Behavioral scientists are consistently no better than, and often worse than, simple heuristics and models; why have markets & experience not eliminated their biases entirely?

Simple models predict behavior at least as well as behavioral scientists. Dillon Bowen. arXiv, August 3, 2022. https://arxiv.org/abs/2208.01167

Abstract: How accurately can behavioral scientists predict behavior? To answer this question, we analyzed data from five studies in which 640 professional behavioral scientists predicted the results of one or more behavioral science experiments. We compared the behavioral scientists’ predictions to random chance, linear models, and simple heuristics like “behavioral interventions have no effect” and “all published psychology research is false.” We find that behavioral scientists are consistently no better than - and often worse than - these simple heuristics and models. Behavioral scientists’ predictions are not only noisy but also biased. They systematically overestimate how well behavioral science “works”: overestimating the effectiveness of behavioral interventions, the impact of psychological phenomena like time discounting, and the replicability of published psychology research

Keywords: Forecasting, Behavioral science

3 Discussion

Critical public policy decisions depend on predictions from behavioral scientists. In this paper, we asked how accurate those predictions are. To answer this question, we compared the predictions of 640 behavioral scientists to those of simple mathematical models on five prediction tasks. Our sample included a variety of behavioral scientists: economists, psychologists, and business professionals from academia, industry, and government. The prediction tasks also covered various domains, including text-message interventions to increase vaccination rates, behavioral nudges to increase exercise, randomized control trials, incentives to encourage effort, and attempts to reproduce published psychology studies. The models to which we compared the behavioral scientists were deliberately simple, such as random chance, linear interpolation, and heuristics like “behavioral interventions have no effect” and “all published psychology research is false.” We consistently found that behavioral scientists are no better than - and often worse than - these simple heuristics and models. In the exercise, flu, and RCT studies, null models significantly outperformed behavioral scientists. These null models assume that behavioral treatments have no effect; behavioral interventions will not increase weekly gym visits, text messages will not increase vaccination rates, and nudges will not change behavior. As we can see in Table 1, compared to behavioral scientists, null models are nearly indistinguishable from the oracle. In the effort study, linear interpolations performed at least as well as professional economists. These interpolations assumed that all psychological phenomena are inert; people do not exhibit risk aversion, time discounting, or biases like framing effects. In the reproducibility study, professional psychologists’ Brier scores were virtually identical to those of a null model, which assumed that all published psychology research is false. Professional psychologists were significantly worse than both linear regression and random chance. Notably, the linear regression model used data from the reproducibility study, which were not accessible to psychologists during their participation. While this is not a fair comparison, we believe it is a useful comparison, as the linear regression model can serve as a benchmark for future attempts to predict reproducibility. Why is it so hard for behavioral scientists to outperform simple models? One possible answer is that human predictions are noisy while model predictions are not [Kahneman et al., 2021]. Indeed, there is likely a selection bias in the prediction tasks we analyzed. Recall that most of the prediction tasks asked behavioral scientists to predict the results of ongoing or recently completed studies. Behavioral scientists presumably spend time researching questions that have not been studied exhaustively and do not have obvious answers. In this case, the prediction tasks were likely exceptionally challenging, and behavioral scientists’ expertise would be of little use. However, behavioral scientists’ predictions are not only noisy but also biased. Previous research noted that behavioral scientists overestimate the effectiveness of nudges [DellaVigna and Linos, 2022, Milkman et al., 2021]. Our research extends these findings, suggesting that behavioral scientists believe behavioral science generally “works” better than it does. Behavioral scientists overestimated the effectiveness of behavioral interventions in the exercise, flu, and RCT studies. In the exercise study, behavioral scientists significantly overestimated the effectiveness of all 53 treatments, even after correcting for multiple testing. Economists overestimated the impact of psychological phenomena in the effort study, especially for motivational crowding out, time discounting, and social preferences. Finally, psychologists significantly overestimated the replicability of published psychology research in the reproducibility study. In general, behavioral scientists overestimate not only the effect of nudges, but also the impact of psychological phenomena and the replicability of published behavioral science research. Behavioral scientists’ bias can have serious consequences. A recent study found that policymakers were less supportive of an effective climate change policy (carbon taxes) when a nudge solution was also available [Hagmann et al., 2019]. However, accurately disclosing the nudge’s impact shifted support back towards carbon taxes and away from the nudge solution. In general, when behavioral scientists exaggerate the effectiveness of their work, they may drain support and resources from potentially more impactful solutions. Our results raise many additional questions. For example, is it only behavioral scientists who are biased, or do people, in general, overestimate how well behavioral science works? The general public likely has little exposure to RCTs, social science experiments, and academic psychology publications, so there is no reason to expect that they are biased in either direction. Then again, the little exposure they have had likely gives an inflated impression of behavioral science’s effectiveness. For example, a TED talk with 64 million as of May 2022 touted the benefits of power posing, whereby one can reap the benefits of improved self-confidence and become more likely to succeed in life by adopting a powerful pose for one minute [Carney et al., 2010, Cuddy, 2012]. However, the power posing literature was based on p-hacked results [Simmons and Simonsohn, 2017], and researchers have since found that power posing yields no tangible benefits [Jonas et al., 2017]. Additionally, people may generally overestimate effects due to the “What you see is all there is” (WYSIATI) bias [Kahneman, 2011]. For example, the exercise study asked behavioral scientists to consider, among other treatments, how much more people would exercise if researchers told them they were “gritty.” After the initial “gritty diagnosis,” dozens of other factors determined how often participants in that condition went to the gym during the following four-week intervention period. Work schedule, personal circumstances, diet, mood changes, weather, and many other factors also played key roles. These other factors may not have even crossed the behavioral scientists’ minds. The WYSIATI bias may have caused them to focus on the treatment and ignore the noise of life that tempers the treatment’s signal. Of course, this bias is likely to cause everyone, not only behavioral scientists, to overestimate the effectiveness of behavioral interventions and the impact of psychological phenomena. If people generally overestimate how well behavioral science works, are they more or less biased than behavioral scientists? Experimental economics might suggest that behavioral scientists are less biased because people with experience tend to be less biased in their domain of expertise. For example, experienced sports card traders are less susceptible to the endowment effect [List, 2004], professional traders exhibit less ambiguity aversion than novices [List and Haigh, 2010], experienced bidders are immune to the winner’s curse [Harrison and List, 2008], and CEOs who regularly make high-stakes decisions are less susceptible to possibility and certainty effects [List and Mason, 2011]. Given that most people have zero experience with behavioral science, they should be more biased than behavioral scientists. Then again, there are at least three reasons to believe that behavioral scientists should be more biased than the general population: selection bias, selective exposure, and motivated reasoning. First, behavioral science might select people who believe in its effectiveness. On the supply side, students who apply to study psychology for five years on a measly PhD stipend are unlikely to believe that most psychology publications fail to replicate. On the demand side, marketing departments and nudge units may be disinclined to hire applicants who believe their work is ineffective. Indeed, part of the experimental economics argument is that markets filter out people who make poor decisions [List and Millimet, 2008]. The opposite may be true of behavioral science: the profession might filter out people with an accurate assessment of how well behavioral science works. Second, behavioral scientists are selectively exposed to research that finds large and statistically significant effects. Behavioral science journals and conferences are more likely to accept papers with significant results. Therefore, most of the literature behavioral scientists read promotes the idea that behavioral interventions are effective and psychological phenomena substantially influence behavior. However, published behavioral science research often fails to replicate. Lack of reproducibility plagues not only behavioral science [Collaboration, 2012, 2015, Camerer et al., 2016, Mac Giolla et al., 2022] but also medicine [Freedman et al., 2015, Prinz et al., 2011], neuroscience [Button et al., 2013], and genetics [Hewitt, 2012, Lawrence et al., 2013]. Scientific results fail to reproduce for many reasons, including publication bias, p-hacking, and fraud [Simmons et al., 2011, Nelson et al., 2018]. Indeed, most evidence that behavioral scientists overestimate how well behavioral science works involves asking them to predict the results of nudge studies. However, there is little to no evidence that nudges work after correcting for publication bias [Maier et al., 2022]. Even when a study successfully replicates, the effect size in the replication study is often much smaller than that reported in the original publication [Camerer et al., 2016, Collaboration, 2015]. For example, the RCT study paper estimates that the academic literature overstates nudges’ effectiveness by a factor of six [DellaVigna and Linos, 2022]. Finally, behavioral scientists might be susceptible to motivated reasoning [Kunda, 1990, Epley and Gilovich, 2016]. As behavioral scientists, we want to believe that our work is meaningful, effective, and true. Motivated reasoning may also drive selective exposure [B´enabou and Tirole, 2002]. We want to believe our work is effective, so we disproportionately read about behavioral science experiments that worked. Our analysis finds mixed evidence of the relationship between experience and bias in behavioral science. The RCT study informally examined the relationship between experience and bias for behavioral scientists predicting nudge effects and concluded that more experienced scientists were less biased. While we also estimate that more experienced scientists are less biased, we do not find statistically significant pairwise differences between the novice, moderately experienced, and most experienced scientists. Even if the experimental economics argument is correct that behavioral scientists are less biased than the general population, why are behavioral scientists biased at all? The experimental economics literature identifies two mechanisms to explain why more experienced people are less biased [List, 2003, List and Millimet, 2008]. First, markets filter out people who make poor decisions. Second, experience teaches people to think and act more rationally. We have already discussed that the first mechanism might not apply to behavioral science. And, while our results are consistent with the hypothesis that behavioral scientists learn from experience, they still suggest that even the most experienced behavioral scientists overestimate the effectiveness of nudges. The remaining bias for the most experienced scientists is larger than the gap between the most experienced scientists and novices. Why has experience not eliminated this bias entirely? Perhaps the effect of experience competes with the forces of “What you see is all there is,” selection bias, selective exposure, and motivated reasoning such that experience mitigates but does not eliminate bias in behavioral science. Finally, how can behavioral scientists better forecast behavior? One promising avenue is to use techniques that help forecasters predict political events [Chang et al., 2016, Mellers et al., 2014]. For example, the best political forecasters begin with base rates and then adjust their predictions based on information specific to the event they are forecasting [Tetlock and Gardner, 2016]. Behavioral scientists’ predictions would likely improve by starting with the default assumptions that behavioral interventions have no effect, psychological phenomena do not influence behavior, and published psychology research has a one in three chance of replicating [Collaboration, 2012]. Even though these assumptions are wrong, they are much less wrong than what behavioral scientists currently believe.

