The causal relationships in mean and variance between stock returns and foreign institutional investment in India

This paper examines the causalities in mean and variance between stock returns and Foreign Institutional Investment (FII) in India. The analysis in this paper applies the Cross Correlation Function approach from Cheung and Ng (1996), and uses daily data for the timeframe of January 1999 to March 2008 divided into two periods before and after May 2003. Empirical results showed that there are uni-directional causalities in mean and variance from stock returns to FII flows irrelevant of the sample periods, while the reverse causalities in mean and variance are only found in the period beginning with 2003. These results point to FII flows having exerted an impact on the movement of Indian stock prices during the more recent period.

Impact attribution models to evaluate drought effects: economic impacts, risk analyses and management strategies in Spain and Chile

La sequía es un fenómeno natural que se origina por el descenso de las precipitaciones con respecto a una media, y que resulta en la disponibilidad insuficiente de agua para alguna actividad. La creciente presión que se ha venido ejerciendo sobre los recursos hídricos ha hecho que los impactos de la sequía se hayan visto agravados a la vez que ha desencadenado situaciones de escasez de agua en muchas partes del planeta. Los países con clima mediterráneo son especialmente vulnerables a las sequías, y, su crecimiento económico dependiente del agua da lugar a impactos importantes. Para reducir los impactos de la sequía es necesaria una reducción de la vulnerabilidad a las sequías que viene dada por una gestión más eficiente y por una mejor preparación. Para ello es muy importante disponer de información acerca de los impactos y el alcance de este fenómeno natural. Esta investigación trata de abarcar el tema de los impactos de las sequías, de manera que plantea todos los tipos de impactos que pueden darse y además compara sus efectos en dos países (España y Chile). Para ello se proponen modelos de atribución de impactos que sean capaces de medir las pérdidas económicas causadas por la falta de agua. Los modelos propuestos tienen una base econométrica en la que se incluyen variables clave a la hora de evaluar los impactos como es una variable relacionada con la disponibilidad de agua, y otras de otra naturaleza para distinguir los efectos causados por otras fuentes de variación. Estos modelos se adaptan según la fase del estudio en la que nos encontremos. En primer lugar se miden los impactos directos sobre el regadío y se introduce en el modelo un factor de aleatoriedad para evaluar el riesgo económico de sequía. Esto se hace a dos niveles geográficos (provincial y de Unidad de Demanda Agraria) y además en el último se introduce no solo el riesgo de oferta sino también el riesgo de demanda de agua. La introducción de la perspectiva de riesgo en el modelo da lugar a una herramienta de gestión del riesgo económico que puede ser utilizada para estrategias de planificación. Más adelante una extensión del modelo econométrico se desarrolla para medir los impactos en el sector agrario (impactos directos sobre el regadío y el secano e impactos indirectos sobre la Agro Industria) para ello se adapta el modelo y se calculan elasticidades concatenadas entre la falta de agua y los impactos secundarios. Por último se plantea un modelo econométrico para el caso de estudio en Chile y se evalúa el impacto de las sequías debidas al fenómeno de La Niña. iv Los resultados en general muestran el valor que brinda el conocimiento más preciso acerca de los impactos, ya que en muchas ocasiones se tiende a sobreestimar los daños realmente producidos por la falta de agua. Los impactos indirectos de la sequía confirman su alcance a la vez que son amortiguados a medida que nos acercamos al ámbito macroeconómico. En el caso de Chile, su diferente gestión muestra el papel que juegan el fenómeno de El Niño y La Niña sobre los precios de los principales cultivos del país y sobre el crecimiento del sector. Para reducir las pérdidas y su alcance se deben plantear más medidas de mitigación que centren su esfuerzo en una gestión eficiente del recurso. Además la prevención debe jugar un papel muy importante para reducir los riesgos que pueden sufrirse ante situaciones de escasez. ABSTRACT Drought is a natural phenomenon that originates by the decrease in rainfall in comparison to the average, and that results in water shortages for some activities. The increasing pressure on water resources has augmented the impact of droughts just as water scarcity has become an additional problem in many parts of the planet. Countries with Mediterranean climate are especially vulnerable to drought, and its waterdependent economic growth leads to significant impacts. To reduce the negative impacts it is necessary to deal with drought vulnerability, and to achieve this objective a more efficient management is needed. The availability of information about the impacts and the scope of droughts become highly important. This research attempts to encompass the issue of drought impacts, and therefore it characterizes all impact types that may occur and also compares its effects in two different countries (Spain and Chile). Impact attribution models are proposed in order to measure the economic losses caused by the lack of water. The proposed models are based on econometric approaches and they include key variables for measuring the impacts. Variables related to water availability, crop prices or time trends are included to be able to distinguish the effects caused by any of the possible sources. These models are adapted for each of the parts of the study. First, the direct impacts on irrigation are measured and a source of variability is introduced into the model to assess the economic risk of drought. This is performed at two geographic levels provincial and Agricultural Demand Unit. In the latter, not only the supply risk is considered but also the water demand risk side. The introduction of the risk perspective into the model results in a risk management tool that can be used for planning strategies. Then an extension of the econometric model is developed to measure the impacts on the agricultural sector (direct impacts on irrigated and rainfed productions and indirect impacts on the Agri-food Industry). For this aim the model is adapted and concatenated elasticities between the lack of water and the impacts are estimated. Finally an econometric model is proposed for the Chilean case study to evaluate the impact of droughts, especially caused by El Niño Southern Oscillation. The overall results show the value of knowing better about the precise impacts that often tend to be overestimated. The models allow for measuring accurate impacts due to the lack of water. Indirect impacts of drought confirm their scope while they confirm also its dilution as we approach the macroeconomic variables. In the case of Chile, different management strategies of the country show the role of ENSO phenomena on main crop prices and on economic trends. More mitigation measures focused on efficient resource management are necessary to reduce drought losses. Besides prevention must play an important role to reduce the risks that may be suffered due to shortages.

