It looks like Turkey’s presidential election will go to a runoff, while the ruling AKP and allies have won a majority of assembly seats.
In the official reporting of results from Sunday’s elections, something looks implausible. The ballots for presidential candidates and (closed) party lists were separate. Yet the votes for incumbent President Recep Tayyip Erdogan and the alliance backing him are almost identical. In fact, for a good time yesterday the NTV site was showing the percentages as precisely identical to two decimal places. Today, at last check, they are 49.50% for the president and 49.49% for the assembly lists. So they are diverging. Kind of.
I have spent a lot of time over many years analyzing the interplay of presidential and assembly votes, and I would say this almost never happens. There is basically always enough ticket splitting for the percentages to diverge, with the leading presidential candidate usually out-polling the supporting party or alliance. In this case, Erdogan is far ahead of his own party, which has 35.6%, but has this essentially identical percentage when the alliance partners are included.
I am not alleging fraud. There are plenty of folks closer to the events doing that (for instance), and I certainly can’t claim evidence. This just looks strange. If they were going to inflate their vote one might think they’d look for a way to push the presidential vote over 50%, so perhaps it is the assembly vote that deserves more scrutiny than it is getting. Or maybe it is just one of those strange but true results. The reported seat total is not a narrow majority–the AKP, MHP, and a third partner together have 322 seats out of 600.
For the opposition, the divergence of presidential and assembly vote percentages is more normal-looking. The main opposition candidate, Kemal Kilcdaroglu, has 44.89% while the alliance backing him has 35.04%. The alliance of two left-wing parties (including the re-organized HDP) has 10.55%. If you add those together, however, their total of 45.59% is only slight higher than Kilcdaroglu’s, but this looks rather more normal.
The third presidential candidate in the race, Sinan Ogan, is on 5.17% while the ATA alliance backing him won only 2.44%. This is also odd, in that usually smaller political forces do better in assembly than in presidential elections. However, consider the unusual nature of the rules for these elections. The presidential election, first round, is arguable more “permissive” than the assembly electoral system, given the latter has a 10%* nationwide threshold. Obviously ATA was far short of this; its voters may have felt much more free to vote for their presidential candidate (who then could have leverage in the contest for support in a likely second round) than for assembly (where it would be a wasted vote).
Note that the 10%* threshold is applied to alliances, not to individual parties. If parties register an alliance, then the individual parties’ votes can contribute to seat winning even if the party itself fails to break 10% (as long as the alliance as a whole clears). Thus three alliances have won seats, but lists of seven different parties will be represented. *CORRECTION: That threshold is now 7% (see comments).
A ballot image shows how the parties that are allied are grouped on the ballot.
Thanks to Henry for finding and sharing this photo. Also note the very unusual split vote cast by this voter: Erdogan and the leftist TIP. Also, once I noticed the shoes of the voter, that was kind of all I could see.
As for the presidential votes, obviously a first-round percentage as high as 49.5%, taking it at face value even though there are allegations it is not “real,” makes a runoff comeback almost impossible. Not only is the leading candidate barely short of the required majority already, but also he has more than a four-and-a-half percentage-point lead over the runner up. Even if we knew nothing about the political leanings of voters who supported candidates other than the top two, we might be tempted to conclude the runoff is a foregone conclusion. In this case, the ATA alliance is right-wing and nationalist, so it seems likely its votes would go to Erdogan. (Perhaps those with actual knowledge of Turkish politics can disabuse me of this assumption.)
Erdogan made an interesting claim on election night, saying that if he did not win a majority in the first round, the majority his alliance won in parliament will encourage voters to support him in a second round (via journalist Ayla Jean Yackley on Twitter). Independent of the validity of his claim, no other case comes to mind of a presidential candidate claiming that a concurrent assembly election outcome will shape a presidential runoff. I suppose it is possible, although I am skeptical. On the other hand, I also would not expect voters to specifically vote to check the AKP and allies with their presidential vote. As I have said before in different contexts, elections in presidential (and semi-presidential) systems do not really work that way. They are more more like referendums on the president or presidential candidate–in favor when happening in close succession, and against at midterm and later.