Both laypersons & police officers were worse at detecting deception when judging handcuffed suspects compared to non-handcuffed suspects, while not affecting their judgement bias; police officers were also overconfident in their judgements

Looking guilty: Handcuffing suspects influences judgements of deception. Mircea Zloteanu,Nadine L. Salman,Eva G. Krumhuber,Daniel C. Richardson. Journal of Investigative Psychology and Offender Profiling, September 7 2022. https://doi.org/10.1002/jip.1597

Abstract: Veracity judgements are important in legal and investigative contexts. However, people are poor judges of deception, often relying on incorrect behavioural cues when these may reflect the situation more than the sender's internal state. We investigated one such situational factor relevant to forensic contexts: handcuffing suspects. Judges—police officers (n = 23) and laypersons (n = 83)—assessed recordings of suspects, providing truthful and deceptive responses in an interrogation setting where half were handcuffed. Handcuffing was predicted to undermine efforts to judge veracity by constraining suspects' gesticulation and by priming stereotypes of criminality. It was found that both laypersons and police officers were worse at detecting deception when judging handcuffed suspects compared to non-handcuffed suspects, while not affecting their judgement bias; police officers were also overconfident in their judgements. The findings suggest that handcuffing can negatively impact veracity judgements, highlighting the need for research on situational factors to better inform forensic practice.

