LEADER 01559nam--2200421---450- 001 990003387980203316 005 20100805141326.0 010 $a978-88-387-5527-2 035 $a000338798 035 $aUSA01000338798 035 $a(ALEPH)000338798USA01 035 $a000338798 100 $a20100415d2010----km-y0itay50------ba 101 $aita 102 $aIT 105 $a||||||||001yy 200 1 $a<> concorso per istruttore e istruttore direttivo nell'Area economico finaziaria degli Enti locali$emanuale per la preparazione ai concorsi di categoria C e D nell' Area Economico-Finanziaria$eaggiornato alla L. 23-12-2009, n. 191...$fB. Consales ...[et al.] 210 $aSantarcangelo di Romagna$cMaggioli$d2010 215 $a765 p.$d24 cm 225 2 $aConcorsi pubblici$v102 410 0$12001$aConcorsi pubblici$v, 102 454 1$12001 461 1$1001-------$12001 606 0 $aDiritto pubblico$xManuali per concorsi$2BNCF 676 $a351.076 700 1$aCONSALES,$bBiancamaria$0567310 801 0$aIT$bsalbc$gISBD 912 $a990003387980203316 951 $aXXI.6. 235$b67030 G.$cXXI.6.$d00257210 959 $aBK 969 $aGIU 979 $aFIORELLA$b90$c20100415$lUSA01$h1519 979 $aFIORELLA$b90$c20100415$lUSA01$h1524 979 $aANDRIA$b90$c20100528$lUSA01$h1842 979 $aANDRIA$b90$c20100805$lUSA01$h1413 979 $aCHIARA$b90$c20110715$lUSA01$h1138 996 $aConcorso per istruttore e istruttore direttivo nell'Area economico finaziaria degli Enti locali$91113567 997 $aUNISA LEADER 01482nam--2200445---450- 001 990001770420203316 005 20101217090701.0 010 $a88-238-3061-3 035 $a000177042 035 $aUSA01000177042 035 $a(ALEPH)000177042USA01 035 $a000177042 100 $a20040618d2004----km-y0enga50------ba 101 0 $aita 102 $aIT 105 $ay|||z|||001yy 200 1 $a<> societą$ecommento al D. lgs. 6/2003 e successive modifiche$fPaolo Costanzo, Massimo Gazzani, Francesca Novati$gpresentazione di Claudio Siciliotti 205 $a2. ed 210 $aMilano$cEgea$d2004 215 $aXII, 481 p.$d21 cm 225 2 $a<> riforma delle societą 410 0$12001$a<> riforma delle societą 606 0 $aSocietą $xRiforma 606 0 $aSocietą $yItalia 676 $a346.45066 700 1$aCOSTANZO,$bPaolo$0280808 701 1$aGAZZANI,$bMassimo$0325484 701 1$aNOVATI,$bFrancesca$0502006 801 0$aIT$bsalbc$gISBD 912 $a990001770420203316 951 $aXXV.3.E. 585 (IG II 924 A)$b39408 G.$cXXV.3.E. 585 (IG II)$d00093525 959 $aBK 969 $aGIU 979 $aACQUISTI$b10$c20040618$lUSA01$h1050 979 $aRENATO$b90$c20041005$lUSA01$h1526 979 $aPATRY$b90$c20050429$lUSA01$h1109 979 $aRSIAV4$b90$c20090724$lUSA01$h1308 979 $aRSIAV4$b90$c20101217$lUSA01$h0907 996 $aSocietą$9951964 997 $aUNISA LEADER 05444oam 22011294 450 001 9910788232703321 005 20230721045625.0 010 $a1-4623-9111-7 010 $a1-4527-8641-0 010 $a1-4518-7041-8 010 $a1-282-84134-3 010 $a9786612841347 035 $a(CKB)3170000000055083 035 $a(EBL)1607966 035 $a(SSID)ssj0000944161 035 $a(PQKBManifestationID)11503328 035 $a(PQKBTitleCode)TC0000944161 035 $a(PQKBWorkID)10983260 035 $a(PQKB)10048888 035 $a(OCoLC)761981611 035 $a(MiAaPQ)EBC1607966 035 $a(IMF)WPIEE2008183 035 $a(EXLCZ)993170000000055083 100 $a20020129d2008 uf 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aKernel Density Estimation Based on Grouped Data : $eThe Case of Poverty Assessment /$fCamelia Minoiu, Sanjay Reddy 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2008. 215 $a1 online resource (36 p.) 225 1 $aIMF Working Papers 225 0$aIMF working paper ;$vWP/08/183 300 $aDescription based upon print version of record. 311 $a1-4519-1494-6 320 $aIncludes bibliographical references. 327 $aContents; I. Motivation; II. The Data Structure and the Bias of the Estimator; III. The Bandwidth and Kernels Considered; IV. Monte Carlo Study; A. Theoretical Distributions; B. Summary Statistics, Density Estimates and Diagrams; C. Poverty Estimates; V. Country Studies; VI. Global Poverty; VII. Conclusions; References; Appendix; Appendix Figures; 1. Distributions used in Monte Carlo analysis; 2. Bias of KDE-based density (log-normal distribution); Appendix Tables; 1. Summary statistics from KDE-based sample; 3. Bias of estimated density (multimodal distribution) 327 $a4. Bias of estimated density (Dagum distribution)2. Bias of poverty measures (Low and High Poverty Lines); 5. Bias in the poverty headcount ratio versus location