May 01, 2023
Methodology for TFP Bioeconomy Impact post Covid-19 on the agricultural economy
- 1National Autonomous University of Nicaragua, Leon
- C A Zuniga-Gonzalez: Escuela de Ciencias Agrarias y Veterinarias. Departamento de Agroecologia.
Protocol Citation: C A Zuniga-Gonzalez 2023. Methodology for TFP Bioeconomy Impact post Covid-19 on the agricultural economy. protocols.io https://dx.doi.org/10.17504/protocols.io.q26g7yeo3gwz/v1
Manuscript citation:
Submitting to PONE-D-23-10369
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: April 29, 2023
Last Modified: May 01, 2023
Protocol Integer ID: 81179
Keywords: CRS, DEAP, Frontier Analysis indicators, Technology, Efficiency
Abstract
Methods: The panel data was organized with FAO Statistic data. Linear programming with an enveloping data analysis (DEA) approach was used to measure the Malmquist TFP indices to determine the inter-annual changes by region in productivity and technical efficiency.
Materials
Resources
FAO Statistic
DEAP 2.1
VOSviewer
Before start
The model of Georgescu-Roegen (1976)was considered to define the structure of Panel Data and the DEAP software.
Methodology for TFP Bioeconomy Impact post Covid-19 on the agricultural economy
Methodology for TFP Bioeconomy Impact post Covid-19 on the agricultural economy
Panel Data. The data was organized from the statistic FAO in panel data. These variables are Value Agriculture (VAit), Land use (LUit), Unit Capital Stock (UCSit), Annual population (APit), Trade Indices (TIit), Consumer Prices, and Food Indices (2015 = 100) (CPFIit). All variables were affected by Covid-19.
DEAP 2.1, Data Envelopment Analysis (Computer) Program (RRID:SCR_023002) was used, Coelli [17]. Three text files were used for running computing. The text file refers to panel data containing 60 observations of six regions over the 2012-2021 years period. The second file is Instructions, where the procedure is indicated, and the third is the results (output) that are shown in the results sections. One output is considered with five inputs listed in the next section.
Processing data was the last phase for the built chart and table that explain the effect of Covid-19 on the agricultural economy. The Bioeconomy was and is an alternative to change a mitigate the effects.
Protocol references
[41] Zuniga-Gonzalez, C.A. (2023): Data for: TFP Bioeconomy Impact post Covid-19 on agricultural economy. figshare. Dataset. https://doi.org/10.6084/m9.figshare.22337914.v1
[42] Toruño, P. J., Zuniga-Gonzalez, C. A., Castellón, J. D. , Hernández-Rueda, M. J., & Gutierrez-Espinoza, E. I. . (2022). Identification of the productive paths of the Bioeconomy in CNU Universities and the agricultural sector. Rev. Iberoam. Bioecon. Cambio Clim., 8(16), 1929–1946. https://doi.org/10.5377/ribcc.v8i16.15016
[43] Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 2020(5):533-534. doi: 10.1016/S1473-3099(20)30120-1pmid: 32087114
[44] Vo, T. P. T., Ngo, H. H., Guo, W., Turney, C., Liu, Y., Nguyen, D. D., ... & Varjani, S. (2023). Influence of the COVID-19 pandemic on climate change summit negotiations from the climate governance perspective. Science of The Total Environment, 878, 162936.
[45]Agarwal, P., Soni, R., Kaur, P., Madan, A., Mishra, R., Pandey, J., ... & Singh, G. (2022). Cyanobacteria as a promising alternative for sustainable environment: Synthesis of biofuel and biodegradable plastics. Frontiers in Microbiology, 13.