7 DISCUSSION

The present research explored whether a situational factor related to interrogation procedures (i.e., the use of handcuffs on suspects) can negatively impact veracity judgements. Confirming our hypothesis, the handcuffing manipulation affected both laypersons' and police officers' ability to detect deception (i.e., H2 was supported; moderate effect size). Statements made by handcuffed suspects were harder to classify for both police officers and laypersons. Converting the handcuffing effect size (ξ = 0.37) to more intuitive estimates (as recommended by Fritz et al., 2012), we obtain a Number Needed to Treat (NNT) of 5.01. Meaning for every fifth person that is interviewed wearing handcuffs we would expect one more misclassification of veracity. Or, based on the Common Language (CL) effect size, the probability that a suspect selected at random from the handcuffed condition is misclassified in terms of statement veracity compared to a suspect from the non-handcuffed condition is 64.3%. This decrease in accuracy was attributable to the study's manipulation affecting veracity discriminability rather than a shift in judgement response tendencies (H1 was not supported), as all judges remained truth-biased overall (H3 was not supported; NNT = 10.54, CL = 56.7%). For both judge groups, truths were easier to detect than lies (NNT = 12.02, CL = 55.9%; replicating the veracity effect; Levine et al., 1999).

Unsurprisingly, police officers did not perform better at judging veracity than laypersons (see Aamodt & Custer, 2006), and judging handcuffed suspects made this process even harder. However, the manipulation did not affect officers' response bias (H5 was not supported). This contrasts research arguing for a veracity detection reversal in professionals (i.e., police officers showing higher lie detection, but lower truth detection compared to laypersons; Meissner & Kassin, 2002). The similarity in response patterns with laypersons indicates that police officers were not overall more suspicious of suspects. This could, however, be due to the relatively junior sample of officers recruited (see Table 1), or, potentially, due to the “suspects” being naïve students which may have mitigated lie bias towards them; however, we note that the instructions never mention the status of suspects.

A more worrying result, and per our prediction, police officers displayed higher confidence while being no more accurate than laypersons (i.e., H4 was supported; moderate-to-large effect size; NNT = 3.66, CL = 70.2%), even showing a trend towards lower accuracy (e.g., below chance lie detection; NNT = 5.88, CL = 62.2%). This parallels findings of professionals tending to be overconfident in their veracity judgements (Aamodt & Custer, 2006; DePaulo & Pfeifer, 1986; Masip et al., 2016). While the police officers' level of experience may have not been sufficient to bias their judgements in the direction of a lie, it was able to increase their confidence in catching liars (e.g., Masip et al., 2016).

Overall, judges performed worse at discriminating veracity when viewing handcuffed suspects, supporting our assertions that situational factors can negatively impact the discriminability between deceptive and honest suspects (for a more detailed breakdown of the honesty scale data, see SI). Such effects may have serious ramifications for the forensic domain (Verschuere et al., 2016), especially when considering the already poor deception detection rates in the absence of the handcuffing manipulation. Interestingly, both laypersons and police officers were less confident in their judgements when they watched the handcuffed (vs. non-handcuffed) videos (NNT = 5.32, CL = 63.6%). Judges may have found deception detection more difficult when suspects were handcuffed, tempering their confidence.

These results illustrate that situational elements can impact the perception and judgement of both laypersons and police officers. Reducing the impact of such artificial factors could improve forensic practices and deception detection procedures, whilst reducing the risk of potential miscarriages of justice. Such effects are especially pertinent in situations of judgement under uncertainty where external and contextual information often influence the perception of ambiguous or ambivalent information (Masip et al., 2009; Mobbs et al., 2006). In line with research on investigative interviewing, it would seem recommendable that the space and circumstances under which an interrogation takes place are comfortable and do not restrict the individual (Goodman-Delahunty et al., 2014; Kelly et al., 2013).

7.1 Future directions

The current work sought to highlight the effects of situational factors on veracity judgements, particularly in forensic contexts. Future research could elaborate on the different ways in which handcuffing affects senders and judges by separating their influence on suspect perceptions (e.g., handcuffs as a visual cue of criminality; Stiff et al., 1992) from the effect on suspects' ability to gesticulate (within-sender features). For this, handcuffed and non-handcuffed suspects' movements could be restricted by asking them, for example, to place their hands flat on a table throughout the interrogation. This would equate the nonverbal differences whilst having the presence/absence of handcuffs as the only factor that differs between conditions. Alternatively, the videos could be edited to show the same suspect with or without handcuffs, revealing whether any impressions brought about by being handcuffed are due to the presence of external visual cues.

Considerations should also be given to the content of the stimuli themselves. An analysis of the videos may reveal verbal, paraverbal, and/or nonverbal cues which may aid in understanding the current findings. Such an investigation could uncover if behavioural differences between the liars and truth-tellers are indeed reduced by handcuffing and if differences in impression management are brought about by the manipulation (e.g., handcuffed suspects may “compensate” for their restricted gesticulation by modifying their speech and, by extension, their verbal cues may differ; see Verschuere et al., 2021).

Additionally, given the within-sender variability typically seen in deception research (Levine, 2010; Zloteanu, Bull, et al., 2021), the current stimulus set may be expanded to show a larger number of senders which would provide more precise effect size estimates and reduced uncertainty (Levine et al., 2022). Future research should also employ a more in-depth statistical approach (i.e., multi-level modelling) that accounts for both sender and decoder variability. This may be especially relevant in understanding if handcuffing interacts with senders' demeanour and judges' expectations. The possibility exists that the manipulation may not affect all individuals to the same degree or in the same manner (see DAG in SI for the potential influence of within/between subject and stimuli variance on the judgement process).

