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Measuring Discretion and Delegation in Legislative Texts: Methods and Application to US States

Published online by Cambridge University Press:  26 May 2020

Matia Vannoni Open the ORCID record for Matia Vannoni [Opens in a new window] ,
Elliott Ash Open the ORCID record for Elliott Ash [Opens in a new window]  and
Massimo Morelli Open the ORCID record for Massimo Morelli [Opens in a new window]
Matia Vannoni*
Affiliation:
King’s College London, WC2B 4BG London, UK. Email: matia.vannoni@kcl.ac.uk
Elliott Ash
Affiliation:
ETH Zurich, 8092 Zürich, Switzerland. Email: ashe@ethz.ch
Massimo Morelli
Affiliation:
Bocconi University and CEPR, 20136 Milan, Italy. Email: massimo.morelli@unibocconi.it
*
* Email: matia.vannoni@kcl.ac.uk
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Abstract

Bureaucratic discretion and executive delegation are central topics in political economy and political science. The previous empirical literature has measured discretion and delegation by manually coding large bodies of legislation. Drawing from computational linguistics, we provide an automated procedure for measuring discretion and delegation in legal texts to facilitate large-scale empirical analysis. The method uses information in syntactic parse trees to identify legally relevant provisions, as well as agents and delegated actions. We undertake two applications. First, we produce a measure of bureaucratic discretion by looking at the level of legislative detail for US states and find that this measure increases after reforms giving agencies more independence. This effect is consistent with an agency cost model, where a more independent bureaucracy requires more specific instructions (less discretion) to avoid bureaucratic drift. Second, we construct measures of delegation to governors in state legislation. Consistent with previous estimates using non-text metrics, we find that executive delegation increases under unified government.

Keywords

natural language processingtext analysisexecutive delegationbureaucratic independenceUS politics

Information

Type
Articles
Information
Political Analysis , Volume 29 , Issue 1 , January 2021 , pp. 43 - 57
Copyright
Copyright © The Author(s) 2020. Published by Cambridge University Press on behalf of the Society for Political Methodology.