Finally, it is notable that the AKP’s own vote percentage this time, at around 35%, is almost identical to what it won in 2002, when it and Erdogan first came to power. However, in that election, the party was able to turn that into 66% of the seats, due to so many parties falling below the 10% threshold.
From Erdogan’s perspective, it looks like the decision to move to presidentialism was a good call. The party is evidently not as popular as he is, and this time various other parties have grabbed on to his coattails in the form of an alliance. Presidentialization at work. On the other hand, of course, it could still turn out badly for him, if he loses the runoff. (I wonder if the allies would stay with him then. Maybe not, given the very same logic of presidentialization.)
The runoff, assuming it is indeed required per the final first-round results, will be on 28 May.
In a recent publication (details below), Reut Itzkovitch-Malka and I investigate when parties “check” partners in coalition governments and when they “stack” via the committee overseeing a ministry. Here’s a clear case of stacking in the incoming Israeli coalition: Otzma Yehudit reportedly will get both the ministry it most wanted as well as the chair of the parliamentary committee overseeing that ministry as part of the new Israeli government.
Broadly put, when coalitions are bargained, the parties forming the government have a choice of “stacking” whereby they agree to give one party full control over certain policy portfolios, or “checking” whereby two parties are given organizational bases from which to check one another in a given portfolio. There is considerable literature in political science on questions such as these, mostly focused on the degree of authority delegated to cabinet ministers. For instance, Laver and Shepsle (1996) famously developed a model to predict which cabinet deals would form, based on the policy preferences of the parties to the deal, and with the theoretical claim that the holder of a portfolio was a “policy dictator” in that policy domain. Within the cabinet coalitions literature, this has been challenged by the observation that often junior ministers are appointed from a different coalition party than the one that gets the (senior) minister in order for one party to “keep tabs” on the other (see Thies 2001). These views of the process are in direct tension with one another. The first assumes that what makes a coalition “work” is that all parties understand they get to do whatever they want in their portfolios and thus the bargain is credible (everyone knows this up front, so they won’t intervene in each others’ domains over the life of the coalition). The second assumes that what makes it work is the parties can have agents monitoring other parties to be sure they stick to compromises reached at formation of the coalition (the junior observes some “ministerial drift” and reports back to his or her own party).
In recent years, more attention has been turned to how parties might use parliamentary committees and their chair positions as part of the overall coalition bargain (e.g., Martin and Vanberg 2004, 2011). The notion of stacking vs. checking can also be applied here. For instance, the coalition agreement could see the party that gets a given ministerial portfolio also get the chair of the parliamentary committee that is charged with overseeing the ministry. That would be stacking. Alternatively, the committee chair could be from a coalition partner, creating an opportunity for checking within the coalition. (A third possibility is that the chair is from an opposition party. Most parliaments in coalition-based systems parcel out the chairs proportionally to all parties, so some committees will be allocated in a way that facilitates “monitoring” by the opposition.) All of these combinations assume chairs have some authority. That is generally true–they have agenda power within the committee. Even though a majority of the committee typically can override decisions of the chair, everyone’s time and attention is limited, and thus chairs should be in a privileged position in terms of hearings to schedule, witnesses to call, etc. And, at least among coalition partners, they may prefer to resolve things quietly rather than let conflicts erupt in the open. The ability of the chairs to acquire information on behalf of their parties serves to keep partners in line, or so the argument goes for checking. For stacking, it’s the opposite: the chair may be able to bury information that would raise the ire of a coalition partner or the opposition.
The deal first reported last week between Likud, the party of incoming Prime Minister Benjamin Netanyahu, and Otzma Yehudit, led by Itamar Ben Gvir, offers a clear-cut case of stacking. Ben Gvir will be named Minister of National Security, in charge of the national police and various other functions. It is a newly expanded ministry and portfolio, and thus a plum position for the far-right party leader. In addition, a member of his party is expected to be named chair of the Knesset Public Security Committee. Thus Otzma Yehudit gets both the policing ministry and the parliamentary committee chair responsible for domestic security policy and related matters.
The stacking, and evident cession of considerable autonomy to Otzma, in the area of public security grants Ben Gvir one of the aims he most regularly called for during the campaign leading up the recent election. He said repeatedly that he would demand the policing portfolio. And he got it. While this might not quite make him a literal “policy dictator,” that he also has the associated legislative committee surely limits the risk that he gets stymied by Likud or other partners.
