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The Evolution of American Government Implications for Business and Industry

The Evolution of American Government Implications for Business and Industry. Frank R. Baumgartner Professor and Head The Pennsylvania State University Management Strategy and the Business Environment The Wharton School, University of Pennsylvania March 27, 2004. Outline of Today’s Talk.

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The Evolution of American Government Implications for Business and Industry

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  1. The Evolution of American GovernmentImplications for Business and Industry Frank R. Baumgartner Professor and Head The Pennsylvania State University Management Strategy and the Business Environment The Wharton School, University of Pennsylvania March 27, 2004

  2. Outline of Today’s Talk • The Policy Agendas Project • With Bryan D. Jones • The Policy Advocacy Project • With Berry, Hojnacki, Leech, and Kimball • The Evolution of American Government • Book manuscript with Jones, in progress • Drawing Lobbyists To Washington • Lobby Disclosure Reports data linked to Agendas Project data • With Beth Leech (Rutgers) • My focus today…

  3. Intellectual Goals • Develop Punctuated Equilibrium Theory of Government • Encourage attention to forces of stability and forces of change, simultaneously • Encourage larger-scale empirical work • Often in collaboration • Orders of magnitude larger then typical work • Provide infrastructure for teaching and research

  4. The Policy Agendas Project • Http://www.policyagendas.org/ • With Bryan D. Jones • Interactive web site: allows analysis as well as dataset retrieval • Research, archive, teaching uses NSF grants # SBR–9320922 and SBR–0111611

  5. Policy Agendas - Datasets • Congressional Hearings (~72,000 cases) • Statutes (12,000) • Stories in CQ Almanac (18,000) • Sample of NYTimes Abstracts (36,000) • OMB Budget, by 62 categories (3,000) • Gallup Most Important Problem data • All are comprehensive, from 1947-

  6. Policy Agendas – In Progress • Bill Introductions (~400,000 cases) • Supreme Court Decisions • Executive Orders of the President • State of the Union Speeches • Association Activities, from the Encyclopedia of Associations, from 1959 to present (with John McCarthy) • ~25,000 associations in 2002 • ~6,000 associations in 1959 • Other data sources to be added in the future…

  7. Agendas Project - Organization • Everything coded according to: • 21 Major Topics of Policy Activity • Macro-economics • Health • Agriculture • Etc. • 226 subtopics • Each major topic further subdivided • Consistently coded over time, allows time-series analysis • Facilitates systematic historical work, often by adding new coding from same sources. • Sophisticated index system for public sources. • Can be used alone, or as a base for more detailed analysis.

  8. The Policy Advocacy Project • Http://lobby.la.psu.edu • Frank Baumgartner (PSU) • Jeff Berry (Tufts) • Marie Hojnacki (PSU) • Beth Leech (Do you know her?) • David Kimball (Missouri, St Louis) • Grads: Christine Mahoney and Tim LaPira NSF grants SBR–9905195 and SBR–0111224

  9. The Policy Advocacy Project • Sample of lobbyists, weighted by level of activity with the federal government • “Could you take the most recent issue you've been spending time on and describe what you're trying to accomplish on this issue and what type of action are you taking to make that happen?” • Then snow-ball sample of others involved in that issue. • Result: A random sample of objects of lobbying.

  10. The Policy Advocacy Project • Random sample of 102 issues, based on 350+ interviews, extensive internet research on each case as well, all archived on our web site. • Focus on issue-definition, advocacy efforts • Micro-approach on advocacy and policy definitions, how change or stability occur, in a cross-section.

  11. The Combination • Macro-level attention to characteristics of the American political system over 50 years, evidence for p-e theory of policy change. • Micro-level attention to the struggles of policy advocates and government officials to work within this environment. • Theory testing but also infrastructure development for political science: large scope.

