Estimation with the Nested Logit Model: Specifications and Software Particularities

Due to its ability to allow and account for similarities betweenpairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. As the NNNL specification is not consistent with random utility theory (RUT), the UMNL form is preferred. This article introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. Additionally, it demonstrates the performance ofsimulation studies with the nested logit model. In simulation studies with the nested logit model using NNNL software (e. g. PROC MDC in SAS(c) ), it must be pointed out that the simulation of the utility function´s error terms needs to assume RUT-conformity. But as the NNNL specification is not consistent with RUT, the input parameters cannot be reproduced without imposing restrictions. The effects of using various software packages on the estimation results of a nested logit model are shown on the basis of a simulation study.nested logit model, utility maximization nested logit, non-normalized nested logit, simulation study

Estimation with the Nested Logit Model: Specifications and Software Particularities

The paper discusses the nested logit model for choices between a set of mutually exclusive alternatives (e.g. brand choice, strategy decisions, modes of transportation, etc.). Due to the ability of the nested logit model to allow and account for similarities between pairs of alternatives, the model has become very popular for the empirical analysis of choice decisions. However the fact that there are two different specifications of the nested logit model (with different outcomes) has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. This paper introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. The effects of using various software packages on the estimation results of a nested logit model are shown using simulated data sets for an artificial decision situation.nested logit model, utility maximization nested logit, nonnormalized nested logit, simulation study

On the Equivalence of Location Choice Models: Conditional Logit, Nested Logit and Poisson

It is well understood that the two most popular empirical models of location choice - conditional logit and Poisson - return identical coefficient estimates when the regressors are not individual specific. We show that these two models differ starkly in terms of their implied predictions. The conditional logit model represents a zero-sum world, in which one region's gain is the other regions' loss. In contrast, the Poisson model implies a positive-sum economy, in which one region's gain is no other region's loss. We also show that all intermediate cases can be represented as a nested logit model with a single outside option. The nested logit turns out to be a linear combination of the conditional logit and Poisson models. Conditional logit and Poisson elasticities mark the polar cases and can therefore serve as boundary values in applied research.firm location, residential choice, conditional logit, nested logit, Poisson count model

Estimation with the nested logit model: specifications and software particularities

The paper discusses the nested logit model for choices between a set of mutually exclusive alternatives (e.g. brand choice, strategy decisions, modes of transportation, etc.). Due to the ability of the nested logit model to allow and account for similarities between pairs of alternatives, the model has become very popular for the empirical analysis of choice decisions. However the fact that there are two different specifications of the nested logit model (with different outcomes) has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. This paper introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. The effects of using various software packages on the estimation results of a nested logit model are shown using simulated data sets for an artificial decision situation

Estimation with the nested logit model: specifications and software particularities

Due to its ability to allow and account for similarities between pairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties, influencing the estimation results in a different manner. As the NNNL specification is not consistent with random utility theory (RUT), the UMNL form is preferred. This article introduces distinct specifications of the nested logit model and indicates particularities arising from model estimation. Additionally, it demonstrates the performance of simulation studies with the nested logit model. In simulation studies with the nested logit model using NNNL software (e. g. PROC MDC in SAS), it must be pointed out that the simulation of the utility function's error terms needs to assume RUT-conformity. But as the NNNL specification is not consistent with RUT, the input parameters cannot be reproduced without imposing restrictions. The effects of using various software packages on the estimation results of a nested logit model are shown on the basis of a simulation study

Accommodating Complex Substitution Patterns in a Random Utility Model of Recreational Fishing

We employed a cross-nested logit (CNL) model that permits a rich pattern of substitution among alternatives within a closed form choice model. The specification we employed is ideal for applications with many choice alternatives, such as the 431 fishing sites in this application. The CNL model provided a significant improvement over multinomial and nested logit model specifications at explaining observed recreational fishing site choices by residents of northern Ontario, Canada. Results from two scenarios illustrated the implications of using the CNL model on spatial substitution patterns and welfare measures associated with attribute change scenarios. The CNL model forecasts demonstrated that the relative change in fishing site use was lower at the most affected sites and higher at sites near the affected sites than was predicted by the multinomial logit model. No consistent pattern was found in mean or variance of welfare estimates associated with hypothetical attribute changes.Compensating variation, cross-nested logit, fishing site choice, random utility model, spatial substitution, Demand and Price Analysis, Institutional and Behavioral Economics, Q26,

Specification(s) of Nested Logit Models

The nested logit model has become an important tool for the empirical analysis of discrete outcomes. There is some confusion about its specification of the outcome probabilities. Two major variants show up in the literature. This paper compares both and finds that one of them (called random utility maximization nested logit, RUMNL) is preferable in most situations. Since the command nlogit of Stata 7.0 implements the other variant (called non-normalized nested logit, NNNL), an implementation of RUMNL called nlogitrum is introduced. Numerous examples support and illustrate the differences of both specifications.

A Nested Logit Model of Strategic Promotion

Retailers use sales "price promotions" for a number of potential reasons. There is relatively little research, however, on their strategic role among frequently consumed perishable products. Using a two-stage, nested logit model of retail equilibrium, we show that promotion will be most effective (ie. increase store-level sales) if products are highly differentiated, but stores are relatively similar. To test this hypothesis, we an oligopolistic model of promotion rivalry with category-level scanner data from the four largest supermarket retailers in a major U.S. metropolitan market. The results show that promotion has a greater impact on store share than product share, because the elasticity of substitution among stores is larger than the elasticity of substitution among products. Consequently, promotion has its greatest value in driving demand for differentiated products among stores that are similar. This finding supports the observed trend toward premium private label products being offered by supermarket retailers.Research Methods/ Statistical Methods,

Broadband delivered entertainment services: forecasting Australian subscription intentions

This study estimates a nested multinomial logit (NMNL) model of broadband delivered entertainment service subscription that allows for the impact of an installation fee and rental price, service attributes and household demographic variables on subscription. The model is estimated on stated-preference data obtained from an Australia-wide survey of capital cities and provincial centres. Nested multinomial logit model estimates are used to provide forecasts that suggest 65 per cent of separate residences passed are likely to subscribe at 2000. This percentage translates into 1237 744 subscriber.Broadband entertainment services; forecasting Australian subscription demand

Exploring the potential for cross-nesting structures in airport-choice analysis: A case-study of the Greater London area

The analysis of air-passengers’ choices of departure airport in multi-airport regions is a crucial component of transportation planning in many large metropolitan areas, and has been the topic of an increasing number of studies over recent years. In this paper, we advance the state of the art of modelling in this area of research by making use of a Cross-Nested Logit (CNL) structure that allows for the joint representation of inter-alternative correlation along the three choice dimensions of airport, airline and access-mode. The analysis uses data collected in the Greater London area, which arguably has the highest levels of inter-airport competition of any multi-airport region; the authors of this paper are not aware of any previous effort to jointly analyse the choice of airport, airline and access-mode in this area. The results of the analysis reveal significant influences on passenger behaviour by access-time, access-cost, flight-frequency and flight-time. A structural comparison of the different models shows that the cross-nested structure offers significant improvements over simple Nested Logit (NL) models, which in turn outperform the Multinomial Logit (MNL) model used as the base model