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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 25-34 |
| Number of pages | 10 |
| Journal | Socio-Economic Planning Sciences |
| Volume | 27 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 1 1993 |
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All Science Journal Classification (ASJC) codes
- Geography, Planning and Development
- Economics and Econometrics
- Strategy and Management
- Statistics, Probability and Uncertainty
- Management Science and Operations Research
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Estimating county-level demand for educational attainment. / Goetz, Stephan J.; Debertin, David L.
In: Socio-Economic Planning Sciences, Vol. 27, No. 1, 01.01.1993, p. 25-34.Research output: Contribution to journal › Article
TY - JOUR
T1 - Estimating county-level demand for educational attainment
AU - Goetz, Stephan J.
AU - Debertin, David L.
PY - 1993/1/1
Y1 - 1993/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0011644180&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0011644180&partnerID=8YFLogxK
U2 - 10.1016/0038-0121(93)90026-F
DO - 10.1016/0038-0121(93)90026-F
M3 - Article
AN - SCOPUS:0011644180
VL - 27
SP - 25
EP - 34
JO - Socio-Economic Planning Sciences
JF - Socio-Economic Planning Sciences
SN - 0038-0121
IS - 1
ER -