Another social science looks at itself Experimental economists have joined the reproducibility discussion by replicating selected published experiments from two top-tier journals in economics. Camerer et al. found that two-thirds of the 18 studies examined yielded replicable estimates of effect size and direction. This proportion is somewhat lower than unaffiliated experts were willing to bet in an associated prediction market, but roughly in line with expectations from sample sizes and P values. Science , this issue p. 1433

Concerns about a lack of reproducibility of statistically significant results have recently been raised in many fields, and it has been argued that this lack comes at substantial economic costs. We here report the results from prediction markets set up to quantify the reproducibility of 44 studies published in prominent psychology journals and replicated in the Reproducibility Project: Psychology. The prediction markets predict the outcomes of the replications well and outperform a survey of market participants' individual forecasts. This shows that prediction markets are a promising tool for assessing the reproducibility of published scientific results. The prediction markets also allow us to estimate probabilities for the hypotheses being true at different testing stages, which provides valuable information regarding the temporal dynamics of scientific discovery. We find that the hypotheses being tested in psychology typically have low prior probabilities of being true (median, 9%) and that a "statistically significant" finding needs to be confirmed in a well-powered replication to have a high probability of being true. We argue that prediction markets could be used to obtain speedy information about reproducibility at low cost and could potentially even be used to determine which studies to replicate to optimally allocate limited resources into replications.reproducibility | replications | prediction markets T he process of scientific discovery centers on empirical testing of research hypotheses. A standard tool to interpret results in statistical hypothesis testing is the P value. A result associated with a P value below a predefined significance level (typically 0.05) is considered "statistically significant" and interpreted as evidence in favor of a hypothesis. However, concerns about the reproducibility of statistically significant results have recently been raised in many fields including medicine (1-3), neuroscience (4), genetics (5, 6), psychology (7-11), and economics (12, 13). For example, an industrial laboratory could only reproduce 6 out of 53 key findings from "landmark" studies in preclinical oncology (2) and it has been argued that the costs associated with irreproducible preclinical research alone are about US$28 billion a year in the United States (3). The mismatch between the interpretation of statistically significant findings and a lack of reproducibility threatens to undermine the validity of statistical hypothesis testing as it is currently practiced in many research fields (14).The problem with inference based on P values is that a P value provides only partial information about the probability of a tested hypothesis being true (14,15). This probability also depends on the statistical power to detect a true positive effect and the prior probability that the hypothesis is true (14). Lower statistical power increases the probability that a statistically significant effect is a false positive (4, 14). Statistically significant results from small studies are therefore more likely to be fals...

Women typically participate less than men in the stock market, while also scoring lower on financial literacy. We explore the link between the gender gap in stock market participation and financial literacy. Using survey data on a random sample of 1,300 individuals that is representative of the Swedish population, we show that controlling for basic financial literacy, essentially a measure of numeracy that does not require knowledge about the stock market, may explain a large part of the gender gap in stock market participation. We also find that women report being less risk taking than men. This gender gap in risk attitudes remains significant also when controlling for financial literacy.

Women typically participate less than men in the stock market, while also scoring lower on financial literacy. We explore the link between the gender gap in stock market participation and financial literacy. Using survey data on a random sample of 1,300 individuals that is representative of the Swedish population, we show that controlling for basic financial literacy, essentially a measure of numeracy that does not require knowledge about the stock market, may explain a large part of the gender gap in stock market participation. We also find that women report being less risk taking than men. This gender gap in risk attitudes remains significant also when controlling for financial literacy.

No abstract