vol. 12 núm. 2 (2019)

Estimados lectores, desde el equipo editorial de la revista Comunicaciones en Estadística queremos enviarles un cordial saludo y agradecer el apoyo de todos nuestros autores, revisores y lectores. Fiel a su línea editorial, la revista Comunicaciones en Estadística continúa presentando trabajos de investigación con aplicaciones en diferentes áreas del conocimiento. En este nuevo número contamos con trabajos en econometría y series detiempo, métodos multivariados y modelos de regresión, aplicados en economía, educación y salud pública.

In this article a method to select one classifi cation threshold to establish whether vaccinating a pregnant mother against whooping cough allows the transmission of the necessary antibodies to prevent a neonate from getting this disease before receiving their rst vaccine is proposed. Additionally, gamma regression is proposed to identify mother's antibodies production associated factors and the transmission of these to the newborn. Finally, as a result of this study, the pro les of mothers who have a higher probability of transmitting antibodies to their children during the gestation period were obtained, information that can be used by the District Department of Health (SDS) in the approach of preventive campaigns and public policies that have an impact on the population most vulnerable to this disease in the city of Bogotá.

The school performance is a multidimensional phenomenon determined by the student, the school and the socio-economical context in which they are immerse. In order to measure the performance of the educational institutions, the Ministry of Education applies a set of standardized tests which form the Measurement System of Quality in Education, SIMCE for its initials in Spanish. There are some factors which determine the performance in the SIMCE. Along this line, many authors hold that the socio-economical level of the students is the most important one to explain the school performance. However, the data indicates that, not only the dependence of the educational institution but also the geographical locationwhere it is located affect the school performance. This research aims to determine which are the best predictors in the SIMCE score of mathematics in educational institutions of the Araucania region. The nested data will be modelling by using a Generalized Linear Mixed Model.

With the objective of addressing the scheme of the ght against poverty in Mexico and the de nition of strategies for an adequate public policy, an analysis methodology is proposed that identi ed the probability of risk in ve localities affected by poverty. For this, the degree of sensitivity of the variables that explain the poverty condition of the heads of household in 5 rural locations in Mexico was identi ed; Based on information collected through a census, a probabilistic regression model was formulated, with which three types of indicators were estimated: marginal effects, elasticities and odds ratio. Among the main results, it is worth highlighting that variables such as income, educational level, overcrowding and housing services have an inverse relationship in probability, while food, sex, and speaking indigenous language indicate a direct relationship in the prevailing factors. about the probability that the head of household is poor. Concluding that the explanatory factors of qualitative and quantitative nature of the head of household, in combination with those related to housing and the home, allow generating probabilitydistributions consistent with the theoretical argument.

Food inflation is a macroeconomic agent of notable impact on the cost of living of citizens and in the approach to decision-making of entities that have an impact onmonetary policy. Therefore, it is of interest to have the ability, with some degree of certainty, to obtain relevant information on the variation in food prices. On the other hand, The SIPSA (DANE unit) is the government entity responsible for collecting the prices with which the products are sold in the country’s supply centers. In this paper, the problem of contributing to the prediction of food inflation based on a SIPSA index proposed by the authors, is addressed. Three methodologies are used for this purpose. Namely: integrated auto-regressive averagemean with exogenous variables models (SARIMAX), vectorial auto-regressive structural models (SVAR) and vector error correction model (VECM). Our results indicate the variations of SIPSA explain about 40 % of the variability of food inflation, in addition to the relationship in the short and long term. The creation and use of indicator stories can become ideal tools for the planning and management of portfolio investment strategies with a view to the technology of investment proposals in the capitalmarket.

This document aims to identify explanatory elements to the variability observed in the results of the Saber Pro tests in the modules of Written Communication, English, Critical Reading, Quantitative Reasoning and Citizen Competences from databases supplied by the Colombian Institute for the Promotion of Higher Education Institute in the period between 2012-10 y 2015-30 of students of Ponti cal Bolivarian University. It was analyzed variables of binary type corresponding to the existence or not of resources such as Internet, Television, Telephony, Washing Machine, Oven, Microwave, Fridge, Car, and DVD Player in the homes in which the student resides. In virtue of the large amounts of data the two-step-cluster analysis technique was selected to know the grouping of the information. Whith these results a parallel was made with the scores obtained in the Saber Pro test and it was found that, mostly, the students with more economic resources obtain better scores in the test.

The objective of this article is analyze the effects and relationships of three variables of the international economy expressed in elasticities such as the Exchange Terms Index (TDI), the Real Exchange Rate Index as an estimator of the Producer Price Index (ITCR IPP) and the Total Colombian Debt Index in dollars (TDPYP), which are susceptible to external and internal monetary, exchange and scal policy shocks, evaluated through a multivariate time series model known as VEC for periods from January 2009 to December 2018, where a direct relationship between the TDI and TDPYP variables and an inverse relationship between TDI and ITCR IPP was found.