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Andrew G. Meyer

Researcher at Marquette University

Publications -  36
Citations -  651

Andrew G. Meyer is an academic researcher from Marquette University. The author has contributed to research in topics: Intertemporal choice & Unemployment. The author has an hindex of 9, co-authored 35 publications receiving 447 citations. Previous affiliations of Andrew G. Meyer include University of Colorado Boulder & College of Business Administration.

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Does education increase pro-environmental behavior? Evidence from Europe

TL;DR: In this article, a regression discontinuity design was used to estimate the increase in educational attainment due to changes in compulsory education laws in 20th century Europe, and they found a positive local average treatment effect for 7 of the 8 pro-environmental behaviors.
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Heterogeneity in the preferences and pro-environmental behavior of college students: the effects of years on campus, demographics, and external factors

TL;DR: In this paper, the authors examined the characteristics of students that are associated with more environmentally friendly behavior and quantify the desirability of different environmental initiatives and found that the probability of pro-environmental behavior substantially increases with each additional year that a student spends on campus.
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Intertemporal Valuation of River Restoration

TL;DR: In this paper, the authors estimate the present value of immediate and delayed Minnesota River Basin improvements using discount rates directly estimated from the econometric model, and show that Minnesota residents lose almost half of the benefits when cleanup is delayed by 5 years.
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Environmental performance of state-owned and privatized eastern European energy utilities

TL;DR: In this paper, the authors compare the environmental performance of state-owned and privatized energy utility plants in Eastern Europe utilizing a novel panel data that includes reported sulfur dioxide emissions, energy input, and ownership status.
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Estimating discount factors for public and private goods and testing competing discounting hypotheses

TL;DR: In this paper, the authors developed a new framework, consistent with the random utility model, which directly models the intertemporal utility function and produces explicit maximum likelihood estimates of discounting parameters.