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Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India
Do firms benefit more from agglomeration-based spillovers than the technical know-how obtained through inter-firm collaboration? Quantifying the relative value of the industrial policy of cluster development vis-à-vis firm’s internal decision of collaboration can be valuable for policy-makers and en...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer India
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10157132/ https://www.ncbi.nlm.nih.gov/pubmed/37360927 http://dx.doi.org/10.1007/s40953-023-00349-8 |
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author | Gupta, Samarth |
author_facet | Gupta, Samarth |
author_sort | Gupta, Samarth |
collection | PubMed |
description | Do firms benefit more from agglomeration-based spillovers than the technical know-how obtained through inter-firm collaboration? Quantifying the relative value of the industrial policy of cluster development vis-à-vis firm’s internal decision of collaboration can be valuable for policy-makers and entrepreneurs. I observe the universe of Indian MSMEs inside an industrial cluster (Treatment Group 1), those in collaboration for technical know-how (Treatment Group 2) and those outside clusters with no collaboration (Control Group). Conventional econometric methods to identify the treatment effects would suffer from selection bias and misspecification of the model. I use two data-driven, model-selection methods, developed by (Belloni, A., Chernozhukov, V., and Hansen, C. (2013). Inference on treatment e ects after selection among high-dimensional controls. Review of Economic Studies, 81(2):608 650.) and (Chernozhukov, V., Hansen, C., and Spindler, M. (2015). Post selection and post regulariza- tion inference in linear models with many controls and instruments. American Economic Review, 105(5):486 490.), to estimate the causal impact of the treatments on GVA of firms. The results suggest that ATE of cluster and collaboration is nearly equal at 30%. I conclude by offering policy implications. |
format | Online Article Text |
id | pubmed-10157132 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-101571322023-05-09 Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India Gupta, Samarth J Quant Econ Original Article Do firms benefit more from agglomeration-based spillovers than the technical know-how obtained through inter-firm collaboration? Quantifying the relative value of the industrial policy of cluster development vis-à-vis firm’s internal decision of collaboration can be valuable for policy-makers and entrepreneurs. I observe the universe of Indian MSMEs inside an industrial cluster (Treatment Group 1), those in collaboration for technical know-how (Treatment Group 2) and those outside clusters with no collaboration (Control Group). Conventional econometric methods to identify the treatment effects would suffer from selection bias and misspecification of the model. I use two data-driven, model-selection methods, developed by (Belloni, A., Chernozhukov, V., and Hansen, C. (2013). Inference on treatment e ects after selection among high-dimensional controls. Review of Economic Studies, 81(2):608 650.) and (Chernozhukov, V., Hansen, C., and Spindler, M. (2015). Post selection and post regulariza- tion inference in linear models with many controls and instruments. American Economic Review, 105(5):486 490.), to estimate the causal impact of the treatments on GVA of firms. The results suggest that ATE of cluster and collaboration is nearly equal at 30%. I conclude by offering policy implications. Springer India 2023-05-04 /pmc/articles/PMC10157132/ /pubmed/37360927 http://dx.doi.org/10.1007/s40953-023-00349-8 Text en © The Author(s), under exclusive licence to The Indian Econometric Society 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Gupta, Samarth Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India |
title | Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India |
title_full | Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India |
title_fullStr | Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India |
title_full_unstemmed | Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India |
title_short | Model-Selection Inference for Causal Impact of Clusters and Collaboration on MSMEs in India |
title_sort | model-selection inference for causal impact of clusters and collaboration on msmes in india |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10157132/ https://www.ncbi.nlm.nih.gov/pubmed/37360927 http://dx.doi.org/10.1007/s40953-023-00349-8 |
work_keys_str_mv | AT guptasamarth modelselectioninferenceforcausalimpactofclustersandcollaborationonmsmesinindia |