Ratios of parameter estimates are often used in econometric applications. However, the test of these ratios when estimated can cause difficulties since the ratio of asymptotically normally distributed random variables have a Cauchy distribution for which there are no finite moments. This paper...

Instructors and researchers have used the ‘flow' of knowledge (post-test score minus pre-test score) to measure learning in the classroom for the past fifty years. Walstad and Wagner (2016) and Smith and Wagner (2018) move this practice forward by disag- gregating the flow of knowledge and...

This paper develops an alternative approach for demand estimation. Taking willingness to pay as model primitive, it establishes a general and yet analytically simple demand function, and proposes an estimation procedure that uses survey to solicit consumers' willingness to pay with which the...

An explanation of the Dunning-Kruger effect is provided which does not require any psychological explanation, because it is derived as a statistical artefact. This is achieved by specifying a simple statistical model which explicitly takes the (random) boundary constraints into account. This...

The intuition behind linear regression can be difficult for students to grasp particularly without a readily accessible context. This paper uses basketball statistics to demonstrate the purpose of linear regression and to explain how to interpret its results. In particular, the student will...

The problem of multicollinearity in the assessments of coefficients is well established. However, it is rarely researched in the estimations of macroeconomic variables and economic performance of developing countries. Predicatively, it has impacts on the estimations of coefficients that should...

We propose a new methodology for structural estimation of infinite horizon dynamic discrete choice models. We combine the Dynamic Programming (DP) solution algorithm with the Bayesian Markov Chain Monte Carlo algorithm into a single algorithm that solves the DP problem and estimates the...

This study considers heckit-type approximations useful for a number of different trivariate probit models. They are simple to use and have no convergence problems like full maximum likelihood. Simulations show that a heckit and a least squares approximation perform as well as the trivariate...

The performances of alternative two-stage estimators for the endogenous switching regression model with discrete dependent variables are compared, with regard to their usefulness as starting values for maximum likelihood estimation. This is especially important in the presence of large...

The Dichotomous Choice Contingent Valuation Method can be used either in the single or double bound formulation. The former is easier to implement, while the latter is known to be more efficient. We analyse the bias of the ML estimates produced by either model, and the gain in efficiency...