… for jointly estimating the distribution of unobservables, and the structural parameters of the
… This paper demonstrated the sensitivity of parameter estimates obtained from econometric …

… parameter estimates. To ensure consistency of the results, the … Biogeme estimates and
conditional parameter estimates … distribution, which is only implemented with some parameter …

… Even in fitting the standard model to simulated data generated from the standard model,
there can be biases in parameter estimates, especially when there are limited numbers of …

… We consider testing distributional assumptions by using … that are robust against parameter
estimation error uncertainty in … by testing the Student distributional assumption of T-GARCH …

… Here we address several general questions about the robustness of LMMs to violations of
distributional assumptions at each level of a model. We focus on parameter estimates, ie the …

… procedure directed towards determining departures from assumptions concerning distributional
shape. Specifically we consider the usefulness of estimates of the distribu tion function of …

… We iterate this process until the end of the dataset for a total of 35 parameter estimates and
700 one-step ahead forecasts. Table A1 in Appendix B reports the complete list of windows …

… 2.3 Distributional Assumptions and Estimation As noted in the introduction, the properties
of the parameter estimates can be sensitive to the distributional assumptions. Various …

… parameter estimates, right through to parameter estimates fundamentally losing their intended
1 By “distributional assumption” we mean an assumption … , or multivariate distribution of …

… for X i (or test alternate distributions), (iii) estimating distribution parameters (eg, mean
and standard deviation in case of normality) for X i . The cardinality of the various X i can be …