This paper proposes a new estimation procedure for the first-order spatial autoregressive (SAR) model, where disturbance term also follows autoregression and its innovations may be heteroscedastic. The is based on principle of indirect inference that matches ordinary least squares estimator two SAR coefficients (one in outcome equation other equation) with approximate analytical expectation. re...

several characterizations of marshall-olkin generalized distributions, introduced by gui (2013) and by al-saiari et al. (2014) are presented. these characterizations are based on: (i) a simple relationship between two truncated moments ; (ii) the hazard function.

We address the problem of estimating the parameters of a time-homogeneous Markov chain given only noisy, aggregate data. This arises when a population of individuals behave independently according to a Markov chain, but individual sample paths cannot be observed due to limitations of the observation process or the need to protect privacy. Instead, only population-level counts of the number of i...

We introduce a new family of continuous models called the beta odd log-logistic generalized family of distributions. We study some of its mathematical properties. Its density function can be symmetrical, left-skewed, right-skewed, reversed-J, unimodal and bimodal shaped, and has constant, increasing, decreasing, upside-down bathtub and J-shaped hazard rates. Five special models are discussed. W...

Hyperbolic absolute risk aversion (HARA) utility, (See is a more Carroll and Kimball, 1996), realistic alternative to the power utility used in consumption-based capital asset pricing models (CCAPM). We propose a new estimator for the HARA based on Godambe-Durbin “estimating functions” and small sigma asymptotics (SSA). This is an alternative to the generalized method of moments (GMM). Since th...

Rank breaking is a methodology introduced by Azari Soufiani et al. (2013a) for applying a Generalized Method of Moments (GMM) algorithm to the estimation of parametric ranking models. Breaking takes full rankings and breaks, or splits them up, into counts for pairs of alternatives that occur in particular positions (e.g., first place and second place, second place and third place). GMMs are of ...