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Nonlinear models of disability and age applied to census data

Albarran, I.; Alonso, P. J.; Marin, J. M. - In: Journal of Applied Statistics 38 (2011) 10, pp. 2151-2163

more the level of disability he/she suffers. However, empirical evidence shows that this assessment is not always true, or … at least, it is not true in the Spanish population. The study tries to assess the impact of age on disability in Spain … the idea that the relationship among age and the intensity of disability is not always direct. One of the concluding …

Persistent link: https://www.econbiz.de/10009279031

Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off

PERRON, Benoît - Département de Sciences Économiques, Université de … - 1999

Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between...

Persistent link: https://www.econbiz.de/10005133197

Returns to scale, productivity and efficiency in US banking (1989-2000): the neural distance function revisited

Michaelides, Panayotis G.; Vouldis, Angelos T.; … - Bank of Greece - 2011

Productivity and efficiency analyses have been indispensable tools for evaluating firms’ performance in the banking sector. In this context, the use of Artificial Neural Networks (ANNs) has been recently proposed in order to obtain a globally flexible functional form which is capable of...

Persistent link: https://www.econbiz.de/10009141702

Returns to scale, productivity and efficiency in US banking (1989-2000) : the neural distance function revisited

Michaelides, Panagiotis G.; Vouldis, Angelos T.; … - 2022

Persistent link: https://www.econbiz.de/10014080274

Mean-Variance and Mean-Variance-Correlation Neural Network Regression Models

Gabrielli, Andrea - 2019

We introduce two neural network models designed for application in statistical learning. The mean-variance neural network regression model allows us to simultaneously model the mean and the variance of a response variable. In case of a two-dimensional response vector, the...

Persistent link: https://www.econbiz.de/10014104671

Neural Network Embedding of the Over-Dispersed Poisson Reserving Model

Gabrielli, Andrea - 2018

The main idea of this paper is to embed a classical actuarial regression model into a neural network architecture. This nesting allows us to learn model structure beyond the classical actuarial regression model if we use as starting point of the neural network calibration exactly the classical...

Persistent link: https://www.econbiz.de/10012907645

A Neural Network Boosted Double Over-Dispersed Poisson Claims Reserving Model

Gabrielli, Andrea - 2019

We present an actuarial loss reserving technique that takes into account both claim counts and claim amounts. Separate (over-dispersed) Poisson models for the claim counts and the claim amounts are combined by a joint embedding into a neural network architecture. As starting point of the neural...

Persistent link: https://www.econbiz.de/10012889273

Tackling large outliers in macroeconomic data with vector artificial neural network autoregression

Polito, Vito; Zhang, Yunyi - 2021

We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure...

Persistent link: https://www.econbiz.de/10012668293

Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression

Polito, Vito; Zhang, Yunyi - 2021

Persistent link: https://www.econbiz.de/10013314694

Estimating nonlinear heterogeneous agents models with neural networks

Kase, Hanno; Melosi, Leonardo; Rottner, Matthias - 2022

Economists typically make simplifying assumptions to make the solution and estimation of their highly complex models feasible. These simplifications include approximating the true nonlinear dynamics of the model, disregarding aggregate uncertainty or assuming that all agents are identical. While...

Persistent link: https://www.econbiz.de/10013257224