Kernel density estimation for multivariate data is an important technique that has a wide range of applications in … interest in multivariate kernel density estimation is mainly due to the increased difficulty in deriving an optimal data … bandwidth matrices for multivariate kernel density estimation. Our approach is based on treating the elements of the bandwidth …

We consider the estimation of a large number of GARCH models, say of the order of several hundreds. Especially in the … multivariate case, the number of parameters is extremely large. To reduce this number and render estimation feasible, we regroup …

Abstract In many areas of economic analysis, economic theory restricts the shape as well as other characteristics of … extend and improve upon currently available estimation methods for imposing regularity conditions by imposing regularity on a … conditions in estimation, (b) to provide regularity preserving point estimates, (c) to avoid biases existent in previous …

parameter in a panel autoregressive model to illustrate the consequences of the higher order.terms and the improvement that …

What brings persistence into the macroeconomy? This is one of the big unresolved issues in current macroeconomic theory …