LEADER 04598oam 22011174 450 001 9910973342803321 005 20250426110741.0 010 $a9786613822512 010 $a9781462371990 010 $a146237199X 010 $a9781452789484 010 $a1452789487 010 $a9781282565180 010 $a1282565184 010 $a9781451909937 010 $a1451909934 035 $a(CKB)3360000000443286 035 $a(EBL)3014338 035 $a(SSID)ssj0000940816 035 $a(PQKBManifestationID)11528536 035 $a(PQKBTitleCode)TC0000940816 035 $a(PQKBWorkID)10955964 035 $a(PQKB)11705944 035 $a(OCoLC)698585538 035 $a(IMF)WPIEE2006280 035 $a(MiAaPQ)EBC3014338 035 $a(IMF)WPIEA2006280 035 $aWPIEA2006280 035 $a(EXLCZ)993360000000443286 100 $a20020129d2006 uf 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aFinancial Versus Monetary Mercantilism : $eLong-Run View of Large International Reserves Hoarding /$fJaewoo Lee, Joshua Aizenman 205 $a1st ed. 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2006. 215 $a1 online resource (24 p.) 225 1 $aIMF Working Papers 300 $a"December 2006." 311 08$a9781451865400 311 08$a1451865406 320 $aIncludes bibliographical references. 327 $a""Contents""; ""I. OVERVIEW""; ""II. FINANCIAL VERSUS MONETARY MERCANTILISM OVER THE DECADES: 1970a??? 2005""; ""III. THE HAZARD OF COMPETITIVE HOARDING""; ""IV. BANK FRAGILITY: ON THE OBSERVATION EQUIVALENCE OF MONETARY MERCANTILISM AND SELF- INSURANCE""; ""V. CONCLUSION""; ""REFERENCES"" 330 3 $aThe sizable hoarding of international reserves by several East Asian countries has been frequently attributed to a modern version of monetary mercantilism-hoarding international reserves in order to improve competitiveness. From a long-run perspective, manufacturing exporters in East Asia adopted financial mercantilism-subsidizing the cost of capital- during decades of high growth. They switched to hoarding large international reserves when growth faltered, making it harder to disentangle the monetary mercantilism from a precautionary response to the heritage of past financial mercantilism. Monetary mercantilism also lowers the cost of hoarding through its short-term boost to external competitiveness, but may be associated with negative externalities leading to competitive hoarding. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2006/280 606 $aMercantile system$zEast Asia$xMathematical models 606 $aBalance of trade$zEast Asia 606 $aBanking$2imf 606 $aBanks and Banking$2imf 606 $aCurrency$2imf 606 $aEconomic & financial crises & disasters$2imf 606 $aFinancial Crises$2imf 606 $aFinancial crises$2imf 606 $aFinancial Institutions and Services: General$2imf 606 $aFinancial Risk Management$2imf 606 $aFinancial sector$2imf 606 $aFinancial services industry$2imf 606 $aForeign exchange reserves$2imf 606 $aForeign Exchange$2imf 606 $aForeign exchange$2imf 606 $aIndustries: Financial Services$2imf 606 $aInternational reserves$2imf 606 $aMonetary Policy$2imf 606 $aReal exchange rates$2imf 606 $aReserves accumulation$2imf 607 $aJapan$2imf 615 0$aMercantile system$xMathematical models. 615 0$aBalance of trade 615 7$aBanking 615 7$aBanks and Banking 615 7$aCurrency 615 7$aEconomic & financial crises & disasters 615 7$aFinancial Crises 615 7$aFinancial crises 615 7$aFinancial Institutions and Services: General 615 7$aFinancial Risk Management 615 7$aFinancial sector 615 7$aFinancial services industry 615 7$aForeign exchange reserves 615 7$aForeign Exchange 615 7$aForeign exchange 615 7$aIndustries: Financial Services 615 7$aInternational reserves 615 7$aMonetary Policy 615 7$aReal exchange rates 615 7$aReserves accumulation 700 $aLee$b Jaewoo$01816497 701 $aAizenman$b Joshua$0122521 712 02$aNational Bureau of Economic Research. 