Servicio de comunicación causal bidirecciional sin contención.

Las arquitecturas jerárquicas de comunicación causal se presentan como una alternativa habitual para reducir el elevado tamaño de la información de control causal a enviar en cada mensaje, cuando la comunicación se realiza entre un subconjunto de procesos que pertenecen a un grupo muy numeroso. Sin embargo, en estas arquitecturas, los nodos intermedios de la jerarquía padecen un efecto indeseable denominado efecto convoy. Estos nodos intermedios tienden a generar ráfagas de envíos que sobrecargan tanto a los nodos de los niveles inferiores de la jerarquía como a la red, provocando pérdidas de mensajes y periodos entre ráfagas de infrautilización de la red. Este artículo presenta un servicio causal bidireccional sin contención que, aplicado a los nodos intermedios de la jerarquía, soluciona el efecto convoy. Este servicio causal sin contención entrega a la capa de aplicación y envía al sistema un mensaje sin esperar la entrega o el envío previo de mensajes que constituyen la historia causal del primero, por lo que evita las ráfagas de entrega y de envío de mensajes. La entrega de un mensaje va acompañada de un identificador causal, que es un número natural que indica el número de orden de ese mensaje en la secuencia causal total. El envío de un mensaje supone construir un vector causal válido a partir de un identiificador causal, que permita ordenar dicho mensaje en orden causal en el proceso receptor.

Using a causal smoothing to improve the performance of an on-line neural network glucose prediction algorithm

This work evaluates a spline-based smoothing method applied to the output of a glucose predictor. Methods:Our on-line prediction algorithm is based on a neural network model (NNM). We trained/validated the NNM with a prediction horizon of 30 minutes using 39/54 profiles of patients monitored with the Guardian® Real-Time continuous glucose monitoring system The NNM output is smoothed by fitting a causal cubic spline. The assessment parameters are the error (RMSE), mean delay (MD) and the high-frequency noise (HFCrms). The HFCrms is the root-mean-square values of the high-frequency components isolated with a zero-delay non-causal filter. HFCrms is 2.90±1.37 (mg/dl) for the original profiles.

