Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-23T00:49:42.008Z Has data issue: false hasContentIssue false
  • English
  • Français

A dynamic linear modelling approach to public policy change

Published online by Cambridge University Press:  16 October 2017

Matt W. Loftis  and
Peter B. Mortensen
Matt W. Loftis
Affiliation:
Department of Political Science, Aarhus University, Denmark E-mail: [email protected]
Peter B. Mortensen
Affiliation:
Department of Political Science, Aarhus University, Denmark E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Theories of public policy change, despite their differences, converge on one point of strong agreement: the relationship between policy and its causes can and does change over time. This consensus yields numerous empirical implications, but our standard analytical tools are inadequate for testing them. As a result, the dynamic and transformative relationships predicted by policy theories have been left largely unexplored in time series analysis of public policy. This article introduces dynamic linear modelling (DLM) as a useful statistical tool for exploring time-varying relationships in public policy. The article offers a detailed exposition of the DLM approach and illustrates its usefulness with a time series analysis of United States defense policy from 1957 to 2010. The results point the way for a new attention to dynamics in the policy process, and the article concludes with a discussion of how this research programme can profit from applying DLMs.

Keywords

policy dynamicspublic policypublic spendingPunctuated Equilibrium Theory
Type
Research Article
Information
Journal of Public Policy , Volume 38 , Issue 4 , December 2018 , pp. 553 - 579
Copyright
© Cambridge University Press, 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baltagi, B. (2011) Econometrics , 5th ed. Berlin: Springer Texts in Business and Economics.Google Scholar
Baumgartner, F. R. and Jones, B. D. (1993) Agendas and Instability in American Politics. Chicago, IL: University of Chicago Press.Google Scholar
Baumgartner, F. R. and Jones, B. D. (eds.) (2002) Policy Dynamics. Chicago: University Of Chicago Press.Google Scholar
Baumgartner, F. R. and Jones, B. D. (2015) The Politics of Information: Problem Definition and the Course of Public Policy in America. Chicago: University Of Chicago Press.Google Scholar
Baumgartner, F. R., Jones, B. D. and Mortensen, P. B. (2014) Punctuated equilibrium theory: Explaining stability and change in public policymaking. In P. A. Sabatier and C. M. Weible (eds.), Theories of the Policy Process, 3rd ed. New York, NY: Westview Press, 59–103.Google Scholar
Beck, N. (1983) Time-Varying Parameter Regression Models. American Journal of Political Science 27(3): 557–600.Google Scholar
Blyth, M. (2013) Paradigms and Paradox: The Politics of Economic Ideas in Two Moments of Crisis. Governance 26(2): 197–215.Google Scholar
Brandt, P. T., Williams, J. T., Fordham, B. O. and Pollins, B. (2000) Dynamic Modeling for Persistent Event-Count Time Series. American Journal of Political Science 44(4): 823–843.Google Scholar
Cairney, P. and Heikkila, T. (2014) A Comparison of Theories of the Policy Process. In P. A. Sabatier and C. M. Weible (eds.), Theories of the Policy Process, 3rd ed. New York, NY: Westview Press. pp. 363–390.Google Scholar
Campbell, J. L. (2002) Ideas, Politics, and Public Policy. Annual Review of Sociology 28(1): 21–38.Google Scholar
Caporin, M. and McAleer, M. (2013) Ten Things You Should Know About the Dynamic Conditional Correlation Representation. Econometrics 1(1): 115–126.Google Scholar
Commandeur, J. J. F. and Koopman, S. J. (2007) An Introduction to State Space Time Series Analysis. Oxford: Oxford University Press.Google Scholar
