On the Interaction among Economic Growth, Energy-Electricity Consumption, CO2 Emissions, and Urbanization in Latin America

This paper is aimed at studying the dynamics and long-run interaction among changes in CO2 emissions, economic growth, changes in energy and electricity use, and changes from rural to urban population among Latin American countries (LA) during the period from 1990 to 2014. A Panel VEC (VAR) approach using data from the World Bank shows that the first and second differences in the log of the proportion of the urban population to total population explain: CO2 emissions, GDP per capita, energy-electricity per capita, and the urbanization process. Moreover, CO2 emissions are cointegrated with the first difference in the log of the proportion of urban population. The empirical results show no evidence of the existence of an environmental Kuznets curve. Moreover, it is not possible to generalize the nature of the economic growth-energy consumption-urbanization and CO2 emissions relationships across different latitudes. Finally, a limitation of this study is that the limited availability of data for several countries in the LA region restricts the scope of the econometric analysis.Esta investigación tiene como objetivo estudiar las interacciones dinámicas de largo plazo entre los cambios en las emisiones de CO2, el crecimiento económico, los cambios en el uso de energía y electricidad, y los cambios de la población rural a la urbana en América Latina (AL) durante el período 1990-2014. Un enfoque de datos panel VEC (VAR) con datos del Banco Mundial muestra que la primera y segunda diferencias de los logaritmos de la proporción de la población urbana con respecto a la población total explican: emisiones de CO2, PIB per cápita, consumo de energía, electricidad per cápita y el proceso de urbanización. Además, las emisiones de CO2 se cointegran con la primera diferencia con el logaritmo de la proporción de la población urbana. Los resultados empíricos no sugieren evidencia de la existencia de una curva ambiental de Kuznets. Tampoco es posible generalizar la naturaleza de las relaciones de crecimiento económico-consumo de energía-urbanización y emisiones de CO2 en diferentes latitudes. Una delimitación de este documento es la disponibilidad limitada de datos para varios países de AL, lo cual restringe el alcance del análisis econométric

The Real Estate Investment Trust Industry and the Financial Crisis: Modeling Volatility (1985-2016)

This work measures the sensitivity of the residual volatility of the risk premiums of various Real Estate Investment Trusts (REITs) sectors to systemically important economic events between January 2, 1985, and December 30, 2016. To this end, the residual yields of the REITs are calculated and, with them, a GARCH (1,1) model is estimated, with dummy variables that identify eleven sub-periods delimited by systemic events that occurred in the American economy. The volatility of residual yields is found to decrease with the S&P500 risk premium, and increases only for some sectors with increases in Treasury Bond yields (T-Bills). Similarly, residual yield volatility increased in some periods (e.g., after the Black Monday crash, the low-quality mortgage crisis, and the Great Recession), but did not during the period of stock market collapse caused by companies in the “new economy” (known as the dot-com bubble). Knowledge of these stylized facts opens up new risk management possibilities for those investors considering in including these alternative investments in their portfolios.La industria de fideicomisos de inversión inmobiliaria y la crisis financiera: modelando la volatilidad (1985-2016)Este trabajo mide la sensibilidad de la volatilidad residual de las primas de riesgo de varios sectores de Fondos de Inversión de Bienes Raíces (REITs) a eventos económicos de importancia sistémica, entre el 2 de enero de 1985, y el 30 de diciembre de 2016. Con tal fin, se calculan los rendimientos residuales de los REITs, y con ellos se estima un modelo GARCH(1,1), con variables dummy que identifican once subperiodos delimitados por eventos sistémicos que se presentaron en la economía americana. Se encuentra que la volatilidad de los rendimientos residuales disminuye con el premio por riesgo del S&P500; y aumenta sólo para algunos sectores con aumentos de los rendimientos de los bonos del tesoro (T-Bills). De manera similar, la volatilidad residual de los rendimientos aumentó en algunos periodos (e.g., posterior al crash del lunes-negro, crisis de las hipotecas de baja calidad, y la Gran Recesión), pero no lo hizo durante el periodo del colapso bursátil originado por las empresas de la “nueva economía” (conocida como la crisis de las dot.com). El conocimiento de estos hechos estilizados abre nuevas posibilidades de administración de riesgos para aquellos inversionistas que consideran incluir estas inversiones alternativas en sus portafolios

