Causation, Laws and Regularities

Abstract

AbstractIn this chapter we explore the connections between on the one hand causal relations and on the other hand strict and less strict laws, i.e., regularities, expressed as correlations and regressions.It is tempting to think that laws and regularities describe general causal relations. They do not. Neither laws nor regularities distinguish between cause and effect, they state relations between quantities only; the causal aspect is connected to the manipulation and this aspect is not represented in formulations of laws and regularities.Non-strict laws, often called ‘regularities’, differ from strict laws in that they are conditioned on ceteris paribus clauses, i.e., unspecified clauses of the form ‘all else the same’. This makes generalisations, i.e., inferences to unobserved situations, difficult.The main points of this chapter are: Laws, strict and non-strict, express relations between quantities, not cause-effect relations. Regularities are expressed by two measures, coefficient of correlation and regression. Inferring causal relations from laws and regularities requires additional information. Having such information one may represent causal relations using directed graphs and/or structural equations.