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on Discrete Choice Models |
| By: | Tiet, Tuyen; Nguyen-Van, Phu; Pham, Thi Kim Cuong; Stenger, Anne; To-The, Nguyen; Boun My, Kene; Nguyen, Huy |
| Keywords: | Environmental Economics and Policy, Agricultural and Food Policy, Research Methods/Statistical Methods |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea21:313946&r= |
| By: | Martin FAULQUES (University of Caen-Normandy, CREM-CAEN, UMR CNRS 6211, UFR SEGGAT, esplanade de la paix 14000 Caen (France)); Jean BONNET (University of Caen-Normandy, CREM-CAEN, UMR CNRS 6211, UFR SEGGAT, esplanade de la paix 14000 Caen (France)); Sébastien BOURDIN (EM Normandie Business School, Métis Lab, 9 rue Claude Bloch, 14000 Caen (France)); Marine JUGE (ENGIE); Jonas PIGEON (ENGIE); Charlotte RICHARD (ENGIE) |
| Abstract: | The development of Renewable Energies(RE)must be stepped upin the coming years if we areto successfullyrealizethe ambitiousenergy transition challenge set by manygovernments across the globe. In this context, we used a Discrete Choice Experiment (DCE) combined with a Geographical Information System (GIS) to assess the willingness of individualsin the French context to switchto a more virtuousenergy mixbasedon three energy sources(wind, photovoltaic and biogas). Our findingsshowthatinhabitants living in areas with the presence of REwith negative externalities(Wind Turbines and Anaerobic Digestion units)tend to have a lower Willingness to Pay(WTP)than other areas, indicatinga principle of territorial distributive justice. In this context, people ask for greaterterritorial equity in the distribution of externalitiessincethey consider they “have already done their part”.Accordingly, our study argues for morepublic policy effort to plan the location of future RE facilitiesin a more equitable way. |
| Keywords: | Environmental justice, renewable energies, willingness to pay, discrete choice experiment, territory |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:tut:cremwp:2021-01&r= |
| By: | Bartolucci, Francesco; Pigini, Claudia; Valentini, Francesco |
| Abstract: | We propose a multiple-step procedure to compute average partial effects (APEs) for fixed-effects panel logit models estimated by Conditional Maximum Likelihood (CML). As individual effects are eliminated by conditioning on suitable sufficient statistics, we propose evaluating the APEs at the ML estimates for the unobserved heterogeneity, along with the fixed-T consistent estimator of the slope parameters, and then reducing the induced bias in the APE by an analytical correction. The proposed estimator has bias of order O(T −2 ), it performs well in finite samples and, when the dynamic logit model is considered, better than alternative plug-in strategies based on bias-corrected estimates for the slopes, especially with small n and T. We provide a real data application based on labour supply of married women. |
| Keywords: | Average partial effects, Bias reduction, Binary panel data, Conditional Maximum Likelihood |
| JEL: | C12 C23 C25 |
| Date: | 2021–10–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110031&r= |
| By: | Chen, Xuan; Hu, Wuyang; Qing, Ping; Li, Jian |
| Keywords: | Marketing, Agricultural and Food Policy, Institutional and Behavioral Economics |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea21:314010&r= |
| By: | Lordan, Grace; Pischke, Jorn-Steffen |
| Abstract: | Occupational segregation and pay gaps by gender remain large, while many of the constraints traditionally believed to be responsible for these gaps seem to have weakened over time. We explore the possibility that women and men have different tastes for the content of the work that they do. We relate job satisfaction and job mobility to measures that proxy for the content of the work in an occupation, which we label ‘people’, ‘brains’ and ‘brawn’. The results suggest that women value jobs high on ‘people’ content and low on ‘brawn’. Men care about job content in a similar fashion, but have much weaker preferences. High school students show similar preferences in a discrete choice experiment and indicate that they make their choices based mainly on preferences for the work itself. We argue that the more pronounced preferences of women can account for occupational sorting, which often leads them into careers with large pay penalties for interruptions due to childbearing. |
| Keywords: | ES/M010341/1 |
| JEL: | R14 J01 |
| Date: | 2021–09–16 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:111928&r= |
| By: | Astaiza-Gómez, José Gabriel |
| Abstract: | I estimate a demand model for online services of financial data, from a random parameters or mixed logit model, using a sample with searches at Bloomberg Terminals and at the EDGAR system. My preliminary results suggest that the substitution investors make of financial information providers, are affected by the subscription prices, investors' expectations on stock returns, and investors' income. |
| Keywords: | random parameters, open access services, subscription providers, market shares. |
| JEL: | D80 D82 D83 D84 G00 G14 G23 L86 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110008&r= |
| By: | Bartolucci, Francesco; Pigini, Claudia; Valentini, Francesco |
| Abstract: | We propose a Markov chain Monte Carlo Conditional Maximum Likelihood (MCMC-CML) estimator for two-way fixed-effects logit models for dyadic data. The proposed MCMC approach, based on a Metropolis algorithm, allows us to overcome the computational issues of evaluating the probability of the outcome conditional on nodes in and out degrees, which are sufficient statistics for the incidental parameters. Under mild regularity conditions, the MCMC-CML estimator converges to the exact CML one and is asymptotically normal. Moreover, it is more efficient than the existing pairwise CML estimator. We study the finite sample properties of the proposed approach by means of a simulation study and three empirical applications, where we also show that the MCMC-CML estimator can be applied to binary logit models for panel data with both subject and time fixed effects. Results confirm the expected theoretical advantage of the proposed approach, especially with small and sparse networks or with rare events in panel data. |
| Keywords: | Directed network, Fixed effects, Link formation, Metropolis algorithm, Panel data |
| JEL: | C23 C25 C63 |
| Date: | 2021–10–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110034&r= |
| By: | Zawojska, Ewa; Gastineau, Pascal; Mahieu, Pierre-Alexandre; Cheze, Benoit; Paris, Anthony |
| Keywords: | Environmental Economics and Policy, Institutional and Behavioral Economics, Research Methods/Statistical Methods |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea21:313977&r= |
| By: | Yehouenou, Lauriane S.; Grogan, Kelly A.; Yehouenou, Lauriane S.; Morgan, Stephen N. |
| Keywords: | Environmental Economics and Policy, Research Methods/Statistical Methods, Community/Rural/Urban Development |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea21:313934&r= |