LEADER 04231nam 2200673 a 450 001 9910970661403321 005 20251116141121.0 010 $a9780309171601 010 $a0309171601 010 $a9780309501736 010 $a0309501733 035 $a(CKB)110986584753154 035 $a(EBL)3375512 035 $a(SSID)ssj0000246943 035 $a(PQKBManifestationID)11195627 035 $a(PQKBTitleCode)TC0000246943 035 $a(PQKBWorkID)10194957 035 $a(PQKB)11519047 035 $a(MiAaPQ)EBC3375512 035 $a(Au-PeEL)EBL3375512 035 $a(CaPaEBR)ebr10038791 035 $a(OCoLC)923256782 035 $a(Perlego)4737288 035 $a(BIP)53854583 035 $a(BIP)6750564 035 $a(EXLCZ)99110986584753154 100 $a20001121d2000 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSmall-area income and poverty estimates $epriorities for 2000 and beyond /$fConstance F. Citro and Graham Kalton, editors ; Panel on Estimates of Poverty for Small Geographic Areas, Committee on National Statistics, Commission on Behavioral and Social Sciences and Education, National Research Council 205 $a1st ed. 210 $aWashington, D.C. $cNational Academy Press$dc2000 215 $a1 online resource (221 p.) 300 $aDescription based upon print version of record. 311 08$a9780309071468 311 08$a0309071461 320 $aIncludes bibliographical references (p. 191-199). 327 $a""Cover""; ""Front Matter""; ""Acknowledgments""; ""Contents""; ""Executive Summary""; ""1 Introduction""; ""2 Needs for Small-Area Income and Poverty Estimates""; ""3 Current SAIPE Models""; ""4 Future Model Development: The Role of Surveys""; ""5 Future Model Development: The Role of Administrative Records""; ""6 Using Estimates in Allocation Formulas""; ""7 Recommendations for Producers and Users""; ""APPENDIX Interactions Between Survey Estimates and Federal Funding Formulas""; ""References and Bibliography""; ""Biographical Sketches of Panel Members and Staff"" 330 $aRecent trends in federal policies for social and economic programs have increased the demand for timely, accurate estimates of income and poverty for states, counties, and even smaller areas. Every year more than $130 billion in federal funds is allocated to states and localities through formulas that use such estimates. These funds support a wide range of programs that include child care, community development, education, job training, nutrition, and public health. A new program of the U.S. Census Bureau is now providing more timely estimates for these programs than those from the decennial census, which have been used for many years. These new estimates are being used to allocate more than $7 billion annually to school districts, through the Title I program that supports educationally disadvantaged children. But are these estimates as accurate as possible given the available data? How can the statistical models and data that are used to develop the estimates be improved? What should policy makers consider in selecting particular estimates? This new book from the National Research Council provides guidance for improving the Census Bureau's program and for policy makers who use such estimates for allocating funds. 606 $aIncome$zUnited States$xRegional disparities$xStatistical methods 606 $aPoverty$zUnited States$xStatistical methods 607 $aUnited States$xEconomic conditions$y1981-2001$xRegional disparities$xStatistical methods 607 $aUnited States$xEconomic conditions$y1981-2001$xStatistical services 607 $aUnited States$xEconomic conditions$y1981-2001$vDatabases 615 0$aIncome$xRegional disparities$xStatistical methods. 615 0$aPoverty$xStatistical methods. 676 $a339.220723 701 $aCitro$b Constance F$g(Constance Forbes),$f1942-$01804879 701 $aKalton$b Graham$0124277 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910970661403321 996 $aSmall-area income and poverty estimates$94357016 997 $aUNINA