Policy Design

Session 01. Introduction
Getting to know each other. Short debate on the course topics. Overview of the course structure, resources, and expectations.
Backing materials:
Easton, D. (1957). An Approach to the Analysis of Political Systems. World Politics, 9(3), 383-400. https://doi.org/10.2307/2008920
Robertson, D. B. (1984). Program implementation versus program design: which accounts for policy "failure"?. Review of Policy Research, 3(3‐4), 391-405. https://doi.org/10.1111/j.1541-1338.1984.tb00133.x

Session 02. Policy design, logic models, and theory of change
Exploring the systematic approach to policy design through logic models and theories of change. Understanding how interventions connect to outcomes, building culturally responsive frameworks, and applying institutional analysis to policy development.
Backing materials:
Meyer, M. L., Louder, C. N., & Nicolas, G. (2021). Creating with, not for people: theory of change and logic models for culturally responsive community-based intervention. American Journal of Evaluation, 43(3), 378-393. https://doi.org/10.1177/10982140211016059
Polski, M.M., and E. Ostrom. (2017) An Institutional Framework for Policy Analysis and Design. In Cole, D.H. and M.D. McGinnis (eds.), Elinor Ostrom and the Bloomington School of Political Economy: Volume 3, A Framework for Policy Analysis. Lanham, MD: Lexington Books, 13-48.

Module A1.
Unpacking policy problems
Session 03. Policy problems and their structure
Analyzing how policy problems are defined, structured, and framed. Examining the social construction of target populations and how problem definition shapes policy solutions and political dynamics.
Backing materials:
Peters, B. G. (2018). Policy Problems and Policy Design, Edwar Elgar, Ch. 1
Schneider, A. and Ingram, H. (1993). Social construction of target populations: implications for politics and policy, American Political Science Review 87(2), 334-347. https://www.jstor.org/stable/2939044

Session 04. Theoretical foundations: old and new behavioralism
Tracing the evolution from rational choice theory to behavioral insights in policy studies. Examining bounded rationality, behavioral models, and prospect theory applications to political science and policy design.
Backing materials:
Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 69(1), 99-118. https://doi.org/10.2307/1884852
Caraley, D. (1964). The political behavior approach: methodological advance or new formalism?-- a review article. Political Science Quarterly, 79(1), 96-108. https://doi.org/10.2307/2146576
Mercer, J., 2005. Prospect theory and political science. Annual Review of Political Science, 8(1), 1-21. https://doi.org/10.1146/annurev.polisci.8.082103.104911

Session 05. Theoretical foundations: neoinstitutionalisms
Understanding historical, rational, sociological, and discursive institutionalism .
Backing materials:
Immergut, E. M. (1998). The theoretical core of the new institutionalism. Politics & Society, 26(1), 5-34. https://doi.org/10.1177/0032329298026001002
Hall, P. A., & Taylor, R. C. R. (1996). Political science and the three new institutionalisms. Political Studies, 44(5), 936-957. https://doi.org/10.1111/j.1467-9248.1996.tb00343.x
Carstensen, M. B., & Schmidt, V. A. (2015). Power through, over, and in ideas: conceptualizing ideational power in discursive institutionalism. Journal of European Public Policy, 23(3), 318-337. https://doi.org/10.1080/13501763.2015.1115534

Session 06. Conceptual foundations: Coleman's boat
Policy problems' drivers: situational, action-formation, and transformational mechanisms.
Backing materials:
Hedström, P. and Ylikoski, P., 2010. Causal mechanisms in the social sciences. Annual Review of Sociology, 36(1), pp.49-67. https://doi.org/10.1146/annurev.soc.012809.102632
Raub, W., Buskens, V. and Van Assen M.A.L.M. (2011). Micro-macro links and microfoundations in sociology. The Journal of Mathematical Sociology, 35:1-3, 1-25. https://doi.org/10.1080/0022250X.2010.532263

Session 07. Group exercise
Select a current policy challenge. Unpack it in terms of Coleman's boat, with special attention to plausible situational, action formation, and aggregation mechanisms. Present your analysis to class.
Deliverable to submit: a max 1500-word written report, including the visualization of your Coleman's boat, according to the following template:
a) title
b) description of the policy problem
c) identification of the key actors
d) analysis of each mechanism (situational → action formation → transformation)
e) Coleman's boat visualization
f) concluding reflections
The deliverable will be assigned:
- max 4 pts for comprehension and use of the Coleman's boat framework (correct, complete, clear, consistent discussion of the mechanisms);
- max 2 pts for analytical depth (credible justification of the mechanism in light of course and external knowledge)
- max 1 pts for the quality of the visualization (accurate and clear diagram);
- max 1 pts for writing quality (organized and clear writing).

