This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This journal is licensed by a Creative Commons Attribution License (CC BY-NC-SA 4.0) Attribution-Non Commercial 4.0 International. For the CC licenses, the principle isthe creative freedom. This system complements the copyright without opposing it, conscious of its importance in our culture. The content of the articles is the responsibility of each author, and does not compromise in any way, to the journal or the university. It allows the transmission and reproduction of titles, abstracts and full content, with academic, scientific, cultural ends, provided acknowledgment of the respective source. This work cannot be used for commercial purposes.
They journal does not charge authors for submission or publication.
Abstract
This paper explores the relationship between residential confinement to reduce the spread of the COVID-19 virus, seen as a public policy, and how it affects the informal labor sector, as well as the response
of individuals to the pandemic in the states of Mexico. Forming panels for various levels of informality applied to panel vector auto-regressive (PVAR) shows that staying at home as public policy becomes more effective as informality decreases. In addition, the response of individuals to an increase in the spread of the pande-
mic depends on the level of informality: for states with lower rates of informality, individuals respond to a higher concentration of residential confinement. But for states with a higher level of informality, the evidence is not significant. The paper considers the role of informality in the development of an effective public policy.
Keywords:
References
Abrigo, M. R. M., & Love, I. (2016). Estimation of panel vector autoregression in Stata. Stata Journal, 16(3), 778-804. https://doi.org/10.1177/1536867x1601600314
Akaike, H. (1969). Fitting autoregressive models for prediction. Annals of the Institute of Statistical Mathematics, 21(1), 243-247. https://doi.org/10.1007/BF02532251
Altamirano, Á., Azuarra, O., González, S., & Banco Interamericano de Desarrollo (BID). (2020). ¿Cómo impactará la COVID-19 al empleo?: Posibles escenarios para América Latina y el Caribe. Banco Interamericano de Desarrollo, 7. https://publications.
iadb.org/publications/spanish/document /Cómo_impactará_la_COVID-19_al_em-pleo_Posibles_escenarios_para_América_Latina_y_el_Caribe.pdf
Andersen, M. (2020). Early evidence on social distancing in response to COVID-19 in the United States. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3569368
Banxico (2020). Reporte sobre las economías regionales julio-septiembre 2020. https://www.banxico.org.mx/publicaciones-y-prensa/reportes-sobre-las-economias-regionales/%7B8427BCB2-D8F2-C28A-8DD4-EB8DD9770681%7D.pdf
Bargain, O., & Aminjonov, U. (2020). Trust and compliance to public health policies in times of COVID-19. Journal of Public Economics, 104316. https://doi.org/10.1016/j.jpubeco.2020.104316
Bloomberg (2020a). Coronavirus pandemic: Ranking the best, worst places to be. Bloomberg. https://www.bloomberg.com/graphics/covid-resilience-ranking/?utm_medium=social&cmpid=socialflow-twitter-business&utm_source=twitter&utm_campaign
=socialflow-organic&utm_content=business
Bloomberg (2020b). Inside Bloomberg’s covid resilience ranking - Bloomberg. Bloomberg. https://www.bloomberg.com/news/articles/2020-11-24/inside-bloomberg-s-covid-resilience-ranking
Brotherhood, L., Kircher, P., Santos, C., & Tertilt, M. (2020). An economic model of the Covid-19 epidemic: The importance of testing and age-specific policies. IZA Institute of Labor Economics - Discussion Paper Series, 13265, 1–71. www.RePEc.org
Busso, M., Camacho, J., Messina, J., & Montenegro, G. (2021). Social protection and informality in Latin America during the COVID-19 pandemic. PLoS ONE, 16(11November). https://doi.org/10.1371/journal.pone.0259050
Catherine, S., Miller, M., & Sarin, N. (2020). Relaxing household liquidity cons- traints through social security. Journal of Public Economics, 189, 104243. https://doi.org/10.1016/j.jpubeco.2020.104243
Chapa, J. (2020). Impacto Económico del COVI-19 en las regiones de México. Revista Ciencia UANL, 23(102). https://doi.org/10.29105/cienciauanl23.102-1
CONAGUA. (2020). Servicio Meteorológico Nacional. https://smn.conagua.gob.mx/es/
Dingel, J. I., & Neiman, B. (2020). How many jobs can be done at home? Journal of Public Economics, 189. https://doi.org/10.1016/j.jpubeco.2020.104235
Engle, S., Stromme, J., & Zhou, A. (2020). Staying at home: mobility effects of COVID-19. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3565703
Esquivel, G. (2020). Los impactos económicos de la pandemia en México. EconomíaUNAM, 17(51), 28–44. https://doi.org/10.22201/FE.24488143E.2020.51.543
Esquivel, G., & Campos-Vázquez, R. M. (2020). Consumption and geographic mobility in pandemic times: Evidence from Mexico. Cepr Press Covid Economics, 38, 218-252.