The Global Automotive Industry Stock Returns During the COVID-19 Pandemic

The Global Automotive Industry Stock Returns During the COVID-19 Pandemic mundial durante la pandemia de COVID-19Este estudio analiza la relación de los puntajes ESG a nivel de empresa y los rendimientos de las acciones de una base de datos mundial para la industria automotriz. Mide la importancia de la relación ESG y CFP durante la última década, e incluye una comparación de aquellas empresas con diferentes niveles de puntaje ESG, así como entre empresas con puntuaciones ESG y empresas que carecen de dichas puntuaciones. Se estiman un modelo cuasi-experimental de diferencia en diferencias (DID) y un panel de datos para examinar el impacto de las puntuaciones ESG y las puntuaciones combinadas ESG en el rendimiento de las acciones de las empresas antes y durante el período de pandemia de COVID-19. Los resultados sugieren que las acciones sostenibles durante la pandemia disminuyeron los rendimientos de las acciones, como lo indican los coeficientes negativos de las puntuaciones ESGC y ESG. Los términos de interacción con el tamaño de la empresa revelaron que los puntajes ESGC y ESG tuvieron una relación positiva con los rendimientos de las acciones durante la pandemia. Por lo tanto, los rendimientos de las empresas más grandes se beneficiaron de puntuaciones ESG más altas durante la crisis de COVID-19. La rentabilidad de las acciones de las empresas en la muestra estratificada, en el contexto de la emergencia sanitaria de la COVID-19, es una contribución original a la literatura sobre la relación ESG-CFP.This study analyzes the relationship of firm-level ESG scores and stock returns from a worldwide database for the automotive industry. It measures the significance of the ESG and CFP relationship during the last decade, and includes a comparison of those firms with different levels of ESG scores, as well as between firms with ESG scores and to firms that lack such scores. A quasi-experimental difference-in-differences (DID) design and a panel data are estimated to examine the impact of ESG scores and ESG combined scores on firms’ stock return before and during the COVID-19 pandemic period. The results suggest that sustainable actions during the pandemic lessened stock returns, as evidenced by the negative coefficients of the ESGC and ESG scores. The interaction terms with firm size, revealed that ESGC and ESG scores had a positive relationship with stock returns during the pandemic. Thus, larger firms’ returns benefited from higher ESG scores during the COVID-19 crisis. The performance of the stratified sample firms’ stock returns in the context of the COVID-19 sanitary emergency is an original contribution to the literature on the ESG-CFP relationship

The “day-of-the-week” effects in the exchange rate of Latin American currencies

This paper studies the "day of the week" anomaly in the exchange rate of the currencies of Argentina, Brazil, Chile, Colombia, Mexico and Peru, with respect to the United States’ dollar. In all cases, yields are stationary, allowing the combined use of linear regressions with GARCH, TARCH, and EGARCH models to explore the "day of the week" anomaly. The presence of "abnormal" effects on some of the currencies is confirmed, particularly on Fridays and Mondays. In addition, volatility in exchange rates shows clusters of volatility as well as leverage effects. This work contributes to the literature by studying the "day of the week" effect on the currency exchange rate market, an innovation with respect to the analysis of the stock market. The reported results are useful for currency brokers, foreign exchange risk managers, monetary authorities, and financial policy designers. Subsequent studies should incorporate transaction costs and tax implications to determine if there are economically interesting arbitrage opportunities in these markets.Este artículo estudia la anomalía “día de la semana” en el tipo de cambio de la moneda de Argentina, Brasil, Chile, Colombia, México y Perú, con respecto al dólar de Estados Unidos. En todos los casos, los rendimientos son estacionarios, lo que permite combinar regresiones lineales con modelos GARCH, TARCH y EGARCH, para explorar la anomalía “día de la semana”. Se confirma la presencia de efectos “anormales” en algunas de las monedas, particularmente los viernes y los lunes. Además, la volatilidad en los tipos de cambio muestra racimos de volatilidad, así como efectos de apalancamiento. Este trabajo contribuye a la literatura al estudiar el efecto “día de la semana” en el mercado de tipos de cambio de moneda, una innovación con respecto al análisis del mercado accionario. Los resultados reportados son de utilidad para corredores de moneda, administradores de riesgo cambiario, autoridades monetarias, y diseñadores de política financiera. Estudios posteriores deberán incorporar los costos de transacción y las implicaciones fiscales para determinar si existen oportunidades de arbitraje económicamente interesantes en estos mercados

Mexican bank's stocks performance during the banking privatization process (1990-1992)

Doctor of Philosoph

Volatility dependence structure between the Mexican Stock Exchange and the World Capital Market

This paper studies the integration of the Mexican Stock Exchange (MSE) into the World Capital Market (WCM). We detect a long-run equilibrium relationship, despite the effects of structural breaks associated to different financial crises during our period of analysis (1987-2012). The analytical approach begins with the estimation of a bivariate VECM in the mean, including several dummy variables that capture the main crisis episodes that took place during the estimation period. Next, we specify a VARMA-GARCH model with Dynamic Conditional Correlation, and, finally, we fit a Clayton copula to returns, conditional on two volatility regimes (low and high), in order to further understand the nature of their dependence structure. © 2015

Cointegración entre las principales bolsas de Europa continental en presencia de rompimientos estructurales (1999-2014)

