05774oam 22012734 450 991078833510332120230721045734.01-4623-6283-41-4527-0769-31-282-84326-51-4518-7258-59786612843266(CKB)3170000000055265(EBL)1608295(SSID)ssj0000943256(PQKBManifestationID)11484315(PQKBTitleCode)TC0000943256(PQKBWorkID)10975385(PQKB)11447616(OCoLC)645513330(MiAaPQ)EBC1608295(IMF)WPIEE2009111(EXLCZ)99317000000005526520020129d2009 uf 0engurcn|||||||||txtccrSpillovers to Emerging Equity Markets : An Econometric Assessment /Tao Sun, L. PsalidaWashington, D.C. :International Monetary Fund,2009.1 online resource (34 p.)IMF Working PapersDescription based upon print version of record.1-4519-1688-4 Includes bibliographical references.Contents; I. Introduction; II. Performance of Emerging Market Equity Markets; Figures; 1. Selected Equity Market Indices; 2. Emerging Market Economies: Composition of Capital Inflows; 3. Current Account Balances and Capital Flows from a Global Perspective; 4. Stock Market Capitalization; 5. Total Equity Market Returns; 6. Emerging Market Economies: Price/Earnings Ratios; 7. Total Foreign Holdings of Equity; 8. Emerging Markets Equity Indices and Foreign Investor Presence; Tables; 1. Emerging Equity Market Peaks and Troughs: Current and Previous Episodes; III. Methodology of Panel Estimation2. Unit Root Tests 3. Pedroni Heterogeneous Panel Co-integration Tests; IV. Results of the Panel Estimation; 4. Fixed-Effects Panel Least-Squares Estimation, First Specification; 5. Fixed-Effects Panel Least-Squares Estimation, Second Specification; V. Scenarios of impact; 6. Effects of External Shocks on the Growth Rates of Emerging Market Equity Prices; VI. Contribution of domestic and external factors; VII. Vector Auto-regression Model and results; 7. Contribution of Global and Domestic Factors to Equity Price Changes; 9. Impulse Responses to the Global Shocks for the Seven CountriesVIII. Main Conclusions Annexes; I. Methodological Issues; II. Data and explanatory variables; ReferencesThis paper shows that emerging market equity prices are influenced by growing global factors, and therefore global factors constitute a significant channel for spillovers when the international economic environment changes. Strengthening their resilience to equity price declines remains an important goal for emerging market economies.IMF Working Papers; Working Paper ;No. 2009/111InvestmentsMathematical modelsEconometricsBanks and BankingimfFinance: GeneralimfInvestments: StocksimfGeneral Financial Markets: General (includes Measurement and Data)imfPension FundsimfNon-bank Financial InstitutionsimfFinancial InstrumentsimfInstitutional InvestorsimfFinancing PolicyimfFinancial Risk and Risk ManagementimfCapital and Ownership StructureimfValue of FirmsimfGoodwillimfFinancial Markets and the MacroeconomyimfFinanceimfInvestment & securitiesimfFinancial services law & regulationimfStock marketsimfStocksimfEmerging and frontier financial marketsimfMarket riskimfMarket capitalizationimfFinancial marketsimfFinancial institutionsimfFinancial regulation and supervisionimfStock exchangesimfFinancial services industryimfFinancial risk managementimfUnited StatesimfInvestmentsMathematical models.Econometrics.Banks and BankingFinance: GeneralInvestments: StocksGeneral Financial Markets: General (includes Measurement and Data)Pension FundsNon-bank Financial InstitutionsFinancial InstrumentsInstitutional InvestorsFinancing PolicyFinancial Risk and Risk ManagementCapital and Ownership StructureValue of FirmsGoodwillFinancial Markets and the MacroeconomyFinanceInvestment & securitiesFinancial services law & regulationStock marketsStocksEmerging and frontier financial marketsMarket riskMarket capitalizationFinancial marketsFinancial institutionsFinancial regulation and supervisionStock exchangesFinancial services industryFinancial risk managementSun Tao1103303Psalida L1472687DcWaIMFBOOK9910788335103321Spillovers to Emerging Equity Markets3685556UNINA04109oam 22004575 450 991079654720332120180809092336.010.1596/978-1-4648-1099-2(CKB)4100000000771631(MiAaPQ)EBC5105814(The World Bank)211099(US-djbf)211099(EXLCZ)99410000000077163120020129d2017 uf 0engurcn|||||||||txtrdacontentcrdamediacrrdacarrierData for Learning : Building a Smart Education Data System /Husein Abdul-HamidWashington, D.C. :The World Bank,2017.1 online resource (336 pages)Directions in Development;Directions in Development - Human Development1-4648-1100-8 1-4648-1099-0 Includes bibliographical references.What Is an Education Management Information System, and Who Uses It? -- Value of Data: Better Data, Better Education -- Understanding Where You Are Today: Assessing the Current State of Education Management Information Systems -- How to Design and Implement Routine Data Collection from Schools -- How to Build and Select an Effective Software Solution -- Integration of Databases for Decision Making to Improve Learning Outcomes -- Innovation in Advanced and Decentralized Systems: The Case of the United States -- How to Build Progressive Centralized and Hybrid Data Systems: The Cases of Chile and Australia -- Developing an Affordable and School-Centered EMIS: The Case of Fiji -- Building and Education Management Information System in a Fragile Environment: The Case of Afghanistan.Data are a crucial ingredient in any successful education system, but building and sustaining a data system are challenging tasks. Many countries around the world have spent significant resources but still struggle to accomplish a functioning Education Management Information System (EMIS). On the other hand, countries that have created successful systems are harnessing the power of data to improve education outcomes. Increasingly, EMISs are moving away from using data narrowly for counting students and schools. Instead, they use data to drive system-wide innovations, accountability, professionalization, and, most important, quality and learning. This broader use of data also benefits classroom instruction and support at schools. An effective data system ensures that education cycles, from preschool to tertiary, are aligned and that the education system is monitored so it can achieve its ultimate goal-producing graduates able to successfully transition into the labor market and contribute to the overall national economy. Data for Learning: Building a Smart Education Data System and its forthcoming companion volume shed light on challenges in building a data system and provide actionable direction on how to navigate the complex issues associated with education data for better learning outcomes and beyond. Data for Learning details the key ingredients of successful data systems, including tangible examples, common pitfalls, and good practices. It is a resource for policy makers working to craft the vision and strategic road map of an EMIS, as well as a handbook to assist teams and decision makers in avoiding common mistakes. It is designed to provide the Show-to and to guide countries at various stages of EMIS deployment. A forthcoming companion volume will focus on digging deeper into the practical applications of education data systems by various user groups in different settings.World Bank e-Library.Educational statisticsData processingEducational statisticsData processing.370.212Abdul-Hamid Husein1561839Abdul-Hamid Husein1561839World Bank Group,DJBFDJBFBOOK9910796547203321Data for Learning3868429UNINA01077nam 2200337 450 99657546310331620230416155818.01-7281-2268-6(CKB)4100000009184175(NjHacI)994100000009184175(EXLCZ)99410000000918417520230416d2019 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrier2019 IEEE/ACM International Workshop on Genetic Improvement (GI) /Institute of Electrical and Electronics EngineersPiscataway :IEEE,2019.1 online resource (various pagings) illustrations1-7281-2269-4 2019 IEEE/ACM International Workshop on Genetic Improvement Genetic programming (Computer science)Genetic programming (Computer science)006.31NjHacINjHaclPROCEEDING9965754631033162019 IEEE2247201UNISA