This paper describes an empirical investigation into the predictive ability of four credit scoring models as applied to US personal loans. The models tested include the Logit model (LM), the divergence – a discriminant – method (DVM), neural networks (NN), and the generalized additive model...

This paper discusses nonparametric series estimation of integrable cointegration models using Hermite functions. We establish the uniform consistency and asymptotic normality of the series estimator. The Monte Carlo simulation results show that the performance of the estimator is numerically...

This paper develops a cointegrating nonlinear autoregressive distributed lag (NARDL) model in which short- and long-run nonlinearities are introduced via positive and negative partial sum decompositions of the explanatory variables. We demonstrate that the model is estimable by OLS and that...

This paper develops an alternative approach to the widely used Difference-In-Difference (DID) method for evaluating the effects of policy changes. In contrast to the standard approach, we introduce a nonlinear model that permits changes over time in the effect of unobservables (e.g., there may...

Public finance sustainability plays a central role in the stabilization efforts in Latin America. The emphasis on fiscal policy in these countries goes back to the debt crisis of the 1980s, which was associated with large fiscal imbalances. We analyze the sustainability of government debt for a...

One of the important issues in behavioral analysis is that the time consistency property is lost due to the distortion in performance probability. The standard approach in performance optimization, the dynamic programming, fails to work in this area. In this paper, we propose to use an...

Recent empirical work in several economic fields, particularly environmental and energy economics, has adapted the regression discontinuity (RD) framework to applications where time is the running variable and treatment begins at a particular threshold in time. In this guide for practitioners,...

Methods textbooks in sociology and other social sciences routinely recommend the use of the logit or probit model when an outcome variable is binary, an ordered logit or ordered probit when it is ordinal, and a multinomial logit when it has more than two categories. But these methodological...