B2DI a bayesian BDI agent model with causal belief updating based on MSBN

In this paper, we introduce B2DI model that extends BDI model to perform Bayesian inference under uncertainty. For scalability and flexibility purposes, Multiply Sectioned Bayesian Network (MSBN) technology has been selected and adapted to BDI agent reasoning. A belief update mechanism has been defined for agents, whose belief models are connected by public shared beliefs, and the certainty of these beliefs is updated based on MSBN. The classical BDI agent architecture has been extended in order to manage uncertainty using Bayesian reasoning. The resulting extended model, so-called B2DI, proposes a new control loop. The proposed B2DI model has been evaluated in a network fault diagnosis scenario. The evaluation has compared this model with two previously developed agent models. The evaluation has been carried out with a real testbed diagnosis scenario using JADEX. As a result, the proposed model exhibits significant improvements in the cost and time required to carry out a reliable diagnosis.

Three independent lines of evidence suggest retinoids as causal to schizophrenia

Retinoid dysregulation may be an important factor in the etiology of schizophrenia. This hypothesis is supported by three independent lines of evidence that triangulate on retinoid involvement in schizophrenia: (i) congenital anomalies similar to those caused by retinoid dysfunction are found in schizophrenics and their relatives; (ii) those loci that have been suggestively linked to schizophrenia are also the loci of the genes of the retinoid cascade (convergent loci); and (iii) the transcriptional activation of the dopamine D2 receptor and numerous schizophrenia candidate genes is regulated by retinoic acid. These findings suggest a close causal relationship between retinoids and the underlying pathophysiological defects in schizophrenia. This leads to specific strategies for linkage analyses in schizophrenia. In view of the heterodimeric nature of the retinoid nuclear receptor transcription factors, e.g., retinoid X receptor β at chromosome 6p21.3 and retinoic acid receptor β at 3p24.3, two-locus linkage models incorporating genes of the retinoid cascade and their heterodimeric partners, e.g., peroxisome proliferator-activated receptor α at chromosome 22q12-q13 or nuclear-related receptor 1 at chromosome 2q22-q23, are proposed. New treatment modalities using retinoid analogs to alter the downstream expression of the dopamine receptors and other genes that are targets of retinoid regulation, and that are thought to be involved in schizophrenia, are suggested.

O nexo causal entre crédito rural e crescimento do produto agropecuário na economia brasileira

O nexo causal entre desenvolvimento financeiro e crescimento econômico vem ganhando destaque na literatura desde o início dos anos 1990. As principais linhas teóricas nessa área buscam demonstrar qual a significância da relação e o sentido da causalidade, se houver. Causalidade unidirecional no sentido do desenvolvimento financeiro para o crescimento econômico, bicausalidade entre ambos, e causalidade reversa, no sentido do crescimento para o desenvolvimento financeiro, são as principais hipóteses testadas nas pesquisas empíricas. O presente trabalho de tese tem por objetivo avaliar o nexo causal entre crédito (como um indicador do desenvolvimento financeiro) e crescimento no setor agropecuário brasileiro. O crédito rural como proporção do PIB agropecuário cresceu substancialmente desde meados da década de 90, passando de 15,44% em 1996 para 65,24% em 2014. Ao longo do período 1969-2014, a razão média anual entre crédito rural e PIB agropecuário foi de 43,87%. No mesmo período, o produto agropecuário cresceu em média 3,76% ao ano. Questiona-se se no mercado rural o crédito causa o crescimento agropecuário, se ocorre causalidade reversa ou se se opera a hipótese de bicausalidade. Para avaliar o nexo causal entre essas duas variáveis econômica foram empregados quatro procedimentos metodológicos: teste de causalidade de Granger em uma representação VAR com a abordagem de Toda e Yamamoto, teste de causalidade de Granger em um modelo FMOLS (Fully Modified OLS), teste de causalidade de Granger em um modelo ARDL (Autoregressive-Distributed Lag) e teste de causalidade de Granger no domínio da frequência, com o uso do método de Breitung e Candelon. Os resultados mostram de forma uniforme a presença de causalidade unidirecional do crédito rural para o crescimento do produto agropecuário. Causalidade reversa, no sentido do crescimento agropecuário para o crédito rural, não foi detectada de forma significativa em nenhum dos quatro métodos empregados. A não detecção de bicausalidade pode ser uma evidência do impacto da forte política de subsídio governamental ao crédito rural. A decisão do Governo quanto ao montante anual de crédito rural disponível a taxas de juros subsidiadas pode estar impedindo que o desempenho do setor, medido pela sua taxa de crescimento, exerça uma influência significativa na dinâmica do crédito rural. Os resultados também abrem a possibilidade a testar a hipótese de exogeneidade do crédito rural, o que seria uma extensão direta dos resultados obtidos.

