Causal and Deductive Reasoning in Socio-Economic Systems

Abstract

From the perspective of causal inference, this chapter addresses propensity score matching as a data-based statistical causal inference and ABM as a model-based deductive causal inference. The case study analyzing the effects of external support for startups shows that propensity scores allow the effects of similar measures to be estimated from hypothetically randomized data sets, even when experiments are difficult. For a new policy, the case of deductive causal inference for passing on knowledge and the case of deductive causal inference of urban dynamics show that agent-based deductive causal inference is effective. It can deductively predict the future to a certain extent in a model-based manner.