This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension is finite and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be...

We propose a new semiparametric procedure for estimating multivariate models with conditioning variables. The semiparametric model is based on the parametric conditional copula and nonparametric conditional marginals. To avoid the curse of dimensionality in the estimation of the latter, we...

This paper proposes Lagrange Multiplier based panel unit root tests allowing for structural breaks through simple extensions of existing group mean and combination tests. The proposed tests are more general than those previously suggested. They consider potential breaks in the intercept, in the...

Neyman and Scott define the incidental-parameter problem. In panel data with $T$ observations per individual, the estimator of the common parameter is usually constistent with O(1/T). This paper shows that the integrated likelihood estimator becomes consistent with O(1/T^2) if an...

Many economic time series are charecterized by high persistence which typically requires nonstandard limit theory for inference. This paper proposes a new method for constructing confidence intervals for the impulse response functions of nearly nonstationary processes. The method is based on...

I consider the problem of detecting and predicting regime switching behaviour in the context of Indian Stock Market data. First I discuss detection of volatility change points using the LRT and the Binary Segmentation procedure of Vostrikova (1981). The detected volatility changes are correlated...