Local noise analysis of a Schottky contact: combined thermionic-emissiondiffusion theory

A theoretical model for the noise properties of Schottky barrier diodes in the framework of the thermionic-emission¿diffusion theory is presented. The theory incorporates both the noise inducedby the diffusion of carriers through the semiconductor and the noise induced by the thermionicemission of carriers across the metal¿semiconductor interface. Closed analytical formulas arederived for the junction resistance, series resistance, and contributions to the net noise localized indifferent space regions of the diode, all valid in the whole range of applied biases. An additionalcontribution to the voltage-noise spectral density is identified, whose origin may be traced back tothe cross correlation between the voltage-noise sources associated with the junction resistance andthose for the series resistance. It is argued that an inclusion of the cross-correlation term as a newelement in the existing equivalent circuit models of Schottky diodes could explain the discrepanciesbetween these models and experimental measurements or Monte Carlo simulations.

Indirect likelihood inference (revised)

Standard indirect Inference (II) estimators take a given finite-dimensional statistic, Z_{n} , and then estimate the parameters by matching the sample statistic with the model-implied population moment. We here propose a novel estimation method that utilizes all available information contained in the distribution of Z_{n} , not just its first moment. This is done by computing the likelihood of Z_{n}, and then estimating the parameters by either maximizing the likelihood or computing the posterior mean for a given prior of the parameters. These are referred to as the maximum indirect likelihood (MIL) and Bayesian Indirect Likelihood (BIL) estimators, respectively. We show that the IL estimators are first-order equivalent to the corresponding moment-based II estimator that employs the optimal weighting matrix. However, due to higher-order features of Z_{n} , the IL estimators are higher order efficient relative to the standard II estimator. The likelihood of Z_{n} will in general be unknown and so simulated versions of IL estimators are developed. Monte Carlo results for a structural auction model and a DSGE model show that the proposed estimators indeed have attractive finite sample properties.