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An Analysis for New Institutionality in Science, Technology and Innovation in Colombia Using a Structural Vector Autoregression Model

Clara Inés Pardo Martínez, Alexander Cotte Poveda () and Nicolas Ronderos

European Research Studies Journal, 2019, vol. XXII, issue 2, 218-228

Abstract: Purpose: The purpose of this article is to analyze the strengths and the institutionality of the Ministry of Science Technology and Innovation (MSTI) in increasing investments in research and development as well as promoting the generation of knowledge. Design/Methodology/Approach: We use structural vector autoregression (SVAR) and structural vector error correction (SVEC) to examine the effects of institutionality in science, technology and innovation in the Ministry of Science, Technology and Innovation (MSTI) using three variables (i.e., investments in activities of science, technology and innovation (STIA), investments in research and development (R&D) and independence index). Findings: The results indicate that increasing the independence and transparency of the MSTI leads to higher investments in STIA and R&D over time. SVAR and SVEC models were used to assess the robustness and reliability of the results. Practical Implications: The results are important for assessing the effective governance and functionality of the new MSTI and its mission to adopt new policies and instruments that may strengthen science, technology and innovation in Colombia as the country migrates to a knowledge-based society. Originality/Value: In this context, Colombia opted to implement this model; using law 1951 of 2019, the country created this ministry. It is important to analyse the implications and key elements that allow the ministry to operate and achieve better investments to promote research, innovation, and the application of new technologies.

Keywords: Science; technology; innovation; institutionality; structural vector autoregression model; Colombia. (search for similar items in EconPapers)
JEL-codes: O30 O32 O38 C32 (search for similar items in EconPapers)
Date: 2019
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