In the paper we use the set of models Ω defined in Definition 3 in Section 4. In Section 5.4 we also report findings conditional on the set of models Ω̃. In this online appendix we give the details of the exercise conditional on Ω̃. The motivation for this exercise is the following. The set of models Ω̃ is larger than the set of models Ω. In particular, Ω includes models with one Granger-noncausal...

It is well known that in a vector autoregressive (VAR) model Granger non-causality is characterized by a set of restrictions on the VAR coefficients. This characterization has been derived under the assumption of non-singularity of the covariance matrix of the innovations. This note shows that if this assumption is violated, then the characterization of Granger non-causality in a VAR model fail...

We have prepared an appendix to address the proofs for Proposition 3, Theorems 1 and 2 which we provide in the following sections. For this purpose we will use a few extra notations which we define here. We will use τN (A) for the normalised trace of a square matrix A of order N and we drop N when there is no confusion. In addition, we derive analytic expressions of the VAR model in the last se...

We review, under a historical perspective, the developement of the problem of nonfundamentalness of Moving Average (MA) representations of economic models, starting from the work by Hansen and Sargent [1980]. Nonfundamentalness typically arises when agents’ information space is larger than the econometrican’s one. Therefore it is impossible for the latter to use standard econometric techniques,...

We compare the performance of a subset of CBO’s economic forecasts against that of an unrestricted vector autoregression (VAR) model. We evaluate forecasts of real economic indicators as well as budget-related nominal statistics. We find that under most specifications, the VAR performs competitively with, if slightly worse than, the corresponding CBO forecasts at up to 20 quarters. Therefore, a...

This paper discusses model based inference in a vector autoregressive model for cofractional processes based on the Gaussian likelihood. The model allows the process Xt to be fractional of order d and cofractional of order d−b, that is, there exist vectors β for which βXt is fractional of order d − b. The parameters b and d satisfy either d ≥ b ≥ 1/2, d = b ≥ 1/2, or d = d0 ≥ b ≥ 1/2. We model ...

The main objective is Paralleling Brushless A.C. Generator to Grid system in constant VAR or in PF mode. Presently, the trend is to feed power to Grid from different sources of potential heads. That is available in different valley regions in India for meeting the power demand. Hence, the question of feeding power to national Grid. Power generated from different mini and micro Hydel projects ar...

A dynamic factor VAR model, estimated by MCMC simulation, is employed to assess the relative severity of post-war U.S. recessions. Joint modeling and estimation of all model unknowns yields rank estimates that fully account for parameter uncertainty. A convenient by-product of the simulation approach is a probability distribution of possible recession ranks that (i) accommodates uncertainty abo...

1 Chris Laing, Southampton Institute, Technology Faculty, Southampton, SO14 0YN, UK, [email protected] 2 Alan Robinson, Southampton Institute, Technology Faculty, Southampton, SO14 0YN, UK, [email protected] 3 Graham King, Southampton Institute, Technology Faculty, Southampton, SO14 0YN, UK, [email protected] Abstract  As an increasing higher priority United Kingdo...

In this work we construct a class of locally asymptotically most stringent (in the Le Cam sense) tests for independence between two sets of variables in the VAR models. These tests are based on multivariate ranks of distances and multivariate signs of the observations and are shown to be asymptotically distribution-free under very mild assumptions on the noise, which is obtained by applying a l...