Structural response and input identification

Three major goals were delineated: (1) to develop a general method for determining the response of a structure to combined base and acoustic random excitation: (2) to develop parametric relationships to aid in the design of plates which are subjected to random force or random base excitation: (3) to develop a method to identify the individual acoustic and base input to a structure with only a limited number of measurement channels, when both types of excitation act simultaneously

Identifying asymmetric, multi-period Euler equations estimated by non-linear IV/GMM

In this article, the identification of instrumental variables and generalized method of moment (GMM) estimators with multi-period perceptions is discussed. The state space representation delivers a conventional first order condition that is solved for expectations when the Generalized Bézout Theorem holds. Here, it is shown that although weak instruments may be enough to identify the parameters of a linearized version of the Quasi-Reduced Form (Q-RF), their existence is not sufficient for the identification of the structural model. Necessary and sufficient conditions for local identification of the Quasi-Structural Form (Q-SF) derive from the product of the data moments and the Jacobian. Satisfaction of the moment condition alone is only necessary for local and global identification of the Q-SF parameters. While the conditions necessary and sufficient for local identification of the Q-SF parameters are only necessary to identify the expectational model that satisfies the regular solution. If the conditions required for the decomposition associated with the Generalized Bézout Theorem are not satisfied, then limited information estimates of the Q-SF are not consistent with the full solution. The Structural Form (SF) is not identified in the fundamental sense that the Q-SF parameters are not based on a forward looking expectational model. This suggests that expectations are derived from a forward looking model or survey data used to replace estimated expectations

Econometric Analysis of Structural Systems with Permanent and Transitory Shocks

This paper considers the implications of the permanent/transitory decomposition of shocks for identification of structural models in the general case where the model might contain more than one permanent structural shock. It provides a simple and intuitive generalization of the influential work of Blanchard and Quah (1989), and shows that structural equations with known permanent shocks can not contain error correction terms, thereby freeing up the latter to be used as instruments in estimating their parameters. The approach is illustrated by a re-examination of the identification schemes used by Wickens and Motto (2001), Shapiro and Watson (1988), King, Plosser, Stock, Watson (1991), Gali (1992, 1999) and Fisher (2006).Permanent shocks; structural identification; error correction models; IS-LM models

Design of non-linear filter in the problem of structural identification of biomedical signals with locally concentrated properties

In this paper we propose a generalized method of structural identification of biomedical signals with locally concentrated properties using a digital non-linear filter. The experimental verification of the detecting function was performed by using different ways to describe the model of the desired class of structural elements

Comment to "Weak instruments robust tests in GMM and the New Keynesian Phillips curve" by Frank Kleibergen and Sophocles Mavroeidis

I discuss the identifiability of a structural New Keynesian Phillips curve when it is embedded in a small scale dynamic stochastic general equilibrium model. Identification problems emerge because not all the structural parameters are recoverable from the semi-structural ones and because the objective functions I consider are poorly behaved. The solution and the moment mappings are responsible for the problems.Identification, DSGE models, New Keynesian Phillips curve, Identification robust estimation methods

Nonparametric Identification and Estimation of Nonadditive Hedonic Models

This paper studies the identification and estimation of preferences and technologies in equilibrium hedonic models. In it, we identify nonparametric structural relationships with nonadditive heterogeneity. We determine what features of hedonic models can be identified from equilibrium observations in a single market under weak assumptions about the available information. We then consider use of additional information about structural functions and heterogeneity distributions. Separability conditions facilitate identification of consumer marginal utility and firm marginal product functions. We also consider how identification is facilitated using multimarket data.hedonic models, hedonic equilibrium, nonadditive models, identification, non-parametric estimation

CSI sensing and control: Analytical and experimental results

Recent work on structural identification and large-angle maneuvers with vibration suppression was presented. The recent work has sought to balance structural and controls analysis activities by involving the analysts directly in the validation and experimental aspects of the research. Some new sensing, actuation, system identification, and control concepts were successfully implemented. An overview of these results is given