Manski argues that public policy is based on untrustworthy analysis. Failing to account for uncertainty in an uncertain world, policy analysis routinely misleads policy makers with expressions of certitude. Manski critiques the status quo and offers an innovation to improve both how policy research is conducted and how it is used by policy makers.

Policy analysis, like all empirical research, combines assumptions and data to draw conclusions about a population of interest. The logic of empirical inference is summarized by the relationship: assumptions + data → conclusions. Data alone do not suffice to draw conclusions. Inference requires assumptions that relate the data to the population of interest … Holding fixed the available data, and presuming avoidance of errors in logic, stronger assumptions yield stronger conclusions. At the extreme, one may achieve certitude by posing sufficiently strong assumptions. [However,] the credibility of inference decreases with the strength of the assumptions maintained … Researchers regularly express certitude about the consequences of alternative [policy] decisions. Exact predictions of outcomes are common, and expressions of uncertainty are rare. Yet policy predictions are often fragile. Conclusions may rest on critical, unsupported assumptions or on leaps of logic. Then the certitude of policy analysis is not credible.

查尔斯·F. 曼斯基　Charles F. Manski

麻省理工学院经济学博士，西北大学经济系校董事会讲席教授，美国科学院院士，英国科学院院士，美国艺术与科学院院士，计量经济学会院士，美国科学促进协会成员，美国经济学会杰出会员，曾任职于美国国家研究委员会。

主要研究领域包括：计量经济学、理性选择理论、判断和决策以及社会政策分析。作为预测和决策方面的专家，他开启了计量经济学“部分识别”（partial identification）研究的大门，将社会互动理论推上了一个新高峰。2015年，其因“对于部分识别的描述和社会互动的经济学分析”而入选“汤森路透引文桂冠奖”。