029,2032,2035,2038,2041,2044,2048,2051,2054,2057,2060,2063,2066,2069,2072,2075,2079,2082,2085,2088,2091,2094,2097,2100,2103,2106,2109,2112,2115,2118,2121,2124,2127,2130,2133,2136,2139,2142,2145,2148,2151,2154,2157,2160,2163,2166,2169],{"id":24,"text":2030,"url":24,"identifiers":2031},"10.1016\u002FS0022-1996(03)00081-3",{"doi":2030},{"id":24,"text":2033,"url":24,"identifiers":2034},"10.1057\u002Fpalgrave.jibs.8490107",{"doi":2033},{"id":24,"text":2036,"url":24,"identifiers":2037},"10.1093\u002Foep\u002F53.3.541",{"doi":2036},{"id":24,"text":2039,"url":24,"identifiers":2040},"BatteseGE CoelliTJ.1993.A stochastic frontier production function incorporating a model for technical inefficiency effects.Econometrics and Applied Statistics Working Paper Series No. 69 Department of Econometrics University of New England Armidale Australia.",{},{"id":24,"text":2042,"url":24,"identifiers":2043},"10.1007\u002FBF01205442",{"doi":2042},{"id":24,"text":2045,"url":24,"identifiers":2046},"Bernanke B, 2003, Is growth exogenous? Taking Mankiw, Romer, and Weil seriously, NBER Macroeconomics Annual 2001, 16, 11, 10.1086\u002F654431",{"doi":2047},"10.1086\u002F654431",{"id":24,"text":2049,"url":24,"identifiers":2050},"BlomströmM KokkoA.2003.Human capital and inward FDI. EIJSWorking Paper Series No. 167 European Institute of Japanese Studies Stockholm.",{},{"id":24,"text":2052,"url":24,"identifiers":2053},"10.1057\u002F9780230598447_2",{"doi":2052},{"id":24,"text":2055,"url":24,"identifiers":2056},"BoyleG McQuinnK.2004.Why do some countries produce so much more output per worker than others? A note.Research Technical Paper No. 9\u002FRT\u002F04 Central Bank and Financial Services Authority of Ireland Dublin.",{},{"id":24,"text":2058,"url":24,"identifiers":2059},"10.2307\u002F1913388",{"doi":2058},{"id":24,"text":2061,"url":24,"identifiers":2062},"10.1016\u002F0014-2921(94)00100-E",{"doi":2061},{"id":24,"text":2064,"url":24,"identifiers":2065},"10.2307\u002F2233763",{"doi":2064},{"id":24,"text":2067,"url":24,"identifiers":2068},"10.2307\u002F2393553",{"doi":2067},{"id":24,"text":2070,"url":24,"identifiers":2071},"Creane S, 2003, Banking on development, Finance and Development, IMF, 40",{},{"id":24,"text":2073,"url":24,"identifiers":2074},"10.1080\u002F713693833",{"doi":2073},{"id":24,"text":2076,"url":24,"identifiers":2077},"Epstein G, 2005, Capital Flight and Capital Controls in Developing Countries, 10.4337\u002F9781781008058",{"doi":2078},"10.4337\u002F9781781008058",{"id":24,"text":2080,"url":24,"identifiers":2081},"Färe R, 1994, Productivity growth, technical progress and efficiency changes in industrial countries, American Economic Review, 84, 66",{},{"id":24,"text":2083,"url":24,"identifiers":2084},"GörgH GreenawayD.2001.Foreign direct investment and intra‐industry spillovers: a review of the literature.Research Paper2001\u002F37 Globalisation and Labour Markets Programme Leverhulme Centre for Research on Globalisation and Economic Policy Nottingham UK.",{},{"id":24,"text":2086,"url":24,"identifiers":2087},"10.1162\u002F003355399555954",{"doi":2086},{"id":24,"text":2089,"url":24,"identifiers":2090},"10.1057\u002Fpalgrave.jibs.8490080",{"doi":2089},{"id":24,"text":2092,"url":24,"identifiers":2093},"HestonASummersR AtenB.2002.Penn World Table Version 6.1. Center for International Comparisons University of Pennsylvania.",{},{"id":24,"text":2095,"url":24,"identifiers":2096},"10.2307\u002F2946651",{"doi":2095},{"id":24,"text":2098,"url":24,"identifiers":2099},"KnellerR StevensPA.2002.The role of efficiency as an explanation of international income differences.NIESR Discussion Papers No. 205 NIESR