02608nam 2200589Ia 450 991045064610332120200520144314.01-280-16499-997866101649980-8213-6182-1(CKB)1000000000031569(EBL)459402(OCoLC)60785420(SSID)ssj0000085340(PQKBManifestationID)11126207(PQKBTitleCode)TC0000085340(PQKBWorkID)10007566(PQKB)10950476(MiAaPQ)EBC459402(Au-PeEL)EBL459402(CaPaEBR)ebr10082373(CaONFJC)MIL16499(OCoLC)865698465(EXLCZ)99100000000003156920050610g20059999 uf 0engur|n|---|||||txtccrAnalyzing the distributional impact of selected reforms[electronic resource] /edited by Aline Coudouel and Stefano PaternostroWashington, DC World Bank2005-1 online resource (318 p.)Description based upon print version of record.0-8213-6181-3 Includes bibliographical references.CONTENTS; Foreword; Acknowledgments; Introduction; 1 Trade Policy Reforms; FIGURES; BOXES; 2 Monetary and Exchange Rate Policy Reforms; TABLES; 3 Utility Reforms; 4 Agricultural Market Reforms; 5 Land Policy Reforms; 6 Education Policy ReformsThe analysis of the distributional impact of policy reforms on the well-being or welfare of different stakeholder groups, particularly on the poor and vulnerable, has an important role in the elaboration and implementation of poverty reduction strategies in developing countries. In recent years this type of work has been labeled as Poverty and Social Impact Analysis (PSIA) and is increasingly implemented to promote evidence-based policy choices and foster debate on policy reform options. While information is available on the general approach, techniques and tools for distributional analysis, ePovertyDeveloping countriesDeveloping countriesEconomic policyElectronic books.Poverty339.4/6/091724Coudouel Aline870947Paternostro Stefano877525MiAaPQMiAaPQMiAaPQBOOK9910450646103321Analyzing the distributional impact of selected reforms1959556UNINA01257nam0 22003493i 450 VAN027870820240627101815.307N978303138747020240627d2023 |0itac50 baengCH|||| |||||ˆAn ‰introduction to statistical learningwith Applications in PythonGareth James ... [et al.]ChamSpringer2023xv, 60 p.ill.24 cm001VAN00367912001 Springer texts in statistics210 Berlin [etc.]Springer1985-Data MiningKW:KInferenceKW:KPythonKW:KPython softwareKW:KStatistical learningKW:KSupervised learningKW:KUnsupervsied learningKW:KUSNew YorkVANL000011JamesGarethVANV091174Springer <editore>VANV108073650ITSOL20240628RICAhttps://doi.org/10.1007/978-3-031-38747-0E-book – Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o ShibbolethNVAN0278708Introduction to statistical learning1468100UNICAMPANIA