  12. The Evolution of American Politics • Important changes from 1947 to present in structure and functions of government. • Implications of rise of new issues in politics, complexity of the governmental agenda. • Information-based theory of government attention. • Manuscript forthcoming, University of Chicago Press, revisions to be completed in next several months • (Comments therefore welcome and timely)

  13. The Evolution of American Government: Information, Attention, and Policy Punctuations Chapter 1 Introduction: Information Processing and the Evolution of American Government Chapter 2 American Government, Then and Now Part I: Signal Detection and Public Policy Chapter 3 Information Processing and Policy Evolution Chapter 4 The Inefficiencies of Attention Allocation Chapter 5 Is Agenda Setting Event Driven? Chapter 6 Representation and Agenda Setting Part II: Policy Punctuations and Macro Policy Chapter 7 Issue Intrusion and Policy Punctuations Chapter 8 The Pace of Legislation Chapter 9 How the US Government Budget Evolved Chapter 10 ‘Understandable Complexity’ in the Budget Chapter 11 Policy Punctuations Chapter 12 Institutional Friction and Policy Punctuations Part III: Issues and Structures of Government Chapter 13 Co-evolution of Issues and Structures in Congress Chapter 14 Entropy, Institutional Overlap, and Politics Chapter 15 The Punctuation Entropy Paradox Chapter 16 Information Processing and Governance

  14. Inefficiency in Attention-Shifting • Given multi-dimensional issues, how does attention shift from one dimension to another? • Individuals: attention-allocation • Organizations: agenda-setting • Agenda-setting: the first step in decision-making

  15. A Model of Decision-Making

  16. Two approaches to theory building in public policy: • One case-study-at-a-time • State of the art in the policy sciences • Value in understanding particular policies • Post-hoc and ad-hoc approach • No ability to predict when shifts occur • Theories often don’t apply from one policy area to another • Broad theoretical breakthroughs not likely with this approach • (Agendas data can be used for this)

  17. Two approaches (cont.) • Stochastic modeling • Measure policy changes across scores of policies across scores of years • Combine policy change indicators • Analyze the resulting distribution of changes • No ability to discuss particulars of cases • More analogous to biology than to physics • Attention is on probabilities, behavior of the population, not of individual units in the population • Hopefully, greater theoretical possibilities even if less useful for studying particular policies

  18. Explaining a Punctuated Equilibrium Model Attention to equilibrium periods is just as important to the punctuations A focus on the causes and inevitability of discontinuities and inefficiencies in decision-making. Cascades, Sieves, and Friction as sources of inefficiency in decision-making

  19. Studying Policy Change Stochastically Indicators of Change: • Change in attention • Media Attention • Congressional Hearings • Change in Levels of Activity • Lawmaking • Major Laws • Change in Policy • Budgets

  20. What is Incrementalism? Pt = Pt-1 + et • Policy today is a function of fluctuations of policies yesterday. Rearranging the terms yields: (Pt - Pt-1) = et • That is, policy is a random walk in time. • The resulting distribution of policy changes: Normal Distribution. • This is logical if one thinks of efficient institutions responding to stochastic (random) inputs • Easily testable by taking all annual change measures across all years and all policies.

  21. Is Normality Expected in a P-E Model? Under bounded rationality, choices are inefficient as attention moves from one issue to another. • Over-attention to previously defined attributes; no constant weighting to all relevant dimensions; zero-weights to many potentially relevant issues. • Friction, resistance to change, inefficient reaction to new information. • Individuals: ideology, cognitive limits • Organizations: “missions” and focus on particular solutions rather than (inherently multidimensional) problems • Both under- and over-reactions expected.

  22. Three Explanations of Inefficiency: Cascades, Sieves, and Friction Cascades: imitation, cue-taking, threshold models Sieves: informational short-cuts, satisficing Friction: zero attention to particular elements until they are forced on the agenda. New institutions (agencies) may be created, suddenly focusing large amounts of attention (and effort) on a new dimension. All imply lurching rather than smooth responses to change

  23. Fig. 11-2. Response with Interactive Costs

  24. Disproportionate Response to Inputs Reaction to low levels of input: close to zero Reaction to medium levels: close to zero Reaction to sufficient levels: extreme Should be significantly different from Normal, specifically leptokurtic: high peak, low shoulders, high extremes

  25. Leptokurtosis: A Signature Characteristic of Friction-Heavy Processes Friction and inertia lead to much greater than normal incrementalism: reduced variance seems apparent. However, this is combined with occasional bursts of extreme change. Variance is actually quite significant, but skewed. Moderate change is lower than expected. Kurtosis, a measure of peakedness (k=0 for Normal curve

