, this gender-product gap shrinks towards zero. Further, consistent with a sampling bias mechanism, we find that the …

class of indirect inference models. Our smoothing procedure makes use of importance sampling weights in estimation of the … auxiliary model on simulated data. The importance sampling weights are constructed from likelihood contributions implied by the …

effective sample for the American Community Survey (ACS) is much smaller than it was for Census 2000, to which it is being … level of sampling variation and bias due to the smaller sample. This study uses 100% microdata from the 1940 census to … simulate the impact of different sampling rates on estimates of several measures of segregation and to propose and test the …

first characterize the biases in both network statistics and estimates of network effects under non-random sampling …-classical measurement-error problems when applied as regressors. Apart from the sampling rate and the elicitation procedure, these biases … applied to network data collected via both designed and non-designed sampling procedures, does not require one to assume any …