Commandeur, J. J. F., Koopman, S. J. and Ooms, M. (2011) Statistical Software for State Space Methods. Journal of Statistical Software 41(1): 1–18.Google Scholar
Correa, H. and Kim, J.-W. (1992) A Causal Analysis of the Defense Expenditures of the USA and the USSR. Journal of Peace Research 29(2): 161–174.Google Scholar
Cusack, T. R. (1992) On the Domestic Political-Economic Sources of American Military Spending. In A. Mintz (ed.) The Political Economy of Military Spending in the United States. London: Routledge. pp. 103–133.Google Scholar
Cusack, T. R. and Ward, M. D. (1981) Military Spending in the United States, Soviet Union, and the People’s Republic of China. The Journal of Conflict Resolution 25(3): 429–469.Google Scholar
De Boef, S. and Keele, L. (2008) Taking Time Seriously. American Journal of Political Science 52(1): 184–200.Google Scholar
Engle, R. (2002) Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models. Journal of Business & Economic Statistics 20(3): 339–350.Google Scholar
Enns, P. K. and McAvoy, G. E. (2011) The Role of Partisanship in Aggregate Opinion. Political Behavior 34(4): 627–651.Google Scholar
Fariss, C. J. (2014) Respect for Human Rights has Improved Over Time: Modeling the Changing Standard of Accountability. American Political Science Review 108: 297–318.Google Scholar
Finseraas, H. and Vernby, K. (2011) What Parties are and What Parties Do: Partisanship and Welfare State Reform in an Era of Austerity. Socio-Economic Review 9(4): 613–638.Google Scholar
Gerber, A. and Green, D. P. (1998) Rational Learning and Partisan Attitudes. American Journal of Political Science 42(3): 794–818.Google Scholar
Green, D. P., Gerber, A. S. and de Boef, S. L. (1999) Tracking Opinion Over Time: A Method for Reducing Sampling Error. The Public Opinion Quarterly 63(2): 178–192.Google Scholar
Griffin, L. J., Wallace, M. and Devine, J. (1982) The Political Economy of Military Spending: Evidence from the United States. Cambridge Journal of Economics 6(1): 1–14.Google Scholar
Hall, P. A. (1993) Policy Paradigms, Social Learning, and the State: The Case of Economic Policymaking in Britain. Comparative Politics 25: 275–296.Google Scholar
Hall, P. A. (2003) Aligning Ontology and Methodology in Comparative Research. Comparative Historical Analysis in the Social Sciences. Chapter 11. Cambridge and New York: Cambridge University Press. pp. 373–404.Google Scholar
Hall, P. A. (2006) Systematic Process Analysis: When and How to Use it. European Management Review 3(1): 24–31.Google Scholar
Hartley, T. and Russett, B. (1992) Public Opinion and the Common Defense: Who Governs Military Spending in the United States? The American Political Science Review 86(4): 905–915.Google Scholar
Higgs, R. and Kilduff, A. (1993) Public Opinion: A Powerful Predictor of U.S. Defense Spending. Defence Economics 4: 227–238.Google Scholar
Hogan, J. and Howlett, M. (eds.) (2015) Policy Paradigms in Theory and Practice. Discourses, Ideas and Anomalies in Public Policy Dynamics. London: Palgrave Macmillan.Google Scholar
Huber, E. and Stephens, J. D. (2001) Welfare State and Employment Regimes in the Era of Retrenchment. In P. Pierson (ed.) The New Politics of the Welfare State. Oxford: Oxford University Press, 107–145.Google Scholar
Jenkins-Smith, H. C., Nohrstedt, D., Weible, C. M. and Sabatier, P. A. (2014) The Advocacy Coalition Framework: Foundations, Evolution, and Ongoing Research. In P. A. Sabatier and C. M. Weible (eds.), Theories of the Policy Process, 3rd ed. New York, NY: Westview Press. pp. 183–223.Google Scholar
Jones, B. D. (1994) Reconceiving Decision-Making in Democratic Politics: Attention, Choice, and Public Policy. Chicago: University Of Chicago Press.Google Scholar
