Publications
This paper is concerned with the historical roots of gender equality. It proposes and empirically assesses a new determinant of gender equality: gender-specific outside options in the marriage market. In particular, enlarging women’s options besides marriage—even if only temporarily—increases their bargaining power with respect to men, leading to a persistent improvement in gender equality. We illustrate this mechanism focusing on Belgium, and relate gender-equality levels in the 19th century to the presence of medieval, female-only communities called beguinages that allowed women to remain single amidst a society that traditionally advocated marriage. Combining geo-referenced data on beguinal communities with 19th-century census data, we document that the presence of beguinages contributed to decrease the gender gap in literacy. The reduction is sizeable, amounting to a 12.3% drop in gender educational inequality. Further evidence of the beguinal legacy is provided leveraging alternative indicators of female agency.
Top incomes are often related to Pareto distribution. To date, economists have mostly used Pareto Type I distribution to model the upper tail of income and wealth distribution. It is a parametric distribution, with interesting properties, that can be easily linked to economic theory. In this paper, we first show that modeling top incomes with Pareto Type I distribution can lead to biased estimation of inequality, even with millions of observations. Then, we show that the Generalized Pareto distribution and, even more, the Extended Pareto distribution, are much less sensitive to the choice of the threshold. Thus, they can provide more reliable results. We discuss different types of bias that could be encountered in empirical studies and, we provide some guidance for practice. To illustrate, two applications are investigated, on the distribution of income in South Africa in 2012 and on the distribution of wealth in the United States in 2013.
This study examines the impact of personalized gender-based communication to encourage the screening of depression and seeking out mental health care consultation. An internet search engine advertisement was deployed on Bing, Microsoft during the COVID-19 pandemic lockdowns in the Provence–Alpes–Côte d'Azur (PACA) region in France during the month of May 2020, the height of the France lockdowns. A two-armed study was conducted with Arm A containing a non-personalized (control) advertisement and Arm B containing a personalized gender-based advertisement. 53,185 advertisements were shown between the two arms. Results show that receiving a personalized gender-based message increases the probability of clicking on the advertisement. However, upon clicking the advertisement, there was no significant difference in the completion of the depression questionnaire between the two groups. These results suggest that although personalized gender messaging is effective at drawing in a greater click rate, it did not increase, nor decreased, the conversion rate to monitor depression by self-assessment.
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.
The goal of this paper is to provide and examine an important extension of the usual portfolio insurance, namely to study the notion of portfolio performance participation. In this framework, the portfolio is based on two risky assets: the first one corresponds to a reserve asset, while the second one is considered as an active asset which has usually both a higher mean and a higher variance. We aim at insuring a given percentage of the reserve asset return, whatever the market fluctuations. The two main performance participation methods are the Option-Based Performance Participation (OBPP) and the Constant Proportion Performance Participation (CPPP). We compare these two portfolio strategies by means of various criteria such as their payoffs at maturity, their four first moments and their cumulative distributions functions. We also compare their dynamic hedging properties by computing in particular their deltas and vegas.
In finitely repeated public goods games, contributions are initially high, and gradually decrease over time. Two main explanations are consistent with this pattern: (i) the population is composed of free-riders, who never contribute, and conditional cooperators, who contribute if others do so as well; (ii) strategic players contribute to sustain mutually beneficial future cooperation, but reduce their contributions as the end of the game approaches. This paper analyzes experimentally these explanations, by manipulating group composition to form homogeneous groups on both the preference and the strategic ability dimensions. Our results highlight the role of strategic ability in sustaining contributions, and suggest that the interaction between the two dimensions also matters: we find that groups that sustain high levels of cooperation are composed of members who share a common inclination toward cooperation and also have the strategic abilities to recognize and reap the benefits of enduring cooperation.
Most patient-reported experience measures (PREMs) are paper-based, leading to a high burden for patients and care providers. The aim of this study was to (1) calibrate an item bank to measure patients’ experience of respect and dignity for adult patients with serious mental illnesses and (2) develop computerized adaptive testing (CAT) to improve the use of this PREM in routine practice. Patients with schizophrenia, bipolar disorder, and major depressive disorder were enrolled in this multicenter and cross-sectional study. Psychometric analyses were based on classical test and item response theories and included evaluations of unidimensionality, local independence, and monotonicity; calibration and evaluation of model fit; analyses of differential item functioning (DIF); testing of external validity; and finally, CAT development. A total of 458 patients participated in the study. Of the 24 items, 2 highly inter-correlated items were deleted. Factor analysis showed that the remaining items met the unidimensional assumption (RMSEA = 0.054, CFI = 0.988, TLI = 0.986). DIF analyses revealed no biases by sex, age, care setting, or diagnosis. External validity testing has generally supported our assumptions. CAT showed satisfactory accuracy and precision. This work provides a more accurate and flexible measure of patients’ experience of respect and dignity than that obtained from standard questionnaires.
In this paper, we investigate what are the drivers of cross-border equity acquisitions made by Sovereign Wealth Funds (SWFs) of the Gulf Cooperation Council (GCC) countries. GCC SWFs are considered as relatively opaque investors and strongly politicized, raising some concerns for perceived political and security risks. Using both Logit and ordered Logit models, we test if the usual determinants of SWFs investments still stand when we look at large or majority acquisitions made by GCC SWFs. Unlike results found in the literature investigating the determinants of SWFs cross-border investments, we find that GCC SWFs do not take into account the financial characteristics of the target firm by taking majority stakes, apart from its financial wealth. The economic, institutional and financial factors of the target country as well as the existence of trade agreements between both countries do not matter in their acquisition/control decision. We also find that firms operating in strategic sectors are targeted by GCC SWFs for diversification purposes but not for the purpose of acquisition or control. Overall, our results lend support to the hypothesis that GCC SWFs differ from other institutional investors in terms of acquisition decision strategy and that financial and commercial motives are not the exclusive target of their acquisition strategy.
This paper evaluates the effect on mental health of consecutive terrorist attacks in France in 2015 and 2016. We compile information about the three main terrorist attacks that struck France over this period and assess whether the potential effect on mental health (i.e., depression) of a terrorist attack is smoothed once people consider terrorist attacks as “the new normality.” We exploit data from the French Constances epidemiological survey and combine an event study strategy with a difference-in-difference approach to compare before-after changes in mental health the year of the attack with the same changes the year before. We show that the negative effect of a terrorist attack on mental health decreases over time from one attack to another, and disappears completely for the last attack. Socio-demographic composition of the sample, geographical or socio-demographic proximity to the victims or media exposure do not arise as factors responsible for this changing effect of terrorist attacks on mental health.
In the context of credit scoring, ensemble methods based on decision trees, such as the random forest method, provide better classification performance than standard logistic regression models. However, logistic regression remains the benchmark in the credit risk industry mainly because the lack of interpretability of ensemble methods is incompatible with the requirements of financial regulators. In this paper, we propose a high-performance and interpretable credit scoring method called penalised logistic tree regression (PLTR), which uses information from decision trees to improve the performance of logistic regression. Formally, rules extracted from various short-depth decision trees built with original predictive variables are used as predictors in a penalised logistic regression model. PLTR allows us to capture non-linear effects that can arise in credit scoring data while preserving the intrinsic interpretability of the logistic regression model. Monte Carlo simulations and empirical applications using four real credit default datasets show that PLTR predicts credit risk significantly more accurately than logistic regression and compares competitively to the random forest method.
