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This paper contains the R-code and output for all experiments of partial derivative estimation using NNS, np, and OLS …
Persistent link: https://www.econbiz.de/10012824663
from multivariate partial derivative estimates using nonlinear non-parametric regressions in a finite difference method …
Persistent link: https://www.econbiz.de/10012824721
The weighted Average Quantile Derivative (AQD) is the expected value of the partial derivative of the conditional … by researchers and the density function of the covariates that is parallel to the average mean derivative in Powell …
Persistent link: https://www.econbiz.de/10014114113
This paper makes several important contributions to the literature about nonparametric instrumental variables (NPIV) estimation and inference on a structural function h0 and its functionals. First, we derive sup-norm convergence rates for computationally simple sieve NPIV (series 2SLS)...
Persistent link: https://www.econbiz.de/10011596624
For typical sample sizes occurring in economic and financial applications, the squared bias of estimators for the memory parameter is small relative to the variance. Smoothing is therefore a suitable way to improve the performance in terms of the mean squared error. However, in an analysis of...
Persistent link: https://www.econbiz.de/10012312096
This paper makes several important contributions to the literature about non- parametric instrumental variables (NPIV ) estimation and inference on a structural function h 0 and functionals of h 0 .First,wederivesup-normconvergence rates for computationally simple sieve NPIV (series two-stage...
Persistent link: https://www.econbiz.de/10011884399
We augment the usual regression discontinuity design model by considering an endogenously chosen cutoff, perhaps chosen to maximize certain criterion that the treatment provider has. This regime faces the challenge that, conditional on realization of the cutoff, observations are no longer...
Persistent link: https://www.econbiz.de/10012845190
In this paper we propose an alternative and modified Generalized Regression Neural Networks Autoregressive model (GRNN-AR) in S&P 500 and FTSE 100 index returns, as also in Gross domestic product growth rate of Italy, USA and UK. We compare the forecasts with Generalized Autoregressive...
Persistent link: https://www.econbiz.de/10013126947
In this paper we present a very brief description of least mean square algorithm with applications in time-series analysis of economic and financial time series. We present some numerical applications; forecasts for the Gross Domestic Product growth rate of UK and Italy, forecasts for S&P 500...
Persistent link: https://www.econbiz.de/10013138755
In this paper we examine feed-forward neural networks using genetic algorithms in the training process instead of error backpropagation algorithm. Additionally real encoding is preferred to binary encoding as it is more appropriate to find the optimum weights. We use learning and momentum rates...
Persistent link: https://www.econbiz.de/10013138757