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Footnotes

Contributing Editor: Jeff Gill

References

Al-Ubaydli, O., and McLaughlin, P. A.. 2017. “RegData: A Numerical Database on Industry-Specific Regulations for All United States Industries and Federal Regulations, 1997–2012.” Regulation & Governance 11(1):109–123.CrossRefGoogle Scholar
Ash, E.2016. “The Political Economy of Tax Laws in the US States.” Working Paper.Google Scholar
Ash, E., MacLeod, B., and Naidu, S.. “The Language of Contract: Promises and Power in Union Collective Bargaining Agreements.” Working Paper.Google Scholar
Baker, C. F., Fillmore, C. J., and Lowe, J. B.. 1998. “The Berkeley Framenet Project.” In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics-Volume 1 , 86–90. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Beyle, T. 1990. “The Powers of the Governor in North Carolina: Where the Weak Grow Strong-Except for the Governor.” North Carolina Insight 12:27–45.Google Scholar
Beyle, T.2007. “Gubernatorial Power: The Institutional Power Ratings for the 50 Governors of the United States.” University of North Carolina at Chapel Hill.Google Scholar
Caughey, D., Xu, Y., and Warshaw, C.. 2017. “Incremental Democracy: The Policy Effects of Partisan Control of State Government.” The Journal of Politics 79(4):1342–1358.CrossRefGoogle Scholar
Ceci, M., Lesmo, L., Mazzei, A., Palmirani, M., and Radicioni, D. P.. 2011. “Semantic Annotation of Legal Texts Through A Framenet-Based Approach.” In International Workshop on AI Approaches to the Complexity of Legal Systems , 245–255. Heidelberg, Germany: Springer.Google Scholar
Choi, J. D., Tetreault, J., and Stent, A.. 2015. “It Depends: Dependency Parser Comparison Using a Web-based Evaluation Tool.” In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing , 387–396. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Correia, Sergio. 2016. “Linear Models with High-Dimensional Fixed Effects: An Efficient and Feasible Estimator.” Technical Report. Working Paper.Google Scholar
Epstein, D., and O’Halloran, S.. 1994. “Administrative Procedures, Information, and Agency Discretion.” American Journal of Political Science 38(3):697–722.Google Scholar
Epstein, D., and O’Halloran, S.. 1999. Delegating Powers . Cambridge: Cambridge University Press.Google Scholar
Franchino, F. 2004. “Delegating Powers in the European Community.” British Journal of Political Science 34(2):269–293.CrossRefGoogle Scholar
Gailmard, S., and Patty, J.. 2012. “Formal Models of Bureaucracy.” Annual Review of Political Science 15(1):353–377.CrossRefGoogle Scholar
Gentzkow, M., and Shapiro, J.. 2010. “What Drives Media Slant? Evidence from US Daily Newspapers.” Econometrica 78(1):35–71.Google Scholar
Goldberg, Y., and Nivre, J.. 2012. “A Dynamic Oracle for Arc-Eager Dependency Parsing.” In Proceedings of COLING 2012 , 959–976.Google Scholar
Grimmer, J., and Stewart, B. M.. 2013. “Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts.” Political Analysis 21(3):267–297.CrossRefGoogle Scholar
Honnibal, M., and Johnson, M.. 2015. “An Improved Non-monotonic Transition System for Dependency Parsing.” In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing , 1373–1378. Stroudsburg, PA: Association for Computational Linguistics.CrossRefGoogle Scholar
Huber, J. D., and Shipan, C. R.. 2002. Deliberate Discretion?: The Institutional Foundations of Bureaucratic Autonomy . Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Huber, J. D., and Shipan, C. R.. 2008. Politics, Delegation, and Bureaucracy . Oxford: Oxford University Press.Google Scholar
Jurafsky, D., and James, H.. 2000. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech . London: Pearson Education.Google Scholar
Klarner, C. 2003. “Measurement of the Partisan Balance of State Government.” State Politics & Policy Quarterly 3(3):309–319.CrossRefGoogle Scholar
Klebanov, B. B., Diermeier, D., and Beigman, E.. 2008. “Lexical Cohesion Analysis of Political Speech.” Political Analysis 16(4):447–463.CrossRefGoogle Scholar
Kousser, T., and Phillips, J. H.. 2012. The Power of American Governors: Winning on Budgets and Losing on Policy . Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Krupnikov, Y., and Shipan, C.. 2012. “Measuring Gubernatorial Budgetary Power: A New Approach.” State Politics & Policy Quarterly 12(4):438–455.CrossRefGoogle Scholar
Lame, G. 2003. “Using Text Analysis Techniques to Identify Legal Ontologies’ Components.” In ICAIL 2003 Workshop on Legal Ontologies & Web Based Legal Information Management , 50–61.Google Scholar
Lauderdale, B., and Herzog, A.. 2016. “Measuring Political Positions from Legislative Speech.” Political Analysis 24(3):374–394.Google Scholar
Laver, M., and Garry, J.. 2000. “Estimating Policy Positions from Political Texts.” American Journal of Political Science 3(44):619–634.CrossRefGoogle Scholar
