Economic and Financial Impacts on MSME Survival in Colombia (2016–2023): Accounting for Unobserved Heterogeneity

Published: 2026-08-25

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Introduction


The survival of micro, small and medium-sized enterprises (MSMEs) is a central indicator of economic and social well-being, given its impact on employment, productivity, and business dynamics, particularly in emerging economies such as Colombia.


Objective


This study aims to determine the economic and financial variables that impact the survival of Colombian MSMEs between 2016 and 2023, with explicit treatment of unobserved heterogeneity and identification of the structural change induced by the COVID-19 pandemic.


Methodology


A discrete-time proportional hazards model with gamma-distributed unobserved heterogeneity was estimated, complemented by the non-parametric Kaplan-Meier estimator, on an unbalanced firm-year panel of 161,085 observations corresponding to 29,737 unique firms. Two multiplicative interactions between firm-level financial covariates and the 2020 indicator were incorporated to capture the structural change induced by the pandemic.


Results


The aggregate six-year survival rate reaches 73.7%, with the highest sectoral rates in real estate and agriculture (around 81%) and the lowest in transportation and human health (below 60%). Profitability and firm liquidity reduce the hazard of exit, while short-term liabilities and firm indebtedness raise it. During 2020, the effect of firm indebtedness on the hazard was approximately three times stronger than in the rest of the period, while liquidity gained relative importance as a protective mechanism.


Conclusions


Sectoral and territorial conditions emerge as substantive determinants of survival, and the design of financial support during macroeconomic shocks should account for the pre-shock leverage position of beneficiaries.

Elcira Solano Benavides, Universidad del Atlántico, Barranquilla, Colombia

Doctora en Ciencias Económicas.

Nelson Alandete-Brochero, Universidad del Atlántico, Barranquilla, Colombia

Magíster en Economía.

Solano Benavides, E., & Alandete-Brochero, N. (2026). Economic and Financial Impacts on MSME Survival in Colombia (2016–2023): Accounting for Unobserved Heterogeneity. Sociedad Y Economía, 58, e20315026. https://doi.org/10.25100/sye.vi58.15026

Abdullah, N. H. N., Said, J., & Savitri, E. (2019). Business survival and sustainability through comprehensive

value creation in Malaysian government-linked companies. International Journal of Business and

Management, 9(2), 195–205.

Aghion, P., & Saint-Paul, G. (1998). Virtues of bad times: Interaction between productivity growth and economic

fluctuations. Macroeconomic Dynamics, 2(3), 322–344. https://doi.org/10.1017/S1365100598008025 DOI: https://doi.org/10.1017/S1365100598008025

Alcantara de Araújo, M., de Lima Andrade, J. R., & de Santana Ribeiro, L. C. (2017). Tasas de supervivencia de

las micro y pequeñas empresas del turismo en Sergipe-Brasil. Estudios y Perspectivas en Turismo, 26(1),

191–208.

Alves, J. C., Lok, T. C., Luo, Y., & Hao, W. (2020). Crisis management for small business during the COVID-19

outbreak: Survival, resilience and renewal strategies of firms in Macau. Research Square, 1-29. https://

doi.org/10.21203/rs.3.rs-34541/v1

Angulo Arboleda, A. C. (2018). Determinantes de la supervivencia empresarial en el municipio de

Palmira 2012-2018 [Master’s thesis]. Universidad del Valle, Caicedonia, Colombia. https://hdl.handle.

net/10893/11267

Ayele, A. W., & Derseh, A. B. (2024). Sustainability time and its determinant factors of small and medium-

scale enterprises in East Gojjam zone: Parametric survival regression model. Global Business Review,

25(3), 656–682. https://doi.org/10.1177/0972150920988657 DOI: https://doi.org/10.1177/0972150920988657

Banco de la República. (2024). Macroeconomic Statistics Series (2016-2023). https://suameca.banrep.gov.