Jones, B. D. and Baumgartner, F. R. (2005) The Politics of Attention. How Government Prioritizes Problems. Chicago, IL: University of Chicago Press.Google Scholar
Kalaba, R. and Tesfatsion, L. (1988) The Flexible Least Squares Approach to Time-Varying Linear Regression. Journal of Economic Dynamics and Control 12: 43–48.Google Scholar
Kamlet, M. S. and Mowery, D. C. (1987) Influences on Executive and Congressional Budgetary Priorities, 1955-1981. The American Political Science Review 81(1): 155–178.Google Scholar
Kiewiet, D. R. and McCubbins, M. D. (1991) The Logic of Delegation: Congressional Parties and the Appropriations Process. Chicago: University Of Chicago Press.Google Scholar
Kim, C.-J. and Nelson, C. R. (2000) State-Space Models with Regime Switching. London: The MIT Press.Google Scholar
Kwon, H. Y. and Pontusson, J. (2010) Globalization, Labour Power and Partisan Politics Revisited. Socio-Economic Review 8(2): 251–281.Google Scholar
Lebo, M. J. and Box-Steffensmeier, J. M. (2008) Dynamic Conditional Correlations in Political Science. American Journal of Political Science 52(3): 688–704.Google Scholar
Lieberman, R. C. (2002) Ideas, Institutions, and Political Order: Explaining Political Change. The American Political Science Review 96(4): 697–712.Google Scholar
Majeski, S. J. (1983) Mathematical Models of the U.S. Military Expenditure Decision-Making Process. American Journal of Political Science 27(3): 485–514.Google Scholar
Majeski, S. J. (1992) Defense Budgeting, Fiscal Policy, and Economic Performance. In A. Mintz (ed.), The Political Economy of Military Spending in the United States. London: Routledge. pp. 217–237.Google Scholar
Mcavoy, G. E. (2006) Stability and Change: The Time Varying Impact of Economic and Foreign Policy Evaluations on Presidential Approval. Political Research Quarterly 59(1): 71–83.Google Scholar
Mergner, S. (2009) Applications of State Space Models in Finance. Göttingen, Germany: Universittsverlag Göttingen.Google Scholar
Mitchell, S. M., Gates, S. and Hegre, H. (1999) Evolution in Democracy-War Dynamics. Journal of Conflict Resolution 43(6): 771–792.Google Scholar
Montana, G., Triantafyllopoulos, K. and Tsagaris, T. (2009) Flexible Least Squares for Temporal Data Mining and Statistical Arbitrage. Expert Systems WITH APPLICATIONS 36(2, Part 2): 2819–2830.Google Scholar
Mortensen, P. B., Green-Pedersen, C., Breeman, G., Chaqus-Bonafont, L., Jennings, W., John, P., Palau, A. M. and Timmermans, A. (2011) Comparing Government Agendas: Executive Speeches in the Netherlands, United Kingdom, and Denmark. Comparative Political Studies 44(8): 973–1000.Google Scholar
Nincic, M. and Cusack, T. R. (1979) The Political Economy of US Military Spending. Journal of Peace Research 16(2): 101–115.Google Scholar
Ostrom, C. W. Jr. (1977) Evaluating Alternative Foreign Policy Decision-Making Models: An Empirical Test Between an Arms Race Model and an Organizational Politics Model. The Journal of Conflict Resolution 21(2): 235–266.Google Scholar
Ostrom, C. W. Jr. (1978) A Reactive Linkage Model of the U.S. Defense Expenditure Policymaking Process. The American Political Science Review 72(3): 941–957.Google Scholar
Ostrom, C. W. Jr. and Marra, R. F. (1986) U.S. Defense Spending and the Soviet Estimate. The American Political Science Review 80(3): 819–842.Google Scholar
Palmer, G., D’Orazio, V., Kenwick, M. and Lane, M. (2015) The MID4 Dataset, 20022010: Procedures, Coding Rules and Description. Conflict Management and Peace Science 32(2): 222–242.Google Scholar
Petris, G. (2010) An R Package for Dynamic Linear Models. Journal of Statistical Software 36(12): 1–16.Google Scholar
