The relationship between inequality, investment, and government expenditure and their impact on economic growth in a panel of countries is empirically analyzed via a fixed effects, semiparametric model. The analysis demonstrates that the marginal impact of inequality on growth is highly nonlinear, and depends critically on both the levels of investment and government expenditure. In the absence...

Parametric nonlinear mixed effects models (NLMEs) are now widely used in biometrical studies, especially in pharmacokinetics research and HIV dynamics models, due to, among other aspects, the computational advances achieved during the last years. However, this kind of models may not be flexible enough for complex longitudinal data analysis. Semiparametric NLMEs (SNMMs) have been proposed by Ke ...

This paper surveys recently developed approaches to analyzing panel data with nonlinear models. We summarize a number of results on estimation of fixed and random effects models in nonlinear modeling frameworks such as discrete choice, count data, duration, censored data, sample selection, stochastic frontier and, generally, models that are nonlinear both in parameters and variables. We show th...

We examine the importance of possible non-random attrition to an econometric model of life cycle labor supply including joint nonlinear taxation of wage and interest incomes and latent heterogeneity. We use a Wald test comparing attriters to nonattriters and variable addition testing based on formal models of attrition. Results from the Panel Study of Income Dynamics are that non-random panel a...

Nonlinear mixed-effects (NLME) models are popular in many longitudinal studies, including human immunodeficiency virus (HIV) viral dynamics, pharmacokinetic analyses, and studies of growth and decay. Generally, the normality of the random effects is a common assumption in NLME models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article...

This paper assesses the existence of a UK ‘wage curve’ to explore the role of regional unemployment in the determination of individual pay. Recent empirical research adheres to the existence of a new empirical law of economics, a stable inverse non-linear relationship between individual pay and the local unemployment rate. Critiques of this research emphasise issues concerning choice of econome...

Aggregate-Level Conditional Status Metrics (ACSMs) describe the status of a group by referencing current performance to expectations given past scores. This paper focuses on seven ACSMs that condition only on past scores, including median Student Growth Percentiles (Betebenner, 2009), aggregated Percentile Ranks of Residuals (Castellano & Ho, 2012) and covariate-adjustment “value-added” models ...

Abstract: Nonlinear models have many applications in different areas such as pharmacokinetics and pharmacodynamics, and random effects are often included to take into account the correlation between observations taken within the same subject. In this context, we propose a bayesian analysis for heavy-tailed nonlinear mixed effects models, which may produce more robust estimates for the parameter...

This paper gives identification and estimation results for marginal effects in nonlinear panel models. We find that linear fixed effects estimators are not consistent, due in part to marginal effects not being identified. We derive bounds for marginal effects and show that they can tighten rapidly as the number of time series observations grows. We also show in numerical calculations that the b...

We present a hierarchical Bayesian model for learning efficient codes of higher-order structure in natural images. The model, a non-linear generalization of independent component analysis, replaces the standard assumption of independence for the joint distribution of coefficients with a distribution that is adapted to the variance structure of the coefficients of an efficient image basis. This ...