of poverty line; 3. Bias of poverty measures (Triweight kernel, Poverty line: 0.25 x median); 4. Bias of poverty measures (Hybrid bandwidth, Poverty line: 0.5 x median); 5. Bias of poverty measures (Epanechnikov kernel, Silverman bandwidth); 6. Bias of poverty measures (Gaussian kernel, Poverty line: Capability); 6. Survey-based and grouped data KDE-based density estimates; 7. Global poverty rates (% poor) 327 $a8. Global poverty counts (millions) 330 3 $aWe analyze the performance of kernel density methods applied to grouped data to estimate poverty (as applied in Sala-i-Martin, 2006, QJE). Using Monte Carlo simulations and household surveys, we find that the technique gives rise to biases in poverty estimates, the sign and magnitude of which vary with the bandwidth, the kernel, the number of datapoints, and across poverty lines. Depending on the chosen bandwidth, the $1/day poverty rate in 2000 varies by a factor of 1.8, while the $2/day headcount in 2000 varies by 287 million people. Our findings challenge the validity and robustness of poverty estimates derived through kernel density estimation on grouped data. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2008/183 606 $aPoverty$xMeasurement 606 $aIncome distribution$xEconometric models 606 $aKernel functions 606 $aEconometrics$2imf 606 $aMacroeconomics$2imf 606 $aDemography$2imf 606 $aPoverty and Homelessness$2imf 606 $aWelfare, Well-Being, and Poverty: General$2imf 606 $aPersonal Income, Wealth, and Their Distributions$2imf 606 $aAggregate Factor Income Distribution$2imf 606 $aDemographic Economics: General$2imf 606 $aEstimation$2imf 606 $aPoverty & precarity$2imf 606 $aPopulation & demography$2imf 606 $aEconometrics & economic statistics$2imf 606 $aPoverty$2imf 606 $aPersonal income$2imf 606 $aIncome distribution$2imf 606 $aPopulation and demographics$2imf 606 $aEstimation techniques$2imf 606 $aIncome$2imf 606 $aPopulation$2imf 606 $aEconometric models$2imf 607 $aNicaragua$2imf 615 0$aPoverty$xMeasurement. 615 0$aIncome distribution$xEconometric models. 615 0$aKernel functions. 615 7$aEconometrics 615 7$aMacroeconomics 615 7$aDemography 615 7$aPoverty and Homelessness 615 7$aWelfare, Well-Being, and Poverty: General 615 7$aPersonal Income, Wealth, and Their Distributions 615 7$aAggregate Factor Income Distribution 615 7$aDemographic Economics: General 615 7$aEstimation 615 7$aPoverty & precarity 615 7$aPopulation & demography 615 7$aEconometrics & economic statistics 615 7$aPoverty 615 7$aPersonal income 615 7$aIncome distribution 615 7$aPopulation and demographics 615 7$aEstimation techniques 615 7$aIncome 615 7$aPopulation 615 7$aEconometric models 676 $a339.46 700 $aMinoiu$b Camelia$0874355 701 $aReddy$b Sanjay$0602369 801 0$bDcWaIMF 906 $aBOOK 912 $a9910788232703321 996 $aKernel Density Estimation Based on Grouped Data$93704156 997 $aUNINA LEADER 01607nam 2200517 450 001 9910819408103321 005 20211025193840.0 010 $a1-4704-3633-7 035 $a(CKB)4340000000190436 035 $a(MiAaPQ)EBC4908278 035 $a(RPAM)19393815 035 $a(PPN)199704147 035 $a(EXLCZ)994340000000190436 100 $a20170808h20172017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aAbelian properties of Anick spaces /$fBrayton Gray 210 1$aProvidence, Rhode Island :$cAmerican Mathematical Society,$d2017. 210 4$d©2017 215 $a1 online resource (124 pages) $cillustrations 225 1 $aMemoirs of the American Mathematical Society,$x1947-6221 ;$vVolume 246, Number 1162 (first of 6 numbers) 311 $a1-4704-2308-1 320 $aIncludes bibliographical references. 410 0$aMemoirs of the American Mathematical Society ;$vVolume 246, Number 1162 (first of 6 numbers) 606 $aAbelian groups 606 $aTopological groups 606 $aTopological spaces 606 $aLoop spaces 606 $aH-spaces 615 0$aAbelian groups. 615 0$aTopological groups. 615 0$aTopological spaces. 615 0$aLoop spaces. 615 0$aH-spaces. 676 $a512.55 700 $aGray$b Brayton$f1940-$0553751 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910819408103321 996 $aAbelian properties of Anick spaces$94101412 997 $aUNINA