AbstractCausation is a macroscopic phenomenon. The temporal asymmetry displayed by causation has no counterpart in the fundamental dynamics of the microscopic world. So causation must somehow emerge from the underlying dynamics, along with other macroscopic phenomena like entropy increase and the arrow of radiation. In this paper I shall offer an account of causation that accounts for this emergence. I shall show how macroscopic events fall into lawlike patterns that are subject to the random influences of microscopic processes. It is the probabilistic independence of these random influences that constitutes these laws as temporally asymmetric and causal. I shall approach these issues by considering ‘causal inference’ techniques that allow causal relations to be inferred from sets of observed correlations. I shall show that these techniques are best explained by a reduction of causation to structures of equations with probabilistically independent exogenous terms. This exogenous probabilistic independence imposes a recursive order on these equations and a consequent distinction between dependent and independent variables that lines up with the temporal asymmetry of causation.