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on Discrete Choice Models |
| By: | Buschmann, Christoph; Röder, Norbert |
| Abstract: | Growing evidence suggests that biodiversity in the agricultural landscape is declining sharply. Farmland birds are particularly affected, the population of the lapwing (Vanellus vanellus) has been decreasing strongly in Germany. Up to now the European Union has tried to tackle the problem of biodiversity loss mainly with voluntary (second pillar) agri-environmental schemes financed by the European Agricultural Fund for Rural Development (EAFRD). However, only a small fraction of the agricultural land is enrolled in such programs. We analyze a potential scheme to protect the lapwing in order to identify drivers and inhibitors of acceptance. The analysis is based on a discrete choice experiment with 270 arable farmers in Germany. Results show that those scheme attributes associated with EAFRD compliance, the type of sanctioning and a minimum participation period of five years, particularly reduce the farmers’ acceptance. Results for other attributes indicate that farmers’ preferences and ecological requirements often contradict each other, so that they constitute an economic-ecological trade-off. Finally, the paper sketches how the identified weak spots of biodiversity protection schemes may be tackled under a different regime of Common Agricultural Policy (CAP). Here, we take up the current CAP reform proposals of the European Commission. |
| Keywords: | Environmental Economics and Policy, Land Economics/Use, Resource /Energy Economics and Policy |
| Date: | 2019–08–26 |
| URL: | http://d.repec.org/n?u=RePEc:ags:gewi19:292288&r=all |
| By: | Petrolia, Daniel R.; Hwang, Joonghyun |
| Abstract: | We revisit three recently-published papers that apply discrete-choice experiment methods to coastal and marine ecosystem goods and services, in light of attribute non-attendance (AN-A). We find that accounting for AN-A does not always improve model fit, but when it does, the improvement can be substantial. Estimated price and attribute coefficients change, but these changes do not follow a consistent pattern, either in direction or magnitude. Mean attribute increment value (i.e., willingness to pay, WTP) estimates change, but also with no discernible pattern. However, in several cases, generally in those cases where accounting for AN-A improves model fit, we observe substantial improvements in the confidence intervals on WTP, i.e., accounting for AN-A appears to produce much more precise WTP estimates. In short, we find that accounting for AN-A is not always warranted, but when it is, the key payoff appears to be more precise WTP estimates. |
| Keywords: | Environmental Economics and Policy, Research Methods/ Statistical Methods |
| Date: | 2019–09–04 |
| URL: | http://d.repec.org/n?u=RePEc:ags:misswp:292344&r=all |
| By: | Andrew T. Ching (Johns Hopkins University); Matthew Osborne (University of Toronto) |
| Abstract: | Understanding how forward-looking consumers respond to price promotions in storable goods markets is an important area of research in empirical marketing and industrial organization. In prior work, researchers have assumed that consumers in these markets are very forward-looking, and calibrated their weekly discount factors to levels around 0.9995. This calibration has been used because earlier research has assumed that a consumer’s storage cost is a continuous func- tion of inventory, which rules out exclusion restrictions that can be used to identify the discount factor. We show that by properly modeling storage cost as a step function of inventory (be- cause storage cost depends on the number of packages stored, instead of the actual amount of inventory), natural exclusion restrictions arise that allow for the discount factor to be point identified. In an application to a storable good category, we find that weekly discount factors are very heterogeneous across consumers, and are on average 0.71. We show through a counter- factual exercise that if one used a model which fixed the discount factor to be consistent with the standard calibrated value, one would overpredict the effect of increased promotional depth for a product on its quantity sold by 18% in the short-term, and 15% in the long-term. |
| Keywords: | Discount Factor, Exclusion Restriction, Stockpiling, Dynamic Programming |
| Date: | 2019–08–16 |
| URL: | http://d.repec.org/n?u=RePEc:cth:wpaper:gru_2019_023&r=all |
| By: | Francisco C. Pereira |
| Abstract: | This paper introduces the concept of travel behavior embeddings, a method for re-representing discrete variables that are typically used in travel demand modeling, such as mode, trip purpose, education level, family type or occupation. This re-representation process essentially maps those variables into a latent space called the \emph{embedding space}. The benefit of this is that such spaces allow for richer nuances than the typical transformations used in categorical variables (e.g. dummy encoding, contrasted encoding, principal components analysis). While the usage of latent variable representations is not new per se in travel demand modeling, the idea presented here brings several innovations: it is an entirely data driven algorithm; it is informative and consistent, since the latent space can be visualized and interpreted based on distances between different categories; it preserves interpretability of coefficients, despite being based on Neural Network principles; and it is transferrable, in that embeddings learned from one dataset can be reused for other ones, as long as travel behavior keeps consistent between the datasets. The idea is strongly inspired on natural language processing techniques, namely the word2vec algorithm. Such algorithm is behind recent developments such as in automatic translation or next word prediction. Our method is demonstrated using a model choice model, and shows improvements of up to 60\% with respect to initial likelihood, and up to 20% with respect to likelihood of the corresponding traditional model (i.e. using dummy variables) in out-of-sample evaluation. We provide a new Python package, called PyTre (PYthon TRavel Embeddings), that others can straightforwardly use to replicate our results or improve their own models. Our experiments are themselves based on an open dataset (swissmetro). |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1909.00154&r=all |
