This study differentiates p-hacking from publication bias by examining biases resulting from selective reporting within studies versus selective publication of entire studies. Analyzing a dataset of 400 meta-studies, encompassing nearly 200,000 estimates from approximately 19,000 individual studies in economics and related social sciences, I observe a notably higher incidence of p-hacking as compared to selective publication. Employing various meta-regression methods, I find that selective reporting within studies is about 20\% more prevalent than publication bias arising from selection among studies. This finding underscores the considerable influence of practices such as p-hacking and method-searching, suggesting that they contribute significantly to selection bias in the economic literature and could affect the perceived reliability of published findings.
Nov 1, 2023
*Work in Progress* When people anticipate a change in the policy, they tend to adjust their behavior before the actual decision is made. The impact of anticipation on the results of VAR literature has been demonstrated particularly by Ramey (2009), who reexamines the differences between traditional Cholesky identification and the Ramey-Shapiro narrative approach with contradictory conclusions on the effect of government spending on consumption and wages. She discusses the importance of timing the identified shock (government spending) and argues that failing to count for the anticipation effect of the shock can cause these contradicting conclusions. So far, these aspects have not been discussed in the context of uncertainty shocks. However, some of the most prominent peaks in uncertainty, such as the Brexit referendum, could have been anticipated before the event actually happened. Daily data will allow studying the evolution of uncertainty related to specific events before and after the specific event so that an identification of the unexpected part of uncertainty will be possible.
Jun 1, 2023