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CAUSALITY

Necessary condition, Sufficient condition

Causality is relationship between two variables such that one (the independent variable) can be claimed to have caused the other (the dependent variable). In order to establish causality there must be a correlation or association between variables, the independent variable (the cause) must occur before the dependent variable (the effect) and the relationship must not be spurious.

Causality in Social Network Analysis - PATRICK DOREIAN, University of Pittsburgh 
Sociological Methods & Research, Vol. 30, No. 1, 81-114 (2001)

The role that causality can play in social network analysis is unclear. The author provides a broad characterization of social network analysis before considering the nature of causality. He distinguishes four types of causality: system causality, statistical causality, mechanism causality, and algorithmic causality. Their potential places in network analysis are discussed.

Understanding generative mechanisms, be they system, mechanism, or algorithmic, seems the most promising way to proceed. The role of statistical causality is a source of potential data analytic tools that can be mobilized within analyses conducted in the spirit of the other three types of causality.

A Comparison of Causality Tests Applied to the Bilateral Relationship between Consumption and GDP in the USA and Mexico - Guisan, M.Carmen, M. Carmen Guisan 
Abstract: This article compares several methodologies for analysing unidirectional and bi-directional causality between Consumption and GDP in the USA, Mexico and other countries during the period 1960-2000. Bilateral causality is analysed comparing Grangerīs test, a modified version of Grangerīs test here suggested, TSLS, Hausmanīs causality test and other approaches. The main conclusion is that the modified version of Grangerīs test performs rather well and that Hausmanīs test is very often useful for reinforcing the conclusions of multiple equations models with contemporaneous interdependence. Regarding the bilateral relationship between Consumption and GDP we conclude that there is a moderate degree of contemporaneous relation, with a high degree of dependence of Private Consumption on GDP and a lower dependence in the case of the reverse relation, because GDP is more dependent on supply side conditions than on demand side. This result is relevant for economic policies in less developed countries where very often emphasis is made more in the reverse relations than in the main ones.

An Action-Related Theory of Causality 
Donald Gillies, Department of Philosophy, King's College London
The paper begins with a discussion of Russell's view that the notion of cause is unnecessary for science and can therefore be eliminated. It is argued that this is true for theoretical physics but untrue for medicine, where the notion of cause plays a central role. Medical theories are closely connected with practical action (attempts to cure and prevent disease), whereas theoretical physics is more remote from applications. This suggests the view that causal laws are appropriate in a context where there is a close connection to action. This leads to a development of an action-related theory of causality which is similar to the agency theory of Menzies and Price, but differs from it in a number of respects, one of which is the following. Menzies and Price connect ‘A causes B’ with an action to produce B by instantiating A, but, particularly in the case of medicine, the law can also be linked to the action of trying to avoid B by ensuring that A is not instantiated. The action-related theory has in common with the agency theory of Menzies and Price the ability to explain causal asymmetry in a simple fashion, but the introduction of avoidance actions together with some ideas taken from Russell enable some of the objections to agency accounts of causality to be met. 
Introduction 
Russell on causality 
Preliminary exposition of the action-related theory 
Differences between the action-related theory and the agency theory of Menzies and Price 
Explanation of causal asymmetry 
Objections to the action-related theory 
Extension of the theory to the indeterminate case

The Causality Between Corruption, Poverty and Growth: a Panel Data Analysis
By: Felix Fofana N’ZUE and Coffi Jose Francis N’GUESSAN
Abstract: The main purpose of this study was to shed more light on the links between corruption, poverty and growth based on the notion of causality in the context of panel data. The study aims specifically at: i) determining whether corruption causes growth or vice-versa; ii) determining whether poverty causes growth or vice-versa; or iii) whether it is the combine effect of corruption and poverty that causes growth. The link between corruption, poverty and growth was analyzed in a panel of 18 African countries for the 1996-2001 time periods.
Indicators of poverty and corruption were identified and tests of the causal relationship between these variables were conducted using panel data analysis. The empirical results suggest that: 1) it is poverty that causes growth but not the other way around. This implies that past information of the state of human development help improve prediction on growth, 2) it is the state of growth that causes corruption and inequality; 3) It is corruption that causes inequality; 4) corruption and poverty together cause growth, 5) poverty and growth together cause corruption; 6) and lastly, inequality together with growth cause corruption. 

Procyclicality or Reverse Causality?
Very Preliminary, Dany Jaimovich, Ugo Panizza
Abstract: There is a large literature showing that fiscal policy is either acyclical or countercyclical in industrial countries and procyclical in developing countries. Most of this literature is based on OLS regressions that focus on the correlation between a fiscal variable (usually the budget balance or expenditure growth) and either GDP growth or some measure of output gap. In this paper, we argue that this methodology does not allow to identify the causal effect of the business cycle on fiscal policy and hence cannot be used to estimate policy reaction functions. We propose a new instrument for GDP growth and show that, once GDP growth is properly instrumented, procyclicality tends to disappear.