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Meet the researcher: Dale Griffin, David Hardisty, Chuck Howard

Posted on February 22, 2019

Selected for the TFI long-term research grant: Dale Griffin, David Hardisty and Ray Charles "Chuck" Howard. They will study income prediction bias among workers in the "gig" economy. Who are the researchers and what motivated them to apply?

An important and previously unstudied aspect of employment in the "gig" or independent-worker economy is that independent contract work typically produces variable and uncertain income flows. In the present research we examine how well workers in the gig economy are able to forecast variations in their income, and whether systematic biases in these forecasts affect workers' financial well-being. We hypothesize that individuals who face such income variability will tend to over-predict their future income, and that this optimistic income prediction bias occurs because forecasters focus narrowly on their specific income prediction and do not sufficiently attend to the statistical distribution of their past and future income. We further expect that this income prediction bias has negative financial consequences for both the individuals who commit it and the firms for whom they work.

Finally, we hypothesize that prediction accuracy can be improved by prompting people to incorporate distributional information into their predictions through simple forecasting interventions. We test these three hypotheses in a series of studies using on-line survey participants working for piecework wages and drivers working for an internationally distributed ride-share provider. We first document the size and robustness of the income prediction bias and examine its economic significance for workers' personal finances, then test several manipulations to improve prediction accuracy. We also assess whether these manipulations lead to improvements in workers' financial security, job satisfaction, and personal well-being.

“We expect that income prediction bias has negative financial consequences for both the individuals who commit it and the firms for whom they work”

What motivated you to apply for the Think Forward Initiative research grant?

We were motivated to apply for the TFI research grant because the overarching goal of our research is to improve people’s financial well-being, which aligns with the goals of the Think Forward Initiative. This grant will support several studies on consumer income prediction, a PhD student who will coordinate the studies, and dissemination of the research results, none of which would be possible without the grant.


How do you expect that your research will contribute to people’s financial well-being?

If income prediction bias leads to negative financial outcomes, then improving income prediction accuracy has the potential to improve people’s financial well-being. Improvement may come about directly through communicating techniques to improve prediction to workers or their employers in the gig economy, or indirectly through influence on education and financial literacy. As there are implications for household financial predictions beyond the gig economy, through articles in the popular press we also hope to influence financial practices in households of all kinds. This research also has important practical implications for firms hiring workers in the gig economy. If income prediction bias leads to lower worker satisfaction and higher worker turnover, then improving income prediction accuracy can improve a firm's ability to retain workers, and reduce recruitment and retention costs. The research also has public policy implications for regulation of both worker rights and for the increasing practice of turning employees into independent contractors.

Dale W. Griffin is a Professor of Marketing and Behavioural Science at the UBC Sauder School of Business, University of British Columbia, and previously taught at the Stanford Graduate School of Business. He obtained his PhD from Stanford University, supervised by Amos Tversky and Lee Ross. Interested in forecasting, risk, social judgment and decision-making, he has published widely in Social and Cognitive Psychology, Marketing, and Management.

Co-researcher on the project is David J. Hardisty, Assistant Professor of Marketing & Behavioural Science at the UBC Sauder School of Business. He holds a PhD in Psychology from Columbia University, New York, and previously worked as a statistical consultant at the Institute for Social and Economic Research and Policy, Columbia University. His main interests are intertemporal choice, attribute framing and prosocial marketing.

The third researcher on the project is Ray Charles “Chuck” Howard, currently pursuing his PhD at the U.B.C. Sauder School of Business. His dissertation is entitled “Essays on consumer financial misprediction”.