LEADER 04927nam 22007335 450 001 9910254097803321 005 20250504233854.0 010 $a3-319-31822-5 024 7 $a10.1007/978-3-319-31822-6 035 $a(CKB)3710000000734706 035 $a(DE-He213)978-3-319-31822-6 035 $a(MiAaPQ)EBC4561879 035 $a(PPN)194379043 035 $a(EXLCZ)993710000000734706 100 $a20160620d2016 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSeasonal Adjustment Methods and Real Time Trend-Cycle Estimation /$fby Estela Bee Dagum, Silvia Bianconcini 205 $a1st ed. 2016. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016. 215 $a1 online resource (XVI, 283 p. 52 illus., 10 illus. in color.) 225 1 $aStatistics for Social and Behavioral Sciences,$x2199-7365 311 08$a3-319-31820-9 320 $aIncludes bibliographical references at the end of each chapters. 327 $aIntroduction -- Time Series Components -- Part I: Seasonal Adjustment Methods -- Seasonal Adjustment: Meaning, Purpose and Methods -- Linear Filters Seasonal Adjustment Methods: Census Method II and its Variants -- Seasonal Adjustment Based on ARIMA Decomposition: TRAMO-SEATS.- Seasonal Adjustment Based on Structural Time Series Models -- Part II: Trend-Cycle Estimation.- Trend-Cycle Estimation.- Further Developments on the Henderson Trend-Cycle Filter.- A Unified View of Trend-Cycle Predictors in Reproducing Kernel Hilbert Spaces (RKHS).- Real Time Trend-Cycle Prediction.- The Effect of Seasonal Adjustment on Real-Time Trend-Cycle Prediction -- Glossary. 330 $aThis book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies.  Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportation, and consumers in general to decide on appropriate action. This book appeals to practitioners in government institutions, finance and business, macroeconomists, and other professionals who use economic data as well as academic researchers in time series analysis, seasonal adjustment methods, filtering and signal extraction. It is also useful for graduate and final-year undergraduate courses in econometrics and time series with a good understanding of linear regression and matrix algebra, as well as ARIMA modelling. 410 0$aStatistics for Social and Behavioral Sciences,$x2199-7365 606 $aStatistics 606 $aStatistics 606 $aSocial sciences$xStatistical methods 606 $aMacroeconomics 606 $aProbabilities 606 $aEconometrics 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aStatistical Theory and Methods 606 $aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy 606 $aMacroeconomics and Monetary Economics 606 $aProbability Theory 606 $aEconometrics 615 0$aStatistics. 615 0$aStatistics. 615 0$aSocial sciences$xStatistical methods. 615 0$aMacroeconomics. 615 0$aProbabilities. 615 0$aEconometrics. 615 14$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aStatistical Theory and Methods. 615 24$aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. 615 24$aMacroeconomics and Monetary Economics. 615 24$aProbability Theory. 615 24$aEconometrics. 676 $a330.0182 700 $aBee Dagum$b Estela$4aut$4http://id.loc.gov/vocabulary/relators/aut$0630556 702 $aBianconcini$b Silvia$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910254097803321 996 $aSeasonal Adjustment Methods and Real Time Trend-Cycle Estimation$92155976 997 $aUNINA