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The impact of information-based interventions on conservation behavior: A meta-analysis

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  • Nemati, Mehdi
  • Penn, Jerrod

Abstract

Interest in using information-based interventions to induce energy and water conservation has increased in recent years but have shown mixed evidence of their effectiveness. This paper seeks to answer two main questions - whether these programs are broadly effective in inducing conservation, and what are the most effective versions of these programs. Using a meta-analysis of 116 studies, we examine the effects of information-based interventions on residential customers' consumption of electricity, gas, and water. We find evidence of publication bias in this literature. After correcting for publication bias, meta-analysis results indicate that information-based interventions reduce consumption by an average of 6.24%, 95% CI [-10.72, -1.76]. In addition, we find that studies employing RCTs find smaller conservation effects, (-5.2%, 95% CI [−9.53, −0.51]). Our results show that the effectiveness of information-based interventions at the household level are significantly larger than those at the aggregate level (such as dorms and buildings). Finally, interventions with a shorter duration or with more frequent reporting show larger estimated effect sizes.

Suggested Citation

  • Nemati, Mehdi & Penn, Jerrod, 2020. "The impact of information-based interventions on conservation behavior: A meta-analysis," Resource and Energy Economics, Elsevier, vol. 62(C).
  • Handle: RePEc:eee:resene:v:62:y:2020:i:c:s0928765518303828
    DOI: 10.1016/j.reseneeco.2020.101201
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    as
    1. Ferraro, Paul J. & Miranda, Juan José, 2013. "Heterogeneous treatment effects and mechanisms in information-based environmental policies: Evidence from a large-scale field experiment," Resource and Energy Economics, Elsevier, vol. 35(3), pages 356-379.
    2. Ian Ayres & Sophie Raseman & Alice Shih, 2013. "Evidence from Two Large Field Experiments that Peer Comparison Feedback Can Reduce Residential Energy Usage," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 29(5), pages 992-1022, October.
    3. Hunt Allcott, 2015. "Site Selection Bias in Program Evaluation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(3), pages 1117-1165.
    4. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    5. Jerrod M Penn & Wuyang Hu, 2018. "Understanding Hypothetical Bias: An Enhanced Meta-Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(4), pages 1186-1206.
    6. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    7. Hummel, Dennis & Maedche, Alexander, 2019. "How effective is nudging? A quantitative review on the effect sizes and limits of empirical nudging studies," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 80(C), pages 47-58.
    8. Charles F. Manski, 2004. "Statistical Treatment Rules for Heterogeneous Populations," Econometrica, Econometric Society, vol. 72(4), pages 1221-1246, July.
    9. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    10. Djebbari, Habiba & Smith, Jeffrey, 2008. "Heterogeneous impacts in PROGRESA," Journal of Econometrics, Elsevier, vol. 145(1-2), pages 64-80, July.
    11. Nelson, Jon P., 2014. "Estimating the price elasticity of beer: Meta-analysis of data with heterogeneity, dependence, and publication bias," Journal of Health Economics, Elsevier, vol. 33(C), pages 180-187.
    12. Shrestha, Ram K. & Loomis, John B., 2001. "Testing a meta-analysis model for benefit transfer in international outdoor recreation," Ecological Economics, Elsevier, vol. 39(1), pages 67-83, October.
    13. Isaiah Andrews & Maximilian Kasy, 2019. "Identification of and Correction for Publication Bias," American Economic Review, American Economic Association, vol. 109(8), pages 2766-2794, August.
    14. Lindhjem, Henrik & Navrud, Ståle, 2008. "How reliable are meta-analyses for international benefit transfers?," Ecological Economics, Elsevier, vol. 66(2-3), pages 425-435, June.
    15. Paul J. Ferraro & Michael K. Price, 2013. "Using Nonpecuniary Strategies to Influence Behavior: Evidence from a Large-Scale Field Experiment," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 64-73, March.
    16. Mullaly, Cathy, 1998. "Home energy use behaviour: a necessary component of successful local government home energy conservation (LGHEC) programs," Energy Policy, Elsevier, vol. 26(14), pages 1041-1052, December.
    17. Burgess, Jacquelin & Nye, Michael, 2008. "Re-materialising energy use through transparent monitoring systems," Energy Policy, Elsevier, vol. 36(12), pages 4454-4459, December.
    18. John List & Craig Gallet, 2001. "What Experimental Protocol Influence Disparities Between Actual and Hypothetical Stated Values?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 20(3), pages 241-254, November.
    19. Wichman, Casey J. & Ferraro, Paul J., 2017. "A cautionary tale on using panel data estimators to measure program impacts," Economics Letters, Elsevier, vol. 151(C), pages 82-90.
    20. Sheila M. Olmstead, 2010. "The Economics of Managing Scarce Water Resources," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 4(2), pages 179-198, Summer.
    21. Allcott, Hunt & Rogers, Todd T, 2012. "How Long Do Treatment Effects Last? Persistence and Durability of a Descriptive Norms Intervention's Effect on Energy Conservation," Scholarly Articles 9804492, Harvard Kennedy School of Government.
    22. Daniel A. Brent & Joseph H. Cook & Skylar Olsen, 2015. "Social Comparisons, Household Water Use, and Participation in Utility Conservation Programs: Evidence from Three Randomized Trials," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 2(4), pages 597-627.
    23. Hristos Doucouliagos & T. D. Stanley, 2009. "Publication Selection Bias in Minimum‐Wage Research? A Meta‐Regression Analysis," British Journal of Industrial Relations, London School of Economics, vol. 47(2), pages 406-428, June.
    24. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    25. Allcott, Hunt & Rogers, Todd, 2012. "How Long Do Treatment Effects Last? Persistence and Durability of a Descriptive Norms Intervention's Effect on Energy Conservation," Working Paper Series rwp12-045, Harvard University, John F. Kennedy School of Government.
    26. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
    27. Steg, Linda, 2008. "Promoting household energy conservation," Energy Policy, Elsevier, vol. 36(12), pages 4449-4453, December.
    28. Penn, Jerrod & Hu, Wuyang, 2019. "Cheap talk efficacy under potential and actual Hypothetical Bias: A meta-analysis," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 22-35.
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    2. Bastola, Sapana & Penn, Jerrod & Blazier, Michael, 2022. "Assessing Hypothetical Bias in Nudging: Willingness to Pay for Consultation towards Improved Forest Management," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322477, Agricultural and Applied Economics Association.
    3. Yuan Wu & Jin Zhang & Shoulin Liu & Lianrui Ma, 2022. "Does Government-Led Publicity Enhance Corporate Green Behavior? Empirical Evidence from Green Xuanguan in China," Sustainability, MDPI, vol. 14(6), pages 1-32, March.
    4. Zhou, Jiehong & Zhang, Jing & Zhoui, Li, 2022. "Information interventions and health promotion behavior: evidence from China after cadmium rice events," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 25(4), September.
    5. Zhang, Chaoqun & Zha, Donglan & Jiang, Pansong & Wang, Fu & Yang, Guanglei & Salman, Muhammad & Wu, Qing, 2023. "The effect of customized information feedback on individual electricity saving behavior: Evidence from a field experiment in China," Technological Forecasting and Social Change, Elsevier, vol. 193(C).

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