Certificate-of-need regulation and the diffusion of innovations: A random coefficient model
In this paper, we examine empirically the effect that certificate-of-need regulation by state health planning organizations has had on the speed of diffusion of a relatively new medical technology--haemodialysis. Specifically, we test the hypothesis that a requirement that investments be subject to...
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Veröffentlicht in: | Journal of applied econometrics (Chichester, England) England), 1995-01, Vol.10 (1), p.73-78 |
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creator | Caudill, Steven B. Ford, Jon M. Kaserman, David L. |
description | In this paper, we examine empirically the effect that certificate-of-need regulation by state health planning organizations has had on the speed of diffusion of a relatively new medical technology--haemodialysis. Specifically, we test the hypothesis that a requirement that investments be subject to certificate-of-need review has significantly slowed the rate of adoption of this particular treatment modality. In subjecting this hypothesis to empirical verification, we estimate a random coefficient model. This approach allows us to make more efficient use of the available data than the traditional two-stage approach to modelling diffusion processes wherein separate logistic functions are first estimated over the time series observations followed by hypothesis tests conducted over the cross-sectional observations. We find evidence that certificate-of-need regulation slows the spread of haemodialysis technology. |
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We find evidence that certificate-of-need regulation slows the spread of haemodialysis technology.</description><identifier>ISSN: 0883-7252</identifier><identifier>EISSN: 1099-1255</identifier><identifier>DOI: 10.1002/jae.3950100107</identifier><identifier>CODEN: JAECET</identifier><language>eng</language><publisher>Chichester: Wiley Subscription Services, Inc., A Wiley Company</publisher><subject>Certificates of need ; Coefficients ; Commercial regulation ; Dialysis ; Diffusion coefficient ; Economic models ; Economic regulation ; Fishing regulations ; Government regulation ; Health care ; Health care industry ; Health planning ; Hemodialysis ; Hypotheses ; Industrial regulation ; Innovation ; Innovation diffusion ; Innovations ; Maximum likelihood estimation ; Policy making ; Regulation ; Studies ; Technological change</subject><ispartof>Journal of applied econometrics (Chichester, England), 1995-01, Vol.10 (1), p.73-78</ispartof><rights>Copyright 1995 John Wiley & Sons, Ltd.</rights><rights>Copyright © 1995 John Wiley & Sons, Ltd.</rights><rights>Copyright Wiley Periodicals Inc. 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Appl. Econ</addtitle><description>In this paper, we examine empirically the effect that certificate-of-need regulation by state health planning organizations has had on the speed of diffusion of a relatively new medical technology--haemodialysis. Specifically, we test the hypothesis that a requirement that investments be subject to certificate-of-need review has significantly slowed the rate of adoption of this particular treatment modality. In subjecting this hypothesis to empirical verification, we estimate a random coefficient model. This approach allows us to make more efficient use of the available data than the traditional two-stage approach to modelling diffusion processes wherein separate logistic functions are first estimated over the time series observations followed by hypothesis tests conducted over the cross-sectional observations. We find evidence that certificate-of-need regulation slows the spread of haemodialysis technology.</description><subject>Certificates of need</subject><subject>Coefficients</subject><subject>Commercial regulation</subject><subject>Dialysis</subject><subject>Diffusion coefficient</subject><subject>Economic models</subject><subject>Economic regulation</subject><subject>Fishing regulations</subject><subject>Government regulation</subject><subject>Health care</subject><subject>Health care industry</subject><subject>Health planning</subject><subject>Hemodialysis</subject><subject>Hypotheses</subject><subject>Industrial regulation</subject><subject>Innovation</subject><subject>Innovation diffusion</subject><subject>Innovations</subject><subject>Maximum likelihood estimation</subject><subject>Policy making</subject><subject>Regulation</subject><subject>Studies</subject><subject>Technological change</subject><issn>0883-7252</issn><issn>1099-1255</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1995</creationdate><recordtype>article</recordtype><sourceid>K30</sourceid><recordid>eNqFkc1rFDEYh4NUcLt69eQhVPA2az4mX96WYd1Wih52QcFDiDNvNOvspE1m1P73po5ULIinkPye5-UlP4SeUrKihLCXBwcrbgQpF0rUA7SgxJiKMiFO0IJozSvFBHuETnM-EEIkIWqBPjaQxuBD60aooq8GgA4n-Dz1bgxxwG7o8PgFcBe8n_LtS_Q4DEP89ivPr_AapwLFI24j-DIowDDiY-ygf4weetdnePL7XKL9682-Oa8u320vmvVl1dZSqMrVWjCpRAetAVBaqa72krfUtJoaZ0jnjK-hoJwYJrpaA_tEvBPagdCeL9GLeexVitcT5NEeQ26h790AccqWayWZ4bKAZ_fAQ5zSUFazjBZIG8YK9PxfEOXlZw3TUhRqNVNtijkn8PYqhaNLN5YSe9uGLW3YP20UwczC99DDzX9o-2a9-ct9NruHPMZ05zKma1PXJa7mOOQRftzFLn21UnEl7Pu3W6uE2Mtm98Hu-E8DzqUU</recordid><startdate>199501</startdate><enddate>199501</enddate><creator>Caudill, Steven B.