| By: | Martey, Edward |
| Keywords: | Research and Development/Tech Change/Emerging Technologies |
| Date: | 2019–06–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea19:290836&r=all |
| By: | Altmann, Brianne Andrea; Risius, Antje; Anders, Sven |
| Abstract: | Increasing global demand for animal-based proteins will require the integration of alternative protein sources as a means to ensure products can be sustainably produced into the future. We elicit German consumer preferences for chicken breast produced using spirulina or insect meal compared to the traditional protein feed source – soybean meal within a discrete choice experimental approach with an information treatment. Spirulina is known for darkening the meat colour when incorporated into poultry diets; insect meal can also slightly alter meat colour. When no information is given about the feed used in production–the source of meat discolouration–consumers were apathetic towards the dark colour produced with spirulina, and consumers preferred chicken breast produced with insect meal. Consumers who received information on the feed type used in production behaved heterogeneously; non-environmentally-conscious consumers were not willing to accept chicken breast produced with insect meal, whereas environmentally-conscious preferred this product. Overall, German consumers are not likely to reject chicken breast produced using alternative protein sources; however, this study points to the importance that credible information and labelling play in consumers’ product choice decisions and thus raises questions over the need for the mandatory declaration of novel feedstuffs in meat production. |
| Keywords: | Agricultural and Food Policy, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries |
| Date: | 2019–08–26 |
| URL: | http://d.repec.org/n?u=RePEc:ags:gewi19:292296&r=all |
| By: | Castleman, Benjamin L. (University of Virginia); Murphy, Francis X. (United States Army); Patterson, Richard (United States Military Academy); Skimmyhorn, William L. (College of William and Mary) |
| Abstract: | The Post-9/11 GI Bill allows service members to transfer generous education benefits to a dependent. We run a large-scale experiment to test whether active choice framing impacts US Army service members' decision to transfer benefits. Individuals who received email messages framing GI Bill use as an active choice between own use and transfer to a family member are more likely to pursue information about the benefit than individuals receiving outreach that does not frame the decision as an active choice. While we find no overall effect of framing on transfer, active choice increases transfer among service members with graduate degrees. |
| Keywords: | active choice, GI Bill, randomized controlled trial |
| JEL: | D91 H52 I24 |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12523&r=all |
| By: | Akay, Alpaslan (Department of Economics, School of Business, Economics and Law, Göteborg University); Karabulut, Gökhan (Istanbul University, Department of Economics); Terzioğlu, Bilge (Istanbul University, Department of Economics) |
| Abstract: | Studies show that people are concerned with other people’s consumption position in a varying degree with respect to the type of goods consumed and individual characteristics. Using both survey experiments and a large survey of subjective wellbeing(SWB) dataset, this paper presents robust associations between the degree of empathic capacity and positional concerns for consumption items involving pleasure and pain. The paper exploits both empathy quotient (EQ) and interpersonal reactivity index (IRI) measures of empathic capacity, i.e., dispositional empathy, which are sufficient measures capturing affective and cognitive aspects of empathy. Positional concerns are identified directly using a series of stated choice experiments and indirectly using the SWB approach. The main result of the paper is that positional concerns vary substantially with the levels of empathic capacity. Both EQ and IRI are found to be positively associated with positional concerns for “goods” (e.g., after-tax income, market value of a luxury car), reflecting a degree of selfregarded feelings and behavior to reduce personal distress, and negatively associated with positional concerns for “bads” (e.g., working hours and poverty rates), reflecting a degree of other-regarding feelings and behavior. The results are robust with respect to various checks including statistical specifications, reference groups, and omitted variables (e.g., prosocial behavior and competitivity) that could bias the results. |
| Keywords: | Dispositional Empathy; Survey Experiments; Positional Concerns |
| JEL: | C90 D63 |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:gunwpe:0773&r=all |