Conditional Cash Transfer Programs (CCT) have been implemented in México and LatinAmerica since the late 1990's. This type of program focuses on providing social government services by way of direct cash transfers to poor families that are often conditioned to the use of public education and health services. Despite the apparent short-term success of these CCT programs in the Latin American context, there still is much debate about whether CCT programs are effective in alleviating poverty. This paper analyzes the effectiveness of conditional cash transfer programs as a long-term incentive in the use of public services-health and education-among beneficiary families of PROSPERA-Oportunidades in Mexico. The Average Effect of Treatment on the Treated (ATT) for the time period 2002-2012 is estimated based on data from the Mexican Family Life Survey (MxFLS) using Propensity Score Matching (PSM). The results show that the program's impact on the use of preventive health and education services by poor families cannot be sustained in the long-term, which puts in doubt the effectiveness of this social protection intervention program in combating poverty in Mexico.
En este trabajo se analiza el efecto de diversas variables socioeconómicas sobre el grado de inclusión financiera en México. Para ello, se emplean los modelos de probabilidad logit y probit, así como un modelo de regresión lineal robusta. Mediante la información de la Encuesta Nacional de Inclusión Financiera 2012 y 2015 se estima la magnitud del impacto positivo que tienen las remesas, la educación y el ingreso por salarios, lo cual confirma la ruta que debe seguirse para impulsar la inclusión financiera en México.
This work proposes a model starting from the Three-Circle Model, based on the reality of the small and medium-sized family business sector in the Mexico City Metropolitan Area. The present paper proposes a new model that was built based on the Three Circle Model, but it is based on the reality of the Small and Medium Mexican family business sector. The model does not include the Ownership Subsystem, but it includes the Environment Subsystem, a subsystem that has a vital influence on the life and performance of an organization of that size. These three subsystems intersect in common elements such as culture, economy or company vision, triggering the success or failure of the company itself. The methodology used was a mixed methodology, with both qualitative and quantitative elements. First, the Delphi method was used on a scale that was applied to 25 owners of Small and Medium Enterprises and then, to make an additional confirmation, hypothesis testing, factorial analysis and the technique of structural equations were used. It was seen that the ownership subsystem has a lower weight than the business, environment and family subsystems, is the least relevant.
ResumenEl objetivo de esta investigación es describir y comparar la estimación del Valor en Riesgo (VaR), considerando un modelo GARCH univariado con la innovación de la distribución α-estable. Los resultados estadísticos sugieren que el modelo VaR α-estable proporciona estimaciones del VaR más precisas que el modelo bajo la hipótesis gaussiana, el cual subestima significativamente el VaR en períodos de alta volatilidad. Por el contrario, en el período posterior a la crisis, el VaR al 95% bajo la hipótesis gaussiana muestra resultados aceptables y el obtenido bajo el modelo α-estable se encuentra por debajo del rango admisible. La principal aportación de esta investigación es que propone una distribución condicional alternativa para los rendimientos de los precios de los activos en el mercado financiero mexicano, considerando un modelo GARCH con la innovación de la distribución α-estable. Porúltimo, esta investigación proporciona evidencia de que el modelo VaR α-estable estima satisfactoriamente el VaR para niveles altos de confianza incluso en períodos de alta volatilidad. En contraste, en períodos de relativa tranquilidad para niveles de confianza bajos este modelo sobrestima las pérdidas potenciales. is below the admissible range. The main contribution of this research is that it proposes an alternative conditional distribution for asset price yields in the Mexican financial market, considering a GARCH model with the innovation of the α-stable distribution. Finally, this research provides evidence that the α-stable VaR model satisfactorily estimates the VaR for high levels of confidence even in periods of high volatility. In contrast, in periods of relative financial tranquility for low confidence levels, this model overestimates potential losses.JEL Classification: G17, C22, C13.
Purpose The purpose of this paper is to analyze the dependence between the Chinese and Market Integrated Latin America (MILA) stock markets. Design/methodology/approach The authors adjust the multivariate probability distribution Variance Gamma (VG) on data yields from the Hang Seng Index (HSI) and MILA and they use the estimated parameters under VG to find a robust estimator of the correlation matrix yields. Findings The degree of dependence between stock indices from China, Peru, Mexico, Colombia and Chile. In addition, the impact of the change in the HSI affects mostly the movements of the selective stock price index (IPSA) and equally affects the index of the Mexican stock exchange (IPC) and Lima Stock Exchange (S&P/BVL). The effect on index of the Colombia Stock Exchange (COLCAP) is not significant. Research limitations/implications Over time there are different structural changes so the time has been restricted to the years 2000-2015, but could extend the analysis to other time periods and sectors of listed companies in the indices. Practical implications The results can guide policy makers to assess the effect of a random crash on stock markets and measure the level of risk from other markets. Social implications The results can generate a greater understanding of the relationship between the stock markets of China and the emerging countries of Latin America. Originality/value The value of this paper is to focus on alternative methodology to calculate the correlation matrix yields and measure the dependence between the Chinese and MILA stock markets.
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