Multicollinearity hampers empirical econometrics. The remedies proposed to date suffer from pitfalls of their own. The ridge estimator is not generally accepted as a vital alternative to the ordinary least−squares (OLS) estimator because it depends upon unknown parameters. The generalized maximum entropy estimator depends upon subjective exogenous information. This paper presents a novel maximu...

In this paper, we consider the role of “leads” of the first difference of integrated variables in the dynamic OLS estimation of cointegrating regression models. Specifically, we investigate Stock and Watson’s (1993) claim that the role of leads is related to the concept of Granger causality by a Monte Carlo simulation. From the simulation results, we find that the dynamic OLS estimator without ...

We address the problem of assessing the statistical significance of candidate periodicities found using the so-called ‘multi-harmonic’ periodogram, which is being used for detection of non-sinusoidal signals, and is based on the least-squares fitting of truncated Fourier series. The recent investigation (Baluev 2008) made for the LombScargle periodogram is extended to the more general multi-har...

We provide a general valuation approach for capital budgeting decisions involving the modularization in the design of a system. Within the framework developed by Baldwin and Clark (2000), we implement a valuation approach using a numerical procedure based on the Least Squares Monte Carlo method proposed by Longstaff and Schwartz (2001). The approach is accurate, general and flexible.

In this paper new methodologies for clustering and dimensionality reduction of large data sets are illustrated using both a least-squares and maximum likelihood approach. The methodologies are described by both real applications and Monte Carlo simulations.

The performances of the seven different parameter estimation methods for the Gumbel distribution are compared with numerical simulations. Estimation methods used in this study are the method of moments (ME), the method of maximum likelihood (ML), the method of modified maximum likelihood (MML), the method of least squares (LS), the method of weighted least squares (WLS), the method of percentil...

This paper studies inference about the values of the parameters in the threshold model in a generalized method of moments (GMM) framework. First, we establish that the extensively studied least squares method leads to substantially oversized tests and confidence intervals when the coeffi cient change is not large. Second, by re-ordering the data to recast the threshold model as a structural bre...

An algorithm to compute forces at the sea bed from a finite element solution to the mild slope wave equation is devised in this work. The algorithm is best considered as consisting of two logical parts: The first is concerned with the computation of the derivatives to a finite element solution, given the associated mesh; the second is a bi–quadratic least squares fit which serves to model the s...

In this paper we propose a modified Newton-Raphson method to obtain super efficient frequency estimators of sinusoidal signals in presence of stationary noise. It is observed that if we start from an initial estimator with convergence rate Op(n ) and use the NewtonRaphson algorithm with proper step factor modification, then it produces super efficient frequency estimator in the sense it has asy...

This paper provides a valuation algorithm based on Monte Carlo simulation for valuing a wide set of capital budgeting problems with many embedded real options dependent on many state variables. Along the lines of Gamba and Trigeorgis (2002b), we decompose a complex real option problem with many options into a set of simple options, properly taking into account deviations from value additivity d...