Large Time-Varying Parameter Vars: A Non-Parametric Approach

Estimating overidentied, non-recursive, time varying coe¢ cients structural VARs

This paper provides a general procedure to estimate structural VARs. The algorithm can be used in constant or time varying coe¢ cient models, and in the latter case, the law of motion of the coe¢ cients can be linear or non-linear. It can deal in a uni…ed way with just-identi…ed (recursive or non-recursive) or overidenti…ed systems where identi…cation restrictions are of linear or of nonlinear ...

Estimating Overidentified, Nonrecursive Time-Varying Coefficients Structural VARs

This paper provides a method to estimate time varying coe¢ cients structural VARs which are non-recursive and potentially overidenti…ed. The procedure allows for linear and non-linear restrictions on the parameters, maintains the multi-move structure of standard algorithms and can be used to estimate structural models with di¤erent identi…cation restrictions. We study the transmission of moneta...

International Interest Rate Linkages: a Time Varying Parameter Approach

This paper examines the issue of state contingency in interest rate linkages across the G7 economies by employing Kalman (1960,1963) filter techniques to estimate time varying parameter models of bilateral dependence. Our results show that there is convincing evidence that international linkages in interest rates vary considerably over time. There are periods when international interest rate mo...

On - line appendix to " Estimating overidenti ed , non - recursive , time varying coe ¢ cients structural VARs

A new non-parametric approach for suppliers selection

In this paper we propose a simple non-parametric model for multiple crite-ria supplier selection problem. The proposed model does not generate a zeroweight for a certain criterion and ranks the suppliers without solving the modeln times (one linear programming (LP) for each supplier) and therefore allowsthe manager to get faster results. The methodology is illustrated using anexample.