correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also … deerived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation … conditional LM tests when spatial correlation or heteroskedasticity is present. …

homoskedasticity against the alternative of heteroskedasticity in both error components. It contrasts this joint LM test with marginal … LM tests that ignore the heteroskedasticity in one of the error components. Monte Carlo results show that misleading … inference can occur when using marginal rather than joint tests when heteroskedasticity is present in both components. …

correlation, as well as a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context … alternatives, have good size and power under various forms of heteroskedasticity including exponential and quadratic functional …

) heteroskedasticity and nonlinearity in the relation between the error-ridden covariate and another, error-free, covariate in the equation …

We present a new genuine jackknife estimator for instrumental variable inference with unknown heteroskedasticity. It …

allowance for heteroskedasticity is generally important. The solution is a Fuller (1977) like estimator and standard errors that … are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high asymptotic … homoskedasticity, and have much lower bias and dispersion under heteroskedasticity, in nearly all cases considered. …

-alone test procedures for heteroskedasticity, overidentification, and endogeneity in the IV context are also described. …