In addition some reports had said he, or a member of the party, could obtain the agriculture ministry. I never would have imagined a far-right ultra-nationalist (and, frankly, racist) party being the defender of Israeli famers, but I’ve been informed that this is also related to his public-security interests. Theft of animals and equipment has become a serious issue in parts of rural Israel, and the politics around the problem is often tinged with racism. I wonder if his emphasis on this issue during the campaign actually earned him votes in the farm sector. The agreement does not grant Otzma the agriculture ministry, but it does transfer from that ministry to the new super-ministry Ben Gvir will head certain agencies responsible for the sector.
Ben Gvir is notorious for a history of racist comments and convictions for incitement against Arabs, along with admiration for the late Meir Kahane. In this election, his Otzma faction was part of a joint list with Religious Zionism. Together the RZ alliance list won 14 seats out of 120. Six of those elected from the list were Otzma candidates. The parties had declared their alliance a “technical bloc” and, as planned, formally split shortly after the election. Thus the two parties (plus a third, Noam, with just one of the electoral alliance’s seats) have been bargaining separately with Likud. This has made Shas (the Sephardi Haredi party), with 11 seats, technically the second largest party in the emerging coalition. It also means there will likely be five separate coalition agreements between Likud and a partner (Otzma, RZ, Noam, Shas, and the other Haredi party, UTJ) . It will be interesting to see which of the major ministries each partner gets will be “checked” by a coalition partner and in which portfolios the party will be granted “stacked” control via the committee chairs allocation.
The question of stacking and checking is a major theme of my paper with Itzkovitch-Malka. We find that stacking is quite common in Israel. We suggest that this may be due to the need of parties under conditions of high party fragmentation to make credible commitments that a partner, having been given a privileged position over the portfolio (via the minister) will be more able to deliver by also having the committee chair (given agenda control over proceedings, which Israeli committee chairs definitely have).
An interrelated theme of the paper is the expertise of the Knesset Members who obtain committee seats and chairs (expanding the party personnel research). Expertise is a subordinate, but still important, consideration that Israeli parties use. We do the first–to our knowledge–statistical analysis of any parliamentary system’s committee assignments to combine data on individual member attributes with an indicator of the partisan relation of chairs and ministers. Parties are somewhat more likely to appoint someone with pre-legislative experience to chair a committee when the party also has the associated minister, especially, we show, in “public goods” policy areas (like health and education). We suggest this is a further form of stacking–ensuring that the chair overseeing a co-partisan minister also has expertise in related policies. I am not sure yet which Otzma legislator is getting the Public Security committee chair in the new Knesset; I will take note of whether it is someone with any expertise in the policy area.
As for Ben Gvir himself, I suppose having been arrested and convicted on security matters counts as “expertise” of a sort in policing and public security, although not quite in the way I normally would code it.
The paper mentioned above is:
Committee assignment patterns in fragmented multiparty settings: Party personnel practices and coalition management, by Reut Itzkovitch-Malka and Matthew S. Shugart, Party Politics, 2022. Abstract:
This paper addresses the way parties assign members to parliamentary committees in fragmented multiparty settings. Thus, it analyzes how the two most central institutions of parliamentary politics––political parties and parliamentary committees––interact with one another. To the best of our knowledge, no research into this subject has systematically explored the intersection of considerations based on individual legislator characteristics and coalition management in committee assignment. Using Israel as our case study, we show that legislators’ expertise modestly shapes committee assignment patterns. However, parties in coalition often have another set of considerations to take into account when assigning members to committees. We show that parties in coalition do not only bargain on ministerial positions or committee chairs––they also bargain on their members’ assignment to committees and use this resource to allow (or hinder) each other to augment influence and control in a given policy area, or to perform affective monitoring.
Works cited in this entry:
Laver M and Shepsle KA (1996) Making and Braking Govern- ments: Cabinets and Legislatures in Parliamentary De- mocracies. Cambridge: Cambridge University Press.
Martin LW and Vanberg G (2004) Policing the bargain: coalition government and parliamentary scrutiny. American Journal of Political Science 48(1): 13–27.
Martin LW and Vanberg G (2011) Parliaments and Coalitions: The Role of Legislative Institutions in Multiparty Governance. Oxford: Oxford University Press.
