The March 2008 issue of Developmental Psychology contains a special series of around 15 methodolocially and statistically oriented articles (Table of Contents). Three of the articles explicitly refer in their titles to causal inference, and others of the articles may have relevant ideas, as well. The three titles mentioning causation are as follows:
From statistical associations to causation: What developmentalists can learn from instrumental variables techniques coupled with experimental data (Gennetian, Magnuson, & Morris)
Using full matching to estimate causal effects in nonexperimental studies: Examining the relationship between adolescent marijuana use and adult outcomes (Stuart & Green)
Combining group-based trajectory modeling and propensity score matching for causal inferences in nonexperimental longitudinal data (Haviland, Nagin, Rosenbaum, & Tremblay)
At this stage, I have only skimmed through these (and other) articles in the issue. The techniques of "instrumental variables" and "matching" have, of course, been around for many years. I will be interested to see in greater depth what new contributions these articles make with such established techniques. Only within the past six months did I first hear the term "propensity score;" in skimming the many articles in the issue that use propensity scores, however, I've learned that this approach, too, has been around for decades!
Causal inference from nonexperimental data clearly is a complex, tricky endeavor. Perhaps it is for this reason that the kinds of techniques discussed in the special series have needed a quarter-century or longer to be absorbed, tested in different contexts, and diffused across disciplines.