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We document three remarkable features of the Opower program, in which social comparison-based home energy reports are repeatedly mailed to more than six million households nationwide. First, initial reports cause high-frequency "action and backsliding," but these cycles attenuate over time. Second, if reports are discontinued after two years, effects are relatively persistent, decaying at 10–20 percent per year. Third, consumers are slow to habituate: they continue to respond to repeated treatment even after two years. We show that the previous conservative assumptions about post-intervention persistence had dramatically understated cost effectiveness and illustrate how empirical estimates can optimize program design.(JEL D12, D83, L94, Q41)

Public opinion researchers, campaigns, and political scientists often rely on self-predicted vote to forecast turnout, allocate resources, and measure political engagement. Despite its importance, little research has examined the accuracy of self-predicted vote responses. Seven pre-election surveys with postelection vote validation from three elections (N = 29,403) reveal several patterns. First, many self-predicted voters do not actually vote (flake-out). Second, many self-predicted nonvoters do actually vote (flake-in). This is the first robust observation of flake-in. Third, actual voting is more accurately predicted by past voting (from voter file or recalled) than by self-predicted voting. Finally, self-predicted voters differ from actual voters demographically. Actual voters are more likely to be White (and not Black), older, and partisan than actual nonvoters (i.e., there is participatory bias), but self-predicted voters and self-predicted nonvoters do not differ much. Vote self-prediction is 'biased' in that it misleadingly suggests that there is no participatory bias. [Reprinted by permission of Sage Publications Inc., copyright holder.]

Public opinion researchers, campaigns, and political scientists often rely on self-predicted vote to forecast turnout, allocate resources, and measure political engagement. Despite its importance, little research has examined the accuracy of self-predicted vote responses. Seven pre-election surveys with postelection vote validation from three elections ( N = 29,403) reveal several patterns. First, many self-predicted voters do not actually vote (flake-out). Second, many self-predicted nonvoters do actually vote (flake-in). This is the first robust observation of flake-in. Third, actual voting is more accurately predicted by past voting (from voter file or recalled) than by self-predicted voting. Finally, self-predicted voters differ from actual voters demographically. Actual voters are more likely to be White (and not Black), older, and partisan than actual nonvoters (i.e., there is participatory bias), but self-predicted voters and self-predicted nonvoters do not differ much. Vote self-prediction is "biased" in that it misleadingly suggests that there is no participatory bias.