A COMPOSITE LOGISTIC REGRESSION APPROACH FOR ORDINAL PANEL DATA REGRESSION
ABSTRACT
We propose in this article a Composite Logistic Regression (CLR) approach for ordinal panel data regression. The new method transforms the original ordinal regression problem into a number of binary ones. Thereafter, the method of conditional logistic regression (Chamberlain, 1984; Wooldridge, 2001; Hsiao, 2003) can be directly applied. As a result, the new method allows the unobserved subject effects to be correlated with the observed predictors in an arbitrary manner.
Computationally, the new method is able to profile out unobserved subject effects in a very neat manner. This not only makes computational implementation very easy but also makes theoretical treatment straightforward. In particular, we show theoretically that the resulting estimator is n-consistent and asymptotically normal. Both simulations and a real example are reported to demonstrate the usefulness of the new method.
CHAPTER ONE
1.1 Introduction
… This chapter will address the background information that motivated this study, the challenges that prompted it, its aim, and its objectives as a preface to subsequent sections of the study. Additional factors include the study's significance, scope, limitations, research questions and hypotheses, and the definition of technical terms.
CHAPTER TWO
2.0 Literature Review
2.1 Introduction
The review of relevant literature is the main topic of this chapter. A literature review covers theoretical and methodological contributions to a certain issue in addition to the state of knowledge at the time of writing. It provides information about the state of the art in relation to the subject you are writing about. It examines the body of work on the chosen subject. The literature evaluation in this study comprises the …
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