Subsequent work may also explore the effect of handcuffing on the relationship quality between suspect and interrogator (also, see SI). Due to the interactive nature of the interrogation task, handcuffs may have affected the rapport between the interrogator and suspect, which in turn could shape the behaviour of suspects (Kassin et al., 2003; Paton et al., 2018). The present manipulation demonstrates that deception detection does not happen in isolation. Future studies investigating veracity judgements should expand the range of factors being considered, both within the lab and in the real world.

7.2 Limitations

The issue of generalisability in the deception field is rarely addressed; nonetheless, a few elements of the current research must be considered. First, the type of lie told by suspects related to personal information that liars misrepresented. It can be argued that differences in performance and judgement may emerge if other types of lies (e.g., lies about transgressions) are employed (Levine, Kim, & Blair, 2010; cf. Hartwig & Bond, 2014; Hauch et al., 2014). Second, although some have argued that using students instead of real suspects may impact the detection rate (see O’Sullivan et al., 2009), both empirical investigations and meta-analyses report that deception detection is unaffected by whether the sender is a student or not (Hartwig & Bond, 2014; Zhang et al., 2013), nor do police officers show better accuracy rates even in naturalistic high-stakes settings (Hartwig, 2004; Meissner & Kassin, 2002). However, using different type of senders may influence perceptions and judgements.

Presently, it is difficult to separate the effect of handcuffing on judges' perception (i.e., pure external features) from that on sender performance (i.e., within-sender features) as our manipulation may have been affecting either or both. For example, handcuffing could attenuate behavioural differences between liars and truth-tellers resulting in poorer overall veracity discrimination. However, considering the dynamics between the interrogator and the suspects, being handcuffed could have also prompted senders as to the added scrutiny and behavioural restrictions, and compensated through increased impression management to produce a more convincing performance (Buller & Burgoon, 1996; Burgoon et al., 1996). The interplay between the interviewee and the interviewer is an important unknown, as some response variability may be due to the interrogator himself, given that rapport strongly influences interviewing outcomes (Abbe & Brandon, 2013).

The interrogation style used should also be weighed. Currently, while we did not find any effect of probing, this element could not be explored in depth due to a lack of variability in the use of the three probes by the interrogator (see SI). The literature on probing is equivocal on its use impacting veracity judgements (Buller et al., 1991). Nonetheless, it may impact rapport building and disclosure (Paton et al., 2018). Different probes may result in changes in the interdynamics of the interrogator and suspect, as well as subsequent judges (e.g., biasing impressions based on the valence of the probe used during the questioning). Future research could consider manipulating (e.g., standardising) the probing element to investigate how it interacts with the handcuffing element (e.g., Granhag & Strömwall, 2001); specific probes may bolster (e.g., negative) or attenuate (e.g., positive) the effects of handcuffing.

Finally, a more pronounced limitation is the relatively small and unbalanced sample. Underpowered studies are less likely to find true effects (i.e., Type II error), have a higher chance of found effects being statistical artefacts (i.e., Type I error), inflate estimates of true effects (i.e., Type M error), and have lower replicability (Fraley & Vazire, 2014; Gelman & Carlin, 2014). For instance, the CIs around the handcuffing effect indicate that the data is compatible with a wide range of effect sizes, from large and of potential interest (ξ = 0.58) to small and potentially unimportant (ξ = 0.10). Thus, we advise readers to interpret the results with care. Still, considering the forensic-relevant sample alongside the implications of our findings (especially for miscarriages of justice), on balance, we consider that the value of the research outweighs its drawbacks (Eckermann et al., 2010; Sterling et al., 1995).

To increase usability, we report all necessary measurements of uncertainty and variability (Calin-Jageman & Cumming, 2019), permitting future hypothesis generation and integration into meta-analyses (Cumming, 2014; Fritz et al., 2012). For example, replications can consider the effect sizes reported and their confidence intervals to estimate future results (e.g., prediction intervals; Cumming, 2008), and calculate the statistical power needed to reproduce the effect (e.g., considering ξ33%; see, Simonsohn, 2015).

Overall life satisfaction: Satisfaction with family life and health are the strongest predictors while satisfaction with income and leisure time are the weakest predictors

Happiness, domains of life satisfaction, perceptions, and valuation differences across genders. Stefani Milovanska-Farrington, Stephen Farrington. Acta Psychologica, Volume 230, October 2022, 103720. https://doi.org/10.1016/j.actpsy.2022.103720

Highlights

• Using German panel data, we examine the association between satisfaction with domains of life, values, and relative perceptions and overall subjective well-being. We also explore valuation differences between men and women.

• The findings suggest that perceived satisfaction with different domains of life has a significant impact on overall life satisfaction.

• We also find that how happy people believe they are with different life aspects is a stronger determinant of their overall life satisfaction than their actual circumstances.

• Family and health satisfaction consistently matter the most for overall life satisfaction while financial satisfaction is least important for both women and men in almost all specifications. We also find gender differences in values.

• Family and health satisfaction matter the most for overall well-being of both men and women. However, men exhibit higher valuation of work satisfaction than women, whereas women value their partner's happiness more than men.

Abstract: Happiness is strongly correlated with goal attainment, productivity, mental health and suicidal risk. This paper examines the association between satisfaction with areas of life and overall life satisfaction, the importance of relative perceptions compared to absolute measures in predicting overall life satisfaction, and differences in the domains of life which are the most strongly related to overall life satisfaction of men and women. The findings suggest that relative perceptions have a large statistically significant association with SWB. Satisfaction with family life and health are the strongest predictors while satisfaction with income and leisure time are the weakest predictors of overall life satisfaction for both genders. Work satisfaction is more important for men than for women, whereas partner's happiness is more valued by female respondents. Satisfaction with household compared to personal income has a larger association with life satisfaction in all subsamples except employed women. Understanding the perceived and factual determinants of happiness has urgent implications discussed in the article.