Estados Unidos Mexicanos (2020a). DOF - Diario Oficial de la Federación. https://www.
dof.gob.mx/nota_detalle.php?codigo=5589479&fecha=16/03/2020&print=true
Estados Unidos Mexicanos. (2020b). DOF - Diario Oficial de la Federación. https://www.dof.gob.mx/nota_detalle.php?codigo=5590914&fecha=31/03/2020&print=true
Ferraresi, M., Kotsogiannis, C., Rizzo, L., & Secomandi, R. (2020). “Lockdown” and institutions COVID-19. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports .
Gasca, N. C., Reyes-Garza, J., Lozano-Esparza, S., del Pino, P. O., Olivas-Martínez, A., Ulloa-Pérez, E., Garbuno-Inigo, A., & Arroyo, J. (2022). Effect of Mexico’s vaccination program on Covid-19 cases, hospitalizations, and deaths among older adults in Mexico
City. Salud Pública de México, 64(4, jul-ago), 424-428. https://doi.org/10.21149/13402
Gausman, J., & Langer, A. (2020). Sex and gender disparities in the COVID-19 pandemic. Journal of Women’s Health, 29(4), 465-466. https://doi.org/10.1089/jwh.2020.8472
Gobierno de México, (GobMx), & Secretaría de Salud, (SALUD). (2020). Coronavirus gob.mx. Gobierno de México (GobMx).
Google LLC. (2020). Google COVID-19 community mobility reports. Https://www.Google.Com/Covid19/Mobility/ Accessed: <18 May 2020>.
ILO, I. L. O. (2020). COVID-19 and the world of work. ILO Monitor Fourth Edition.
INEGI. (2020a). Banco de datos. Banco de Información Economica. https://www.inegi.org.mx/sistemas/bie/
INEGI. (2020b). Indicacadores de ocupación y empleo. Cifras oportunas durante enero del 2020. Febrero.
INEGI. (2020c). Investigación - Estado de ánimo de los tuiteros. INEGI. https://www.inegi. org.mx/app/animotuitero/#/app/multiline
Kong, E., & Prinz, D. (2020). Disentangling policy effects using proxy data: Which shutdown policies affected unemployment during the COVID-19 pandemic? Journal of Public Economics, 189, 104257. https://doi.org/10.1016/j.jpubeco.2020.104257
Langer, A., Meleis, A., Knaul, F. M., Atun, R., Aran, M., Arreola-Ornelas, H., Bhutta, Z. A., Binagwaho, A., Bonita, R., Caglia, J. M., Claeson, M., Davies, J., Donnay, F. A., Gausman, J. M., Glickman, C., Kearns, A. D., Kendall, T., Lozano, R., Seboni, N., ... Frenk, J. (2015). Women and health: The key for sustainable development. The Lancet, 36(9999), 1165–1210. Lancet Publishing Group. https://doi.org/10.1016/S0140-6736(15)60497-4
Leyva, A. G. (2020). Propuesta metodológica del indicador “Grado de Felicidad Local”, asociación de indicadores relativos a la felicidad, bienestar y estado de ánimo. Interconectando Saberes. https://doi.org/10.25009/is.v0i10.2663
Loayza, N., & Pennings, S. M. (2020). Macroeconomic policy in the time of COVID-19: A primer for developing countries. World Bank Research and Policy Briefs, 147291. https://ourworldindata.org/coronavirus-source-data ,
Luque Zúñiga, B. G., Moreno Salazar Calderón, K. A. B., & Lanchipa Ale, T. M. (2021). Impactos del COVID-19 en la agricultura y la seguridad alimentaria. Centro Agrícola. http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S0253-57852021000100072
Lütkepohl, H. (2005). New introduction to multiple time series analysis. New introduc- tion to Multiple Time Series Analysis. Springer. https://doi.org/10.1007/978-3-540-27752-1
Maloney, W., & Taskin, T. (2020). Determinants of social distancing and economic activity during COVID-19: A global view. World Bank Policy Research Working Paper, 9242. http://www.worldbank.
