A new theoretical solution to the Behrens-Fisher (BF) problem is developed using empirical likelihood method. The sampling properties of the empirical likelihood ratio (ELR) test for the BF problem are derived using Monte Carlo simulation technique for a wide range of situations. A comparison of...

The empirical likelihood ratio (ELR) test for the problem of testing for normality in a linear regression modell is derived in this paper. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using Monte Carlo simulation. The ELR test has good...

In this paper we derive an empirical likelihood type Wald (ELW)test for the problem testing for structural change in a linear regression model when the variance of error term is not known to be equal across regimes. The sampling properties of the ELW test are analyzed using Monte Carlo...

Using generalizations of Benford’s Law we test for the absence of psychological barriers at various price levels in eBay auctions for professional football tickets. Our empirical results indicate that this hypothesis cannot be rejected.

The Anderson-Darling goodness-of-fit test has a highly skewed and non-standard limit distribution. Various attempts have been made to tabulate the associated critical points, using both theoretical approximations and simulation methods. We show that a standard saddlepoint approximation performs...

A spurious regression model is one in which the dependent and independent variables are non-stationary, but not cointegrated, and the data are not filtered (e.g., by differencing) before the model is estimated. It is well known that in this case the asymptotic behaviour of the least squares...

A “spurious regression” is one in which the time-series variables are non-stationary and independent. It is well-known that in this context the OLS parameter estimates and the R2 converge to functionals of Brownian motions; the “t-ratios” diverge in distribution; and the Durbin-Watson...

Interpreted as an instrumental variables estimator, nonlinear least squares constructs its instruments optimally from the explanatory variables using the nonlinear specification of the regression function. This has implications for the use of GMM estimators in nonlinear regression models,...

We show that the full asymptotic null distribution for Watson’s 2N U statistic, modified for discrete data, can be computed simply and exactly by standard methods. Previous approximate quantiles for the uniform multinomial case are found to be accurate. More extensive quantiles are presented...

Testing for multivariate cointegration when the data exhibit structural breaks is a problem that is encountered frequently in empirical economic analysis. The standard tests must be modified in this situation, and the asymptotic distributions of the test statistics change accordingly. We supply...