Module A2.
Changing people's behavior
Session 08. Policy tools: behavioral assumptions of addressees' compliance
Tweaking situational mechanisms.
Backing materials:
Vedung, E. (2017). Policy instruments: Typologies and theories. In Bemelmans-Videc, M.-L., Rist, R. C., & Vedung, E. (Eds.). Carrots, Sticks and Sermons (pp. 21-58). Routledge.
Schneider, A., & Ingram, H. (1990). Behavioral assumptions of policy tools. The Journal of Politics, 52(2), 510-529. https://doi.org/10.2307/2131904
McDonnell, L. M., & Elmore, R. F. (1987). Getting the job done: alternative policy instruments. Educational Evaluation and Policy Analysis, 9(2), 133-152. https://doi.org/10.2307/1163726
Strassheim, H. (2021). Behavioural mechanisms and public policy design: Preventing failures in behavioural public policy. Public Policy and Administration, 36(2), 187-204. https://doi.org/10.1177/0952076719827062

Session 09. Regulation
Examining regulation as a policy tool, from command-and-control to meta-regulation approaches. Understanding compliance behavior, enforcement strategies, and potential crowding-out effects of regulatory interventions.
Backing materials:
Lemaire, D. (2017). The stick: regulation as a tool of government. In Bemelmans-Videc, M. L., Rist, R. C., & Vedung, E. (Eds.). Carrots, Sticks and Sermons (pp. 59-76). Routledge.
Scott, C. (2003). Speaking softly without big sticks: Meta‐regulation and public sector audit. Law & Policy, 25(3), 203-219.
Reinders Folmer, C. P. (2021). Crowding-out effects of laws, policies, and incentives on compliant behaviour. In B. van Rooij & D. D. Sokol (Eds.), The Cambridge Handbook of Compliance (pp. 326-340). Cambridge University Press. https://doi.org/10.1017/9781108759458.023

Session 10. Taxation and expenditure
Analyzing fiscal tools as policy instruments. Exploring tax expenditures, subsidies, and direct spending programs. Understanding how economic incentives shape behavior and are expected to achieve policy goals.
Backing materials:
McIlroy-Young, B., Henstra, D., & Thistlethwaite, J. (2022). Treasure tools: using public funds to achieve policy objectives. In Howlett, M, (Ed). The Routledge Handbook of Policy Tools (pp. 332-344). Routledge.
Hakelberg, L., & Seelkopf, L. (2021). Introduction. In Id. (ds.), Handbook on the Politics of Taxation. Edward Elgar, pp. 1-15. https://doi.org/10.4337/9781788979429.00008
Guerra, A., & Harrington, B. (2021). Why do people pay taxes? Explaining tax compliance by individuals. In Hakelberg, L., & Seelkopf, L. (Eds.). Handbook on the Politics of Taxation. Edward Elgar, pp. 355-373. https://doi.org/10.4337/9781788979429.00036
Burton, M., & Sadiq, K. (2013). Tax Expenditure Management: A Critical Assessment Cambridge University Press, Ch.2. https://doi.org/10.1017/CBO9780511910142.002
Clements, B. and Hugounenq, R. and Schwartz, G., (1995). Government subsidies: concepts, international trends, and reform options . IMF Working Paper No. 95/91, https://ssrn.com/abstract=883238
Pope, K. R. (2017). All the Queen's Horses. https://www.dailymotion.com/video/x9hl3zg

Session 11. Information
Information as a policy instrument: from public campaigns to educational testing. Understanding persuasion mechanisms, framing effects, and the strategic use of information in policy effectiveness.
Backing materials:
Vedung, E., & van der Doelen F.C.J. (2017). The sermon: information programs in the public policy process—choice, effects, and evaluation. In Bemelmans-Videc, M.-L., Rist, R.C., & Vedung, E. (Eds.). Carrots, Sticks and Sermons (pp. 103-128). Routledge.
McDonnell, L.M. (2004). Politics, Persuasion, and Educational Testing, Harvard University Press, Ch.2. https://doi.org/10.4159/9780674040786-005
Druckman, J. N. (2022). A framework for the study of persuasion. Annual Review of Political Science, 25(1), 65-88. https://doi.org/10.1146/annurev-polisci-051120-110428

