Jump or Kink? Identification of Binary Treatment Regression Discontinuity Design without the Discontinuity

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The State of Applied Econometrics - Causality and Policy Evaluation (2016, neutral): “[2015], Dong [2014]. The basic idea is that at a threshold for the forcing variable, the slope of the outcome function (as a function of the forcing variable) changes, and the goal is to estimate this change in slope. To make this clearer, let us discuss the example in Card et al. [2015]. The forcin”
Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models (2015, methodology): “Dong (2014a) uses changes in the derivative or slope of the treatment probability at the threshold to identify standard fuzzy RD design treatment effects in applications where there is a kink instead of, or in addition to, a discontinuity in this probability at the threshold.”
Regression discontinuity design with many thresholds (2017, unknown): “Assumption 8 is a generalized version of the sufficient conditions for identification of the treatment effect on compliers in the case with one cutoff as in Hahn, Todd, and Van der Klaauw (2001) and Dong (2015). It also states that the functional form of treatment effects does not vary across differ”