While correlation measures are used to discern statistical relationships between observed variables in almost all branches of datadriven scientific inquiry, what we are really interested in is the existence of causal dependence. Statistical tests for causality, it turns out, are significantly harder to construct; the difficulty stemming from both philosophical hurdles in making precise the noti...

conclusions our study showed severe neonate indirect hyperbilirubinemia is still prevalence in fars province and ethnic and cultural background of the mothers was more effective than school education in preventing hyperbilirubinemia complication. patients and methods all infants less than 28 days referred due to severe indirect hyperbilirubinemia were included. complete history, physical examin...

This paper develops a minimally supervised approach, based on focused distributional similarity methods and discourse connectives, for identifying of causality relations between events in context. While it has been shown that distributional similarity can help identifying causality, we observe that discourse connectives and the particular discourse relation they evoke in context provide additio...

The traditional linear Granger test has been widely used to examine the linear causality among several time series in bivariate settings as well as multivariate settings. Hiemstra and Jones [19] develop a nonlinear Granger causality test in bivariate settings to investigate the nonlinear causality between stock prices and trading volume. This paper extends their work by developing a non-linear ...

Using a sample of province-level panel data, this paper investigates the Granger causality associations among economic growth (GDP), foreign direct investment (FDI) and CO2 emissions in China. By applying the bootstrap Granger panel causality approach (Kónya, 2006), we consider both cross-sectional dependence and homogeneity of different regions in China. The empirical results support that the ...

As one of the most successful approaches to uncover complex network structures from experimental data, Granger causality has been widely applied to various reverse engineering problems. This chapter first reviews some current developments of Granger causality and then presents the graphical user interface (GUI) to facilitate the application. To make Granger causality more computationally feasib...

Econometric Causality This paper presents the econometric approach to causal modeling. It is motivated by policy problems. New causal parameters are defined and identified to address specific policy problems. Economists embrace a scientific approach to causality and model the preferences and choices of agents to infer subjective (agent) evaluations as well as objective outcomes. Anticipated and...

in this article, we estimate the vertical price transmission through the iranian rice marketing chain by usingmonthly data from march 2000 to february, 2009 and error correction model (ecm).the causality testresults indicate that changes in the producer price clearly led changes in wholesale and retail prices. inproducer-retail and wholesale-retail models, price transmission is asymmetric but i...