co/descarga-multiple-de-datos/

Bekele, E., & Worku, Z. (2008). Factors that affect the long-term survival of micro, small and medium DOI: https://doi.org/10.1111/j.1813-6982.2008.00207.x

enterprises in Ethiopia. South African Journal of Economics, 76(3), 548–568. https://doi.org/10.1111/

j.1813-6982.2008.00207.x

Ben Jabeur, S., Stef, N., & Carmona, P. (2023). Bankruptcy prediction using the XGBoost algorithm and variable DOI: https://doi.org/10.1007/s10614-021-10227-1

importance feature engineering. Computational Economics, 61(2), 715–741. https://doi.org/10.1007/

s10614-021-10227-1

Bragoli, D., Ferretti, C., Ganugi, P., Marseguerra, G., Mezzogori, D., & Zammori, F. (2022). Machine-learning

models for bankruptcy prediction: Do industrial variables matter? Spatial Economic Analysis, 17(2), 156–

177. https://doi.org/10.1080/17421772.2021.1977377 DOI: https://doi.org/10.1080/17421772.2021.1977377

Cao, Y. (2012). A survival analysis of small and medium enterprises (SMEs) in central China and their

determinants. African Journal of Business Management, 6(10), 3834–3843. https://doi.org/10.5897/

AJBM11.2759

Castro Rojas, Y., Huertas Kaleda, C. A., & Obando Granadillo, C. E. (2017). Survival analysis for bankruptcy

prediction: The case of the retail industry in Colombia. Revista Facultad de Ciencias Económicas, 25(2),

161-180.

Chhatwani, M., Mishra, S. K., Varma, A., & Rai, H. (2022). Psychological resilience and business survival

chances: A study of small firms in the USA during COVID-19. Journal of Business Research, 142, 277–286.

https://doi.org/10.1016/j.jbusres.2021.12.048 DOI: https://doi.org/10.1016/j.jbusres.2021.12.048

Confecámaras. (2023). Dinámica de creación y supervivencia de las empresas en Colombia. Confederación

Colombiana de Cámaras de Comercio. https://confecamaras.org.co/images/Informe-Dinamica-de-

creacion-de-empresas-2023.pdf

Crane, L. D., Decker, R. A., Flaaen, A., Hamins-Puertolas, A., & Kurz, C. (2022). Business exit during the

COVID-19 pandemic: Non-traditional measures in historical context. Journal of Macroeconomics, 72,

103419. https://doi.org/10.1016/j.jmacro.2022.103419 DOI: https://doi.org/10.1016/j.jmacro.2022.103419

DANE –National Administrative Department of Statistics–. (2024). Macroeconomic and Sectoral Statistics

(2016-2023). https://www.dane.gov.co/index.php/estadisticas-por-tema/cuentas-nacionales

D’Arrigo, G., Leonardis, D., Abd ElHafeez, S., Fusaro, M., Tripepi, G., & Roumeliotis, S. (2021). Methods to

analyse time-to-event data: The Kaplan-Meier survival curve. Oxidative Medicine and Cellular Longevity,

2021, 2290120. https://doi.org/10.1155/2021/2290120 DOI: https://doi.org/10.1155/2021/2290120

Decker, R. A., Haltiwanger, J., Jarmin, R. S., & Miranda, J. (2020). Changing business dynamism and

productivity: Shocks versus responsiveness. American Economic Review, 110(12), 3952–3990. https://

doi.org/10.1257/aer.20190680

Rey, M. de C. (2023). La supervivencia empresarial en Colombia: estudio de los factores clave que impulsan la

permanencia de las empresas en el mercado [Master’s tesis]. Universidad Nacional de Colombia, Bogotá,

Colombia. https://repositorio.unal.edu.co/handle/123456789/86720

Donthu, N., & Gustafsson, A. (2020). Effects of COVID-19 on business and research. Journal of Business

Research, 117, 284–289. https://doi.org/10.1016/j.jbusres.2020.06.008 DOI: https://doi.org/10.1016/j.jbusres.2020.06.008

Drnevich, P. L., & West, J. (2023). Performance implications of technological uncertainty, age, and size for

small businesses. Journal of Small Business Management, 61(4), 1806–1841. https://doi.org/10.1080/0