Keywords: Subjective well-beingSatisfaction with areas of lifePerceptionsValuesGender differences

6. Discussion and implications

In this section, we provide some potential explanations of our finding that perceptions are a better predictor of happiness than variables reflecting actual circumstances, and explore implications of the study.

First, individuals' satisfaction is a function of their target, a notion known as the aspiration theory, or multiple discrepancies theory, in psychology. It suggests that individuals are not able or willing to make absolute judgements. They form aspirations by comparing themselves to the past, expected future or the surrounding environment, and evaluate outcomes based on the discrepancies between their aspired goals and current circumstances (Stutzer and Henne, 2014). Therefore happiness depends on the gap between aspiration and achievement rather than the achievement itself (Michalos 1991). For example, Stutzer (2004) finds a negative correlation between a larger gap between aspiration and income, and happiness. Similarly, happiness depends on people's reference group. Literature has found a negative relationship between happiness, and income (Clark and Oswald, 1996; McBride, 2001; Guilbert and Paul, 2009) and education of the comparison group (Nikolaev, 2016). If this is true, social comparisons, aspiration and gaps between goals and achievements explain why personal interpretation of the facts has a greater association with overall life satisfaction as compared to the true state of reality.

Second, our results are consistent with the findings in the psychology literature that individuals' behavior depends on what they believe the external environment is rather than what it actually is. Psychology explains discrepancies between perceived and actual circumstances by bounded rationality and cognitive biases, including confirmation (i.e., interpreting facts to match prior beliefs, judgement and choices), anchoring (i.e., judging based on initial information), randomness (i.e., attributing value to irrelevant experiences) and availability (i.e., judging based on readily available information which does not necessarily accurately reflect reality) biases. In addition, genetic factors are found to explain about 44–52 % percent of the variation in SWB (Lykken and Tellegen, 1996).

Third, Easterlin's (1974) paradox suggests that our current economic system might be sacrificing human well-being in exchange for GDP per capita growth. The dominance of relative perception over objective level of consumption as determinants of happiness, if externally valid outside of the German panel data analyzed here, would provide an acceptable solution to the puzzle that Easterlin observed.

It may be the case that only rapid economic growth would allow for individuals to notice the increased quality of life in a meaningful way. If so, we would expect to see increased levels of happiness only during periods of extremely rapid economic growth where people have a reference point within their own memory of less abundant times. Regarding the second industrial revolution, Keynes (1919) writes: “What an extraordinary episode in the economic progress of man that age was which came to an end in August 1914! The greater part of the population, it is true, worked hard and lived at a low standard of comfort, yet were, to all appearances, reasonably contented with this lot.” The almost overnight transition from iron to steel of the Second Industrial Revolution and the subsequent falling consumer prices could have provided such a time period where quality of life improved fast enough for people to perceive the difference and to derive happiness from their perceptions.

It may also be the case that cultural values play a much larger role in mitigating unhappiness from relative income dissatisfaction. Cultures which promote happiness through relative perceptions might employ devices to alter those perceptions. Mealtime prayers often included reminders of gratitude, and the first links between gratitude, economics, and psychology are starting to be recognized (Desteno et al., 2014). Also, depending on the version, 20 % to 30 % of the ten commandments contain prohibitions against covetousness which is shown by Milfont and Gouveia (2009) to negatively affect SWB. Alternatively, cultures which do not succeed in mitigating unhappiness from relative income dissatisfaction might glamorize conspicuous consumption (Veblen, 1899) such as the social media phenomenon of the “Instagram model” which could be a major cause of the current mental health crisis in the US through the vector of unhappiness. It also potentially sheds some light on the historical pejorative “nuveau riche” as wealthy members of stable societies may have benefited from avoiding ostentatious displays and harbored animosity toward people who through conspicuous consumption fostered unhappiness in lower income individuals thereby destabilizing society. This is a fruitful area for future research, but the dominance of perception over objective state takes the enigma out of Easterlin's puzzle.

Because of the relationship between happiness, and health, productivity and goals attainment, understanding its determinants is important for predicting individual and social outcomes. More importantly, the recent social isolation, uncertainty about the future, health and financial concerns have led to a decline in the ratings of life satisfaction, deterioration of individuals' mental health, increased stress and worry rates, rising number of people experiencing symptoms of depression, and elevated suicidal rates (Witters and Harter, 2020). An insight into the gender differences in the factors which generate greater life satisfaction is useful in predicting the impact of the pandemic on different groups of people, identifying those at greatest risk, and developing a plan for prevention of the forementioned adverse effects. Specifically, public awareness of the finding that self-perceived factors have a larger impact on SWB as compared to actual current circumstances is likely to incentivize people to put effort in viewing reality differently and realizing their happiness with alternative aspects of life. This can increase their level of overall happiness, and thus prevent mental disorders, long-term diseases and suicidal risk.

Furthermore, our finding that satisfaction with family life and health has a larger association with happiness relative to satisfaction with income has implications related to the direction of efforts of decision-makers. Our results suggest that their efforts might have a larger positive impact on societal well-being if directed toward ensuring improvement of health outcomes through prevention of further spread of viruses and assistance provided to infected people and those in high risk groups, and emphasizing the importance of strong family support and close attention to family life, rather than increasing the financial well-being of the population.

We consistently found that positive fortune telling enhanced financial risk taking particularly among men, even non-believers

Positive fortune telling enhances men’s financial risk taking. Xiaoyue Tan, Jan-Willem van Prooijen, Paul A. M. van Lange. PLoS One, September 7, 2022. https://doi.org/10.1371/journal.pone.0273233

Abstract: Fortune telling is a widespread phenomenon, yet little is known about the extent to which people are affected by it—including those who consider themselves non-believers. The present research has investigated the power of a positive fortune telling outcome (vs. neutral vs. negative) on people’s financial risk taking. In two online experiments (n1 = 252; n2 = 441), we consistently found that positive fortune telling enhanced financial risk taking particularly among men. Additionally, we used a real online gambling game in a lab setting (n3 = 193) and found that positive fortune telling enhanced the likelihood that college students gambled for money. Furthermore, a meta-analysis of these three studies demonstrated that the effect of positive fortune telling versus neutral fortune telling was significant for men, but virtually absent for women. Thus, positive fortune telling can yield increased financial risk taking in men, but not (or less so) in women.

