Attribution: quantitative inference of program impact (H5)


This workshop will explore the concepts of causal inference and attribution in program evaluation. It starts with a review of current concepts in causal inference for the social sciences. The foundation rests on concepts drawn from sociology and economics.

The workshop will deconstruct the idea that the randomized control trial is the gold standard and reveal causal thinking as a much more complex concept in the social sciences. Of course this translates to program evaluation and the obvious gap that attributing expected outcomes to the purposeful expenditures of public resources remains an elusive result.

This workshop will review the requirements as well as the advantages and disadvantages of quantitative strategies such as quasi-experimental designs, instrumental variables, regression discontinuity and general linear models. Examples will draw from crime prevention, income support, labour market and health programs.


Greg Mason

Dr. Greg Mason has presented to public sector and professional audiences for over 30 years. He has served as a faculty member at the University of Manitoba since 1974 during which time has taught program evaluation and econometrics at the graduate and undergraduate level.

Workshop Level



Participants should be experienced evaluators with knowledge of quantitative methods. An understanding of social research methods including multivariate statistical models (regression) is useful to get the most out of the workshop.

This workshop will present concepts of causality in the context of program evaluation, but details on calculation techniques and mathematical development will not be stressed. The goal is to present the causal analysis strategies that evaluators may employ.

Date and time

Sunday, June 15, 2014
1:30 pm to 4:30 pm

Alignment with CE Designation Competencies

  • Understands the knowledge base of evaluation (theories, models, types methods and tools)
  • Develops evaluation designs
  • Defines evaluation methods
  • Draws conclusions and makes recommendations
  • Reports evaluation findings and results