Auto-atribuciones académicas: diferencias de género y curso en estudiantes de educación secundaria

El análisis de las autoatribuciones académicas constituye un aspecto esencial del componente afectivo y emocional de la motivación escolar en estudiantes de educación secundaria obligatoria (ESO). El objetivo de este estudio fue analizar, mediante un diseño transversal, las diferencias de género y curso y el papel predictivo de estas variables en las atribuciones causales académicas de los alumnos medidas a través de las escalas generales de la Sydney Attribution Scale (SAS). El cuestionario fue administrado a 2.022 estudiantes (51.08% chicos) de 1º a 4º de ESO. El rango de edad fue de 12 a 16 años (M = 13.81; DT = 1.35). Los resultados derivados de los análisis de varianza y de los tamaños del efecto (índice d) revelaron que los chicos atribuyeron sus éxitos significativamente más a su capacidad, mientras las chicas los atribuyeron significativamente más al esfuerzo. Respecto a las atribuciones de fracaso escolar, los resultados indicaron que los chicos los atribuyeron significativamente más a la falta de esfuerzo que las chicas. Asimismo, se hallaron diferencias de curso académico en la mayoría de las atribuciones causales analizadas. Los análisis de regresión logística indicaron que el género y el curso fueron predictores significativos de las atribuciones causales académicas, aunque los resultados variaron para cada una de las escalas de la SAS. Los resultados son discutidos en relación a la necesidad de diseñar programas de intervención que tengan en cuenta las variables sexo y curso académico.

Motivational profiles Spanish students of Compulsory Secondary Education: Differential analysis of academic self-attributions

Academic goals and academic self-attributions are relevant variables in school settings. The objective of this study is to identify whether there are combinations of multiple goals that lead to different motivational profiles and to determine whether there are significant differences between the groups obtained regarding causal attributions of success and failure (ability, effort, or external causes) in Mathematics and Language and Literature, and in overall academic performance. The Goal Achievement Tendencies Questionnaire (AGTQ) and the Sydney Attribution Scale (SAS) were administered to a sample of 2022 students of compulsory secondary education, ranging in age from 12 to 16 years (M = 13.81, SD = 1.35). Cluster analysis identified four motivational profiles: a group of students with a high generalized motivation profile, a group of students with low generalized motivation profile, a group of students with predominance of learning goals and achievement goals, and a final group of students with predominance of social reinforcement goals. Results revealed statistically significant differences between the profiles obtained in academic self-attributions.

Using causal maps to support ex-post assessment of social impacts of dams

This paper presents the results of an ex-post assessment of two important dams in Brazil. The study follows the principles of Social Impact Management, which offer a suitable framework for analyzing the complex social transformations triggered by hydroelectric dams. In the implementation of this approach, participative causal maps were used to identify the ex-post social impacts of the Porto Primavera and Rosana dams on the community of Porto Rico, located along the High Paraná River. We found that in the operation of dams there are intermediate causes of a political nature, stemming from decisions based on values and interests not determined by neutral, exclusively technical reasons; and this insight opens up an area of action for managing the negative impacts of dams.

Causal Maps and Indirect Influences Analysis in the Diagnosis of Second-Home Tourism Impacts

This paper proposes a method for diagnosing the impacts of second-home tourism and illustrates it for a Mediterranean Spanish destination. This method proposes the application of network analysis software to the analysis of causal maps in order to create a causal network model based on stakeholder-identified impacts. The main innovation is the analysis of indirect relations in causal maps for the identification of the most influential nodes in the model. The results show that the most influential nodes are of a political nature, which contradicts previous diagnoses identifying technical planning as the ultimate cause of problems.