0472778.2020.1867733

Engidaw, A. E. (2022). Small businesses and their challenges during COVID-19 pandemic in developing DOI: https://doi.org/10.1186/s13731-021-00191-3

countries: In the case of Ethiopia. Journal of Innovation and Entrepreneurship, 11(1), 1–22. https://doi.

org/10.1186/s13731-021-00191-3

Esteve Pérez, S., de Lucio, J., Minondo Uribe-Etxeberria, A., Mínguez, R., & Requena Silvente, F. (2017). La

supervivencia exportadora: Un análisis a nivel de empresa, producto y destino. Cuadernos de Información

Económica, 258, 15–33.

Fernández-Villaverde, J., & Guerrón-Quintana, P. A. (2020). Uncertainty shocks and business cycle research. DOI: https://doi.org/10.3386/w26768

Review of Economic Dynamics, 37, S118–S146. https://doi.org/10.1016/j.red.2020.06.005 DOI: https://doi.org/10.1016/j.red.2020.06.005

Fort, T. C., Pierce, J. R., & Schott, P. K. (2018). New perspectives on the decline of US manufacturing DOI: https://doi.org/10.3386/w24490

employment. Journal of Economic Perspectives, 32(2), 47–72. https://doi.org/10.1257/jep.32.2.47 DOI: https://doi.org/10.1257/jep.32.2.47

Giunipero, L. C., Denslow, D., & Rynarzewska, A. I. (2022). Small business survival and COVID-19: An

exploratory analysis of carriers. Research in Transportation Economics, 93, 101087. https://doi.

org/10.1016/j.retrec.2021.101087

Görg, H., & Strobl, E. (2000). Multinational companies, technology spillovers and firm survival: Evidence from

Irish manufacturing (Research Paper No. 12). Institute for Economic Research.

Gupta, J., Gregoriou, A., & Ebrahimi, T. (2018). Empirical comparison of hazard models in predicting SMEs

failure. Quantitative Finance, 18(3), 437–466. https://doi.org/10.1080/14697688.2017.1307514 DOI: https://doi.org/10.1080/14697688.2017.1307514

Hannan, M. T., & Freeman, J. (1977). The population ecology of organizations. American Journal of Sociology,

82(5), 929–964. https://doi.org/10.1086/226424 DOI: https://doi.org/10.1086/226424

Hannan, M. T., & Freeman, J. (1989). Organizational ecology. Harvard University Press. https://doi. DOI: https://doi.org/10.4159/9780674038288

org/10.4159/9780674038288

Hernández, D. M. M. (2022). El tamaño inicial de las empresas y la supervivencia empresarial: Caso sector

comercio de Villavicencio. Cuadernos Latinoamericanos de Administración, 18(34), 1-11. https://doi.

org/10.18270/cuaderlam.v18i34.3787

Jenkins, S. P. (2005). Survival analysis [Lecture notes]. Institute for Social and Economic Research, University

of Essex.

Jiménez Gómez, A. E. (2017). Efecto del acceso al crédito en la probabilidad de supervivencia y la productividad

de las firmas [Doctoral dissertation]. Universidad de los Andes, Bogotá, Colombia. https://repositorio.

uniandes.edu.co/handle/1992/34212.

Jovanovic, B. (1982). Selection and the evolution of industry. Econometrica, 50(3), 649–670. https://doi. DOI: https://doi.org/10.2307/1912606

org/10.2307/1912606

Kalbfleisch, J. D., & Prentice, R. L. (2002). The statistical analysis of failure time data (2nd ed.). Wiley. https:// DOI: https://doi.org/10.1002/9781118032985

doi.org/10.1002/9781118032985

Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the DOI: https://doi.org/10.1080/01621459.1958.10501452

American Statistical Association, 53(282), 457–481. https://doi.org/10.1080/01621459.1958.105014

52

Kauermann, G., & Tutz, G. (2001). Vanishing of risk factors for the success and survival of newly founded

companies. Statistica Neerlandica, 55(2), 201–217. https://doi.org/10.1111/1467-9574.00165 DOI: https://doi.org/10.1111/1467-9574.00165

