Preprint Technical Note Version 1 This version is not peer-reviewed

Regression Models with Stochastic Regressors: An Expository note

Version 1 : Received: 27 September 2018 / Approved: 27 September 2018 / Online: 27 September 2018 (10:04:26 CEST)

How to cite: Bharali, S.; Hazarika, J. Regression Models with Stochastic Regressors: An Expository note. Preprints 2018, 2018090539 (doi: 10.20944/preprints201809.0539.v1). Bharali, S.; Hazarika, J. Regression Models with Stochastic Regressors: An Expository note. Preprints 2018, 2018090539 (doi: 10.20944/preprints201809.0539.v1).

Abstract

Regression models form the core of the discipline of econometrics. One of the basic assumptions of classical linear regression model is that the values of the explanatory variables are fixed in repeated sampling. However, in most of the real life cases, particularly in economics the assumption of fixed regressors is not always tenable. Under a non-experimental or uncontrolled environment, the dependent variable is often under the influence of explanatory variables that are stochastic in nature. There is a huge literature related to stochastic regressors in various aspects. In this paper, a historical perspective on some of the works related to stochastic regressor is being tried to pen down based on literature search.

Subject Areas

Non-normality, Classical Linear Regression Model, Modified Maximum Likelihood Estimation.

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