Thies M (2001) Keeping tabs on partners: The logic of delegation in coalition governments. American Journal of Political Science 45(3): 580–598.
This is a short list of important works in the topic. Many more are cited in the article.
Italy votes in general elections today. The Brothers of Italy is expected to be the largest party, in a pre-electoral alliance with the League and Forza Italia that may end up with a substantial majority of seats in both houses.
The electoral system is similar to that used in 2018 in that it is mixed-member majoritarian despite having just over 60% of seats elected in the party-list proportional component of the system. In an important sense, however, this year’s version is even more majoritarian–the size of both chambers has been reduced substantially. Other things equal–as they are–a smaller assembly is less proportional (or “permissive” to small parties). And when you combine a relatively majoritarian system with a smaller assembly, you get a more majoritarian system overall. The new Chamber of Deputies, at 400 seats, is closer to the cube root law expectation for a country the size of Italy, but nonetheless the impact would be to favor more substantially than before the largest party or pre-electoral alliance, relative to the 2018 system which had a Chamber size of 630. The size of the Senate has been reduced correspondingly from 315 to 200 seats.
How is the system mixed-member majoritarian (MMM) and not mixed-member proportional (MMP)? This question has been asked before. The answer is straightforward: the seats a party wins in the list component are simply added on to those that it wins in the nominal component (single-seat districts decided by plurality). There is no compensation mechanism, not even a partial one like in the 1994–2001 version Italy used.1 There is a single vote, but whether voters can split their votes between nominal and list components has no bearing on the classification, which depends entirely on whether the list seats are allocated so as to compensate for deviations from proportionality arising from the district results (as under MMP) or not (as with “parallel” allocation under MMM).
The results from 2018, aggregated by pre-election alliances that coordinate nominations in the single-seat districts, certainly made this clear. The center-right alliance combined for 37% of the votes. This alliance won 42% of the seats, which is not terribly disproportional. However, we have to remember that more than three fifths of the seats are elected by PR. The nature of the system can be seen by looking at the detailed breakdown. The alliance won 111 nominal seats (out of 232, for 47.8%). Thus they were over-represented in this component of the system, as expected from single-seat plurality. If the list component were compensatory, as under MMP, the share of list seats won by this alliance should have been lower than its share of the vote. Yet it won 39.1% of them (111 of 386). It should have ended up with somewhere around 233 seats were these seats compensatory, but instead won 265 (including 3 seats for Italians overseas).
If we take the largest opposition force, the dynamic is even clearer. This was Five Star, which ran on its own, not as a part of any pre-electoral alliance. It won 32.7% of the vote, and 93 of the 232 nominal seats. That is 40%, so it is also slightly overrepresented in this component. To this it added 133 list seats, which is 34.5%, ending up with 227 seats total (including 1 abroad), or 36.0%. That the system was MMM becomes clearer still if we consider the second largest opposition alliance, the center-left. It had 22.9% of the vote, and won 28 nominal seats. This is only 12.1% of these seats–sever underrepresentation, as expected for a third party under single-seat plurality. Its list seat total was 88, which is 22.8% of the list component. Yes, 22.8%, so it got near-perfect proportional representation. However, it got this proportional result only in the list seats themselves. Overall, due to the punishment in the nominal seats, it was underrepresented, ending up with 122 seats (including 6 from Italians abroad), which is 19.4%. It was not severely underrepresented in the final result because–again–the list component is so large. However, were the system MMP they should have had approximately 110 list seats instead of just 88, in order to make their overall seats proportional to list votes. And, as already covered, the other alliances and parties would have had their list seats cut somewhat due to a compensation mechanism, if it were MMP. Thus the system is MMM, albeit with a large list component. I should also add that when I say “list votes” I mean votes aggregated from the nominal contests, given there is only a single fused ballot and not separate list and nominal votes (as there are in the MMM systems of Japan and Lithuania, or in the MMP systems of Germany and New Zealand).
