This study focuses on the shape optimization of concrete gravity dams considering dam–water–foundation interaction and nonlinear effects subject to earthquake. The concrete gravity dam is considered as a two–dimensional structure involving the geometry and material nonlinearity effects. For the description of the nonlinear behavior of concrete material under earthquake loads, the Drucker–Prager...

Fixed effects estimators of nonlinear panel models can be severely biased due to the incidental parameters problem. In this paper I find that the most important component of this incidental parameters bias for probit fixed effects estimators of index coefficients is proportional to the true value of these coefficients, using a large-T expansion of the bias. This result allows me to derive a low...

Data analysis in FMRI could be performed in one grand multilevel model that incorporates both withinand cross-subjects variabilities. However, it is due to the presence of both variance components that such a nonlinear model makes computation currently impractical, forcing analysts to adopt a two-stage approach: individual analysis with a time series regression model that explores activations i...

In a predictive model, what is the expected difference in the outcome associated with a unit difference in one of the inputs? In a linear regression model without interactions, this average predictive comparison is simply a regression coefficient (with associated uncertainty). In a model with nonlinearity or interactions, however, the average predictive comparison in general depends on the valu...

This article examines the multilevel linear crossed random effects growth model for estimating teacher and school effects from repeated measurements of student achievement. Results suggest that even a small degree of unmodeled nonlinearity can result in a substantial upward bias in the magnitude of the teacher effect, which raises concerns about its appropriateness for estimating teacher effect...

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...

Since its inception and subsequent diffusion, the Internet has been lauded as a potent democratizing agent. Using macro-level panel data from 1994 to 2003, this study examined 152 countries and found that increased Internet diffusion was a meaningful predictor of more democratic regimes. This was shown to be most true in developed countries, where non-linear fixed effects regression models show...

We propose a new approach to the semiparametric analysis of multinomial choice models with fixed effects and a group (or panel) structure. A traditional random utility framework is employed, and the key assumption is a group homogeneity condition on the disturbances. This assumption places no restrictions on either the joint distribution of the disturbances across choices or their within group ...