Abstract
This article provides an overview of the literature on hypotheses testing when the hypotheses or models under consideration are non-nested. Two models are said to be non-nested if neither can be obtained from the other by some limiting process, including the imposition of equality and/or inequality constrains on one of the model’s parameters. Relevant concepts such as closeness measures and pseudo-true values are discussed and alternative approaches to testing non-nested hypotheses, including the Cox procedure, artificial nesting and the encompassing approach, are reviewed. The Vuong approach to model selection is also covered.
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Hashem Pesaran, M., Rodrigo Dupleich Ulloa, M. (2018). Non-nested Hypotheses. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_1835
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DOI: https://doi.org/10.1057/978-1-349-95189-5_1835
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