Greetings, Andrew!

So far as I can tell, I don't believe there is such a thing. Change, whether you classify it as social change (Smith, 2010; Aguilera et al., 2005), systemic change (Watkins & Marsick 1993), transformative change (Grin, Rotmans & Schot, 2010) or whatever concept is in vogue next spring, revolves around processes of rupture and reconfiguration of institutions and relationships. Such processes can be described with quantitative data, sure, but how can you validate such things?

If the question is: how large is a change, then that can only be defined by the criteria selected. But you can only compare directly comparable results, which require a simplified question to begin with. For instance: which process or which revolution led to the greater life expectancy at birth increase? Industrial revolution? French revolution? Plumbing? All these are noteworthy changes and innovation in their own right, but how can you dissociate them from the other by-products that contribute to the end conclusion?

There's a reason why change is usually described in qualitative terms with descriptive data to stress particular aspects. You cannot just throw a bunch of variables into a factor analysis and come up with latent variables that measure change, and hope to get any heuristic value out of it. That's where theories of change come in, and they come in many flavours, suited for all research objects and disciplinary fields, with their own terms (as shown above), methods and theories.

Unless you specify the object of your research I'm afraid I cannot give you a better suggestion.

Kind regards,

J.A. Guerreiro

Exactly right, Jorge André Guerreiro and this is what makes predicting COVID-19 outcomes so difficult.

The size of the middle class, unemployment rates, fragmentation in the elements of governance, and marginalization at the global level can be used as indicators to measure revolutionary change in societies .