-Gaussian DSGE models by sampling the joint likelihood of parameters and latent states. We show that the gradient-based joint … likelihood sampling approach is superior in efficiency and robustness to standard Metropolis-Hastings samplers by estimating a …

testing for PPP or LOOP, model specification and data sampling should not proceed without consideration of the actual …

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 …