General discussion

Three experiments and a meta-analysis uncovered three main findings. First, findings revealed a positive association between superstitious beliefs in fortune telling and financial risk taking. People who reported higher superstitious beliefs in fortune telling also reported an increased tolerance for financial risks (found in Studies 1 and 2). Second, in general participants indicate that they do not believe in fortune telling (across three studies). Third, despite the fact that they did report not to believe in fortune telling, participants (especially men) nevertheless were affected by it: Positive fortune telling enhances men’s financial risk taking (across three studies), whereas no such effect of positive fortune telling emerged among women (except in Study 3). This risk-taking effect for men in the financial domain as consequence of a positive fortune telling was further supported by a meta-analysis of the three experiments.

The paradox–not believing it but acting upon it

Our research findings are consistent with [13]’s claim that people often are susceptible to superstition even when they claim to not believe in it. There is a paradox about believing in superstition in modern times—that is, people act upon superstition while they claim to not believe in it. Since the rise of scientific empiricism, superstition has been negatively valued in society. For instance, it was believed that superstition was caused by the workings of a lower form of human intelligence [45]. New insights produced a shift in common understandings of superstition, however. As various scholars have suggested, it may be part of human nature to construct causal relationships among events, regardless of whether the causal links are real or not (e.g., [12, 16]). Specifically, it is common for people to be superstitious by believing that luck (good or bad) is controllable or predictable, even if they do not admit to it. Across three studies, we found in general, people claimed that they do NOT believe in fortune telling, but nevertheless, particularly men’s financial decisions were affected by the (positive) fortune telling outcomes. Unless people know that they do not want to admit to it, these findings provide novel but indirect evidence that superstition may exert influence on people at a subconscious level.

Gender difference in superstition

There is no scientific consensus yet regarding the question if men or women are more superstitious. Some researchers proposed that women are more superstitious [46]. However, some research evidence is consistent with the notion that men are more superstitious. For instance, a field experiment on lucky numbers suggested that being assigned to lucky numbers does not influence women but increases overconfidence among men [34]. In two of our three studies (Study 1 and 2) we found that men have stronger beliefs in fortune telling. In addition, according to the meta-analytic overview of three studies, men were significantly affected by positive fortune telling whereas women were not. The present research therefore supports the idea that men are more susceptible to superstition than women, at least in financial decision-making situations.

Superstition and risk taking

In two of our three studies (Study 1 and 2) we found significant positive associations between superstition and risk taking. These findings are consistent with the hypothesis that superstition works as a coping-mechanism in a risky decision-making situation. From this point of view, the riskier the situation, the stronger people’s need for superstition. Some groups, including sportsperson, gamblers, sailors, soldiers, miners, financial investors and college students, who have to deal with high-risk situations are also considered as traditionally superstitious groups [1]. Additionally, superstitious beliefs were found to be correlated with gambling intensity among EGM (electronic gaming machine) gamblers [47]. A recent study [48] also suggests that the presence of religious images tends to increase individuals’ subjective probability of winning the lottery, and that subjects therefore believe in a god who intervenes actively in the world in response to their requests.

This point of view may also help people understand why men are more affected by a positive fortune telling. According to a meta-analysis [33], men in general are more risk taking than women. Men consistently take greater risks than women in the financial domain [49, 50]. From an evolutionary perspective, risk-taking behaviors may serve multiple important functions for men, such as acquiring social status and resources, attracting high-quality mates, and establishing and affirming manhood after gender threats (for a review, see [51]). However, risks naturally entail potential losses, and thereby pose potential threats to risk-takers. Men are not totally blind to risks. Superstition suggesting that good luck is ahead may increase men’s expectations of “beating the odds”, decrease anxiety among men, provide a justification for a risky choice, and consequently increase their risk-taking behaviors. Put differently, men are more likely than women to take risks in the financial domain, and positive superstitious beliefs encourage such risk-taking further.

Strengths, limitations, and future directions

At least two strengths are noteworthy. First, as noted earlier, research on the effects of superstition on financial risk taking constitutes largely uncharted territory [21], and thus the present research is filling a gap in the literature on superstition and decision-making. We regard this as an important gap also because it adds to the literature that seemingly irrational factors do affect decision-making, even in a high-status domain (financial decision-making) that many people might associate with logical analysis and precision. Second, most empirical research on this topic was conducted with Asian participants (e.g., [25]), who are from cultures where superstition and rituals are slightly more common. The present research was conducted with Western samples, which may add to the generalizability of the findings on superstition.

We also want to discuss several limitations of the current research. One limitation is that because the empirical study of superstition is quite novel and theories of superstition are still rather preliminary, the present research is mostly driven by assumptions about the underlying processes that cause these effects. We believe the findings reported may therefore contribute to theorizing illuminating why men are subject to superstition when they take financial risks. Another limitation pertains to the scope of the superstition construct that we investigated. Specifically, we only investigated one form of superstition, which is fortune telling. It cannot be concluded with confidence whether the findings will replicate for other forms of superstition. Moreover, the saliency of the payoffs in the experimental study conducted in the lab was relatively low, as compared to the payoffs in a typical economic experiment, and the overall financial incentives for all the participation were rather low as well. According to [52, 53], risk aversion increases sharply when payoffs are scaled up. These low payoffs, particularly the small stakes of mild risks for the gambling decision-making in Study 3 with a fixed payment of 2 euros for both options, could have affected the ecological validity of the studies. But however, throughout history, kings and generals customarily called on astrologists or fortune-tellers to obtain advice prior to making any important decisions (e.g., launching a military campaign) [54], it is a question whether the risk-enhancement effect of a positive fortune telling outcome would be present or absent for a real-life decision making involving big stakes. This suggests worthwhile empirical challenges for further research. Besides, the possibility that it is the “positivity” of the message that actually drives men to take more risks under a positive fortune telling condition cannot be ruled out with the present research. This could be investigated in future research on the effects of fortune telling on people’s risk seeking. Finally, there may be validity issues on the measurement instruments used for the present research. While some of our measures were commonly used by other researchers (e.g., the financial risk tolerance test), other measurement instruments have not been validated in prior research (e.g., the items for beliefs in fortune telling). The items of these scales did directly ask for the constructs of interest, however, substantially minimizing potential threats to the construct validity for these measurement instruments.

