Sociology Index


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 must occur before the dependent variable 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. Bilateral causality is analysed comparing Granger's test, Hausman's causality test. The main conclusion is that the modified version of Granger's test performs well and that Hausman's test is useful for reinforcing the conclusions of multiple equations models with contemporaneous interdependence.

An Action-Related Theory of Causality 
Donald Gillies, Department of Philosophy, King's College London
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. 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 enable some of the objections to agency accounts of causality to be met.

The Causality Between Corruption, Poverty and Growth: a Panel Data Analysis
By: Felix Fofana N’ZUE and Coffi Jose Francis N’GUESSAN.
To shed more light on the links between corruption, poverty and growth based on the notion of causality in the context of panel data. Indicators of poverty and corruption were identified and tests of the causal relationship between these variables were conducted using panel data analysis. The empirical evidence results suggest that, it is poverty that causes growth but not the other way around, it is the state of growth that causes corruption and inequality, it is corruption that causes inequality, corruption and poverty together cause growth, poverty and growth together cause corruption, and inequality together with growth cause corruption. 

Procyclicality or Reverse Causality? - Very Preliminary, Dany Jaimovich, Ugo Panizza.
Most of this literature is based on OLS regressions that focus on the correlation between a fiscal variable. We argue that this methodology does not allow to identify the causal effect of the business cycle on fiscal policy and cannot be used to estimate policy reaction functions.