Ontology type: schema:ScholarlyArticle
2017-09
AUTHORS ABSTRACTThe Hamilton–Perry method, which uses cohort change ratios (CCR) and child-woman ratios (CWR), has gained acceptance as research has demonstrated its practical value and accuracy in forecasting population composition. Assessments of this method have been based on the usual assumption that CCRs and CWRs developed over the base period are held constant over the forecast horizon. We propose several approaches for modifying CCRs and CWRs over the forecast horizon. These alternatives are averaging and trending these ratios and a synthetic method that bases local CCRs and CWRs changes on state-level changes in CCRs and CWRs. We evaluate the errors for these alternatives against the errors holding the CCRs and CWRs constant for counties in Washington State and for census tracts in New Mexico. The evaluation suggests that averaging or trending CCRs and CWRs are not worthwhile strategies, but the synthetic method reduces errors compared to holding the ratios constant over the horizon. More... »
PAGES209-231
http://scigraph.springernature.com/pub.10.1007/s12546-017-9190-7
DOIhttp://dx.doi.org/10.1007/s12546-017-9190-7
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1090284135
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Public Health and Health Services",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Medical and Health Sciences",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "University of California, San Diego",
"id": "https://www.grid.ac/institutes/grid.266100.3",
"name": [
"Department of Economics, University of California, San Diego, 9500 Gilman Drive, 92093, La Jolla, CA, USA"
],
"type": "Organization"
},
"familyName": "Tayman",
"givenName": "Jeff",
"id": "sg:person.012330665434.70",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012330665434.70"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "University of California, Riverside",
"id": "https://www.grid.ac/institutes/grid.266097.c",
"name": [
"Department of Sociology, University of California, Riverside, 900 University Avenue, 92521, Riverside, CA, USA"
],
"type": "Organization"
},
"familyName": "Swanson",
"givenName": "David A.",
"id": "sg:person.010015377733.69",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010015377733.69"
],
"type": "Person"
}
],
"citation": [
{
"id": "sg:pub.10.1007/978-3-319-26603-9_12",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1001395008",
"https://doi.org/10.1007/978-3-319-26603-9_12"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-319-43329-5_23",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004903501",
"https://doi.org/10.1007/978-3-319-43329-5_23"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12546-014-9137-1",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1007992108",
"https://doi.org/10.1007/s12546-014-9137-1"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-94-007-4623-7_3",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017109674",
"https://doi.org/10.1007/978-94-007-4623-7_3"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11113-007-9030-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1017394720",
"https://doi.org/10.1007/s11113-007-9030-0"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1018613879",
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-94-007-7551-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018613879",
"https://doi.org/10.1007/978-94-007-7551-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-94-007-7551-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1018613879",
"https://doi.org/10.1007/978-94-007-7551-0"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11113-015-9380-y",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1028944049",
"https://doi.org/10.1007/s11113-015-9380-y"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s12546-011-9054-5",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1029770019",
"https://doi.org/10.1007/s12546-011-9054-5"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11113-009-9144-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034952435",
"https://doi.org/10.1007/s11113-009-9144-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/s11113-009-9144-7",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1034952435",
"https://doi.org/10.1007/s11113-009-9144-7"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1353/dem.2003.0041",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1042106945",
"https://doi.org/10.1353/dem.2003.0041"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1080/01621459.1995.10476489",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1058304772"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.2307/2579183",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1070004968"
],
"type": "CreativeWork"
},
{
"id": "https://app.dimensions.ai/details/publication/pub.1085040965",
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1007/978-3-319-53745-0",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1085040965",
"https://doi.org/10.1007/978-3-319-53745-0"
],
"type": "CreativeWork"
}
],
"datePublished": "2017-09",
"datePublishedReg": "2017-09-01",
"description": "The Hamilton\u2013Perry method, which uses cohort change ratios (CCR) and child-woman ratios (CWR), has gained acceptance as research has demonstrated its practical value and accuracy in forecasting population composition. Assessments of this method have been based on the usual assumption that CCRs and CWRs developed over the base period are held constant over the forecast horizon. We propose several approaches for modifying CCRs and CWRs over the forecast horizon. These alternatives are averaging and trending these ratios and a synthetic method that bases local CCRs and CWRs changes on state-level changes in CCRs and CWRs. We evaluate the errors for these alternatives against the errors holding the CCRs and CWRs constant for counties in Washington State and for census tracts in New Mexico. The evaluation suggests that averaging or trending CCRs and CWRs are not worthwhile strategies, but the synthetic method reduces errors compared to holding the ratios constant over the horizon.",
"genre": "research_article",
"id": "sg:pub.10.1007/s12546-017-9190-7",
"inLanguage": [
"en"
],
"isAccessibleForFree": false,
"isPartOf": [
{
"id": "sg:journal.1027277",
"issn": [
"1443-2447",
"1835-9469"
],
"name": "Journal of Population Research",
"type": "Periodical"
},
{
"issueNumber": "3",
"type": "PublicationIssue"
},
{
"type": "PublicationVolume",
"volumeNumber": "34"
}
],
"name": "Using modified cohort change and child-woman ratios in the Hamilton\u2013Perry forecasting method",
"pagination": "209-231",
"productId": [
{
"name": "readcube_id",
"type": "PropertyValue",
"value": [
"6d963cb35a84376fe8221e479f977a6da3bcf867a707c87048769a219a45e820"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/s12546-017-9190-7"
]
},
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1090284135"
]
}
],
"sameAs": [
"https://doi.org/10.1007/s12546-017-9190-7",
"https://app.dimensions.ai/details/publication/pub.1090284135"
],
"sdDataset": "articles",
"sdDatePublished": "2019-04-11T12:36",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000363_0000000363/records_70028_00000002.jsonl",
"type": "ScholarlyArticle",
"url": "https://link.springer.com/10.1007%2Fs12546-017-9190-7"
}
]Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12546-017-9190-7'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12546-017-9190-7'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12546-017-9190-7'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12546-017-9190-7'
This table displays all metadata directly associated to this object as RDF triples.
125 TRIPLES
21 PREDICATES
42 URIs
19 LITERALS
7 BLANK NODES