Random Coefficient Panel Data Models

This paper provides a review of linear panel data models with slope heterogeneity, introduces various types of random coefficient models and suggest a common framework for dealing with them. It considers the fundamental issues of statistical inference of a random coefficients formulation using both the sampling and Bayesian approaches. The paper also provides a review of heterogeneous dynamic panels, testing for homogeneity under weak exogeneity, simultaneous equation random coefficient models, and the more recent developments in the area of cross-sectional dependence in panel data models.random coefficient models, dynamic heterogeneous panels, classical and Bayesian approaches, tests of slope heterogeneity, cross section dependence

Efficient Estimation of a Dynamic Error-Shock Model

This paper is concerned with the estimation of the parameters in a dynamic simultaneous equation model with stationary disturbances under the assumption that the variables are subject to random measurement errors. The conditions under which the parameters are identified are stated. An asymptotically efficient frequency-domain class of instrumental variables estimators is suggested. The procedure consists of two basic steps. The first step transforms the model in such a way that the observed exogenous variables are asymptotically orthogonal to the residual terms. The second step involves an iterative procedure like that of Robinson [13].

Design and application of stationary phase combinatorial promoters

Current bacterial synthetic circuits rely on the fast dilution and high protein expression that occurs during exponential phase. However, constant exponential phase is both difficult to ensure in a lab environment and almost certainly impractical in any natural setting. Here, we characterize the performance of 13 E. coli native σ38 promoters, as well as a previously identified σ38 consensus promoter. We then make tetO combinatorial versions of the three strongest promoters to allow for inducible delayed expression. The design of these combinatorial promoters allows for design of circuits with inducible stationary phase activity that can be used for phase-dependent delays in dynamic circuits or spatial partitioning of biofilms

Diagnostic Tests of Cross Section Independence for Nonlinear Panel Data Models

In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the observed dependent variable from its expected value and generalized residuals. We show the asymptotic consistency of the cross section dependence (CD) test of Pesaran (2004). In Monte Carlo experiments it emerges that the CD test has the correct size for any combination of N and T whereas the LM test relies on T large relative to N. We then analyze the roll-call votes of the 104th U.S. Congress and find considerable dependence between the votes of the members of Congress.cross-section dependence, nonlinear panel data model

Estimation and Inference In Short Panel Vector Autoregressions with Unit Roots And Cointegration

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel 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 consistent and asymptotically normally distributed irrespective of the unit root and cointegrating properties of the underlying PVAR model. The transformed likelihood framework is also used to derive unit root and cointegration tests in panels with short time dimension; these tests have the attractive feature that they are based on standard chi-square and normal distributed statistics. Examining Generalized Method of Moments (GMM) estimation as an alternative to our proposed ML estimator, it is shown that conventional GMM estimators based on standard orthogonality conditons break down if the underlying time series contain unit roots. Also, the implementation of extended GMM estimators making use of variants of homoskedasticity and stationarity restrictions as suggested in the literature in a univariate context is subject to difficulties. Monte Carlo evidence is adduced suggesting that the ML estimator and parameter hypothesis and cointegration tests based on it perform well in small sample; this is in marked contrast to the small sample performance of the GMM estimators.Panel vector autoregressions, fixed effects, unit roots, cointegration

Mechanism of Anomalous Photoinduced Transient Current Peak in Amorphous Silicon Thin-Film Transistor

The photoinduced transient current from an amorphous silicon thin-film transistor is computed and the mechanism described in terms of trap-state filling dynamics. The direction of the current flow and the location of the transient peak depends strongly on the distributions of donorlike and acceptorlike trap states in the neighborhood of the dark Fermi level. We show that the transient current can flow in the same direction as in the crystalline transistor, as well as in the opposite direction. There is also an interesting cross-over behavior in which the transient current flows out of the drain terminal as a pulse of positive charge, and then immediately reverses its direction. There is a broadening effect of the transient peak by a simultaneous switch on of the gate voltage. The transient peak typically occurs at 10-4 s and an example is provided. The transient current can be greatly diminished by switching the gate voltage long before illumination, or by doping the channel either partially or completely

Limiting Efficiencies for Multiple Energy-Gap Quantum Devices

We have used a thermodynamic model to calculate theoretical limiting efficiencies for simple and multiple gap solar cells. The limiting efficiency is 26% for a simple solar cell of hydrogenated amorphous silicon, operating at one Sun sensitivity. For a multiple gap cell made from hydrogenated amorphous silicon, together with a second cell, made from a material with lower band gap, it is 38%. The optimum band gap for the second material is 1.0 eV

Diagnostic Tests of Cross Section Interdependence for Nonlinear Panel Data Models

In this paper we discuss tests for residual cross section dependence in nonlinear panel data models. The tests are based on average pair-wise residual correlation coefficients. In nonlinear models, the definition of the residual is ambiguous and we consider two approaches: deviations of the observed dependent variable from its expected value and generalized residuals. We show the asymptotic consistency of the cross section dependence (CD) test of Pesaran (2004). In Monte Carlo experiments it emerges that the CD test has the correct size for any combination of N and T whereas the LM test relies on T large relative to N. We then analyze the roll-call votes of the 104th U.S. Congress and find considerable dependence between the votes of the members of Congress

Design and application of stationary phase combinatorial promoters

Current bacterial synthetic circuits rely on the fast dilution and high protein expression that occurs during exponential phase. However, constant exponential phase is both difficult to ensure in a lab environment and almost certainly impractical in any natural setting. Here, we characterize the performance of 13 E. coli native σ38 promoters, as well as a previously identified σ38 consensus promoter. We then make tetO combinatorial versions of the three strongest promoters to allow for inducible delayed expression. The design of these combinatorial promoters allows for design of circuits with inducible stationary phase activity that can be used for phase-dependent delays in dynamic circuits or spatial partitioning of biofilms

Estimation and inference in short panel vector autoregressions with unit roots and cointegration

Se considera la estimacion y la inferencia de vectores autorregresivos en panel (VAP) con efectos fijos cuando la dimension temporal del panel es finita y la dimension de corte transversal es grande. Se propone un estimador de maxima verosimilitud (MV), basado en una funcion de verosimilitud transformada, que resulta ser consistente y con una distribucion asimptotica normal independientemente de las propiedades de raiz unitaria y de cointegracion del modelo VAP subyacente. La funcion de verosimilitud transformada tambien se utiliza para obtener contrastes de raiz unitaria y de cointegracion en paneles con dimensiones temporales reducidas. Se proporciona evidencia de Monte Carlo, que indica que el estimador MV y los constrastes de cointegracion y de hipotesis de los parametros basados en el se comportan bien en muestras pequeñas. (mb) (ad