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...

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...

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...

There is an immense body of literature on the relationship of money and output, with result-integrity depending on the aggregates used. This paper proposes an alternative two-step approach, based on the reality that: (1) money creation is just the outcome of new bank loans extended, and (2) 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...

A method for treating Contingent Valuation data obtained from a polychotomous response format designed to accommodate respondent uncertainty is developed. The parameters that determine the probability of indefinite responses are estimated and used to truncate utility distributions within a...

In this paper we propose an estimator for models in which an endogenous dichotomous treatment affects a count outcome in the presence of either sample selection or endogenous participation using maximum simulated likelihood. We allow for the treatment to have an effect on both the sample...

In this paper, we propose a new approach to estimating sample selection models that combines Generalized Tukey Lambda (GTL) distributions with copulas. The GTL distribution is a versatile univariate distribution that permits a wide range of skewness and thick- or thin-tailed behavior in the data...

In spite of the widespread use of generalized additive models (GAMs), there is no well established methodology for simultaneous inference and variable selection for the components of GAM. There is no doubt that both, inference on the marginal component functions and their selection, are...

This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density. The error density is approximated by the kernel density estimator of the unobserved errors, while the regression function...