Are there any empirical observations or practices when to prefer Local Volatility Model for pricing over Stochastic Model or vice versa?
There is another reason why Stoc Vol Models should be usually preferred to Local Vol Models, this reason is explained in the Hagan et al. paper "Managing Smile Risk" about SABR process and is in simple terms the fact that "smile dynamics" is poorly predicted by local vol models leading to bad Hedging of exotic options.
Anyway Local Vol models have the good feature to be "arbitrage free" (at the begining) and I think that some link between both approach can be achieved by Markovian Projection Method.for this you can have a look at V. Piterbarg's paper on the subject and the references therein.
For pricing, there are a few products whose prices are sensitive to the forward smile and when you compute that with just local vol, it is not realistic.
So if you are a seller, you go to the next church and find something that looks kindof reasonable, and that kind of can reconstruct a reasonnable forward smile structure.
The game in pricing is to not sell for 0 something that you know can't be 0. Especially if 90% of the product price comes from this particular effect.
For hedging one could try to add this and that dependency, but the chance are you are off big time on 2 other things.
Where you have a strong view on lots of points in your Black-implied volatility surface, both in time and strike, then some of the popular stochastic volatility models introduce calibration error, so you might want to stick the honest local volatility model (non-parametric, calibrate-able to whatever you know about the Black-implied vol surface). If you still want to directly manipulate the shape of the forward skew (that is, the prices of forward starting options), or keep other good parts of stochastic volatility mentioned in answers above, then you need to look up stochastic local volatility models.
Hope this helps.