London.",{},{"id":24,"text":2101,"url":24,"identifiers":2102},"10.1111\u002Fj.1468-0084.2006.00150.x",{"doi":2101},{"id":24,"text":2104,"url":24,"identifiers":2105},"10.2307\u002F1912331",{"doi":2104},{"id":24,"text":2107,"url":24,"identifiers":2108},"10.2307\u002F2109564",{"doi":2107},{"id":24,"text":2110,"url":24,"identifiers":2111},"10.1111\u002F1468-2354.00101",{"doi":2110},{"id":24,"text":2113,"url":24,"identifiers":2114},"10.1257\u002Fjel.39.4.1101",{"doi":2113},{"id":24,"text":2116,"url":24,"identifiers":2117},"10.1017\u002FCBO9781139174411",{"doi":2116},{"id":24,"text":2119,"url":24,"identifiers":2120},"10.1080\u002F00036840050151557",{"doi":2119},{"id":24,"text":2122,"url":24,"identifiers":2123},"10.1111\u002F1467-9396.00307",{"doi":2122},{"id":24,"text":2125,"url":24,"identifiers":2126},"Loungani P, 2001, How beneficial is foreign direct investment for developing countries, Finance and Development, IMF, 38",{},{"id":24,"text":2128,"url":24,"identifiers":2129},"MartinC VelazquezF.1997.The determining factors of foreign direct investment in Spain and the rest of the OECD: Lessons for the CEECS CEPR Discussion Paper Series No. 1637 CEPR London.",{},{"id":24,"text":2131,"url":24,"identifiers":2132},"McLeanB ShresthaS.2002.International financial liberalization and economic growth.Research Discussion Paper RDP 2002‐03 Economic Research Department Reserve Bank of Australia.",{},{"id":24,"text":2134,"url":24,"identifiers":2135},"10.1111\u002F1467-9361.00171",{"doi":2134},{"id":24,"text":2137,"url":24,"identifiers":2138},"NarulaR WakelinK.1997.The pattern and determinants of US foreign direct investment in industrialised countries.Research Memoranda 001 MERIT Maastricht.",{},{"id":24,"text":2140,"url":24,"identifiers":2141},"10.1007\u002FBF02755981",{"doi":2140},{"id":24,"text":2143,"url":24,"identifiers":2144},"OECD.2002.Measuring Productivity Levels: A Reader. OECD Working party on Statistics Directorate for Science technology and Industry.",{},{"id":24,"text":2146,"url":24,"identifiers":2147},"10.1016\u002FS1573-4471(88)01012-5",{"doi":2146},{"id":24,"text":2149,"url":24,"identifiers":2150},"10.2307\u002F2527389",{"doi":2149},{"id":24,"text":2152,"url":24,"identifiers":2153},"RaoDSP CoelliTJ.1998.A cross‐country analysis of GDP growth catch‐up and convergence in productivity and inequality.CEPA Working Paper Series No. 5\u002F98 CEPA University of New England Armdale Australia.",{},{"id":24,"text":2155,"url":24,"identifiers":2156},"10.1093\u002Fwbro\u002F17.2.191",{"doi":2155},{"id":24,"text":2158,"url":24,"identifiers":2159},"10.1007\u002F978-1-349-64373-8",{"doi":2158},{"id":24,"text":2161,"url":24,"identifiers":2162},"10.1080\u002F00074919912331337497",{"doi":2161},{"id":24,"text":2164,"url":24,"identifiers":2165},"10.1023\u002FA:1016565719882",{"doi":2164},{"id":24,"text":2167,"url":24,"identifiers":2168},"Weil D, 2005, Economic Growth",{},{"id":24,"text":2170,"url":24,"identifiers":2171},"10.1016\u002FS0304-3878(00)00093-6",{"doi":2170},{"id":2173,"createTime":2174,"updateTime":2175,"relativeEntities":2176,"slug":2177,"properties":2178,"entityType":135,"verifyStatus":136,"verifyTime":2192,"verifyNote":137,"languages":2193,"translateLanguages":2194,"viewCount":25,"primaryUrl":2195,"fullTextUrl":24,"authors":2196,"publicationType":180,"publisherRelationship":2235,"citationCount":2290,"citationInfo":2291,"publishDate":2305,"publishYear":2292,"citationAnalyzeStatus":23,"lastCitationAnalyze":24,"indexDatabases":2306,"openAccess":24,"references":2307,"isForceReanalyzing":319},"c5ce23fd-b696-4b6a-9d9e-ef6151ca7a8b","2024-12-24T02:01:36.538+00:00","2025-01-08T20:45:09.576+00:00",[],"A-forecast-comparison-of-volatility-models-does-anything-beat-a-GARCH-1-1-",{"openalex":2179,"mag":2181,"abstract":2183,"title":2186,"keywords":2189,"doi":2190},{"VOID":2180},"W3122175640",{"VOID":2182},"3122175640",{"VI":2184,"EN":2185},"\u003Cjats:title>Tóm tắt\u003C\u002Fjats:title>\u003Cjats:p>Chúng tôi so sánh 330 mô hình loại ARCH về khả năng mô tả phương sai có điều kiện. Các mô hình được so sánh ngoài mẫu sử dụng dữ liệu tỷ giá hối đoái DM–$ và dữ liệu lợi nhuận của IBM, trong đó dữ liệu lợi nhuận dựa trên một tập dữ liệu mới về phương sai