Beyond the average effect of the innovation subsidies: Using case selection via matching to break impasse in delivering useful advice to policy makers.

Experts and stakeholders promote the combined use of counterfactual and theory-based approaches in program evaluation. We illustrated combined application of these two approaches in a single evaluation study of innovation subsidies, using "case selection via matching" and follow-up in-depth interviews. We conducted interviews in contrasting pairs of companies-one successful and one unsuccessful-which were otherwise similar on a defined set of covariates. Our procedure helped to reveal factors, which might be overlooked or simply not available in data at hand and hence not accounted for in analyses of the intervention effects. As such it extends beyond the average effect estimate to highlight causes of an intervention success or failure.

Anchoring effect in legal decision-making: A meta-analysis.

Objective: We conducted a meta-analysis to examine whether numeric decision-making in law is susceptible to the effect of (possibly arbitrary) values present in the decision contexts (anchoring effect) and to investigate which factors might moderate this effect. Hypotheses: We predicted that the presence of numeric anchors would bias legal decision-makers' judgment in the direction of the anchor value. We hypothesized that the effect size of anchoring would be moderated by several variables, which we grouped into three categories: methodological (type of stimuli; type of sample), psychological (standard vs. basic paradigm; anchor value; type of scale on which the participants assessed the target value), and legal (relevance of the anchor; type of the anchor; area of law to which the presented case belonged; presence of any salient numeric values other than the main anchor). Method: Twenty-nine studies (93 effect sizes; N = 8,549) met the inclusion criteria. We divided them into two groups, depending on whether they included a control group, and calculated the overall effect size using a random-effects Model with robust variance estimation. We assessed the influence of moderators using random effects metaregression. Results: The overall effect sizes of anchoring for studies with a control group (z = .27, 95% CI [.21, .33], d = .58, 95% CI [.44, .73]) and without a control group (z = .39, 95% CI [.31, .47], d = .91, 95% CI [.69, 1.12]) were both significant, although we provide some evidence of possible publication bias. We found preliminary evidence of a potential moderating effect of some legally relevant factors, such as legal expertise or the anchor relevance. Conclusions: Existing research indicates anchoring effects exist in legal contexts. The influence of anchors seems to depend on some situational factors, which paves the way for future research on countering the problematic effect in legal settings. (PsycInfo Database Record (c) 2021 APA, all rights reserved).