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Simpler is better: Predicting consumer vehicle purchases in the short run.

ABSTRACT: When agencies such as the US Environmental Protection Agency (EPA) establish future greenhouse gas emissions standards for new vehicles, forecasting future vehicle purchases due to changes in fuel economy and prices provides insight into regulatory impacts. We compare predictions from a nested logit model independently developed for US EPA to a simple model where past market share predicts future market share using data from model years 2008, 2010, and 2016. The simple model outperforms the nested logit model for all goodness-of-prediction measures for both prediction years. Including changes in vehicle price and fuel economy increases bias in forecasted market shares. This bias suggests price increases are correlated with unobserved increases in vehicle quality, changes in preferences, or brand-specific changes in market size but not cost pass-through. For 2010, past shares predict better than a nested logit model despite a major shock, the economic disruption caused by the Great Recession. Observed share changes during this turbulent period may offer upper bounds for policy changes in other contexts: the largest observed change in market share across the two horizons is 6.6% for manufacturers in 2016 and 3.4% for an individual vehicle in 2010.

SUBMITTER: Doremus J

PROVIDER: S-EPMC6691498 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Simpler is better: Predicting consumer vehicle purchases in the short run.

Doremus Jacqueline J Helfand Gloria G Liu Changzheng C Donahue Marie M Kahan Ari A Shelby Michael M

Energy policy 20190601

When agencies such as the US Environmental Protection Agency (EPA) establish future greenhouse gas emissions standards for new vehicles, forecasting future vehicle purchases due to changes in fuel economy and prices provides insight into regulatory impacts. We compare predictions from a nested logit model independently developed for US EPA to a simple model where past market share predicts future market share using data from model years 2008, 2010, and 2016. The simple model outperforms the nest ...[more]

PMID: 31409938

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Project description:Kenneth Gillingham is an Associate Professor of Economics at Yale University, with a primary appointment in the School of Forestry & Environmental Studies. In 2015 to 2016, he served as the Senior Economist for Energy and the Environment at the White House Council of Economic Advisers. His research interests cover energy and environmental economics, industrial organization, technological change, and energy modeling. He held a Fulbright to New Zealand and has worked for Resources for the Future and Pacific Northwest National Laboratory. He received a PhD and two MS degrees from Stanford University and an AB from Dartmouth College. Christopher Knittel is the George P. Shultz Professor of Applied Economics in the Sloan School of Management at the Massachusetts Institute of Technology (MIT). He is also the Director of MIT's Center for Energy and Environmental Policy Research, which serves as the hub for social science research on energy and the environmental since the late 1970s. Professor Knittel is also the Co-Director of the MIT Energy Initiative's Electric Power System Low Carbon Energy Center and a co-director of The E2e Project, a research initiative between MIT, UC Berkeley, and the University of Chicago to undertake rigorous evaluation of energy efficiency investments. Jing Li holds the inaugural William Barton Rogers Career Development Chair of Energy Economics at the MIT Sloan School of Management. From 2017-2018, Jing Li was a Postdoctoral Associate of the MIT Energy Initiative. Jing's research interests lie in energy economics and industrial organization, focusing on development and adoption of new technologies. Her most recent work examines compatibility and investment in electric vehicle recharging networks in the United States and cost pass-through in the E85 retail market. Jing received double BSc degrees in Mathematics and Economics from MIT in 2011 and her PhD in Economics from Harvard in 2017. Marten Ovaere is a Postdoctoral Associate in the School of Forestry & Environmental Studies of Yale University. His research interests lie in energy and environmental economics, with a focus on electricity markets, carbon pricing, and renewable energy. Marten holds a MSc in Economics, a MSc in Energy Engineering, and a PhD in Economics from KU Leuven. Mar Reguant is an Associate Professor in Economics at Northwestern University. She received her PhD from MIT in 2011. Her research uses high-frequency data to study the impact of auction design and environmental regulation on electricity markets and energy-intensive industries. She has numerous awards, including a Sloan Research Fellowship in 2016, the Sabadell Prize for Economic Research in 2017, a Presidential Early Career Award for Scientists and Engineers award in 2019, and the European Association of Environmental and Resource Economists Award for Researchers in Environmental Economics under the Age of Forty in 2019.

Project description:ImportanceData are needed to evaluate community interventions to reduce consumption of sugary drinks. Supermarket sales data can be used for this purpose.ObjectiveTo compare beverage sales in Howard County, Maryland (HC), with sales in comparison stores in a contiguous state before and during a 3-year campaign to reduce consumption of sugary beverages.Design, setting, and partipicantsThis observational experiment with a control group included 15 HC supermarkets and 17 comparison supermarkets. Weekly beverage sales data at baseline (January 1 to December 31, 2012) and from campaign years 1 to 3 (January 1, 2013, through December 31, 2015) were analyzed. A difference-in-differences (DID) regression compared the volume sales per product per week in the HC and comparison stores, controlling for mean product price, competitor's product price, product size, weekly local temperature, and manufacturer.ExposuresThe campaign message was to reduce consumption of all sugary drinks. Television advertising, digital marketing, direct mail, outdoor advertising, social media, and earned media during the 3-year period created 17 million impressions. Community partners successfully advocated for public policies to encourage healthy beverage consumption in schools, child care, health care, and government settings.Main outcomes and measuresSales were tracked of sugary drinks highlighted in the campaign, including regular soda, sports drinks, and fruit drinks. Sales of diet soda and 100% juice were also tracked. Sales data are expressed as mean fluid ounces sold per product, per store, per week.ResultsRegular soda sales in the 15 HC supermarkets decreased (-19.7%) from 2012 through 2015, whereas sales remained stable (0.8%) in the 17 comparison supermarkets (DID adjusted mean, -369 fl oz; 95% CI, -469 to -269 fl oz; P < .01). Fruit drink sales decreased (-15.3%) in HC stores and remained stable (-0.6%) in comparison stores (DID adjusted mean, -342 fl oz; 95% CI, -466 to -220 fl oz; P < .001). Sales of 100% juice decreased more in HC (-15.0%) than comparison (-2.1%) stores (DID mean, -576 fl oz; 95% CI, -776 to -375 fl oz; P < .001). Sales of sports drinks (-86.3 fl oz; 95% CI, -343.6 to 170.9 fl oz) and diet soda (-17.8 in HC stores vs -11.3 in comparison stores; DID adjusted mean, -78.9 fl oz; 95% CI, -182.1 to 24.4 fl oz) decreased in both communities, but the decreases were not significantly different between groups.Conclusions and relevanceA locally designed, multicomponent campaign to reduce consumption of sugary drinks was associated with an accelerated decrease in sales of regular soda, fruit drinks, and 100% juice. This policy-focused campaign provides a road map for other communities to reduce consumption of sugary drinks.

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Simpler is better: Predicting consumer vehicle purchases in the short run.

Publications

Simpler is better: Predicting consumer vehicle purchases in the short run.

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