Public good games are at the core of many environmental challenges. In such social dilemmas, a large share of people endorse the norm of reciprocity. A growing literature complements this finding with the observation that many players exhibit a self-serving bias in reciprocation: “weak reciprocators” increase their contributions as a function of the effort level of the other players, but less than proportionally. In this paper, we build upon a growing literature on truth-telling to argue that weak reciprocity might be best conceived not as a preference, but rather as a symptom of an internal trade-off at the player level between (i) the truthful revelation of their private reciprocal preference, and (ii) the economic incentives they face (which foster free-riding). In truth-telling experiments, many players misrepresent private information when this is to their material benefit, but to a significantly lesser extent than what would be expected based on the profit-maximizing strategy. We apply this behavioral insight to strategic situations, and test whether the preference revelation properties of the classic voluntary contribution game can be improved by offering players the possibility to sign a classic truth-telling oath. Our results suggest that the honesty oath helps increase cooperation (by 33% in our experiment). Subjects under oath contribute in a way which is more consistent with (i) the contribution they expect from the other players and (ii) their normative views about the right contribution level. As a result, the distribution of social types elicited under oath differs from the one observed in the baseline: some free-riders, and many weak reciprocators, now behave as pure reciprocators.

This study explores whether an oath to honesty can reduce both shirking and lying among crowd-sourced internet workers. Using a classic coin-flip experiment, we first confirm that a substantial majority of Mechanical Turk workers both shirk and lie when reporting the number of heads flipped. We then demonstrate that lying can be reduced by first asking each worker to swear voluntarily on his or her honor to tell the truth in subsequent economic decisions. Even in this online, purely anonymous environment, the oath significantly reduced the percent of subjects telling “big” lies (by roughly 27%), but did not affect shirking. We also explore whether a truth-telling oath can be used as a screening device if implemented after decisions have been made. Conditional on flipping response, MTurk shirkers and workers who lied were significantly less likely to agree to an ex-post honesty oath. Our results suggest oaths may help elicit more truthful behavior, even in online crowd-sourced environments.

We propose a structural econometric model that incorporates altruism towards other household members into the willingness to pay for a public good. The model distinguishes preferences for public good improvements for oneself from preferences for improvements for other household members. We test for three different types of altruism - ‘pure self-interest’, ‘pure altruism’ and ‘public-good-focused non-pure altruism’. Using French contingent valuation data regarding air quality improvements, we find positive and significant degrees of concern for children under the age of 18, which are explained by determinants related to health and subjective air quality assessment. All other forms of pure or air-quality-focused altruism within the family are insignificant, including for children over 18, siblings, spouses, and parents. This result suggests that benefit estimates that do not consider altruism could undervalue improvements in air quality in France.

An acceleration index is proposed as a novel indicator to track the dynamics of COVID-19 in real-time. Using data on cases and tests in France for the period between the first and second lock-downs—May 13 to October 25, 2020—our acceleration index shows that the pandemic resurgence can be dated to begin around July 7. It uncovers that the pandemic acceleration was stronger than national average for the [59–68] and especially the 69 and older age groups since early September, the latter being associated with the strongest acceleration index, as of October 25. In contrast, acceleration among the [19–28] age group was the lowest and is about half that of the [69–78]. In addition, we propose an algorithm to allocate tests among French “départements” (roughly counties), based on both the acceleration index and the feedback effect of testing. Our acceleration-based allocation differs from the actual distribution over French territories, which is population-based. We argue that both our acceleration index and our allocation algorithm are useful tools to guide public health policies as France might possibly enter a third lock-down period with indeterminate duration.