Programming errors in software applications may produce plausible yet erroneous results, without providing a clear indication of failure. This happens, for instance, when certain inputs have a disproportionate impact on the program result. To address this issue, we propose a novel quantitative static analysis for determining the impact of inputs on the program computations, parametrized in the definition of impact. This static analysis employs an underlying abstract backward analyzer and computes a sound over-approximation of the impact of program inputs, providing valuable insights into how the analyzed program handles them. We implement a proof-of-concept static analyzer to demonstrate potential applications.