Energy consumption and economic growth revisited in African countries

La investigación bioantropológica en la Argentina fue muy activa tanto en la primera etapa, comienzos del siglo XVII a 1936, como en el período que va desde ese año hasta la actualidad. La primera etapa comienza con los monjes españoles de la época de la Conquista quienes se interesaron por la paleontología. Francisco Javier Muñiz realizó la primera actividad verdaderamente científica y también enseñó al joven Ameghino a excavar y reconocer piezas fósiles. Florentino Ameghino y sus dos hermanos -Carlos y Juan- contribuyeron al desarrollo de la paleontología en América. Otros investigadores destacados fueron: Moreno, Zeballos, Castellanos, Senet y Lehmann-Nitsche, entre otros. El segundo período contó con muchos investigadores en antropología biológica y otras ciencias afines, argentinos y europeos. En particular, hacia 1930 Marelli introdujo los cálculos estadísticos en Antropología y Fernando Pérez descubrió un nuevo sistema de orientación craneal. Posteriormente, Marcellino y Cocilovo introdujeron las primeras técnicas de análisis multivariado en el país, empleadas luego por la Antropología Biológica sudamericana. Estos hallazgos, sumados a la introducción de principios genéticos para interpretar movimientos migratorios, respuestas adaptativas bien diferenciadas y modelos estocásticos sobre asentamientos y migraciones humanas, cumplimentan los avances de la Antropología Biológica en la Argentina en los tiempos modernos. Este artículo intenta describir esa historia.Research in Argentine biological anthropology was very active in both the early period, from the early 18th century to 1936, and the one starting from that point to the present. The former period began with the Spanish monks who arrived during the Conquest and were interested in paleontology. Francisco Javier Muñiz did the first truly scientific activity and also taught young Florentino Ameghino to dig and recognize fossil pieces. Ameghino and his brothers -Carlos and Juan- contributed to the development of paleontology in the Americas. Other well-known researchers were: Moreno, Zeballos, Castellanos, Senet, and Lehmann-Nitsche, among others. The second period had many researchers in Physical Anthropology and several attached sciences, both Argentinian and European. In particular, around 1930 Marelli introduced the statistical calculus in anthropology and Fernando Pérez discovered a new cranial orientation system. Later, Marcellino and Cocilovo introduced the earliest techniques of multivariate analysis known in Argentina, employed for solving many South-American physical anthropological problems afterwards. These findings, along with the introduction of genetic principles for interpreting migratory movements and a number of well differentiated adaptive responses and stochastic models concerning man migration and settlements, fulfilled Argentina’s Physical Anthropology advances in modern times. This article attempts to describe that history.Sociedad Argentina de Antropologí

A Panel Data Analysis

Dans cet article, nous étudions le lien entre le développement financier et la croissance économique. L’étude porte sur un échantillon de 71 pays et couvre la période 1960-2004. Les résultats obtenus à l’aide des méthodes DOLS, FMOLS et de panel vecteur autorégressif à correction d’erreur confirment ceux des travaux précédents sur l’existence d’une causalité bidirectionelle entre la finance et la croissance aussi bien au niveau de l’échantillon global que les différents groupes de pays proposés dans l’étude. En outre, notre étude révèle qu’il y a des différences significatives entre les groupes de pays quand on considère les relations de long et de court terme. Pour les pays à revenu faible ou intermédiaire, il n’y a pas d’évidence en faveur d’une relation de court terme entre la finance et la croissance. Ces pays doivent privilégier des politiques de long terme. Cependant, pour les pays à revenu élevé, la croissance affecte la finance aussi bien à court terme qu’à long terme. • Mot clés: Développement financier; croissance; Causalité en panel; cointegration en panel. • Classification JEL: O11, O16, O33. This paper reassesses causal relationship between financial development and economi

Finance-Growth Link In Oecd Countries: Evidence From Panel Causality And Cointegration Tests

In this paper we employ recently developed panel causality and cointegration techniques to examine the long-run relationship between financial development and economic growth of 25 OECD countries. Three measures of financial deepening and stock markets are respectively used. Our results point out a bidirectional causality between financial development and economic growth and support the point of view that although both banking sector and stock market could be a driving force of economic growth, the effects of the former are more powerful. The banking sector is the main channel through which financial development can affect economic growth. Furthermore, the effect of economic growth on stock market indices is more important compared to banking sector indicators. These results have some policy implications.Special Issue "26th Symposium on Money, Banking and Finance" Guest Editors :Sébastien Galanti and Grégory Levieugeinfo:eu-repo/semantics/publishe

Further evidence on finance-growth causality: A panel data analysis

This paper reassesses the causal relationship between financial development and economic growth. Using recently developed panel methods on a data set of 71 developed and developing countries over the period 1960-2004, our study confirms previous results of a bidirectional causality between finance and growth. In addition, we show significant differences among country groups when considering both long-run and short-run causality. While in low and middle income countries there is no supportive evidence of short-run causality between financial development and economic growth, in high income countries economic growth significantly affects financial development.Financial development Economic growth Panel causality Panel cointegration

Finance-Growth Link In Oecd Countries: Evidence From Panel Causality And Cointegration Tests

In this paper we employ recently developed panel causality and cointegration techniques to examine the long-run relationship between financial development and economic growth of 25 OECD countries. Three measures of financial deepening and stock markets are respectively used. Our results point out a bidirectional causality between financial development and economic growth and support the point of view that although both banking sector and stock market could be a driving force of economic growth, the effects of the former are more powerful. The banking sector is the main channel through which financial development can affect economic growth. Furthermore, the effect of economic growth on stock market indices is more important compared to banking sector indicators. These results have some policy implications.Financial development; Economic growth; Panel causality; Panel cointegration

The Feldstein-Horioka puzzle in African countries: A panel cointegration analysis

This paper investigates the Feldstein-Horioka coefficients for 37 African countries using the recently developed Pooled Mean Group (PMG), Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS) panel cointegration techniques. The empirical findings reported in this paper reveal that savings and investment are non-stationary and cointegrated series. The estimated coefficients using FMOLS, DOLS, and PMG are 0.38, 0.58, and 0.36, respectively, for the sample as a whole for the period from 1970 to 2006. These results confirm previous studies' findings that capital was relatively mobile in African countries compared to OECD countries. In addition, our study shows that there are marked differences in savings retention coefficients for different country groups in Africa (CFA franc zone and non-CFA franc zone countries, oil-producing and non-oil-producing countries, civil law and common law countries). These results have some policy implications.Africa Feldstein-Horioka coefficient Panel unit root test Panel cointegration Pooled Mean Group estimator