Kristanti, F. T., & Isynuwardhana, D. (2018). Prediction of financial distress of industrial sectors in Indonesian

companies using survival analysis. Jurnal Keuangan dan Perbankan, 22(1), 23–36. https://doi.

org/10.26905/jkdp.v22i1.1601

Kristanti, F. T., Febrianta, M. Y., Salim, D. F., Riyadh, H. A., Sagama, Y., & Beshr, B. A. H. (2024). Advancing

financial analytics: Integrating XGBoost, LSTM, and Random Forest algorithms for precision forecasting of

corporate financial distress. Journal of Infrastructure, Policy and Development, 8(8), 4972. https://doi.

org/10.24294/jipd.v8i8.4972

Krugman, P. (1991). Increasing returns and economic geography. Journal of Political Economy, 99(3), 483–

499. https://doi.org/10.1086/261763 DOI: https://doi.org/10.1086/261763

Lee, J. (2016). Comparison of startup companies’ survival rate between urban and rural areas. Journal of

Korean Society of Rural Planning, 22(4), 147–157. https://doi.org/10.7851/ksrp.2016.22.4.147 DOI: https://doi.org/10.7851/ksrp.2016.22.4.147

Liu, J., & Pang, D. (2006). Determinants of survival and growth of listed SMEs in China [Working paper].

School of Management, University of Manchester.

Markowicz, I. (2018). Modeling the survival time of trading companies in the Zachodniopomorskie Voivodship. DOI: https://doi.org/10.18778/0208-6018.337.06

Acta Universitatis Lodziensis. Folia Oeconomica, 337(4), 85–97. https://doi.org/10.18778/0208-

6018.337.06

Martínez, A. F. (2006). Determinantes de la supervivencia de empresas industriales en el área metropolitana DOI: https://doi.org/10.32468/eser.41

de Cali 1994-2003. Sociedad y Economía, 11, 112–144. https://doi.org/10.25100/sye.v0i11.4131 DOI: https://doi.org/10.25100/sye.v0i11.4131

Mejía, J. M. A., Alzate, S. G., Plata, M. P. T., & Cardona, J. C. C. (2023). Determinantes de la tasa de supervivencia

de las empresas formales en los departamentos de Colombia. Cuadernos de Administración, 39(73),

1–24.

Melitz, M. J. (2003). The impact of trade on intra-industry reallocations and aggregate industry productivity. DOI: https://doi.org/10.3386/w8881

Econometrica, 71(6), 1695–1725. https://doi.org/10.1111/1468-0262.00467 DOI: https://doi.org/10.1111/1468-0262.00467

Meyer, B. D. (1988). Unemployment insurance and unemployment spells (NBER Working Paper No. 2546).

National Bureau of Economic Research. https://doi.org/10.3386/w2546 DOI: https://doi.org/10.3386/w2546

Meyer, B. D. (1990). Unemployment insurance and unemployment spells. Econometrica, 58(4), 757–782.

https://doi.org/10.2307/2938349 DOI: https://doi.org/10.2307/2938349

Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance, and the theory of investment.

American Economic Review, 48(3), 261–297.

Muhwezi, K., & Kiliman, N. (2023). Survival of Uganda’s small and medium businesses in a Cox model.

African Development Review, 35(2), 308–325.

Myers, S. C., & Majluf, N. S. (1984). Corporate financing and investment decisions when firms have

information that investors do not have. Journal of Financial Economics, 13(2), 187–221. https://doi.

org/10.1016/0304-405X(84)90023-0

Nguyen Thi, N. (2022). SMEs survival and knowledge in emerging economies: Evidence from Vietnam. Heliyon,

8(11), e11387. https://doi.org/10.1016/j.heliyon.2022.e11387 DOI: https://doi.org/10.1016/j.heliyon.2022.e11387

OECD/CAF/SELA. (2024). SME policy index: Latin America and the Caribbean 2024: Towards an inclusive,

resilient, and sustainable recovery. OECD Publishing. https://doi.org/10.1787/ba028c1d-en DOI: https://doi.org/10.1787/ba028c1d-en

