Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/259461 
Year of Publication: 
2021
Citation: 
[Journal:] Latin American Economic Review [ISSN:] 2196-436X [Volume:] 30 [Issue:] 1 [Article No.:] 2 [Publisher:] Centro de Investigación y Docencia Económica (CIDE) [Place:] Ciudad de México [Year:] 2021 [Pages:] 1-20
Publisher: 
Centro de Investigación y Docencia Económica (CIDE), Ciudad de México
Abstract: 
This paper aims to model the dynamics of social deprivation in Mexico using a Markovian approach. First, we establish a scenario where a list of items characterizing social deprivation evolves as a first-order Markov chain under the sample period (2002-2012). Then, we estimate latent states and ergodic vectors of a hidden-Markov model to verify the strength of the conclusions drawn from such a scenario. After collecting results from both kinds of analyses, we find a similar pattern of impoverishment. The paper's conclusions state that the evolution of Mexico's deprivation profile may slightly worsen soon.
Subjects: 
Hidden and direct Markov models
Mexico's social deprivation
poverty profile
latent states
ergodic vectors
JEL: 
C15
I32
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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