Unexploited Connections Between Intra- and Inter-temporal Allocation

This paper shows that a power utility specification of preferences over total expenditure (ie. CRRA preferences) implies that intratemporal demands are in the PIGL/PIGLOG class. This class generates (at most) rank two demand systems and we can test the validity of power utility on cross-section data. Further, if we maintain the assumption of power utility, and within period preferences are not homothetic, then the intertemporal preference parameter is identified by the curvature of Engel curves. Under the power utility assumption, neither Euler equation estimation nor structural consumption function estimation is necessary to identify the power parameter. In our empirical work, we use demand data to estimate the power utility parameter and to test the assumption of the power utility representation. We find estimates of the power parameter larger than obtained from Euler equation estimation, but we reject the power specification of within period utility.elasticity of intertemporal substitution, Euler equation estimation, demand systems

Unexploited Connections Between Intra- and Inter-temporal Allocation

This paper shows that a power utility specification of preferences over total expenditure (ie. CRRA preferences) implies that intratemporal demands are in the PIGL/PIGLOG class. This class generates (at most) rank two demand systems and we can test the validity of power utility on cross-section data. Further, if we maintain the assumption of power utility, and within period preferences are not homothetic, then the intertemporal preference parameter is identified by the curvature of Engel curves. Under the power utility assumption, neither Euler equation estimation nor structural consumption function estimation is necessary to identify the power parameter. In our empirical work, we use demand data to estimate the power utility parameter and to test the assumption of the power utility representation. We find estimates of the power parameter larger than obtained from Euler equation estimation, but we reject the power specification of within period utility.elasticity of intertemporal substitution, Euler equation estimation, demand systems

Is the elasticity of intertemporal substitution constant?

This paper shows that a power utility specification of preferences over total expenditure (ie. CRRA preferences) implies that intratemporal demands are in the PIGL/PIGLOG class. This class generates (at most) rank two demand systems and we can test the validity of power utility on cross-section data. Further, if we maintain the assumption of power utility, and within period preferences are not homothetic, then the intertemporal preference parameter is identified by the curvature of Engel curves. Under the power utility assumption, neither Euler equation estimation nor structural consumption function estimation is necessary to identify the power parameter. In our empirical work, we use demand data to estimate the power utility parameter and to test the assumption of the power utility representation. We find estimates of the power parameter larger than obtained from Euler equation estimation, but we reject the power specification of within period utility.Elasticity of intertemporal substitution, Euler equation estimation, demand systems

Unexploited Connections Between Intra- and Inter-temporal Allocation

This paper shows that a power utility specification of preferences over total expenditure (ie. CRRA preferences) implies that intratemporal demands are in the PIGL/PIGLOG class. This class generates (at most) rank two demand systems and we can test the validity of power utility on cross-section data. Further, if we maintain the assumption of power utility, and within period preferences are not homothetic, then the intertemporal preference parameter is identified by the curvature of Engel curves. Under the power utility assumption, neither Euler equation estimation nor structural consumption function estimation is necessary to identify the power parameter. In our empirical work, we use demand data to estimate the power utility parameter and to test the assumption of the power utility representation. We .nd estimates of the power parameter larger than obtained from Euler equation estimation, but we reject the power specification of within period utility

Development of a structural parameter estimation program for finite element model updating

The condition of America\u27s infrastructure is highlighted by major collapses and overcrowded roadways remind us that our infrastructure is aging and in need of effective maintenance. The American Society of Civil Engineers report card for 2009 graded the nation\u27s bridges as a C. In this period of renovation, rebuilding and limited funding, it is important to use the latest technologies to help make America\u27s roadways safe and establish efficient management protocols. This research develops a program for the purpose of pairing structural health monitoring systems with the power of structural modeling, for the use of model updating and parameter estimation, can help to create a smarter and more efficient method of bridge health monitoring and management. A current and accurate analytical bridge model can help owners assess structural needs as they arise. A first step towards this goal is the creation of a program that utilizes field measurements, bridge inspection reports, analytical structural modeling and the powerful computer based structural model updating methods for bridge condition assessment

Identifiability of generalised Randles circuit models

The Randles circuit (including a parallel resistor and capacitor in series with another resistor) and its generalised topology have widely been employed in electrochemical energy storage systems such as batteries, fuel cells and supercapacitors, also in biomedical engineering, for example, to model the electrode-tissue interface in electroencephalography and baroreceptor dynamics. This paper studies identifiability of generalised Randles circuit models, that is, whether the model parameters can be estimated uniquely from the input-output data. It is shown that generalised Randles circuit models are structurally locally identifiable. The condition that makes the model structure globally identifiable is then discussed. Finally, the estimation accuracy is evaluated through extensive simulations

A comparison between tests for changes in the adjustment coefficients in cointegrated systems

In this paper we examine several approaches to detecting changes in the adjustment coefficients in cointegrated VARs. We adopt recursive and rolling techniques as mis-specification tests for the detection of non-constancy and the estimation of the breakpoints. We find that inspection of the recursive eigenvalues is not useful to detect a break in the adjustment coefficients, whilst recursive estimation of the coefficients can only indicate non-constancy, but not the exact breakpoint. Rolling estimation is found to perform better in detecting non-constancy in the parameters and their true value after the breakpoint. However, it only detects a region where the break is likely to occur. To overcome the drawbacks of these techniques, we use an OLS-based sequential test. To assess its performance, we derive its critical values for different sample sizes. Monte Carlo evidence shows that the test has reasonably good power even in moderately sized samples and that it can be used as a graphical device, as it shows a kink at the breakpoint. As a benchmark we use the Kalman filter, of which we analyse the performance on the same data generating processes (DGP)

On the robustness of the average power ratios in damping estimation: application in the structural health monitoring of composites beams

In composites structures, cracking, delamination will cause changes in the measured dynamic response of structure and so on experimentally modal parameters. Estimation of damping in structural control often poses a difficult problem especially using broadband experiments. If these estimations are faulty, it is difficult to propose a robust Structural Health Monitoring (SHM) algorithm. Recently H.P. Yin introduced the optimal power ratios damping estimator. A new theoretical basis of the bandwidth method for the damping estimation from frequency response functions (in case of a single degree of freedom system) has been proposed. The main goal of this paper is to study the robustness of this enhanced damping estimator on simulated signal (sampling frequency, Signal to Noise Ratio and damping level/density), and also compare its performance with industrial improved estimator like “Polymax” on experimental Frequency Response Functions (FRFs). The pole shifts would be studied as a change in the frequency-damping plane function of level and density of damage