Howard Bloom is retiring this summer after serving as MDRC’s chief social scientist for 18 years. This followed 21 years of teaching research methods, program evaluation, and applied statistics at Harvard University and New York University. At MDRC, Howard has led the development of experimental and quasi-experimental methods for estimating program impacts and worked closely with staff members to build these methods into their research; he intends to continue to work with MDRC on special projects for the foreseeable future.

With Howard’s retirement approaching, his MDRC colleagues asked him to reflect on his career. His response offers lessons he’s learned about the importance of the following topics:

• Simple hypotheses

• Simple graphs

• Simple analytic expressions

• Simple research design parameters

• Cluster random assignment

• Empirical information about research design parameters

• Simple messages

• Simple benchmarks

• Naturally occurring lotteries

• Cross-site impact variation

• Great colleagues