A Problem-Solving Approach to Data Analysis for Economics

Data analysis for formal methods is constrained due to the lengthy dominance of the econometric view within economics. Best practice in statistics suggests a shift in emphasis from making statements about the sampling distribution of numerical data summaries to seeking data summaries that communicate well. The process philosophy perspective informing the original institutionalists and also evident in the tradition of Keynes is amenable to drawing from current developments in the field of statistics toward this goal. Compared to the econometric approach, it emphasizes data analysis over statistical inference, problem-solving over theory testing, and algorithmic over analytic mathematics. In the choice of tools made possible by current technology, it favors general purpose tools that are adaptable. It favors the instrumental efficacy of computational thinking, visualization, exploration, and discovery over the ceremonial aspects of the mathematical rhetoric of economics. It also encourages the attention to ethics and assumptions stressed by statisticians. Our aim is to provide an overview of the philosophical foundation and intellectual history of an alternative to the econometric view and to give some examples of how it might be applied to the data needs of formal methods for social economics.