1 / 29

EITM Institutions Week

EITM Institutions Week. John Aldrich Duke University Arthur Lupia University of Michigan. Coalition Duration. M. Most parliamentary governments can end at any moment. When and how they end has a broad societal impact.

lorimer
Télécharger la présentation

EITM Institutions Week

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. EITM Institutions Week John Aldrich Duke University Arthur Lupia University of Michigan

  2. Coalition Duration • M. Most parliamentary governments can end at any moment. • When and how they end has a broad societal impact. • NH. CD’s causes and consequences are independent of structural attributes, critical events, country-specific factors, negotiation dynamics. • P. Vary by paper. • C. Increasingly integrated theoretical and empirical models yield better explanations of coalition duration.

  3. Empirical Evolution

  4. Browne, et al (1986) • M. Why do governments dissolve before their time? • NH. Structural attributes largely determine a government’s duration. • P. Governance contains stochastic elements. • C. Stochastically occurring critical events explain more variation.

  5. Browne Premises • The probability, p, of a critical event occurring in a given time interval is both low and invariant across time intervals ( a Poisson process). • Partition the CIEP into N intervals (Np=1). • P(X=r|N, p) = [e-Np(Np)r]/r! • P(X(t) dissolved|X(0) undissolved) = 1-e-Npt. • The baseline expectation is of a constant flow of events. • The stated null hypothesis is that observed distributions will not follow this model.

  6. Browne Data • 238 cabinets from 12 European countries 1945-1980. • Caretaker governments excluded.

  7. Browne implications • Cabinets with multiple members, minority governments possess less ability to deflect critical events. • Structural attributes approaches not rejected, but stochastic explanations improve explanations. • Unidentified, however, are the descriptive attributes of such events…

  8. King, Alt, Laver and Burns (1990) • M. Structural attributes versus critical events. • NH. A unified explanation is no better. No cabinets are more durable than others. The real story is country-specific. • P. Unifies the two approaches. Includes censoring, institutional and country-specific variables. • C. The approaches are reconcilable. Unified explanation superior.

  9. KABL Premises • Critical Events: Yi = e-yi • Yi – a random variable describing cabinet duration length,  the rate of event occurrence • 1/  expected duration • Structural Attributes: Yi = xi + i • Could duration be generated by a normal distribution?

  10. KABL Premises • Is cabinet durability constant for the entire history of a country? • The termination hazard has systematic and stochastic components. • Durations are independent. • Governments lasting longer than 12 months before the CIEP ended partly because of its shadow.

  11. King, Alt, et. al. Conclusions • Model 1.1. Browne et al. Baseline • Model 1.2. Censoring improves the fit. • Model 1.3. Include country and structural attributes. Even better fit. • Majority status increases duration. • Number of formation attempts reduce duration.

  12. KABL Premises • Model 2.1. Best Country attributes only model. • Models 2.2 -2.3 Structural attributes added. Improved fit. • Comparing best models, country-specific effects disappear. • Number of formation attempts corresponds to less durability. • Table 3 shows the fit. • Q: Censoring and strategy?

  13. Warwick (1992) • M. Are termination hazard rates constant? • NH. Yes. • P. Event history model applies. • What is the termination rate given survival at time t? • (t)=exp(’x(t))0(t) • (t) – hazard rate; 0(t) baseline rate after x considered. • Censor only involuntary terminations. • T1. Without other factors, (t)/t >0 for most countries. • T3. W/ other factors, baseline rate increases w/ term length.

  14. Coalition Termination and the Strategic Timing of Parliamentary Elections Motivation: • What determines the timing and nature of coalition terminations? • What factors affect government membership and portfolio allocation? Null Hypotheses: • Structural attributes or critical events are sufficient to explain the timing of governmental transitions. A strategic approach adds nothing.

  15. Lupia and Strom:Null Hypotheses • 1. All important determinants of coalition politics are unique to, and embedded in, particular political systems. • 2. Preferences alone explain coalition behavior. • 3. If cooperation among potential coalition partners is mutually advantageous, then a coalition will form and survive.

  16. Conclusions • Favorable electoral prospects are neither necessary or sufficient for replacement or termination. • In coalition governments, a party’s size need not directly effect government composition or action. • Bargaining advantages attributed to size are due to walk-away values. • Bargaining dynamics determine the impact of “critical events.” • Implication: An event’s impact depends heavily on the election cycle.

  17. Premises Party A has 49 seats. Party B has 48 seats. Party C has 4 seats. Any coalition including C produces value. Any coalition without C produces no value. Results C has the fewest seats, but the largest walk-away value. The only sustainable outcome involves a contract giving party C almost all of the power. Example

  18. Tested in • Daniel Diermeier and Randy T. Stevenson. 1999. “Cabinet Survival and Competing Risks” AJPS 43: 1051-1068. • Sanford C. Gordon. 2002. “Stochastic Dependence in Competing Risks” AJPS 46: 200-217. • Bernard Grofman and Peter van Roozendaal. 1995. “Exit models, hazard rates and government duration. With empirical application to government duration in the Benelux countries (1945-1994).” ISCORE paper.

  19. Diermeier and Stevenson (2000) • M. Can institutional and bargaining considerations improve empirical work on cabinet termination? • NH. Critical events, structural attributes, non-strategic approaches or static models are sufficient to answer the question. • P. Stochastic version of Lupia and Strom. • C. Dissolution hazards increase. Replacement hazards do not.

  20. Diermeier and Stevenson Key Assumptions • For all parties si, ci, and ki are constant, negotiation costs are the same for all parties and not “too high.” • As the CIEP approaches, coalition values decline. • Electoral prospects are Poisson RVs. •  time until CIEP. >0. • i,j and ’<, gij() – gij(’)>0. • Implication: The termination hazard is ()=(+o())(s,c,gij()) • The initial coalition is a Nash Equilibrium: parties weakly prefer SQ.

  21. Diermeier and StevensonTheoretical Conclusions • Hazard rates for pooled terminations are strictly monotonically increasing as the CIEP approaches. • Hazard rates for dissolutions are strictly monotonically increasing as the CIEP approaches. • The same is not true for replacement hazards. • Must know more about electoral prospects. • These predictions are different than Browne, other previous empirical work.

  22. Diermeier and StevensonEmpirical Conclusions • No censoring. Data similar to Browne, Warwick, KABL. • Pooled hazards: After big initial spike, HR increasing as CIEP approaches. • Dissolution hazards: after the spike and a flat region, HR increasing as CIEP approaches. • The same is not true for replacement. [F6-8]. • Strategic approach promising. Further progress requires more dynamic models. • Ignoring the bargaining filter yields incorrect predictions.

  23. D&S Results

  24. Institutions • If an institutional, preference, or country-specific factor is to affect a coalition’s contract, it must affect a pivotal actor’s walk away value. • Institutions that affect walk away values • formateur rules (e.g., change in Israel) • size/composition rules • internal party rules • independence of the judiciary and civil service

More Related