In this paper we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts.

A new simple formula is found to correct the underestimation of the standard deviation for total lead time demand when using simple exponential smoothing. This new formula allows one to see readily the significant size of the underestimation of the traditional formula and can easily be...

Let X1,X2,...Xn be i.i.d. N-dimensional random variables having an unknown support of probability density denoted G; we suppose that G belongs to a functional class "g" of compact sets with smooth upper surface called boundary fragments. The problem consists in testing the hypotheses G=Go...

Procedures for estimating a linear single-equation model by means of panel data with errors-in-variables are considered. To eliminate fixed individual heterogeneity, the equation is differenced across one or more than one periods. The differenced equations can be estimated by using as...

This paper takes a computationnaly simple LS approach to develop a more efficient estimation procedure, which we call Residual Augmented Least Square (RALS), than OLS when the errors are not normally distributed. The efficiency gain is from manipulating the higher moment conditions implied by...

The paper proposes new tests for the cointegrating rank of a conditional vector autoregressive process with weakly exogenous variables and a linear time trend. The vovel feature of the applied trend estimation techniques is that they impose the restriction of the cointegrating rank under the...

In this paper the interest is in testing whether a regression function is polynomial of a certain degree. One possible approach to this testing problem is to do a parametric polynomial fit and a nonparametric fit and to reject the null hypothesis of a polynomial function if the distance between...

In this paper we investigate the properties of the Lagrange Multiplier (LM) test for autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliners (AO's). We show analytically that both the asymptotic size and power are adversely...

In this paper we test for (Generalized) AutoRegressive Conditional Heteroskedasticity [(G) ARCH] in daily and weekly data on 22 exchange rates and 13 stock market indices using the standard Lagrange Multiplier [LM] test for GARCH and a new LM test that is resistant to additive outliers. The data...

In some cases the unit root or near unit root behavior of linear autoregressive models fitted to economic time series is not in accordance with the underlying economic theory. To accommodate this feature we consider a threshold autoregressive process with the threshold effect only in the...