Session 12. Nudges and shoves
Applying behavioral insights to policy design through choice architecture. Examining ethical dimensions of libertarian paternalism, manipulation concerns, and the effectiveness of behavioral interventions across policy domains.
Backing materials:
Sunstein, C. R. (2020). Behavioral Science and Public Policy. Cambridge University Press. https://doi.org/10.1017/9781108973144
Miller, D. & Prentice, D. (2013). Psychological levers of behavior change. In E. Shafir (Ed.), The Behavioral Foundations of Public Policy (pp. 301-309). Princeton University Press. https://doi.org/10.1515/9781400845347-021
John, P. (2013). All tools are informational now: how information and persuasion define the tools of government. SSRN. http://dx.doi.org/10.2139/ssrn.2141382
Weber, E. (2013). Doing the right thing willingly: Using the insights of behavioral decision research for better environmental decisions. In E. Shafir (Ed.), The Behavioral Foundations of Public Policy (pp. 380-397). Princeton University Press. https://doi.org/10.1515/9781400845347-026
Thaler, R., Sunstein, C. & Balz, J. (2013). Choice architecture. In E. Shafir (Ed.), The Behavioral Foundations of Public Policy (pp. 428-439). Princeton University Press. https://doi.org/10.1515/9781400845347-029
Lichtenberg, J. (2013). Paternalism, manipulation, freedom, and the good. In E. Shafir (Ed.), The Behavioral Foundations of Public Policy (pp. 494-498). Princeton University Press. https://doi.org/10.1515/9781400845347-034
Malanowski, S. C., Baima, N. R., & Kennedy, A. G. (2022, July). Science, shame, and trust: against shaming policies. In: Resch, M.M., Formánek, N., Joshy, A., Kaminski, A. (eds) The Science and Art of Simulation (pp. 147-160). Springer. https://doi.org/10.1007/978-3-031-68058-8_10

Session 13. Group exercise
Building on Session 7 analysis, revisit and refine your Coleman's boat. Develop a credible theory of change. Select the policy tools that would activate the hypothesized mechanisms. Create a visual logic model. Present your model in class, and engage in peer discussion.
Deliverable to submit: A visual logic model and a max 1000-word written justification explaining your chosen theory of change, a selection of substantive policy tools, and a discussion of the behavioral assumptions that promise to cushion, reduce, or eliminate the policy problem you set in the previous deliverable, according to the following template:
a) Title
b) Theory of change
c) Substantive tools
d) Logic model (figure)
e) Ethical and/or practical reflections
Your deliverable will be graded according to the following rubric:
- max. 3 pts to the coherence of your theory of change (logical, well-justified chain-of-reasoning to expected outcomes)
- max 3 pts to the appropriateness of tool selection (behavioral assumptions credibly triggering the identified change);
- max 1 pt to the logic model (complete, accurate, visually clar);
- max 1 pt to writing quality (clarity, structure)

Module A3.
Making substantive tools work
Session 14. Procedural policy tools
Managing governance through process: consultation mechanisms, participatory instruments, and deliberative approaches. Understanding how procedural tools complement substantive policy instruments in modern governance.
Backing materials:
Howlett, M. (2000). Managing the "hollow state": Procedural policy instruments and modern governance. Canadian Public Administration, 43(4), 412-431. https://doi.org/10.1111/j.1754-7121.2000.tb01152.x
Fung, A. (2006). Varieties of participation in complex governance. Public Administration Review, 66, 66-75. https://doi.org/10.1111/j.1540-6210.2006.00667.x
Fraussen, B. (2022). Consultation tools and agenda-setting. In Howlett, M. (Ed). The Routledge Handbook of Policy Tools (pp. 149-159). Routledge. https://hdl.handle.net/1887/3502352
Wagner, W., West, W., McGarity, T., & Peters, L. (2021). Deliberative rulemaking. Administrative Law Review, 73(3), 609-687. https://www.jstor.org/stable/27178501
Balla, S. J., Beck, A. R., Cubbison, W. C., & Prasad, A. (2019). Where's the spam? Interest groups and mass comment campaigns in agency rulemaking. Policy & Internet, 11(4), 460-479. https://doi.org/10.1002/poi3.224