Levine, M. E., and Forrence, J. L.. 1990. “Regulatory Capture, Public Interest, and the Public Agenda: Toward a Synthesis.” Journal of Law Economics and Organization 6:167–198.CrossRefGoogle Scholar
Lucas, C., Nielsen, R. A., Roberts, M. E., Stewart, B. M., Storer, A., and Tingley, D.. 2015. “Computer-Assisted Text Analysis for Comparative Politics.” Political Analysis 23(2):254–277.CrossRefGoogle Scholar
Martin, E. M. 1997. “An Informational Theory of the Legislative Veto.” Journal of Law Economics and Organization 13(2):319–343.Google Scholar
McCubbins, M. D., Noll, R. G., and Weingast, B. R.. 1987. “Administrative Procedures as Instruments of Political Control.” Journal of Law Economics and Organization 3(2):243–277.Google Scholar
McCubbins, M., and Schwartz, T.. 1984. “Congressional Oversight Overlooked: Police Patrols Versus Fire Alarms.” American Journal of Political Science 28(1):165–179.CrossRefGoogle Scholar
Miller, G. A. 1995. “WordNet: A Lexical Database for English.” Communications of the ACM 38(11):39–41.CrossRefGoogle Scholar
Monroe, B. L., Colaresi, M. P., and Quinn, K. M.. 2008. “Fightin’ Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict.” Political Analysis 16(4):372–403.CrossRefGoogle Scholar
O’Connor, B., Stewart, B. M., and Smith, N. A.. 2013. “Learning to Extract International Relations from Political Context.” Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, Volume 1: Long Papers , 1094–1104.Google Scholar
O’Halloran, S., Maskey, S., McAllister, G., Park, D. K., and Chen, K.. 2016. “Data Science and Political Economy: Application to Financial Regulatory Structure.” RSF: The Russell Sage Foundation Journal of the Social Sciences 2(7):87–109.Google Scholar
Palmirani, M., Ceci, M., Radicioni, D., and Mazzei, A.. 2011. “FrameNet Model of the Suspension of Norms.” In Proceedings of the 13th International Conference on Artificial Intelligence and Law , 189–193.CrossRefGoogle Scholar
Roberts, M. E., Stewart, B. M., Tingley, D., Lucas, C., Luis, J. L., Gadarian, S. K., Albertson, B., and Rand, D. G.. 2014. “Structural Topic Models for Open-Ended Survey Responses.” American Journal of Political Science 58(4):1064–1082.CrossRefGoogle Scholar
Rosenthal, A. 1982. “The State of State Legislatures: An Overview.” Hofstra Law Review 11:1185–1204.Google Scholar
Ruhil, A. V. S., and Camões, P. J.. 2003. “What Lies Beneath: The Political Roots of State Merit Systems.” Journal of Public Administration Research and Theory 13(1):27–42.Google Scholar
Ruppenhofer, J., Ellsworth, M., Petruck, M. R. L., Johnson, C. R., and Scheffczyk, J.. 2006. FrameNet II: Extended Theory and Practice . Berkeley, CA: International Computer Science Institute.Google Scholar
Saias, J., and Quaresma, P.. 2004. “Using NLP Techniques to Create Legal Ontologies in A Logic Programming Based Web Information Retrieval System.” In Workshop on Legal Ontologies and Web Based Legal Information Management of the 9th International Conference on Artificial Intelligence and Law .Google Scholar
Soria, C., Bartolini, R., Lenci, A., Montemagni, S., and Pirrelli, V.. 2007. “Automatic Extraction of Semantics in Law Documents.” In Proceedings of the V Legislative XML Workshop , edited by Biagioli, C., Francesconi, E., and Sartor, G., 253–266. European Press Academic Publishing.Google Scholar
Vakilifathi, M. 2019. “Constraining Bureaucrats Today Knowing You’ll Be Gone Tomorrow: The Effect of Legislative Term Limits on Statutory Discretion.” Policy Studies Journal 47(4):978–1001.CrossRefGoogle Scholar
Van Atteveldt, W., Kleinnijenhuis, J., and Ruigrok, N.. 2008. “Parsing, Semantic Networks, and Political Authority using Syntactic Analysis to Extract Semantic Relations from Dutch Newspaper Articles.” Political Analysis 16(4):428–446.CrossRefGoogle Scholar
van Engers, T. M., van Gog, R., and Sayah, K.. 2004. “A Case Study on Automated Norm Extraction.” In Legal Knowledge and Information Systems. Jurix 2004: The Seventeenth Annual Conference , edited by Gordon, T., 49–58. Amsterdam, Netherlands: IOS Press.Google Scholar
Vannoni, M., Ash, E., and Morelli, M.. 2020. “Replication Data for: Measuring Discretion and Delegation in Legislative Texts: Methods and Application to U.S. States.” https://doi.org/10.7910/DVN/FQTA4A, Harvard Dataverse, V1, UNF:6:jXzgM/eYOZkItuUH2Zdarw== [fileUNF].Google Scholar
Volden, C. 2002. “A Formal Model of the Politics of Delegation in a Separation of Powers System.” American Journal of Political Science 46(1):111–133.CrossRefGoogle Scholar
Wood, B. D., and Bohte, J.. 2004. “Political Transaction Costs and The Politics of Administrative Design.” Journal of Politics 66(1):176–202.CrossRefGoogle Scholar
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