Estimating county-level demand for educational attainment
Identifieur interne : 000304 ( Istex/Corpus ); précédent : 000303; suivant : 000305Estimating county-level demand for educational attainment
Auteurs : Stephan J. Goetz ; David L. DebertinSource :
- Socio-Economic Planning Sciences [ 0038-0121 ] ; 1993.
Abstract
A procedure is developed based on “step-down” methods familiar from input-output studies to estimate county-level demands for educational attainment. Data requirements include state-level sector by occupation and educational attainment by occupation, as well as county-level employment by sector numbers. An empirical example is presented using three Kentucky counties—one that is manufacturing-dependent, another that is agriculture-dependent, and a third that is services-dependent. In the manufacturing-dependent county, a larger than expected number of operatives had less than a high school education. In the agriculture-dependent county, and elsewhere, agriculture appears to be an “employer of last resort” for those with minimal formal education. In the service-dependent county, a relatively high proportion of the employees had high school or college education. Potential applications of the technique include dynamic shift-share analyses, rural labor market studies, and long-range regional economic development planning.
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DOI: 10.1016/0038-0121(93)90026-F
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Goetz</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Kentucky, Lexington, KY 40546-0276, U.S.A.</mods:affiliation></affiliation></author><author><name sortKey="Debertin, David L" sort="Debertin, David L" uniqKey="Debertin D" first="David L." last="Debertin">David L. Debertin</name><affiliation><mods:affiliation>Department of Agricultural Economics, University of Kentucky, Lexington, KY 40546-0276, U.S.A.</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Socio-Economic Planning Sciences</title><title level="j" type="abbrev">SEPS</title><idno type="ISSN">0038-0121</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1993">1993</date><biblScope unit="volume">27</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="25">25</biblScope><biblScope unit="page" to="34">34</biblScope></imprint><idno type="ISSN">0038-0121</idno></series><idno type="istex">67651054CA744CB934B7C50A301AF349F1635137</idno><idno type="DOI">10.1016/0038-0121(93)90026-F</idno><idno type="PII">0038-0121(93)90026-F</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0038-0121</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A procedure is developed based on “step-down” methods familiar from input-output studies to estimate county-level demands for educational attainment. Data requirements include state-level sector by occupation and educational attainment by occupation, as well as county-level employment by sector numbers. An empirical example is presented using three Kentucky counties—one that is manufacturing-dependent, another that is agriculture-dependent, and a third that is services-dependent. In the manufacturing-dependent county, a larger than expected number of operatives had less than a high school education. In the agriculture-dependent county, and elsewhere, agriculture appears to be an “employer of last resort” for those with minimal formal education. In the service-dependent county, a relatively high proportion of the employees had high school or college education. Potential applications of the technique include dynamic shift-share analyses, rural labor market studies, and long-range regional economic development planning.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>Stephan J. 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Data requirements include state-level sector by occupation and educational attainment by occupation, as well as county-level employment by sector numbers. An empirical example is presented using three Kentucky counties—one that is manufacturing-dependent, another that is agriculture-dependent, and a third that is services-dependent. In the manufacturing-dependent county, a larger than expected number of operatives had less than a high school education. In the agriculture-dependent county, and elsewhere, agriculture appears to be an “employer of last resort” for those with minimal formal education. In the service-dependent county, a relatively high proportion of the employees had high school or college education. 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