Mendoza Cota, J. E. (2019). COVID-19 y el empleo en México: impacto inicial y pronósticos de corto plazo. Contaduría y Administración, 65(4), 1-18. https://doi.org/10.22201/fca.24488410e.2020.3028
Milani, F. (2020). COVID-19 Outbreak, social response, and early economic effects: A global VAR analysis of cross-country interdependencies. https://doi.org/10.1101/2020.05.07.20094748
Milani, F. (2021). COVID-19 outbreak, social response, and early economic effects: a global VAR analysis of cross-country interdependencies. Journal of Population Economics, 34(1), 223-252. https://doi.org/10.1007/s00148-020-00792-4
Moreno Salazar Calderón, K. A. B. (2021). Seguridad alimentaria en tiempos de COVID-19: Una visión desde la cadena productiva de recursos hidrobiológicos. Revista Estudios del Desarrollo Social: Cuba y América Latina, 9(1). http://scielo.sld.cu/scielo.php?pid=S2308-01322021000100021&script=sci_arttext&tlng=en
Müller, S., & Rau, H. A. (2020). Economic preferences and compliance in the social stress test of the corona crisis. SSRN Electronic Journal, 104322. https://doi.org/10.2139/ssrn.3575633
Narula, R. (2020). Policy opportunities and challenges from the COVID-19 pandemic for economies with large informal sectors. Journal of International Business Policy, 3(3), 302-310. https://doi.org/10.1057/s42214-020-00059-5
OECD. (2020). COVID-19 in Latin America and the Caribbean: Regional socioeconomic implications and policy priorities. OECD, 1–12. https://www.oecd.org/coronavirus/policy-responses/covid-19-in-latin-america-and-the-caribbean-regional-socio-economic-implications-and-policy-priorities-93a64fde/
Ohnsorge, F., & Yu, S. (2022). The Long shadow of informality: challenges and policies. The Long Shadow of Informality: Challenges and Policies. https://doi.org/10.1596/978-1-4648-1753-3
Peluffo, C., & Viollaz, M. (2020). Intra-Household Insurance in the Time of Covid-19: Lessons from Mexico.
Piguillem, F., & Shi, L. (2020). Optimal COVID-19 quarantine and testing policies. CEPR Discussion Papers. https://www.researchgate.net/publication/340226829
Rangel González, E., Llamosas-Rosas, I., Fonseca, F. J., Rangel González, E., Llamosas- Rosas, I., & Fonseca, F. J. (2021). Aislamiento social y el COVID-19 en las regiones de México. EconoQuantum, 18(2), 1-22. https://doi.org/10.18381/EQ.V18I2.7227
Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1. https://doi.org/10.2307/1912017
Tejedor Estupiñán, J. M. (2021). Vacunación y desarrollo en tiempos de la COVID-19. Revista Finanzas y Política Económica, 13(1), 9-13. https://doi.org/10.14718/REVFINANZPOLITECON.V13.N1.2021.1
Testa, P. F., Snyder, R., Rios, E., Moncada, E., Giraudy, A., & Bennouna, C. (2021). Who stays at home? The politics of social distancing in Brazil, Mexico, and the United States during the COVID-19 pandemic. Journal of Health Politics, Policy and Law, 46(6).
https://doi.org/10.1215/03616878-9349100
The World Bank. (2015). World Development Indicators | DataBank. DataBank.
Yilmazkuday, H. (2020). Stay-at-home works to fight against COVID-19: international evidence from Google mobility data. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3571708
Zhu, D., Mishra, S. R., Han, X., & Santo, K. (2020). Social distancing in Latin America during the COVID-19 pandemic: an analysis using the Stringency Index and Google community mobility reports. Journal of Travel Medicine, 2020, 1-3. https://
doi.org/10.1093/jtm/taaa125