Our main two criteria in selecting papers for publication are rigorous identification and policy relevance. The two go together as we cannot have credible policy recommendations without strong causal inference. Too many of the submitted papers offer simple “determinants” that are partial correlates with no causal value, and yet are the basis for bold policy recommendations, sometimes of first order of importance for development practice. This includes a large number of cross-country panel regressions with only mechanical, and hence not credible, identification, and yet eventually huge claims of policy implications.
The main peeve about submissions is receiving papers with insufficient work, and hence insufficiently solid results. Many authors believe that one regression makes a scientific paper. Good papers need more work. They sometimes take years to polish and numerous presentations to peer audiences before they reach maturity. Typically we want to see solid robustness checks to guarantee that the results are indeed trustworthy and can serve for policy purposes. Recommendation here would be to submit less, but better. Fewer good papers with solid work would be more likely to get your research published and subsequently noted and cited.