The dynamic links between product and process innovations and productivity for Colombian manufacturing
Purpose – This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that int...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Emerald Publishing
2024-03-01
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| Series: | Applied Economic Analysis |
| Subjects: | |
| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/AEA-01-2023-0009/full/pdf |
| _version_ | 1797279198657642496 |
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| author | Juan A. Sanchis Llopis Juan A. Mañez Andrés Mauricio Gómez-Sánchez |
| author_facet | Juan A. Sanchis Llopis Juan A. Mañez Andrés Mauricio Gómez-Sánchez |
| author_sort | Juan A. Sanchis Llopis |
| collection | DOAJ |
| description | Purpose – This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys. Design/methodology/approach – This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models. Findings – The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations. Originality/value – The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized. |
| first_indexed | 2024-03-07T16:21:51Z |
| format | Article |
| id | doaj.art-88416c0e26444e6480c35afa3dc73f76 |
| institution | Directory Open Access Journal |
| issn | 2632-7627 |
| language | English |
| last_indexed | 2024-03-07T16:21:51Z |
| publishDate | 2024-03-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | Applied Economic Analysis |
| spelling | doaj.art-88416c0e26444e6480c35afa3dc73f762024-03-04T05:53:12ZengEmerald PublishingApplied Economic Analysis2632-76272024-03-013294628210.1108/AEA-01-2023-0009The dynamic links between product and process innovations and productivity for Colombian manufacturingJuan A. Sanchis Llopis0Juan A. Mañez1Andrés Mauricio Gómez-Sánchez2Department of Estructura Económica, Universitat de València and ERICES, Valencia, SpainDepartment of Estructura Económica, Universitat de València and ERICES, Valencia, SpainDepartment of Economics, Universidad del Cauca, Popayan, ColombiaPurpose – This paper aims to examine the interrelation between two innovating strategies (product and process) on total factor productivity (TFP) growth and the dynamic linkages between these strategies, for Colombia. The authors first explore whether ex ante more productive firms are those that introduce innovations (the self-selection hypothesis) and if the introduction of innovations boosts TFP growth (the returns-to-innovation hypothesis). Second, the authors study the firm’s joint dynamic decision to implement process and/or product innovations. The authors use Colombian manufacturing data from the Annual Manufacturing and the Technological Development and Innovation Surveys. Design/methodology/approach – This study uses a four-stage procedure. First, the authors estimate TFP using a modified version of Olley and Pakes (1996) and Levinsohn and Petrin (2003), proposed by De Loecker (2010), that implements an endogenous Markov process where past firm innovations are endogenized. This TFP would be estimated by GMM, Wooldridge (2009). Second, the authors use multivariate discrete choice models to test the self-selection hypothesis. Third, the authors explore, using multi-value treatment evaluation techniques, the life span of the impact of innovations on productivity growth (returns to innovation hypothesis). Fourth, the authors analyse the joint likelihood of implementing process and product innovations using dynamic panel data bivariate probit models. Findings – The investigation reveals that the self-selection effect is notably more pronounced in the adoption of process innovations only, as opposed to the adoption of product innovations only or the simultaneous adoption of both process and product innovations. Moreover, our results uncover distinct temporal patterns concerning innovation returns. Specifically, process innovations yield immediate benefits, whereas implementing both product innovations only and jointly process and product innovations exhibit significant, albeit delayed, advantages. Finally, the analysis confirms the existence of dynamic interconnections between the adoption of process and product innovations. Originality/value – The contribution of this work to the literature is manifold. First, the authors thoroughly investigate the relationship between the implementation of process and product innovations and productivity for Colombian manufacturing explicitly recognising that firms’ decisions of adopting product and process innovations are very likely interrelated. Therefore, the authors start exploring the self-selection and the returns to innovation hypotheses accounting for the fact that firms might implement process innovations only, product innovations only and both process and product innovations. In the analysis of the returns of innovation, the fact that firms may choose among a menu of three innovation strategies implies the use of evaluation methods for multi-value treatments. Second, the authors study the dynamic inter-linkages between the decisions to implement process and/or product innovations, that remains under studied, at least for emerging economies. Third, the estimation of TFP is performed using an endogenous Markov process, where past firms’ innovations are endogenized.https://www.emerald.com/insight/content/doi/10.1108/AEA-01-2023-0009/full/pdfProduct innovationProcess innovationSelf-selectionReturns-to-innovationDynamics |
| spellingShingle | Juan A. Sanchis Llopis Juan A. Mañez Andrés Mauricio Gómez-Sánchez The dynamic links between product and process innovations and productivity for Colombian manufacturing Applied Economic Analysis Product innovation Process innovation Self-selection Returns-to-innovation Dynamics |
| title | The dynamic links between product and process innovations and productivity for Colombian manufacturing |
| title_full | The dynamic links between product and process innovations and productivity for Colombian manufacturing |
| title_fullStr | The dynamic links between product and process innovations and productivity for Colombian manufacturing |
| title_full_unstemmed | The dynamic links between product and process innovations and productivity for Colombian manufacturing |
| title_short | The dynamic links between product and process innovations and productivity for Colombian manufacturing |
| title_sort | dynamic links between product and process innovations and productivity for colombian manufacturing |
| topic | Product innovation Process innovation Self-selection Returns-to-innovation Dynamics |
| url | https://www.emerald.com/insight/content/doi/10.1108/AEA-01-2023-0009/full/pdf |
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