Understanding cause-and-effect relationships is crucial for making informed decisions, but studies often give conflicting results. Granger causality testing can be misleading due to overfitting, leading to false-positive results. A new meta-regression model helps correct this bias and shows that many reported causal relationships are not genuine. In the case of energy consumption and economic output, the excess significance found is actually due to overfitting, not a real connection.