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on Discrete Choice Models |
| By: | Mickaël Beaud; Thierry Blayac; Maïté Stéphan |
| Abstract: | This paper derives new monetary measures of traveler’s willingness to pay to save travel time and to improve its reliability. We develop an intuitive model of transport mode choice in which each alternative is fully characterized by its price and the distribution of its random travel time, assuming expected utility preferences over the latter. Hence, the value of time (VOT) and the value of reliability (VOR) are defined and theirs properties are established. Finally, we use data from a discrete choice experiment in stated preferences to illustrate how our measures can provide behavioral estimations of the VOT and the VOR. |
| Date: | 2014–07 |
| URL: | http://d.repec.org/n?u=RePEc:lam:wpaper:14-06&r=dcm |
| By: | Swantje Sundt; Katrin Rehdanz |
| Abstract: | The number of studies published focusing on people’s preferences for green electricity has increased steadily, making it more and more difficult to identify key explanatory factors that determine people’s willingness-to-pay (WTP). Based on results of a meta-regression our results indicate e.g. that hydropower is the least preferred technology. Variables such as information on the type of power plant that will be replaced by renewables, which are often omitted from primary valuation studies, are important in explaining differences in values as well. When assessing the predictive power of our results for out-of-sample value transfers we find median errors of approximately 30%, depending on model specification |
| Keywords: | meta-analysis, renewable energy, valuation, value transfer, willingness to pay |
| JEL: | C53 D62 Q40 Q48 Q51 |
| Date: | 2014–06 |
| URL: | http://d.repec.org/n?u=RePEc:kie:kieliw:1931&r=dcm |
| By: | Bertrand Candelon; Jameel Ahmed; Stefan Straetmans |
| Abstract: | his paper attempts to predict the bear conditions on the US stock market. To this aim we elaborate simple predictive regressions, static and dynamic binary choice (BCM) as well as Markov-switching models. The in- and out-of-sample prediction ability is evaluated and we compare the forecasting performance of various specifications across as well as within models. It turns out that various dynamic extensions of static versions of probit and logit models reveal additional predictive information for both in- and out-of-sample fit. We also find that binary models outperform the Markov-switching model. With respect to the macro-financial variables, terms spreads, inflation and money supply turn out to be useful predictors. The results lead to useful implications for investors practicing active portfolio and risk management and for policy makers as tools to get early warning signals. |
| Keywords: | Bear stock market, S&P 500 Index, Macro-financial variables, Dynamic Binary Response models, Markov-switching model, Bry-Boschan algorithm, Active Trading Strategies. |
| JEL: | C22 C25 C53 G11 G17 |
| Date: | 2014–07–15 |
| URL: | http://d.repec.org/n?u=RePEc:ipg:wpaper:2014-409&r=dcm |