Because polling for today’s election shows the Brothers of Italy in the lead and the combined center-right alliance clearing 40% of the vote while the second place center-left alliance looks to be under 30%, the system likely would provide a substantially larger boost to the center-right this time around than last, even if the rules were unchanged. However, assembly size is a core defining characteristic of an electoral system. If the rules for how seats are allocated are unchanged, and the balance in an MMM system between nominal and list seats is also unchanged, the key variable in how majoritarian it will be overall is assembly size. As already noted, both houses are half as large in the 2022 system as they were in 2018. This change promises a further boost to the winning alliance. There are only 147 single-seat contests in the Chamber of Deputies this time (around as many as in the Australian House of Representatives) and only 74 in the Italian Senate (about as many as in Liberia’s first chamber), it will be even more “work” for the list-PR component allocation to offset, despite its size relative to the nominal, given it is non-compensatory.
In terms of effective seat product, my estimations have it at 920 in the 2018 election. The goal behind the effective seat product is to allow us a rough approximation of what simple electoral system a given complex system is most similar to, in terms of its impact on the party system. Simple, single-tier systems with seat products in the 900–1000 ballpark include Luxembourg (900) and Greenland (961). The former has an assembly about ten percent the size of Italy’s in 2018, yet in terms of impact of the party system, the design of Italy’s system made it more like the simple PR system for the 60-seat assembly of Luxembourg than like other assemblies with 600+ seats and PR allocation (e.g., Germany’s effective seat product is currently around 1800 and Italy’s under its old PR system prior to the early 1990s was around 9800). As for Greenland, they get an effective seat product of 961 from an assembly of only 31 seats by allocating in a single territory-wide district. In other words, while Italy 2018 was a system of MMM, the large assembly and large share of seats allocated in the list component make the Chamber system of 2018 similar to a small-assembly PR system. But what about 2022?
The calculation of the effective seat product for the new Chamber of Deputies system would be around 650. In other words, roughly the same effect on a party system as Britain’s FPTP system, despite the election of over three fifths of deputies in a PR component. This is a fairly substantial reduction. It is based on the “as if” calculation of (1) an MMP system with same parameters as Italy’s new system, which would be an effective seat product of around 2860, and (2) a FPTP system of the actual size of Italy’s nominal component (147). For MMM, we take the geometric average of these two values, which is (rounded) about 650. This is very slightly less restrictive than the MMM system that was in use from 1994 to 2011 (for which the effective seat product could be said to have been around 660). Applying the same procedure to the Senate electoral system of 2022 would yield an effective seat product of around 370, implying roughly the same impact on the party system as the FPTP system of the Canadian House of Commons has.
In conclusion, Italy now has the most restrictive and thus plurality-favoring electoral system it has had in the post-WWII era.2 Despite still having a fragmented multiparty system in which parties enter pre-electoral alliances, it has an electoral system that is more like FPTP in the UK (in the case of the Chamber) or Canada (in the case of Italy’s Senate) than like a PR or MMP system. If the largest alliance clears 40% of the votes, as expected, it should obtain a substantial bonus in seats, due to the relatively majoritarian design of the system.
That system was also MMM. It was often mis-classified in various sources as MMP. The misunderstanding was somewhat more justifiable than for the current one, because of the partial compensation mechanism, which was based on adjusting party-list votes according to nominal seat performance (rather than allocating list seats with regard to nominal seats won as is done under MMP). Even with the partial-compensation mechanism, that former system also should be classified as MMM.
All of Italy’s post-war electoral systems have been complex in one way or another. Above I mentioned that the system in use as of the early 1990s had an effective seat product around 9800. That was a remainder-pooling PR system and Italy has not used a PR system since then. The mixed-member system put in place in 1994 had an effective seat product around 660. The bonus-adjusted system from 2006 through 2013 comes out to around 1325 (but this is a more challenging system to estimate because of its unusual features). In all cases, these numbers refer only to the Chamber. Also, the calculation of effective seat product for the 1994–2001 system does not take the partial compensation mechanism into account. Perhaps it should, which would increase the effective seat product of that former system to some (small) degree. However, it is not clear how one would carry out such an adjustment, given the unusual nature of the mechanism. I do not think it is necessary or worthwhile to attempt.
A question that has arisen* is whether fused ballots–a single vote electing president and assembly, i.e., with no opportunity for ticket-splitting–suppress the number of parties, particularly when the president is elected by plurality and assembly by PR.