thực tế. Chúng tôi không tìm thấy bằng chứng nào cho thấy mô hình GARCH(1,1) bị vượt trội bởi các mô hình phức tạp hơn trong phân tích tỷ giá hối đoái, trong khi đó GARCH(1,1) rõ ràng là kém hơn so với các mô hình có thể tiếp nhận hiệu ứng đòn bẩy trong phân tích lợi nhuận của IBM. Các mô hình được so sánh bằng kiểm tra khả năng dự đoán tốt hơn (SPA) và kiểm tra thực tế cho việc xem xét dữ liệu (RC). Kết quả thực nghiệm của chúng tôi cho thấy RC thiếu sức mạnh đến mức không thể phân biệt được các mô hình 'tốt' và 'xấu' trong phân tích của chúng tôi. Bản quyền © 2005 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>We compare 330 ARCH‐type models in terms of their ability to describe the conditional variance. The models are compared out‐of‐sample using DM–$ exchange rate data and IBM return data, where the latter is based on a new data set of realized variance. We find no evidence that a GARCH(1,1) is outperformed by more sophisticated models in our analysis of exchange rates, whereas the GARCH(1,1) is clearly inferior to models that can accommodate a leverage effect in our analysis of IBM returns. The models are compared with the test for superior predictive ability (SPA) and the reality check for data snooping (RC). Our empirical results show that the RC lacks power to an extent that makes it unable to distinguish ‘good’ and ‘bad’ models in our analysis. Copyright © 2005 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>",{"EN":2187,"VI":2188},"A forecast comparison of volatility models: does anything beat a GARCH(1,1)?","So sánh dự báo của các mô hình biến động: Liệu có mô hình nào vượt trội hơn 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Kết quả này được thúc đẩy bởi sự biến động của giá hợp đồng tương lai so với giá giao ngay, được thể hiện qua chênh lệch giá dầu tương lai. Sự biến động này có thể được giải thích bằng lợi suất tiện nghi cận biên của các kho dự trữ dầu. Sử dụng mô hình tổng quát cân bằng nhiều kỳ hai quốc gia cho thị trường giao ngay và hợp đồng tương lai cho dầu thô, chúng tôi cho thấy rằng sự gia tăng sự không chắc chắn về những thiếu hụt nguồn cung dầu trong tương lai, dưới những giả định hợp lý, dẫn đến việc chênh lệch giá giảm. Sự không chắc chắn gia tăng cũng làm tăng nhu cầu dự phòng cho dầu, dẫn đến sự gia tăng ngay lập tức trong giá giao ngay thực tế. Do đó, giá trị âm của chênh lệch giá dầu tương lai có thể được coi là một chỉ số của sự dao động trong giá dầu thô do nhu cầu dự phòng tác động. Phân tích thực nghiệm của chỉ số này cung cấp bằng chứng về cách mà sự thay đổi trong sự không chắc chắn về nguồn cung dầu trong tương lai ảnh hưởng đến giá giao ngay thực tế của dầu thô. Bản quyền © 2010 John Wiley & Sons, Ltd.\u003C\u002Fjats:p>","\u003Cjats:title>Abstract\u003C\u002Fjats:title>\u003Cjats:p>Despite their widespread use as predictors of the spot price of oil, oil futures prices tend to be less accurate in the mean‐squared prediction error sense than no‐change forecasts. This result is driven by the variability of the futures price about the spot price, as captured by the oil futures spread. This variability can be explained by the marginal convenience yield of oil inventories. Using a two‐country, multi‐period general equilibrium model of the spot and futures markets for crude oil we show that increased uncertainty about future oil supply shortfalls under plausible assumptions causes the spread to decline. Increased uncertainty also causes precautionary demand for oil to increase, resulting in an immediate increase in the real spot price. Thus the negative of the oil futures spread may be viewed as an indicator of fluctuations in the price of crude oil driven by precautionary demand. An empirical analysis of this indicator provides evidence of how shifts in the uncertainty about future oil supply shortfalls affect the real spot price of crude oil. 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