801 0$bDcWaIMF 906 $aBOOK 912 $a9910973342803321 996 $aFinancial Versus Monetary Mercantilism$94372840 997 $aUNINA LEADER 04628nam 22006495 450 001 9910863136103321 005 20250402124400.0 010 $a3-662-62436-2 024 7 $a10.1007/978-3-662-62436-4 035 $a(CKB)4100000011610307 035 $a(MiAaPQ)EBC6407545 035 $a(DE-He213)978-3-662-62436-4 035 $a(PPN)252503090 035 $a(EXLCZ)994100000011610307 100 $a20201123d2020 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSingular Spectrum Analysis for Time Series /$fby Nina Golyandina, Anatoly Zhigljavsky 205 $a2nd ed. 2020. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2020. 215 $a1 online resource (IX, 146 p. 44 illus., 38 illus. in color.) 225 1 $aSpringerBriefs in Statistics,$x2191-5458 311 08$a3-662-62435-4 327 $a1 Introduction -- 1.1 Overview of SSA methodology and the structure of the book -- 1.2 SSA and other techniques -- 1.3 Computer implementation of SSA -- 1.4 Historical and bibliographical remarks -- 1.5 Common symbols and acronyms -- 2 Basic SSA - 2.1 The main algorithm -- 2.2 Potential of Basic SSA -- 2.3 Models of time series and SSA objectives -- 2.4 Choice of parameters in Basic SSA -- 2.5 Some variations of Basic SSA -- 2.6 Multidimensional and multivariate extensions of SSA -- 3 SSA for forecasting, interpolation, filtering and estimation -- 3.1 SSA forecasting algorithms -- 3.2 LRR and associated characteristic polynomials -- 3.3 Recurrent forecasting as approximate continuation -- 3.4 Confidence bounds for the forecasts -- 3.5 Summary and recommendations on forecasting parameters -- 3.6 Case study: ?Fortified wine? -- 3.7 Imputation of missing values -- 3.8 Subspace-based methods and estimation of signal parameters -- 3.9 SSA and filters -- 3.10 Multidimensional/Multivariate SSA. 330 $aThis book gives an overview of singular spectrum analysis (SSA). SSA is a technique of time series analysis and forecasting combining elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA is multi-purpose and naturally combines both model-free and parametric techniques, which makes it a very special and attractive methodology for solving a wide range of problems arising in diverse areas. Rapidly increasing number of novel applications of SSA is a consequence of the new fundamental research on SSA and the recent progress in computing and software engineering which made it possible to use SSA for very complicated tasks that were unthinkable twenty years ago. In this book, the methodology of SSA is concisely but at the same time comprehensively explained by two prominent statisticians with huge experience in SSA. The book offers a valuable resource for a very wide readership, including professional statisticians, specialists in signal and image processing, as well as specialists in numerous applied disciplines interested in using statistical methods for time series analysis, forecasting, signal and image processing. The second edition of the book contains many updates and some new material including a thorough discussion on the place of SSA among other methods and new sections on multivariate and multidimensional extensions of SSA. 410 0$aSpringerBriefs in Statistics,$x2191-5458 606 $aStatistics 606 $aStatistics 606 $aSignal processing 606 $aBiometry 606 $aStatistical Theory and Methods 606 $aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences 606 $aSignal, Speech and Image Processing 606 $aStatistics in Business, Management, Economics, Finance, Insurance 606 $aBiostatistics 615 0$aStatistics. 615 0$aStatistics. 615 0$aSignal processing. 615 0$aBiometry. 615 14$aStatistical Theory and Methods. 615 24$aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences. 615 24$aSignal, Speech and Image Processing. 615 24$aStatistics in Business, Management, Economics, Finance, Insurance. 615 24$aBiostatistics. 676 $a519.55 700 $aGolyandina$b Nina$0145508 702 $aZhigljavsky$b Anatoly 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910863136103321 996 $aSingular Spectrum Analysis for Time Series$92510999 997 $aUNINA