jected tests. Our interpretation is that researchers might be tempted to inflate the value of those just-rejected tests by choosing a "significant" specification. We propose a method to measure this residual and describe how it varies by article and author characteristics.

Journals favor rejection of the null hypothesis. This selection upon tests may distort the behavior of researchers. Using 50, 000 tests published between 2005 and 2011 in the AER, JPE, and QJE, we identify a residual in the distribution of tests that cannot be explained by selection. The distribution of p-values exhibits a two humped camel shape with abundant p-values above 0.25, a valley between 0.25 and 0.10, and a bump slightly below 0.05. The missing tests (with p-values between 0.25 and 0.10) can be retrieved just after the 0.05 threshold and represent 10% to 20% of marginally rejected tests. Our interpretation is that researchers might be tempted to inflate the value of those just-rejected tests by choosing a "significant" specification. We propose a method to measure this residual and describe how it varies by article and author characteristics.

jected tests. Our interpretation is that researchers might be tempted to inflate the value of those just-rejected tests by choosing a "significant" specification. We propose a method to measure this residual and describe how it varies by article and author characteristics.