Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model
Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Ramaul, Nalin Kumar [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© The Indian Econometric Society 2017 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of quantitative economics - [New Delhi] : Springer India, 2003, 16(2017), 2 vom: 31. März, Seite 501-525 |
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| Übergeordnetes Werk: |
volume:16 ; year:2017 ; number:2 ; day:31 ; month:03 ; pages:501-525 |
| Links: |
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| DOI / URN: |
10.1007/s40953-017-0089-0 |
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| Katalog-ID: |
SPR038005700 |
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| 520 | |a Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. | ||
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10.1007/s40953-017-0089-0 doi (DE-627)SPR038005700 (SPR)s40953-017-0089-0-e DE-627 ger DE-627 rakwb eng Ramaul, Nalin Kumar verfasserin aut Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Indian Econometric Society 2017 Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. Industrial location (dpeaa)DE-He213 Econometric models of location choice (dpeaa)DE-He213 Nested logit model (dpeaa)DE-He213 Regional incentives (dpeaa)DE-He213 Special category states in India (dpeaa)DE-He213 Ramaul, Pinki aut Enthalten in Journal of quantitative economics [New Delhi] : Springer India, 2003 16(2017), 2 vom: 31. März, Seite 501-525 (DE-627)843971592 (DE-600)2842078-0 2364-1045 nnns volume:16 year:2017 number:2 day:31 month:03 pages:501-525 https://dx.doi.org/10.1007/s40953-017-0089-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 16 2017 2 31 03 501-525 |
| spelling |
10.1007/s40953-017-0089-0 doi (DE-627)SPR038005700 (SPR)s40953-017-0089-0-e DE-627 ger DE-627 rakwb eng Ramaul, Nalin Kumar verfasserin aut Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Indian Econometric Society 2017 Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. Industrial location (dpeaa)DE-He213 Econometric models of location choice (dpeaa)DE-He213 Nested logit model (dpeaa)DE-He213 Regional incentives (dpeaa)DE-He213 Special category states in India (dpeaa)DE-He213 Ramaul, Pinki aut Enthalten in Journal of quantitative economics [New Delhi] : Springer India, 2003 16(2017), 2 vom: 31. März, Seite 501-525 (DE-627)843971592 (DE-600)2842078-0 2364-1045 nnns volume:16 year:2017 number:2 day:31 month:03 pages:501-525 https://dx.doi.org/10.1007/s40953-017-0089-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 16 2017 2 31 03 501-525 |
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10.1007/s40953-017-0089-0 doi (DE-627)SPR038005700 (SPR)s40953-017-0089-0-e DE-627 ger DE-627 rakwb eng Ramaul, Nalin Kumar verfasserin aut Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Indian Econometric Society 2017 Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. Industrial location (dpeaa)DE-He213 Econometric models of location choice (dpeaa)DE-He213 Nested logit model (dpeaa)DE-He213 Regional incentives (dpeaa)DE-He213 Special category states in India (dpeaa)DE-He213 Ramaul, Pinki aut Enthalten in Journal of quantitative economics [New Delhi] : Springer India, 2003 16(2017), 2 vom: 31. März, Seite 501-525 (DE-627)843971592 (DE-600)2842078-0 2364-1045 nnns volume:16 year:2017 number:2 day:31 month:03 pages:501-525 https://dx.doi.org/10.1007/s40953-017-0089-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 16 2017 2 31 03 501-525 |
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10.1007/s40953-017-0089-0 doi (DE-627)SPR038005700 (SPR)s40953-017-0089-0-e DE-627 ger DE-627 rakwb eng Ramaul, Nalin Kumar verfasserin aut Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Indian Econometric Society 2017 Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. Industrial location (dpeaa)DE-He213 Econometric models of location choice (dpeaa)DE-He213 Nested logit model (dpeaa)DE-He213 Regional incentives (dpeaa)DE-He213 Special category states in India (dpeaa)DE-He213 Ramaul, Pinki aut Enthalten in Journal of quantitative economics [New Delhi] : Springer India, 2003 16(2017), 2 vom: 31. März, Seite 501-525 (DE-627)843971592 (DE-600)2842078-0 2364-1045 nnns volume:16 year:2017 number:2 day:31 month:03 pages:501-525 https://dx.doi.org/10.1007/s40953-017-0089-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 16 2017 2 31 03 501-525 |
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10.1007/s40953-017-0089-0 doi (DE-627)SPR038005700 (SPR)s40953-017-0089-0-e DE-627 ger DE-627 rakwb eng Ramaul, Nalin Kumar verfasserin aut Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Indian Econometric Society 2017 Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. Industrial location (dpeaa)DE-He213 Econometric models of location choice (dpeaa)DE-He213 Nested logit model (dpeaa)DE-He213 Regional incentives (dpeaa)DE-He213 Special category states in India (dpeaa)DE-He213 Ramaul, Pinki aut Enthalten in Journal of quantitative economics [New Delhi] : Springer India, 2003 16(2017), 2 vom: 31. März, Seite 501-525 (DE-627)843971592 (DE-600)2842078-0 2364-1045 nnns volume:16 year:2017 number:2 day:31 month:03 pages:501-525 https://dx.doi.org/10.1007/s40953-017-0089-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 16 2017 2 31 03 501-525 |
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The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. 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Ramaul, Nalin Kumar |
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Ramaul, Nalin Kumar misc Industrial location misc Econometric models of location choice misc Nested logit model misc Regional incentives misc Special category states in India Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model |
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Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model Industrial location (dpeaa)DE-He213 Econometric models of location choice (dpeaa)DE-He213 Nested logit model (dpeaa)DE-He213 Regional incentives (dpeaa)DE-He213 Special category states in India (dpeaa)DE-He213 |
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regional incentives and location choice of new firms in india: a nested logit model |
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Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model |
| abstract |
Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. © The Indian Econometric Society 2017 |
| abstractGer |
Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. © The Indian Econometric Society 2017 |
| abstract_unstemmed |
Abstract This research paper attempts to develop an appropriate econometric model for regional incentives and location choice of new firms in India. The alternative econometric models of location choice include ordinary least squares, multinomial logit model, Poisson (count) model, conditional logit model and nested logit model. The present study utilised two-level Nested logit model, a discrete choice regression technique, to estimate the influence of regional incentives on the location choice of new firms in India. In considering what groupings of location choices to use for the upper nest of the tree structure, we simply categorised areas into designated and non-designated status, as defined by policy. We divided the area in two nests or subgroups, or regions: the Special Category States or the Beneficiary States (Jammu and Kashmir, Himachal Pradesh and Uttarakhand) which have been granted special investment incentives package and the Control Group or the Non-Beneficiary Neighbouring States (Haryana, Punjab and Uttar Pradesh) which were given no regional incentives. We have considered only firms established between 2002–2003 and 2010–2011. The independent variables considered for the analysis include investment incentives (dummy variable), manufacturing agglomeration, market potential and land cost. The nested logit model was estimated with full information maximum likelihood estimation using Stata software. The estimation validated the importance of regional fiscal incentives and manufacturing agglomeration as the most important determinants of industrial location. © The Indian Econometric Society 2017 |
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Regional Incentives and Location Choice of New Firms in India: A Nested Logit Model |
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Ramaul, Pinki |
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