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on Discrete Choice Models |
| By: | SERSE Valerio, (Université catholique de Louvain, CORE, Belgium) |
| Abstract: | Sugar taxes are often considered as a possible tool to tackle excessive sugar consumption. This paper estimates a dynamic multinomial Logit model of cola demand on a novel supermarket scanner dataset in order to study preference heterogeneity and state dependence in product choice. The model estimates allow evaluating the effectiveness of taxation in reducing demand for sugary colas across different consumer types. The results show that a sugar tax would be less effective among the targeted population of heavy sugar consumers. This policy, however, would be more effective among low-income households. Tax policy simulations show that a specific tax on sugar should be preferred to an ad-valorem tax on sugary colas on both corrective and equity grounds. This is because ad-valorem taxes can lead low-income households and heavy sugar consumers to substitute from expensive to cheaper sugary brands. Lastly, because households exhibit state dependence in cola choice, sugar taxes would be more effective in reducing sugar consumption in the long-run. |
| Keywords: | heterogeneity in preferences, state dependence, sugar taxes, discrete choice models |
| JEL: | D12 H31 I18 Q18 |
| Date: | 2019–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:cor:louvco:2019017&r=all |
| By: | Siamuzyulu Moono; Adewunmi Yewande |
| Abstract: | Purpose– This study focuses on establishing the factors that realistically influence office relocation decisions in the Johannesburg metropolitan area. The goal of the study aimed to obtain rank ordering (importance) of nine selected factors.Design/Methodology/Approach–A questionnaire used in the USA to conduct a conjoint study in the real estate sector was adapted to suit the South African context and sent to office tenants. Additional variables and levels were added, to better reflect current findings of the literature. A conjoint methodology was used to analyse the data.Findings– According to the conjoint analysis, the most important factor is parking followed by Landlord reputation; Size is third in importance with Security at fourth and Green Rating in fifth place. Accessibility of the building is sixth; Location of the building is seventh with the rental cost (total cost of occupation) and the grade of the building being the bottom two factors in eighth and ninth places respectively.Research Limitations/Implications–The sample only included office tenants in P-grade, A-grade and B-grade office buildings in the greater Johannesburg metropolis. Current Literature shows that newer “preference” procedures like stated preference elicitation reveal deeper and broader information on customer preferences than that obtained using choice-based conjoint analysis.Originality/Value–The research specifically illustrates the application of market research techniques to the office market in an emerging economy. The use of conjoint analysis in the determination of preferences for would-be tenants in the South African office market will go a long way in reducing financial losses attributable to low occupancy levels and high tenant churn. |
| Keywords: | Analysis; johannesburg.; office tenants; tenant preferences |
| JEL: | R3 |
| Date: | 2018–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:afr:wpaper:afres2018_130&r=all |
| By: | Claudia Pigini (Dipartimento di Scienze Economiche e Sociali - Universita' Politecnica delle Marche) |
| Abstract: | Panel logit models have proved to be simple and effective tools to build Early Warning Systems (EWS) for financial crises. But because crises are rare events, the estimation of EWS does not usually account for country fixed effects, so as to avoid losing all the information relative to countries that never face a crisis. I propose using a penalized maximum likelihood estimator for fixed-effects logit-based EWS where all the observations are retained. I show that including country effects, while preserving the entire sample, greatly improves the predictive power of EWS with respect to the pooled, random-effects and standard fixed-effects models. |
| Keywords: | Keywords: Banking Crisis, Bias Reduction, Fixed-Effects Logit, Separated Data |
| JEL: | C23 C25 G17 G21 |
| Date: | 2019–11 |
| URL: | http://d.repec.org/n?u=RePEc:anc:wpaper:441&r=all |