Petris, G. and Petrone, S. (2011) State Space Models in R. Journal of Statistical Software 41(4): 1–25.Google Scholar
Petris, G., Petrone, S. and Campagnoli, P. (2009) Dynamic Linear Models with R. New York, NY: Springer.Google Scholar
Pierson, P. (1996) The New Politics of the Welfare State. World Politics 48: 143–179.Google Scholar
Pierson, P. (2000) Path Dependence, Increasing Returns, and the Study of Politics. The American Political Science Review 94(2): 251–267.Google Scholar
Princen, S. and ’t Hart, P. (2014) Putting Policy Paradigms in Their Place. Journal of European Public Policy 21(3): 470–474.Google Scholar
Rosenthal, H. and Poole, K. (2015) House Polarization 1st to 113th Congresses, ftp://voteview.com/house-polarization46-113.txt (accessed 13 July 2015).Google Scholar
Sabatier, P. (1987) Knowledge, Policy-Oriented Learning, and Policy Change. Knowledge 8: 649–692.Google Scholar
Sabatier, P. (1988) An Advocacy Coalition Framework of Policy Change and the Role of Policy-Oriented Learning Therein. Policy Sciences 21: 129–168.Google Scholar
Sabatier, P. A. (1998) The Advocacy Coalition Framework: Revisions and Relevance for Europe. Journal of European Public Policy 5(1): 98–130.Google Scholar
Sabatier, P. and Jenkins-Smith, H. (eds.) (1993) Policy Change and Learning: An Advocacy Coalition Approach. Boulder, CO: Westview Press.Google Scholar
Shumway, R. H. and Stoffer, D. S. (2010) Time Series Analysis and its Applications: With R Examples. New York: Springer.Google Scholar
Steinmo, S., Thelen, K. and Longstreth, F. (eds.) (1992) Structuring Politics: Historical Institutionalism in Comparative Analysis. Cambridge: Cambridge University Press.Google Scholar
Su, T.-T., Kamlet, M. S. and Mowery, D. C. (1993) Modeling U.S. Budgetary and Fiscal Policy Outcomes: A Disaggregated, Systemwide Perspective. American Journal of Political Science 37(1): 213–245.Google Scholar
True, J. L. (2002) The Changing Focus of National Security Policy. In F. R. Baumgartner and B. D. Jones (eds.), Policy Dynamics. Chicago, IL: University of Chicago Press, 155–183.Google Scholar
Tusell, F. (2011) Kalman Filtering in R. Journal of Statistical Software 39(2): 1–27.Google Scholar
Weible, C. M., Sabatier, P. A., Jenkins-Smith, H. C., Nohrstedt, D., Henry, A. D. and deLeon, P. (2011) A Quarter Century of the Advocacy Coalition Framework: An Introduction to the Special Issue. The Policy Studies Journal 39(3): 349–360.Google Scholar
Weible, C. M., Sabatier, P. A. and McQueen, K. (2009) Themes and Variations: Taking Stock of the Advocacy Coalition Framework. The Policy Studies Journal 37(1): 121–140.Google Scholar
Whitten, G. D. and Williams, L. K. (2011) Buttery Guns and Welfare Hawks: The Politics of Defense Spending in Advanced Industrial Democracies. American Journal of Political Science 55(1): 117–134.Google Scholar
Wlezien, C. (1996) Dynamics of Representation: The Case of US Spending on Defence. British Journal of Political Science 26(1): 81–103.Google Scholar
Wood, B. D. (2000) Weak Theories and Parameter Instability: Using Flexible Least Squares to Take Time Varying Relationships Seriously. American Journal of Political Science 44(3): 603–618.Google Scholar
Wood, B. D. and Doan, A. (2003) The Politics of Problem Definition: Applying and Testing Threshold Models. American Political Science Review 47(4): 640–653.Google Scholar
Zuk, G. and Woodbury, N. R. (1986) U.S. Defense Spending, Electoral Cycles, and Soviet-American Relations. The Journal of Conflict Resolution 30(3): 445–468.Google Scholar
Supplementary material: PDF

Loftis and Mortensen supplementary material 1

Loftis and Mortensen supplementary material

Download Loftis and Mortensen supplementary material 1(PDF)
PDF 1.3 MB