El objetivo principal de este trabajo es determinar si existe una relación de convergen - cia de largo plazo entre los cuatro mayores mercados bursátiles de Europa continental y evaluar, al mismo tiempo, el impacto que la volatilidad en uno de ellos tiene sobre el resto. La muestra incluye los mercados de París, Frankfurt, Milán, y Madrid, durante un periodo de importantes cambios en el entorno económico y, en particular, episodios de intensa turbulencia. El enfoque metodológico consiste en la construcción de un modelo capaz de representar los índices bursátiles de los cuatro mercados, para caracterizar su comporta - miento histórico mediante técnicas econométricas. El estudio parte de la confirmación de que el comportamiento en el tiempo de los índices bursátiles estudiados no es estacionario en presencia de rupturas estructurales. Validada la evidencia de raíces unitarias, se lleva a cabo un análisis de cointegración de los logaritmos naturales de los índices estudiados y se demuestra la existencia de, al menos, un vector cointegrante. En seguida, se procedió a modelar el comportamiento de las series a través de un modelo de Vectores de Correc - ción de Errores (VECM), cuyos resultados presentaron problemas de heteroscedasticidad en los residuales, por lo que se recurrió a modelos de la familia GARCH para capturar la complejidad de los factores que determinan ese comportamiento. Efectivamente, una vez incorporado el fenómeno de heteroscedasticidad en el modelado, es posible pasar a la in - terpretación de los coeficientes del modelo y de la relación compartida de largo plazo entre las series. Derechos Reservados©2015 Universidad Nacional Autónoma de México, Facultad de Contaduría y Administración. Este es un artículo de acceso abierto distribuido bajo los términos de la Licencia Creative Commons CC BY-NC-ND 4.0

COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets

We estimated the stock market risk premium during the COVID-19 pandemic with a GARCH-in-Mean (GARCH-M)(1,1) model. The analysis then explored the presence of regime changes using a two-regime Markov-Switching GARCH (MS GARCH)(1,1) model. The sample we used included the stock market indexes of nine countries from three geographical regions, including: North America (Canada, USA, and Mexico), South America (Brazil and Argentina), and Asia (Japan, South Korea, Hong Kong, and Singapore), over two periods: (a) pre-COVID (from 1 January 2015 to 31 December 2019); and (b) COVID (from 1 January 2020 to 31 December 2021). Our GARCH-M(1,1) estimation results indicate that the more developed countries’ stock markets experienced an important increase in their risk premium during the COVID period, likely explained by the massive government anticyclical policies. By contrast, developing countries’ stock markets, particularly in Latin America, experienced a reduction, and in some cases, even a total loss of the risk premium effect. From the perspective of investors and portfolio risk managers, the identification of high and low volatility periods and their estimated probability of occurrence is useful for the characterization of stress scenarios and the design of emerging strategies. For governments and central bankers, the implementation of different policies should respond to the more likely scenarios but should also be prepared to respond to other less likely scenarios. Institutional preparedness to respond to as many different scenarios as may be identified with the use of MS GARCH models can make their interventions more successful. This work presents an objective example of how the use of MS GARCH models may be of use to practitioners in both the financial industry and government. We confirmed that the results of a two-regime MS GARCH model are superior to those obtained from a single-regime model

COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets

We estimated the stock market risk premium during the COVID-19 pandemic with a GARCH-in-Mean (GARCH-M)(1,1) model. The analysis then explored the presence of regime changes using a two-regime Markov-Switching GARCH (MS GARCH)(1,1) model. The sample we used included the stock market indexes of nine countries from three geographical regions, including: North America (Canada, USA, and Mexico), South America (Brazil and Argentina), and Asia (Japan, South Korea, Hong Kong, and Singapore), over two periods: (a) pre-COVID (from 1 January 2015 to 31 December 2019); and (b) COVID (from 1 January 2020 to 31 December 2021). Our GARCH-M(1,1) estimation results indicate that the more developed countries’ stock markets experienced an important increase in their risk premium during the COVID period, likely explained by the massive government anticyclical policies. By contrast, developing countries’ stock markets, particularly in Latin America, experienced a reduction, and in some cases, even a total loss of the risk premium effect. From the perspective of investors and portfolio risk managers, the identification of high and low volatility periods and their estimated probability of occurrence is useful for the characterization of stress scenarios and the design of emerging strategies. For governments and central bankers, the implementation of different policies should respond to the more likely scenarios but should also be prepared to respond to other less likely scenarios. Institutional preparedness to respond to as many different scenarios as may be identified with the use of MS GARCH models can make their interventions more successful. This work presents an objective example of how the use of MS GARCH models may be of use to practitioners in both the financial industry and government. We confirmed that the results of a two-regime MS GARCH model are superior to those obtained from a single-regime model