Keju, the Chinese civil service exam system, was an anti-mobility mobility channel, depriving the civil society of access to the best human capital

The Rise and the Fall of the EAST: Examination, Autocracy, Stability and Technology in Chinese History and Today. Hasheng Huang. Yale Univ Press, 2023.

[h/t Tyler Cowen, Marginal Revolution, Sep 9 2022. https://marginalrevolution.com/marginalrevolution/2022/09/the-rise-and-fall-of-the-east.html]

Excerpts:

For many years, I struggled to come up with a coherent explanation for the power, the reach, and the policy discretion of the Chinese state.  There is coercion, ideological indoctrination, and probably a fair amount of societal consent as well.

Keju [the civil service exam system] had a deep penetration both cross-sectionally in society and across time in history.  It was all encompassing, laying claims to time, efforts and cognitive investments of a significant swath of Chinese population.  It was incubatory of values, norms, and cognitions, therefore impacting ideology and epistemology of Chinese minds.  It was a state institution designed to augment the power and the capabilities of the state.  Directly, the state monopolized the very best human capital; indirectly, the state deprived society access to talent and preempted organized religion, commerce, and intelligentsia.  The Chinese state in history and today is an imprinted version of this Keju system.

Chinese state is strong because it reigns without a society.

---
Tyler Cowen adds:

Among the other interesting features of this book, including many, are:

There is a very useful discussion of Sui Wendi, the man who reunified China (and is barely known in the West).

Just how much the exam system expanded in the 17th century, to support a larger and growing Chinese state.

Why Chinese bureaucrats in the provinces tend to be generalists and the ministerial officials tend to be specialists.

[...]

"A state without society is a vertically integrated organization...Keju's powerful platform effect crowded and stymied alternative mobility channels...the Keju was an anti-mobility mobility channel."

"In the 1890s, China's population literacy was only 18 percent, way below 95 percent of England and the Netherlands."

Exam competition takes up so much of individual mind space.  Furthermore the competition atomizes society and makes it harder to form the kinds of collective movements that might lead to democracy.

[...]

"Throughout Chinese history very few emperors were toppled by their generals or senior functionaries, a sharp contrast with the Roman Empire."

[...]

When their primary-school teachers were disproportionately female ca. 1940, female students were more likely to complete high school & attend college, & had increased longevity

The Impact of Female Teachers on Female Students' Lifetime Well-Being. David Card, Ciprian Domnisoru, Seth G. Sanders, Lowell Taylor & Victoria Udalova. NBER Working Paper 30430. Sep 2022. DOI 10.3386/w30430

Abstract: It is widely believed that female students benefit from being taught by female teachers, particularly when those teachers serve as counter-stereotypical role models. We study education in rural areas of the US circa 1940--a setting in which there were few professional female exemplars other than teachers--and find that female students were more successful when their primary-school teachers were disproportionately female. Impacts are lifelong: female students taught by female teachers were more likely to move up the educational ladder by completing high school and attending college, and had higher lifetime family income and increased longevity.

People consistently rated the presence of a health problem as less strongly genetically determined than its absence

Asymmetrical genetic attributions for the presence and absence of health problems. Matthew S. Lebowitz, Kathryn Tabb, Paul S. Appelbaum. Psychology & Health, Sep 6 2022. https://doi.org/10.1080/08870446.2022.2119236

Abstract
Objective: Recent research has suggested that people more readily make genetic attributions for positively valenced or desirable traits than for negatively valenced or undesirable traits—an asymmetry that may be mediated by perceptions that positive characteristics are more ‘natural’ than negative ones. This research sought to examine whether a similar asymmetry in genetic attributions would emerge between positive and negative health outcomes.

Design: Across seven experiments, participants were randomly assigned to read a short vignette describing an individual experiencing a health problem (e.g. hypertension) or a corresponding healthy state (e.g. normal blood pressure).

Main Outcome Measures: All participants provided ratings of naturalness and genetic attributions for the outcome described in their assigned vignette.

Results: For diagnoses other than addictive disorders, participants rated the presence of a diagnosis as less genetically caused than its absence; for addictive disorders, the presence of a diagnosis was rated as more genetically caused than its absence. Participants consistently rated the presence of a health problem as less natural than its absence.

Conclusion: Even within a single domain of health, people ascribe differing degrees of ‘naturalness’ and genetic causation to positive versus negative health outcomes, which could impact their preferences for treatment and prevention strategies.