Session 15. Accountability tools
Transparency, monitoring, and evaluation as policy instruments. Examining fiscal openness, corruption control, and trust-building mechanisms. Understanding how accountability tools enhance policy effectiveness and legitimacy.
Backing materials:
De Renzio, P., & Wehner, J. (2017). The impacts of fiscal openness. The World Bank Research Observer, 32(2), 185-210. https://doi.org/10.1093/wbro/lkx004
Hollyer, J. R., Rosendorff, B. P., & Vreeland, J. R. (2015). Transparency, protest, and autocratic instability. The American Political Science Review, 109(4), 764-784. http://www.jstor.org/stable/24809509
Bourgeois, I., & Maltais, S. (2023). Translating evaluation policy into practice in government organizations. American Journal of Evaluation, 44(3), 353-373. https://doi.org/10.1177/10982140221079837
Olken, B. A. (2007). Monitoring corruption: evidence from a field experiment in Indonesia. Journal of Political Economy, 115(2), 200-249. https://www.jstor.org/stable/10.1086/517935
Ostrom, E. (2009). Building trust to solve commons dilemmas: taking small steps to test an evolving theory of collective action. In: Levin, S.A. (ed.) Games, Groups, and the Global Good (pp. 207-228). Springer. https://doi.org/10.1007/978-3-540-85436-4_13; https://ssrn.com/abstract=1304695

Session 16. Guided group exercise
Embed substantive and procedural tools within an action situation.
Deliverable to submit: Building on the results of Session 13, elaborate a complete action situation scheme that integrates substantive and procedural policy tools and a max 1500-word narrative discussing how the action situation setting can secure the expected policy outcomes, following this template:
a) Title
b) Procedural and substantive tools as the seven elements of the action situation
c) The action situation (figure)
d) Why these joint constraints promise effectiveness?
e) Reflections on limitations
Your deliverable will be assigned:
- max 2 pts to the diagram of the action situation (complete, clear)
- max 3 pts to the discussion of the seven elements (complete and consistent rendering of procedural and substantive tools)
- max 2 pts to the explanation of constraints' effectiveness (consistency, credibility)
- max 1 pt to the identification of limits (credibility)
- max 1 pt to the writing quality (structure, clarity)

Module B.
Establishing policy design effectiveness
Session 17. Design-driven strategies for establishing causation
Applying Mill's methods, counterfactual reasoning, and natural experiments to policy evaluation. Understanding strengths and limitations of quasi-experimental approaches to causal inference.
Backing materials:
Ducheyne, S. (2008): J.S. Mill's canons of induction: from true causes to provisional ones, History and Philosophy of Logic, 29:4, 361-376. http://doi.org/10.1080/01445340802164377
Fearon, J. D. (1991). Counterfactuals and hypothesis testing in political science. World Politics, 43(2), 169-195. https://doi.org/10.2307/2010470
Dunning, T. (2008). Improving causal inference: Strengths and limitations of natural experiments. Political Research Quarterly, 61(2), 282-293. https://doi.org/10.1177/1065912907306470
Holland, P. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81(396), 945-960. https://doi.org/10.1080/01621459.1986.10478354

Session 18. Model-driven strategies for establishing causation
From Aristotelian causation to modern mechanistic explanations. Understanding causal mechanisms, INUS conditions, and causal graphs. Identifying good and bad controls in causal research design.
Backing materials:
Moravcsik, J. M. E. (1974). Aristotle on adequate explanations. Synthese, 28(1), 3-17. http://www.jstor.org/stable/20114949
Glennan, S., Illari, P. & Weber, E. (2022). Six theses on mechanisms and mechanistic science. Journal for General Philosophy of Science 53, 143-161. https://doi.org/10.1007/s10838-021-09587-x
Mackie, J. L. (1965). Causes and conditions. American Philosophical Quarterly, 2(4), 245-264. https://www.jstor.org/stable/20009173
Cinelli, C., Forney, A., & Pearl, J. (2024). A crash course in good and bad controls. Sociological Methods & Research, 53(3), 1071-1104. https://doi.org/10.1177/00491241221099552

Session 19. Building and findings indicators
Constructing valid and reliable indicators, addressing measurement challenges, and linking indicators to theories of change and logic models.
Backing materials:
Goertz, G. (2020). Concept structure: aggregation and substitutability. In Id. Social science concepts and measurement. Princeton University Press, Ch.6.
Adcock, R., & Collier, D. (2001). Measurement validity: a shared standard for qualitative and quantitative research. American Political Science Review, 95(3), 529-546. https://doi.org/10.1017/S0003055401003100

Session 20. Capstone
Students integrate constraints, institutional structure, and actor motivations into a complete design blueprint, ready for empirical testing.
Deliverable to submit: a research proposal (max 1500 words) that includes
- A clear causal question or hypothesis
- The policy design to be tested;
- The proposed methods for establishing causal inference
- Indicators for measuring design features and outcomes
The deliverable will be assigned:
- max 2 pts to the causal question (well-formulated, clear, consistent with the course concepts)
- max 3 pts to the selected methodology (appropriate, consistent with the driving question, well-justified)
- max 2 pts to indicator (consistent and appropriate constructs)
- max 1 pt to writing quality (well-structured, clear)