Extrapolating policy effects : hopes, assumptions, and the extrapolator's bind
Evidence-Based Policy is the movement according to which policy should be based on high-quality evidence for 'what works'. A major problem in using evidence to inform policy is concerned with extrapolation, i.e. using evidence of policy effectiveness from a study population to learn something about the effects of a policy in a novel target population. This thesis provides a critical discussion of extrapolation in Evidence-Based Policy and aims to make general contributions to improving both the theory and practice of extrapolation. It proceeds in three parts. Part I provides a comprehensive analysis of extrapolation, including what different kinds of extrapolation there are, what makes some of them highly challenging, and what successful extrapolation is. Part II critically examines existing strategies for extrapolation proposed by philosophers, econometricians, and computer scientists. Emphasis is put on the empirical assumptions about similarities and differences between populations that these strategies involve, and it is argued that supporting these assumptions is often over-demanding. In particular, the knowledge about the target population required to underwrite an extrapolation is often so extensive
Khosrowi, Donal Djen Gheschlaghi
Extrapolating policy effects : hopes, assumptions, and the extrapolator's bind. Evidence-Based Policy is the movement according to which policy should be based on high-quality evidence for 'what works'. A major problem in using evidence to inform policy is concerned with extrapolation, i.e. using evidence of policy effectiveness from a study population to learn something about the effects of a policy in a novel target population. This thesis provides a critical discussion of extrapolation in Evidence-Based Policy and aims to make general contributions to improving both the theory and practice of extrapolation. It proceeds in three parts. Part I provides a comprehensive analysis of extrapolation, including what different kinds of extrapolation there are, what makes some of them highly challenging, and what successful extrapolation is. Part II critically examines existing strategies for extrapolation proposed by philosophers, econometricians, and computer scientists. Emphasis is put on the empirical assumptions about similarities and differences between populations that these strategies involve, and it is argued that supporting these assumptions is often over-demanding. In particular, the knowledge about the target population required to underwrite an extrapolation is often so extensive
policy effect hope assumption bind evidence based policy movement accord policy base high_quality evidence what work major_problem use evidence inform policy concern extrapolation use evidence policy effectiveness study population learn something effect policy novel target population provide_critical discussion extrapolation evidence based policy aim_make general contribution improve theory_practice extrapolation proceeds three_part part provide_comprehensive analysis extrapolation include different_kind extrapolation make highly challenging successful extrapolation part critically_examine exist strategy extrapolation propose philosopher computer scientist emphasis put empirical assumption similarity_difference population strategy involve argue support assumption often over particular knowledge target population require extrapolation often extensive