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The Impact of Governmental Characteristics on Prime Ministers’ Popularity Ratings: Evidence from Israel

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Abstract

Conventional scholarly wisdom has held that the popularity/approval of political leaders is determined by a governments’ ability to provide peace, prosperity, and security to its citizens. However, for coalition governments in multiparty parliamentary democracies, popularity may also be shaped by legislative and structural divisions among ruling parties. Lower legislative cohesion may decrease the coalition’s political feasibility while structural divisions indicate that policy preferences in the government are diverse, and the government is more constrained to act on potentially divisive issues. These two factors are tested in the context of recent Israeli political history where prime ministers have been historically dependent on coalition governments. Focusing on the consequences of coalition governments characteristics in Israel between 2006 and 2015, this study shows how coalition behavior and structure impact the prime minister’s popularity.

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Notes

  1. A long line of literature has called into question the reward/punish theory. For example, Achen & Bartels (2016) argued that citizens are not as omnipotent and sovereign as common democratic theories presume. Instead, citizens tend to base their decision-making on partisan loyalties.

  2. In a competence-based voting (or popularity) approach, rational citizens observe the performance of the government and use optimally all the available information to infer administrative competence (Alesina et al., 1995, p.189). Here, however, competence is assumed to be directly observed by the public who is watching the behavior of the coalition government.

  3. Nevertheless, the literature shows that reported evidence on economic determinants is sometime inconsistent (Berlemann and Enkelmann, 2014; Stegmaier et al., 2017)

  4. Before the September 11, 2001 attacks in the United States, the literature on popularity ratings of political leaders had rarely focused on terror as one of the main determinants that shape public opinion. Yet this does not mean that terrorism was absent from the study of popularity ratings during that period. A close review of the literature, especially in the United States, reveals that incidents of political violence, which can be described as an act of terror (or an attempt for such act) were often included with other politically salient incidents to capture “political drama” events (e.g., MacKuen, 1983; Ostrom & Simon, 1985; Ostrom & Smith, 1992) that the public is likely to pay attention to.

  5. It has long been acknowledged in the literature on presidential approval that the legislative arena has a major influence on popularity polls (e.g.,  Carlin & Singh, 2015; Ostrom & Simon, 1985; Canes-Wrone & De Marchi, 2002; Christenson & Kriner, 2016, 2017; Reeves & Rogowski, 2016).

  6. It should be noted that the focus here is not on the government’s ability to pass a specific policy. Instead, the theory suggests that even if virtually all proposed legislation by the government gets a majority in the parliament, the prime minister can still be held accountable when some coalition members oppose the bills.

  7. When more than one survey result is available within the aggregated period, a weighted average is computed, which is weighted by the number of respondents in each survey. If no sample size is listed, it is assumed to be the average sample size of the polling firm.

  8. The dependent variable is measured over a period of 114 months. In comparison to studies on popularity in other countries the number of observations is typical (e.g.,  Bellucci, 2006; Kelly, 2003; Treisman, 2011). It is important to note that early studies on popularity in a country tend to have a relatively low number of observations (e.g., Santagata, 1985; Bellucci, 2006), which later studies then expend with more data (e.g., Bellucci and De Angelis, 2013)

  9. Similarly to the popularity data, the Stimson’s (1999) Dyad Ratios Algorithm is used to combine both into a single series.

  10. According to the augmented Dickey-Fuller test the null hypothesis that the combined series follows a unit-root process cannot be rejected; and therefore, the series is transformed to its first-difference.

  11. While it is possible to conceptualize terrorism and war as being part of the same ongoing conflict, we refer to two distinct manifestations of the conflict: military casualties during military operations and civilian casualties during terror events.

  12. The data is available at: http://www.start.umd.edu/gtd/.

  13. The time period of the study, from 2006 through 2015, means that all corruption related events were associated with Olmert. Corruption investigations involving Netanyahu started in December 2016, and are therefore not included in this study

  14. We tested the correlation between the percentage of votes the prime minister participated in and the level of satisfaction over the years. The results show that there was very low correlation (-0.098) between the two series and therefore there is no evidence of a selection bias.

  15. The data on legislative voting can be found in the Knesset website: http://www.knesset.gov.il

  16. In a month when no vote takes place and the public has no new information on coalition cohesion, people are assumed to rely on information that was received in the previous month and therefore missing values are filled using previous month values.

  17. The data is available at: http://www.parlgov.org/.

  18. Replication files are available at the Harvard Dataverse site: https://doi.org/10.7910/DVN/RWFPHU

  19. The coefficient of the variable measuring legislative cohesion within the prime minister’s party remains insignificant even when controlling for the size of the Prime Minister’s party.

  20. The impact of two other ideological indicators from the ParlGov database was also explored. Liberty-authority, which capture the religious dimension, and state-market that focuses on the economic dimension—measured on a 0-10 scale—were inserted in the models but failed to show statistically significant impact. In addition, combining all indicators into a single measurement also had no significant impact.

  21. An important feature of the current model is that it includes factors beyond the lagged satisfaction level and economic performance. We conducted a Wald test of each type of component in the model- war/terror, fractionalization/cohesion, and political events - and found that each type of component makes an independent and significant contribution to the explanatory power of the model beyond that of the lag of satisfaction and the economy. We also conducted a dominance analysis that shows the following rank order of influence in the model: war, cohesion, negative personal events, negative domestic events, economy, terror, positive domestic events, negative international events, fractionalization, and positive international events. While the exact order is interesting, what is important is that there is evidence that a wide range of political factors (war, terror, events) and governmental structure have important explanatory roles.

  22. Since approximately half of the cases in the time period of the study were coalition governments with less than 68 members, the variable takes a value of 1 when the coalition has at least 68 members, and zero otherwise.

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  1. Australian National University, Canberra, ACT, Australia

    Alon P. Kraitzman

  2. Michigan State University, East Lansing, MI, USA

    Charles W. Ostrom Jr.

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Appendices

Appendices

See Tables 3, 4, 5, 6, 7, 8 and 9.

Table 3 Polling firm, publication, number of surveys
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Table 4 List of military operations/war
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Table 5 List of events by date and category
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Table 6 Descriptive statistics
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Table 7 Explaining satisfaction with PM: rice index, oversized coalition and an overall security variable
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Table 8 Checking for multicollinearity
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Table 9 Impact of variables on satisfaction ratings—lowest to highest predicted values of satisfaction over entire range of each variable
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Kraitzman, A.P., Ostrom, C.W. The Impact of Governmental Characteristics on Prime Ministers’ Popularity Ratings: Evidence from Israel. Polit Behav 45, 1143–1168 (2023). https://doi.org/10.1007/s11109-021-09752-4

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