  26. Leptokurtosis (cont.) Reactions are not proportionate to inputs Either extreme resistance to change, or massive over-reactions Earthquakes, forest fires, many natural processes have these characteristics Difficulty to observe when N is low; appears roughly Normal with “a few outliers” Easily apparent, and statistically discernable, when N is high enough, as in our large datasets

  27. Two Normal Distributions Two Normal distributions with mean zero and standard deviation of 5 and 15.

  28. A Normal and a Leptokurtic Distribution of Similar Variance

  29. Analyzing Policy Distributions Level of friction should not be the same across all policy distributions Efficient processes should not have the distinctive pattern we expect in the policy process as a whole. Institutions vary in their relative efficiencies Kurtosis a measure of deviation from Normal Kurtosis a measure of efficiency of decisions

  30. From Inputs to Outputs: Increasing Costs of Decision-Making • Normal distribution expected for problem inputs and low-cost decision-making • Increased stickiness, costliness of decisions made in different institutional environments should yield increased kurtosis scores • Stages of policy process: higher kurtosis

  31. Markets: Not perfectly Normal Figure 12.8. Dow-Jones Industrial Average, Daily returns (percents), 1896-1996.

  32. Election Results: Relatively Efficient Figure 12.7. Election to election change in House vote margin by district, 1898-1992.

  33. Hearings: Moderately low-cost Figure 12.3. Yearly percentage change in Senate hearings by major topic, 1946-1999.

  34. Lawmaking: Moderately Costly Figure 12.4. Yearly percentage change in statutes by major topic, 1948-1999.

  35. The US Budget since 1800: A High-Cost Policy Process Figure 12.6. Annual change in Real US Budget Outlays, 1800-1994.

  36. The Distribution of Annual Budget Changes, 1947-1999

  37. Kurtosis Scores for 12 Processes

  38. Implications • The contingencies of the policy process; mixture of positive and negative feedback processes. • Politicians seek issues on which to make their names; technical communities develop solutions to problems they may not even be working on; advocates seek attention to pressing social concerns…

  39. Implications (cont.) • Models of these complicated processes need to incorporate uncertainty • A stochastic approach is not to supplant, but to supplement, traditional policy studies. • Today’s results show we should not underestimate the forces of stability or the opportunities for dramatic change. • Smooth, efficient, reasonable reactions to changing inputs are missing, however.

  40. Drawing Lobbyists to Washington • 74 Issue Areas Defined in Lobby Disclosure Reports • 56 of these overlap with areas defined by Policy Agendas Project • 8 time periods of lobby registrations • Data reported in paper some have read

  41. Drawing Lobbyists to Washington • Three hypotheses: • Government draws lobbyists, like it or not, to create and expand their government relations / lobbying / public affairs divisions • Government spending draws lobbying by those groups seeking rents • Economic activity creates more interests who naturally come to Washington, simply reflecting greater economic activity

  42. Drawing Lobbyists to Washington • Data: • Number of hearings, contemporaneous period • Number of hearings, previous 10 years • (Number of distinct committee venues also tested; highly collinear with above) • Federal spending (not available for all issue-areas) • Number of firms in this area of the economy (not available for all issue-areas, or for all times)

  43. Drawing Lobbyists to Washington VariableCoeff(St Err) Hearings, 0.009* (0.004) (previous 10 years) Federal spending 0.02** (0.003) (Billions) Firms .0000185 (.0000177) Organizations, t–1 0.98** (0.03) Intercept -0.67 (0.67) R-2 = 0.93; N=84; * p < .05; ** p < .01

  44. Drawing Lobbyists to Washington • Size of Economy not Important • Spending has an impact, no surprise • Much governmental activity is unrelated to federal spending; reflected however in hearings activity • Trade issues • Health and regulations • These explain stronger “pull factor” of hearings.

  45. Drawing Lobbyists to Washington Agendas Project documents Growth in Government Increased Diversity of Range of Government Activities This analysis explains Growth in Group System, increased political involvement of business as a result, not so much a cause of this previous trend

  46. Conclusions Data resources may be of interest to many Government activity is an important variable in studying business activity Variability in government activity by economic sector over time These provide opportunities for academic study; but also have great impacts on business and lobbying strategies. Much is reactive, not proactive.

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