Inflection Points, Kinks, and Jumps: A Statistical Approach to Detecting Nonlinearities

Inflection points, kinks, and jumps identify places where the relationship between dependent independent variables switches in some important way. Although these switch points are often mentioned management research, their presence data is either ignored, or postulated ad hoc by testing arbitrarily specified functional forms (e.g., U inverted U-shaped relationships). This problematic if we want accurate tests for our theories. To address this issue, provide an integrative framework identification of nonlinearities. Our approach constitutes a precursor step that researchers will to conduct before deciding which estimation model may be most appropriate. We also instructions on how can implemented, replicable illustration procedure. illustrative example shows endogenous lead significantly different conclusions compared those obtained when ignored existence conjectured arbitrarily. supports claim capturing empirically nonlinearity should included empirical investigations.