In economic research, a tiny symbol denoting statistical significance can influence publication prospects and hiring decisions, according to Lamis Kattan, an assistant professor of Economics at Georgetown University in Qatar (GU-Q). In a 2026 study published in the European Economic Review, ‘Job Market Stars: Statistical Significance and Academic Hiring in Economics’, Dr. Kattan and her colleagues tracked 200 young economists on the job market and found that candidates whose research crossed the statistical significance threshold were far more likely to land prestigious academic positions than those who fell just short. Dr. Kattan noted that the difference between a p-value of 0.09 and 0.10 is statistically almost meaningless but appears to carry real weight in hiring committees’ decisions, suggesting intellectually honest researchers may be penalised. This incentive structure can lead to “p-hacking,” where analytical choices are shaped by the desire to find significant results. In Nature’s ‘Reproducibility and Robustness of Economics and Political Science Research’, Dr. Kattan and colleagues at the Institute of Replication re-examined 110 published studies. They found that journals requiring mandatory replication packages fostered higher rates of computational reproducibility, yet when reanalysing the underlying data, nearly one in six studies whose findings were examined showed cracks in the foundation.