The quaids ado files written by Brian Poi provide a good template for constructing alternative ado files for maximum likelihood estimation of demand systems. I describe how I used the template to construct ado files to estimate a five commodity almost ideal demand system with demographic...

In this talk, I will review dynamic panel-data analysis and how to perform it using Stata. I also cover static models with predetermined variables. For each model discussed, I review the econometrics and then show how to perform the estimation using Stata.

Many of us, at some point, have received a comment from a member of the audience, a reviewer, or an advisor who thinks the technique used is bad/biased/evil and who knows of some new fancy method that solves the problem. In those cases, you often want to know two things: 1) How big is the...

Finite mixture models provide a natural way of modeling continuous or discrete outcomes that are observed from populations consisting of a finite number of homogeneous subpopulations. Applications of finite mixture models are abundant in the social and behavioral sciences, biological and...

A typical formulation for a linear mixed model is Y = X(be) + Z(u) where (be) is a vector of "fixed" parameters, (u) is a vector of "random effects", and X and Z are matrices whose columns consist of design variables and/or covariates. In many applications the variances of the random effects...

In this talk, I will provide a quick introduction to estimators for the parameters of spatial-autoregressive models and a quick introduction to a suite of user-written Stata commands for managing spatial data and parameter estimation.

In this presentation, I will review the bootstrap for complex surveys with designs featuring stratification, clustering, and unequal probability weights. I will present the Stata module bsweights, which creates the bootstrap weights for designs specified through and supported by svy. I will also...

Users of –logit- or –logistic- occasionally encounter instances in which one or more predictors perfectly predict one or both outcomes (a condition called separation), or in which some outcomes are completely determined (quasicomplete separation). Finite maximum likelihood estimates do not...

We have previously demonstrated Stata implementation of bivariate ramdom effects meta-analysis of the sensitivity and specificity of a single binary diagnostic test by means of the midas module (Dwamena NASUG2007; Dwamena WCSUG 2007). In this presentation we extend our work to paired-comparison...

This research examines the effects of mothers' welfare and work decisions on their children's attainments using two types of estimation methods in Stata: (1) an instrumental variables (IV) and (2) a nonlinear simultaneous equation estimation. The estimator employs sibling comparisons in a random...