A broad body of literature by economists and non-economists, orthodox and heterodox, argues that the field of economics faces a crisis of credibility, replicability, reproducibility, or some combination thereof. In this paper I discuss how that crisis is connected to fundamental epistemological issues underpinning how economists perform their work. Popper argued the core feature of the scientific method is carefully testing a falsifiable hypothesis. While economists have developed an expansive language and statistical framework under which they test and reject economic hypotheses, I assert this current framework is more problematic than the field generally assumes. In the words of the well-established econometrician Wooldridge, the foundation of econometrics is hope: “It is not meaningful to talk about the statistical properties of a set of estimates obtained from a single sample… When we say OLS is unbiased… we HOPE that we have obtained a sample that gives us an estimate close to the population value.” As the clichéd joke goes, how likely is the drunk to find his keys under the light of the lamppost? Are economists looking for falsification where it could be found? Economists rigorously falsify the hypotheses of their econometric models, conditional on the hope of correct specification. But what are the falsifiable hypotheses on the level of model specification? McCloskey has argued that the passive voice typical of economic writing contributes to obfuscating the human characteristics of the author. How might it hinder the advance of economic science to forget that that the humans performing ‘science’ have foibles, conflicts of interest, and inclinations toward self-deception? As Krugman quoting Sinclair reminded, “It’s difficult to get a man to understand something when his salary depends on his not understanding it.” Under the current research framework, by what results would economists know that their theories, hypotheses, and assumptions were wrong? The answer to this question is key to moving the field forward as a rigorous science.