Search results for "Multinomial Logit"

showing 4 items of 4 documents

A competing risks tale on successful and unsuccessful fiscal consolidations

2019

Abstract This paper analyses the transitions out of fiscal consolidations using annual data for 17 industrial countries over the period 1975-2013 and applying a discrete-time competing risks duration model. Our approach allows us to distinguish the factors behind a successful or an unsuccessful end of fiscal consolidation episodes. The results show that economic and political factors, the size and typology of fiscal adjustments and the occurrence of crises explain the differences in the length and the success/failure of fiscal consolidations. Moreover, while fiscal adjustment programmes that end successfully display positive duration dependence, those that end in an unsuccessful manner are …

040101 forestryTypologyEconomics and Econometrics050208 financeApplied economics05 social sciencesDuration dependenceSettore SECS-P/02 Politica Economica04 agricultural and veterinary sciencesMonetary economicsFiscal consolidations Discrete duration data Competing risks Multinomial logitCompeting risksConsolidation (business)0502 economics and business8. Economic growthEconomics0401 agriculture forestry and fisheriesFiscal adjustmentFinanceMultinomial logistic regression
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Design and analysis of discrete choice experiments for models with response time

2013

Settore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaA sector of conjoint analysis (experimental design in marketing research) is made of the so called choice experiments. In choice experiments respondents undergo a questionnaire which is nowadays mostly submitted through the internet. The questionnaire proposes to the respondent a sequence of choice sets each one including two or more profiles being a profile a specific combination of attribute levels. The respondent selects the preferred profile for each choice set. Responses given by a sample of respondents are analysed through suitable methods aimed to eventually find the best combination of attribute levels. One method of analysis adopts the Multinomial Logit (MLN) model. In this article the authors show the results of the MLN analysis compared with another model of analysis which uses an additional response which can be easily recorded by electronically submitted questionnaires. In practice modern survey platforms like “Qualtrics” (the one used for this work) can record the so called “response latency” i.e. the time taken by the respondent to make the choice and select the most preferred profile in the choice set. Thanks to a response latency model further refined in this work it is possible to deduce the relative weight of importance of the profiles for each choice set and respondent. This type of response can be used in place of the dichotomous choice variable in the MLN model. The two models and methods of analysis are deeply compared and it is critically discussed when it is better to use one or the other method. As a result a more reliable estimate of the optimal profile comes up implying lower risks for new investments and marketing decisions.
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Modelling the influence of landscape on pedestrian's route choices using a multinomial logit model

2007

ACTI; International audience

pedestrian's route choices[SHS.GEO] Humanities and Social Sciences/Geography[SHS.GEO]Humanities and Social Sciences/Geography[ SHS.GEO ] Humanities and Social Sciences/Geographyinfluence of landscapemultinomial logit model
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Enhanced multinomial logit model for the analysis of choice experiments

2012

A sector of conjoint analysis (experimental design in marketing research) is made of the so called choice experiments. In choice experiments respondents undergo a questionnaire which is nowadays mostly submitted through the internet. The questionnaire proposes to the respondent a sequence of choice sets each one including two or more profiles, being a profile a specific combination of attribute levels. The respondent selects the preferred profile for each choice set. Responses given by a sample of respondents are analysed through suitable methods aimed to eventually find the best combination of attribute levels. One method of analysis adopts the Multinomial Logit (MLN) model. In this articl…

Multinomial LogitDiscrete choice experimentSettore SECS-S/02 - Statistica Per La Ricerca Sperimentale E TecnologicaSettore SECS-S/01 - Statistica
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