Set of databases to analyze the SAI problem

This datasets are related to the analysis of a critical flaw in the influential Fazzari, Hubbard, and Petersen (1988) model, known as the Accounting Semi-Identity (ASI) problem. Because the model omits parts of a fundamental accounting identity, it can create a mechanical, not causal, link between investment and cash flow, severely biasing the results.The study tests an unrestricted model, with a variable measuring the SAI problem across numerous datasets and finds the ASI distortion is universal (affecting 100% of databases) and dominant (explaining over 83% of the model's variance, versus 17% for the standard model).The conclusion is that a significant portion of past research using this model may be invalid, as their results are very likely statistical artifacts rather than the expression of a real economic behavior. This evidence explains why the literature has been filled with anomalous and contradictory results for decades.