I have data where I suspect there may be reverse causation (Y => X) or simultaneity (Y <=> X). Does the technique of propensity score analysis help to account for this effect? I feel that as part of the technique we are constructing a "control" equivalent sample (through propensity scores) which is counterfactual to any hypothesised simultaneity relationship.
EDIT : Thanks. Can I add a bit more context? I have data on the sale price of houses (Y) in a neighbourhood and the local grocery retail provision (X). I am looking to see if the brand of the retail provision has an effect on the sales price of houses (in the UK this is known as a Waitrose effect, after a premium retailer brand (https://www.lloydsbankinggroup.com/Media/Press-Releases/2018-press-releases/lloyds-bank/090618_Supermarkets_LB/). My concern is that there might be simultaneity, with retail brands locating in areas with high house prices (Y => X) and also the presence of a particular retail brand raising house prices (X => Y). But maybe my concern is actually a selection bias, where certain retail brands are bias to select certain types of areas (high affluence/low affluence) and PS can correct for this?