 Other authors, by contrast, take the causal asymmetry (rather than the initial randomness assumption) to be primary, and argue that the causal asymmetry can then explain, account for, or ground the asymmetry between prevailing initial and final conditions. Thus, Hausman and Woodward (1999) argue that the reason why the values of initial variables characterizing initial states are uncorrelated is that these variables do not have common causes in their past. The causal asymmetry, on this view, is explanatorily prior to the asymmetry between initial and final states. Similarly, Pearl (2009) argues against the view that the initial randomness assumption allows us to derive the causal asymmetry from a non-causal premise that the initial randomness assumption should itself be thought of as a causal assumption. Maudlin (2007: 133) argues that the asymmetry between initial and final conditions is a manifestation of a more fundamental nomic asymmetry, which he however characterizes in strongly causal terms as an asymmetry of later states being nomically produced by or generated from earlier states.