For an example of a DREP model of poverty dynamics in Germany extended to allow for feedback effects on household composition and labour force participation, see Biewen (2009). Biewen (2009: Table IV) reports that the estimate of the APE for lagged poverty status from the extended model is roughly half that of the corresponding APE for the basic DREP model (0.31 compared to 0.61). Thus, different assumptions can make a substantial difference to the estimates. However, fitting DREP models that incorporate feedback effects is difficult, especially since software modules to fit them are not widely available and, in any case, identification of model parameters is hampered by a lack of plausible instruments. Getting definitions right is important not only for intrinsic validity, but because having different definitions in different studies hampers cross-study comparisons of estimates. Additional empirical issues that may have an impact are the length of the panel, whether the panel is ‘balanced’ (i.e. whether all individuals in the sample are observed in each time period), and sample dropout.