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on Discrete Choice Models |
| By: | Guhl, Daniel (HU Berlin); Klapper, Daniel (HU Berlin) |
| Abstract: | The adoption decision for durable goods is intertemporal by definition. However, estimating utility and discount functions from revealed preference data using dynamic discrete choice models is difficult because of an inherent identification problem. To overcome this issue, we use stated preference data. Specifically, we employ the experimental design of Dubé, Hitsch, and Jindal (2014), where future prices are known and that elicits intertemporal adoption decisions for Bluetooth speakers in a discrete choice framework. We estimate several models of discounting (e.g., static, myopic, geometric, and quasi-hyperbolic) and find considerably lower discount factors than typical market interest rates would suggest. The values are also smaller compared to respondents’ matching-based discount factors, even though the correlation is positive and significant. Furthermore, there are substantial differences in discounting across respondents (i.e., heterogeneity in time-preferences) and lastly, there is no strong empirical evidence for quasi-hyperbolic discounting. Thus, the standard economic model seems to be appropriate for the data at hand. |
| Keywords: | intertemporal preferences; dynamic discrete choice models; durable goods adoption; |
| JEL: | C35 D9 D12 M31 |
| Date: | 2019–12–13 |
| URL: | http://d.repec.org/n?u=RePEc:rco:dpaper:216&r= |
| By: | Fiona Burlig; Louis Preonas; Matt Woerman |
| Abstract: | Groundwater is a key resource for agricultural production globally. Increasingly rapid aquifer drawdowns—as well as the policies intended to increase their sustainability—increase costs to agricultural producers, with unknown consequences. This paper provides the first large-scale empirical estimates of how farmers respond to changes in groundwater costs in one of the world's most valuable agricultural areas: California. Using rich administrative data and exogenous variation in the price of electricity, a key input into groundwater extraction, we find that farmers are very price responsive: we estimate large price elasticities of demand for electricity (-1.17) and groundwater (-1.12). We demonstrate that crop switching and fallowing are the main channel through which farmers respond to increases in groundwater costs. Using a static discrete choice model, we estimate that a counterfactual $10 per-acre-foot groundwater tax—a level consistent with California's sustainability targets—would lead farmers to reallocate 3.9 percent of cropland, with increases in fallowing and high-value fruit and nut perennials, and decreases in annual crops and low-value perennials. |
| JEL: | Q15 Q25 Q41 |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28706&r= |
| By: | Burchardi, Konrad (Institute for International Economic Studies, Stockholm University, BREAD, CEPR, CESifo, ThReD); de Quidt, Jonathan (Institute for International Economic Studies, Stockholm University, CAGE, CEPR, CESifo, ThReD); Gulesci, Selim (Trinity College, Dublin, BREAD, CEPR, EUDN, J-PAL, LEAP); Lerva, Benedetta (Mistra Center for Sustainable Markets, Stockholm); Tripodi, Stefano (Department of Economics, Copenhagen Business School) |
| Abstract: | Researchers frequently use variants of the Becker-DeGroot-Marschak (BDM) mechanism to elicit willingness to pay (WTP). These variants involve numerous incentive-irrelevant design choices, some of which carry advantages for implementation but may deteriorate participant comprehension or trust in the mechanism, which are well-known problems with the BDM. We highlight three such features and test them in the field in rural Uganda, a relevant population for many recent applications. Comprehension is very high, and 86 percent of participants bid optimally for an induced-value voucher, with little variation across treatments. This gives confidence for similar applications, and suggests the comprehension-expediency trade-off is mild. |
| Keywords: | JEL Classification: C90, C93, D44, O12 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:cge:wacage:541&r= |
| By: | Charles-Cadogan, G. (University of Leicester) |
| Abstract: | We extend Machina’s (1982) preference functional to abstract Wiener space. This has the advantage of extending utility functions to: infinite dimensional spaces; providing estimates for Machina’s (1982) nonlinear utility functional; and establishing a nexus between microfoundations of local utility, subjective probability, prospect theory, and elements of quantum decision theory without complex valued Hilbert spaces. For example, the class of Markowitz nonconvex utility functions (for which prospect theory’s value function is a special case) are vector valued functions in abstract Wiener space. Instead of preferences over probability distributions, the problem is transformed into one of preferences over states. Under Arzela-Ascoli Theorem, Wiener measure is the limit and unique conjugate prior in Wiener space. By a change of measure local subjective (posterior) probability is a Wiener integral. So, binary choice is stochastic. This poses a challenge for the transitivity axiom because intransitive preferences will occur in that space almost surely. Savage’s (1972) SEU fails in the space because probability is state dependent. JEL codes: C02 ; D81 |
| Keywords: | decision theory ; local utility ; nonlinear subjective probability ; abstract Wiener spaces |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:wcreta:70&r= |
| By: | Ryan Dew; Yuhao Fan |
| Abstract: | Understanding individual customers' sensitivities to prices, promotions, brand, and other aspects of the marketing mix is fundamental to a wide swath of marketing problems, including targeting and pricing. Companies that operate across many product categories have a unique opportunity, insofar as they can use purchasing data from one category to augment their insights in another. Such cross-category insights are especially crucial in situations where purchasing data may be rich in one category, and scarce in another. An important aspect of how consumers behave across categories is dynamics: preferences are not stable over time, and changes in individual-level preference parameters in one category may be indicative of changes in other categories, especially if those changes are driven by external factors. Yet, despite the rich history of modeling cross-category preferences, the marketing literature lacks a framework that flexibly accounts for \textit{correlated dynamics}, or the cross-category interlinkages of individual-level sensitivity dynamics. In this work, we propose such a framework, leveraging individual-level, latent, multi-output Gaussian processes to build a nonparametric Bayesian choice model that allows information sharing of preference parameters across customers, time, and categories. We apply our model to grocery purchase data, and show that our model detects interesting dynamics of customers' price sensitivities across multiple categories. Managerially, we show that capturing correlated dynamics yields substantial predictive gains, relative to benchmarks. Moreover, we find that capturing correlated dynamics can have implications for understanding changes in consumers preferences over time, and developing targeted marketing strategies based on those dynamics. |
| Date: | 2021–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2104.11702&r= |