Orlando, T., & Rodano, G. (2020). Firm undercapitalization in Italy: Business crisis and survival before and

after COVID-19 (Bank of Italy Occasional Paper No. 590). https://doi.org/10.2139/ssrn.3826464 DOI: https://doi.org/10.2139/ssrn.3826464

Parmonangan, L. R., & Rahadi, R. A. (2020). Survival analysis of delisted Indonesian companies. Journal of

Accounting and Finance, 4(1), 1–7. https://doi.org/10.25124/jaf.v4i1.2175 DOI: https://doi.org/10.25124/jaf.v4i1.2175

Penrose, E. T. (2009). The theory of the growth of the firm (4th ed.). Oxford University Press. https://doi.

org/10.1093/0198289774.001.0001

Pérez, A. R. M., Rodríguez, E. C., & Toscano, S. L. M. (2015). Determinantes de la supervivencia empresarial

en la industria alimentaria de México, 2003-2008. Trayectorias, 17(41), 3–28.

Prentice, R. L., & Gloeckler, L. A. (1978). Regression analysis of grouped survival data with application to

breast cancer data. Biometrics, 34(1), 57–67. https://doi.org/10.2307/2529588 DOI: https://doi.org/10.2307/2529588

Puebla, D., Tamayo, D. A., & Feijoó, E. (2018). Factores relacionados a la supervivencia empresarial: Evidencia

para Ecuador. Analítika: Revista de Análisis Estadístico, 16, 119–153.

Román Ramírez, D. (2021). Supervivencia de las nuevas empresas: Una aproximación desde el Machine

Learning [Doctoral dissertation]. Universidad EAFIT, Medellín, Colombia. https://repository.eafit.edu.co/

handle/10784/29845

Salgado, E. B., López, S. F., Búa, M. V., & Gómez, I. N. (2012). Supervivencia de las empresas innovadoras

españolas: Efectos de la innovación. Revista Galega de Economía, 21(2), 107–132.

Santana, L. (2017). Determinantes de la supervivencia de microempresas en Bogotá: Un análisis con modelos

de duración. Innovar, 27(64), 51–61. https://doi.org/10.15446/innovar.v27n64.62368 DOI: https://doi.org/10.15446/innovar.v27n64.62368

Self, S. G., & Liang, K. Y. (1987). Asymptotic properties of maximum likelihood estimators and likelihood

ratio tests under nonstandard conditions. Journal of the American Statistical Association, 82(398), 605–

610. https://doi.org/10.1080/01621459.1987.10478472 DOI: https://doi.org/10.1080/01621459.1987.10478472

Sepúlveda, W. S., & Bustamante-Caballero, S. P. (2024). Segmentation and factors associated with the

resilience of touristic SMEs: Results from Colombia. Tourism and Hospitality Research, 24(4), 615–626.

https://doi.org/10.1177/14673584231165945 DOI: https://doi.org/10.1177/14673584231165945

Superintendence of Companies. (2024). Integrated Corporate Information System (SIIS) - Financial Information

(2016-2023). https://siis.ia.supersociedades.gov.co/#/massivereports

Taiwo, A. (2023). Effect of cost control techniques on the survival of manufacturing companies in Nigeria.

Journal of Accounting and Management, 13(2), 45–59.

Tripathy, A., Vishwakarma, G. K., & Bhattacharjee, A. (2025). Modeling unobserved heterogeneity in multistate

event history data using frailty and weighted survival approaches. Scientific Reports, 15, 30535. https://

doi.org/10.1038/s41598-025-30535-y

Valaskova, K., Gajdosikova, D., & Belas, J. (2023). Bankruptcy prediction in the post-pandemic period: A case DOI: https://doi.org/10.24136/oc.2023.007

study of Visegrad Group countries. Oeconomia Copernicana, 14(1), 253–293. https://doi.org/10.24136/

oc.2023.007

Watson, J., & Everett, J. E. (1996). Do small businesses have high failure rates? Journal of Small Business

Management, 34(4), 45–62.

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