Published

2025-01-01

Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy

Prediciendo el estado de la economía: una aplicación de combinaciones lineales de factores comunes dinámicos a la economía colombiana

DOI:

https://doi.org/10.15446/rce.v48n1.113209

Keywords:

Coincident index, Genetic algorithms, Macroeconomics, Nonconvex optimization, Multivariate time series (en)
Índice coincidente, Algoritmos genéticos, Macroeconomía, Optimización no convexa, Series de tiempo multivariadas (es)

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Authors

  • Mario Enrique Arrieta-Prieto Universidad Nacional de Colombia
  • Fabio Nieto Universidad Nacional de Colombia

The main goal of this work is to propose a general methodology to create a coincident index for the economy of a given country or region based on linear combinations of dynamic common factors, and to validate it on simulated scenarios and on a case study for Colombia. The methodology proposed can effectively handle both stationary and nonstationary macroeconomic variables as input and provides tools to obtain point estimates and confidence regions, and to test hypotheses for the linear-combination coefficients. This work highlights how promising this new proposal is in terms of its contribution with respect to its antecedents in the literature, by showcasing situations in which a linear combination of dynamic factors can enhance the accuracy of the nowcast and address potential problems and limitations of considering only one dynamic factor as index. The application of this work to the Colombian economy is based on the macroeconomic analysis conducted by previous researchers. This work, however, considers and analyzes a much larger set of candidate indices via linear combinations of factors, providing consistent results; which strengthens and validates their previous findings.

El objetivo principal de este trabajo es proponer una metodología general para crear un índice coincidente para la economía de un país o región determinado, basada en combinaciones lineales de factores comunes dinámicos, y validarla en escenarios simulados y en un estudio de caso para Colombia. La metodología propuesta puede manejar de manera efectiva tanto variables macroeconómicas estacionarias como no estacionarias como datos de entrada y proporciona herramientas para obtener estimaciones puntuales y regiones de confianza, así como para probar hipótesis sobre los coeficientes de la combinación lineal. Este trabajo destaca lo prometedora que es esta nueva propuesta en términos de su contribución con respecto a sus antecedentes en la literatura, al mostrar situaciones en las que una combinación lineal de factores dinámicos puede mejorar la precisión del pronóstico del estado de la economía, además de abordar problemas y limitaciones potenciales al considerar solo un factor dinámico como índice. La aplicación de este trabajo a la economía colombiana se basa en el análisis macroeconómico realizado por investigadores previos. Sin embargo, este trabajo considera y analiza un conjunto mucho más amplio de índices candidatos a través de combinaciones lineales de factores, proporcionando resultados consistentes, lo que fortalece y valida sus hallazgos anteriores.

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How to Cite

APA

Arrieta-Prieto, M. E. and Nieto, F. (2025). Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy. Revista Colombiana de Estadística, 48(1), 71–98. https://doi.org/10.15446/rce.v48n1.113209

ACM

[1]
Arrieta-Prieto, M.E. and Nieto, F. 2025. Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy. Revista Colombiana de Estadística. 48, 1 (Jan. 2025), 71–98. DOI:https://doi.org/10.15446/rce.v48n1.113209.

ACS

(1)
Arrieta-Prieto, M. E.; Nieto, F. Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy. Rev. colomb. estad. 2025, 48, 71-98.

ABNT

ARRIETA-PRIETO, M. E.; NIETO, F. Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy. Revista Colombiana de Estadística, [S. l.], v. 48, n. 1, p. 71–98, 2025. DOI: 10.15446/rce.v48n1.113209. Disponível em: https://revistas.unal.edu.co/index.php/estad/article/view/113209. Acesso em: 19 feb. 2025.

Chicago

Arrieta-Prieto, Mario Enrique, and Fabio Nieto. 2025. “Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy”. Revista Colombiana De Estadística 48 (1):71-98. https://doi.org/10.15446/rce.v48n1.113209.

Harvard

Arrieta-Prieto, M. E. and Nieto, F. (2025) “Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy”, Revista Colombiana de Estadística, 48(1), pp. 71–98. doi: 10.15446/rce.v48n1.113209.

IEEE

[1]
M. E. Arrieta-Prieto and F. Nieto, “Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy”, Rev. colomb. estad., vol. 48, no. 1, pp. 71–98, Jan. 2025.

MLA

Arrieta-Prieto, M. E., and F. Nieto. “Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy”. Revista Colombiana de Estadística, vol. 48, no. 1, Jan. 2025, pp. 71-98, doi:10.15446/rce.v48n1.113209.

Turabian

Arrieta-Prieto, Mario Enrique, and Fabio Nieto. “Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy”. Revista Colombiana de Estadística 48, no. 1 (January 21, 2025): 71–98. Accessed February 19, 2025. https://revistas.unal.edu.co/index.php/estad/article/view/113209.

Vancouver

1.
Arrieta-Prieto ME, Nieto F. Nowcasting the State of the Economy: An Application of Linear Combinations of Dynamic Common Factors to the Colombian Economy. Rev. colomb. estad. [Internet]. 2025 Jan. 21 [cited 2025 Feb. 19];48(1):71-98. Available from: https://revistas.unal.edu.co/index.php/estad/article/view/113209

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