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<https://discovery.ucl.ac.uk/id/eprint/10060499> <http://purl.org/ontology/bibo/abstract> "The multinomial logit model with random coefficients is widely used in applied research. This paper is\r\nconcerned with estimating a random coefficients logit model in which the distribution of each coefficient\r\nis characterized by finitely many parameters. Some of these parameters may be zero. The paper gives\r\nconditions under which with probability approaching 1 as the sample size approaches infinity, penalized\r\nmaximum likelihood (PML) estimation with the adaptive LASSO (AL) penalty function distinguishes\r\ncorrectly between zero and non-zero parameters in a random coefficients logit model. If one or more\r\nparameters are zero, then PML with the AL penalty function often reduces the asymptotic mean-square\r\nestimation error of any continuously differentiable function of the model’s parameters, such as a market\r\nshare or an elasticity. The paper describes a method for computing the PML estimates of a random\r\ncoefficients logit model. It also presents the results of Monte Carlo experiments that illustrate the\r\nnumerical performance of the PML estimates. Finally, it presents the results of PML estimation of a\r\nrandom coefficients logit model of choice among brands of butter and margarine in the British groceries\r\nmarket."^^<http://www.w3.org/2001/XMLSchema#string> .
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