Abstract
This study analyzes the economic impact caused by the beginning of the COVID-19 pandemic, characterized by the confinement in the second and third quarters of 2020, on the Colombian manufacturing industry. It implemented a Difference-in-Difference (Dif-in-Dif) set-up model design; in this case, it measures the impacts of the industrial production index on the Colombian manufacturing industry, employment, manufacturing exports, and imports, considering the COVID-19 crisis as a random natural experiment. For this, the Dif-in-Dif methodology was used for time series data and variables to describe the behavior progress of COVID-19 in Colombia. The results show that the COVID-19 pandemic has had a statistically significant impact on the industrial manufacturing production index, the number of employed individuals in the manufacturing sector, and the manufacturing of imports, which signifies a negative impact concerning the number of individuals who tested positive for COVID-19 and the number of deaths and recoveries.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
Notes
On January 12, 2020, China made the genetic sequence of the virus that caused COVID-19 public, and by January 13, 2020, a case of COVID-19 was officially confirmed in Thailand, the first case registered outside China.
The long-term unemployment variable corresponding to question P7320of the GEIH microdata unemployed module for the headline missed two values for the series in April and March 2020. According to DANE's response, the reports and databases for these months were limited because of the COVID-19 contingency; therefore, DANE does not have this information for the unemployed and inactivity module. For this reason, an imputation was applied to the mean using the NNI (Nearest Neighbor Imputation) method.
The interpretation of the coefficient is understood as a semi-elasticity in points of the response variables consistent with a robust log-level OLS estimator: \(\frac{{B}_{i}}{100}=\frac{\Delta y}{100\left(\frac{\Delta x}{x}\right)}=\frac{\Delta y}{\%\Delta x}\).
In this case, an interpretation is considered as a semi-elasticity of the robust OLS estimator Dif-in-Dif of a log-level model, in which: \(100*{\beta }_{i}=\frac{100*\left(\frac{\Delta y}{y}\right)}{\Delta x}=\frac{\%\Delta y}{\Delta x}\).
In this case, an interpretation is considered as an elasticity of the robust OLS estimator of a log-level model, where: \({\beta }_{i}=\frac{100*\left(\frac{\Delta y}{y}\right)}{100*\left(\frac{\Delta x}{y}\right)}=\frac{\%\Delta y}{\%\Delta x}\).
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Arenas, C.D.C., Barreto, D.O. & Cabezas, D.M. The Short-Term Effects of COVID-19 on the Manufacturing Industry in Colombia: Unveiling Insights through a Natural and Exogenous Experiment. J Knowl Econ (2024). https://doi.org/10.1007/s13132-024-01927-8
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DOI: https://doi.org/10.1007/s13132-024-01927-8