Keywords: Geneticssocial cognitionhealth beliefspsychological essentialismcausal attributionmotivated reasoning

Around the globe, parenthood is accompanied by more conservative worldviews, and experimentally inducing a parental mindset boosts conservative thinking

Experimental and cross-cultural evidence that parenthood and parental care motives increase social conservatism. Nicholas Kerry et al. Proceedings of the Royal Society B: Biological Sciences. September 7 2022. https://doi.org/10.1098/rspb.2022.0978

Abstract: Differences in attitudes on social issues such as abortion, immigration and sex are hugely divisive, and understanding their origins is among the most important tasks facing human behavioural sciences. Despite the clear psychological importance of parenthood and the motivation to provide care for children, researchers have only recently begun investigating their influence on social and political attitudes. Because socially conservative values ostensibly prioritize safety, stability and family values, we hypothesized that being more invested in parental care might make socially conservative policies more appealing. Studies 1 (preregistered; n = 376) and 2 (n = 1924) find novel evidence of conditional experimental effects of a parenthood prime, such that people who engaged strongly with a childcare manipulation showed an increase in social conservatism. Studies 3 (n = 2610, novel data from 10 countries) and 4 (n = 426 444, World Values Survey data) find evidence that both parenthood and parental care motivation are associated with increased social conservatism around the globe. Further, most of the positive association globally between age and social conservatism is accounted for by parenthood. These findings support the hypothesis that parenthood and parental care motivation increase social conservatism.

4. Discussion

Results from four studies, using multiple methodologies, measures and samples convergently suggest that parenting motives—assessed both objectively as parenthood status and subjectively as parental care motivation—fundamentally influence social conservatism. Studies 1 (n = 376) and 2 (n = 1871) provided evidence that experimentally inducing a parental mindset leads to increased social conservatism in participants who engaged more with the manipulation. Study 3 (n = 2610) found robust associations between parental care motivation and social conservatism across 10 countries. Consistent with our theoretical framework, the relationships in Studies 1–3 were largely specific to social—not economic—conservatism. Finally, Study 4 (n = 426 444) found evidence that parents, and especially parents of multiple children, have more traditional and more socially conservative views in dozens of countries around the world.

Studies 3 and 4 provide an important insight into age-related increases in social conservatism. Across seven waves of WVS data and in a combined novel sample from 10 countries, the relationship between age and social conservatism appears to be largely a consequence of parents (especially parents of multiple children) scoring higher on social conservatism and, on average, being older. Thus, it appears that parenthood, not age (or the wisdom that comes with it), drives the putative age-conservatism relationship.

The cross-cultural evidence presented in Studies 3 and 4 was correlational, such that we cannot confidently conclude that parenthood itself causes social conservatism. However, the experimental work on US participants, combined with the non-independence of parenthood and age-related increases in social conservatism in the multinational samples of Studies 3 and 4, suggests a provisional hypothesis that some people become more socially conservative as they age because of motivational changes induced by parenthood. While it is not possible to directly test causality by randomly assigning people to become parents, future cross-cultural work using experimental and longitudinal methods should aim to provide further attempts to falsify this hypothesis.

The moderated experimental effects in Studies 1–2, while consistent with a causal explanation, could also plausibly be explained by non-random allocation. An alternative explanation for these moderated effects could be that people high in parental care motivation—who were also higher in social conservatism—responded more strongly to the parenting (versus control-) manipulations, while those lower in parental care motivation—who were less conservative—responded more strongly to the control manipulations. However, this alternative hypothesis would predict a moderated effect of condition (by emotional engagement) on parental care motivation regardless of whether it was measured before or after the manipulation. On the contrary, Study 1 (where the PCAT was administered before the manipulation) found a moderated effect on social conservatism but no moderated effect on parental care motivation. Meanwhile, Study 2 (where both measures were administered after the manipulation), found a moderated effect on parental care motivation, which was larger than the effect on social conservatism and also fully mediated this latter effect (see electronic supplementary material).

Another potential limitation is that the findings relating to parental care motivation in Studies 1–3 were based on self-report data, which allows the possibility that phenomena such as social desirability could, in theory, explain the correlations between parenting motives and social conservatism. However, social desirability seems unlikely to account for the relationship: parental care motivation has been shown to correlate positively with social desirability, while in many countries—including the USA and South Korea, two of the countries in which the relationship between parental care motivation and social conservatism was strongest—socially desirable answering is negatively associated with conservatism (e.g. [33–36]). Thus, controlling for social desirability would be unlikely to decrease the strength of the relationship between parental care motivation and social conservatism.

In Study 4, the relationship between parenthood status and conservative attitudes was widespread but not universal, suggesting the possibility of sociocultural moderators. Further, the present study did not include samples from pre-industrial societies (e.g. hunter–gatherers or horticulturalists). Cultures like these might offer important insights into boundary conditions for the relationship between parenting motives and social conservatism, and also into the reasons for its existence. For example, if biological parenthood itself leads to increases in parental care motivation and social conservatism, this would predict a difference in these variables between parents and non-parents in cultures where childcare is shared relatively evenly within a community (e.g. the Efe culture of the Democratic Republic of Congo [37,38]). However, if engaging in childcare is more important, this would predict similar relationships in non-parents who engage in extensive childcare. Similarly, at an individual level, research on parents of adoptive versus biological children could provide insight into the relative influence of biological versus behavioural parenting.

Future research may also address more precisely how changes in parental care motivation and ideological beliefs correspond to different life stages, such as parenthood, grandparenthood and menopause. For example, are times when fertility or short-term mating opportunities are low—but when childcare is pertinent—associated with more conservative attitudes? Consistent with this theoretical rationale, some preliminary work has found that number of grandchildren is positively associated with some aspects of social conservatism (specifically gender-related issues and conformity) even when controlling for age and number of children [39]. More focused future research should seek to establish whether having multiple young family members is sufficient to change political beliefs, or whether engaging (or investing) in childcare is a necessary component.

If our central hypothesis—that parental care motives lead to more socially conservative attitudes—is correct, this could provide important insights into the long-term impacts of policies and technologies that directly influence birthrates (e.g. abortion restrictions, China's ‘one child policy’, birth control). Similarly, given that birthrates are declining in most of the world—but increasing sharply in some regions [40]—the current findings could have profound implications for the political landscape of the future. Specifically, our findings would suggest that global increases in childlessness could potentially contribute to a process of liberalization on social issues. Consequently, integrating these findings into existing models of political attitudes may contribute to more accurate models of population-level shifts in ideology.