</creator><creator>Ford, Jon M.</creator><creator>Kaserman, David L.</creator><general>Wiley Subscription Services, Inc., A Wiley Company</general><general>John Wiley & Sons</general><general>John Wiley and Sons, Ltd</general><general>Wiley Periodicals Inc</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>HFIND</scope><scope>HZAIM</scope><scope>K30</scope><scope>PAAUG</scope><scope>PAWHS</scope><scope>PAWZZ</scope><scope>PAXOH</scope><scope>PBHAV</scope><scope>PBQSW</scope><scope>PBYQZ</scope><scope>PCIWU</scope><scope>PCMID</scope><scope>PCZJX</scope><scope>PDGRG</scope><scope>PDWWI</scope><scope>PETMR</scope><scope>PFVGT</scope><scope>PGXDX</scope><scope>PIHIL</scope><scope>PISVA</scope><scope>PJCTQ</scope><scope>PJTMS</scope><scope>PLCHJ</scope><scope>PMHAD</scope><scope>PNQDJ</scope><scope>POUND</scope><scope>PPLAD</scope><scope>PQAPC</scope><scope>PQCAN</scope><scope>PQCMW</scope><scope>PQEME</scope><scope>PQHKH</scope><scope>PQMID</scope><scope>PQNCT</scope><scope>PQNET</scope><scope>PQSCT</scope><scope>PQSET</scope><scope>PSVJG</scope><scope>PVMQY</scope><scope>PZGFC</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><scope>JQ2</scope></search><sort><creationdate>199501</creationdate><title>Certificate-of-need regulation and the diffusion of innovations: A random coefficient model</title><author>Caudill, Steven B. ; Ford, Jon M. ; Kaserman, David L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4657-a4852675dec9ee7877d4f63c19c819a90da9f4e65730925d48e2b0fa58ae58f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Certificates of need</topic><topic>Coefficients</topic><topic>Commercial regulation</topic><topic>Dialysis</topic><topic>Diffusion coefficient</topic><topic>Economic models</topic><topic>Economic regulation</topic><topic>Fishing regulations</topic><topic>Government regulation</topic><topic>Health care</topic><topic>Health care industry</topic><topic>Health planning</topic><topic>Hemodialysis</topic><topic>Hypotheses</topic><topic>Industrial regulation</topic><topic>Innovation</topic><topic>Innovation diffusion</topic><topic>Innovations</topic><topic>Maximum likelihood estimation</topic><topic>Policy making</topic><topic>Regulation</topic><topic>Studies</topic><topic>Technological change</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Caudill, Steven B.</creatorcontrib><creatorcontrib>Ford, Jon M.</creatorcontrib><creatorcontrib>Kaserman, David L.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>Periodicals Index Online Segment 16</collection><collection>Periodicals Index Online Segment 26</collection><collection>Periodicals Index Online</collection><collection>Primary Sources Access—Foundation Edition (Plan E) - 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Appl. Econ</addtitle><date>1995-01</date><risdate>1995</risdate><volume>10</volume><issue>1</issue><spage>73</spage><epage>78</epage><pages>73-78</pages><issn>0883-7252</issn><eissn>1099-1255</eissn><coden>JAECET</coden><abstract>In this paper, we examine empirically the effect that certificate-of-need regulation by state health planning organizations has had on the speed of diffusion of a relatively new medical technology--haemodialysis. Specifically, we test the hypothesis that a requirement that investments be subject to certificate-of-need review has significantly slowed the rate of adoption of this particular treatment modality. In subjecting this hypothesis to empirical verification, we estimate a random coefficient model. This approach allows us to make more efficient use of the available data than the traditional two-stage approach to modelling diffusion processes wherein separate logistic functions are first estimated over the time series observations followed by hypothesis tests conducted over the cross-sectional observations. We find evidence that certificate-of-need regulation slows the spread of haemodialysis technology.</abstract><cop>Chichester</cop><pub>Wiley Subscription Services, Inc., A Wiley Company</pub><doi>10.1002/jae.3950100107</doi><tpages>6</tpages></addata></record> |
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subjects | Certificates of need Coefficients Commercial regulation Dialysis Diffusion coefficient Economic models Economic regulation Fishing regulations Government regulation Health care Health care industry Health planning Hemodialysis Hypotheses Industrial regulation Innovation Innovation diffusion Innovations Maximum likelihood estimation Policy making Regulation Studies Technological change |
title | Certificate-of-need regulation and the diffusion of innovations: A random coefficient model |
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