A challenge in addressing this question is that fused ballots are rather rare. Moreover, they may be adopted/abolished by ruling parties/coalitions based on expectations of advantage. In other words, the direction of causality between party-system outputs and rules is more ambiguous than usual. With such caveats reiterated, here is what I find.
This is for pure presidential systems, only because I am not aware of cases of semi-presidential systems that fuse presidential and assembly votes. (In parliamentary systems, the option does not arise, or in a sense the vote is always fused. I did not include the brief case in Israel of separate and direct election of an executive who was still responsible to the parliamentary majority.)
My outcome of interest is the ratio of expected effective number of seat-winning parties (NS) or seat share of the largest party (s1) to the expectation, given the seat product of the assembly (first chamber) electoral system.
For NS, the ratio in non-fused cases is 1.13, for fused it is 0.927. This looks like good news for the hypothesis that fused ballots restrict party systems more than the separate vote does. However, the difference is not close to significant (p=0.12).
For s1, the ratio in non-fused is 1.012, and in fused it is 1.047. Obviously that’s not significant. (Also, the seat product model is pretty good–even for presidential systems!)
Note that for NS, the mean assembly party system in a presidential democracy tends to be more fragmented than expected from its electoral system. Probably not what most people expect. Perhaps this is driven by the unusually fragmented case of Brazil. If I take it out, the ratios in non-fused are 1.083 for Ns and 1.031 for s1. So not much impact.
Perhaps one should drop Uruguay from the set of fused cases. Not because ballots are not clearly fused, but because the electoral system is so different. Before 1999, parties could present multiple presidential candidates (and pool votes at party level for determining which party would win), and since then the fused ballot is only for the first round of a two-round presidential election. However, if we do this, we have only four cases left, so it is kind of meaningless. For the record, we would then have about a p=0.1 signifiant result in the expected direction. But I would put no stock in a result comparing four elections (in two countries) in one group to over 150 in the other group!
This is the list of cases with fused ballots that I am using. If I missed some, please let me know. (Angola, the case that prompted me to investigate this, is not in the dataset, nor are other countries that are not generally classified as democratic.)
To this list could be added Bolivia. However, I did not include it because elections for president were not direct before 2005 (congress chose from top three if the popular vote did not yield a majority) and since 1997 the fusion has been only between the presidential vote and the party list vote of an MMP system.
(* A version of this text was originally posted as a comment in a thread on Angola, but it seemed to warrant a place in the center row of the virtual orchard.)
Earlier this week, in trying to understand the Angolan electoral system, I was unsure whether the allocation of the national list seats was compensatory, or in parallel to the provincial district results. In the comments, Miguel was kind enough to quote the relevant sections of the electoral law, confirming that allocation is parallel.
The results show the ruling MPLA won 51% of the vote and the main opposition UNITA 44%. I will take these as given, and not speculate on whether they are the “real” vote totals or a product of “electoral alchemy.” Rather, I am interested in whether the translation of these votes into seats suggests the MPLA chose a system that would benefit it considerably, or not.
The MPLA has won 124 of the 220 seats. That is 56.3% of the seats, for an advantage ratio (%seats/%votes) of 1.10. How does this compare with an “average” electoral system? I checked my dataset, restricting it to “simple” systems, even though Angola’s is not simple, and to those that are not FPTP or other M=1. The average across 377 such elections is… 1.12.
In other words, if the MPLA was trying to give itself a considerable seat advantage from this electoral system design, it kind of failed.
There is certainly one aspect of the electoral system design that looks like “rigging” via the rules: The provincial tier is highly malapportioned. The 18 provinces vary widely in population, yet each elects five members. See the images with preliminary vote totals in another comment from Miguel or see the CNE site, which also includes seats now. Given the use of D’Hondt at this level and the ample margins in rural provinces, the MPLA won 4-1 in several districts (and 5-0 in one)1 and 3-2 in all others aside from the three where UNITA was ahead. (UNITA won 4-1 in Cabinda.)
What undermines the MPLA’s own advantage considerably is the nationwide list component, which constitutes just under three fifths of all the seats (and uses Hare quota and largest remainders). If the MPLA had really wanted to create a system to advantage itself, it could have done so by making this tier smaller, or by various other designs.
I do note that UNITA is somewhat underrepresented. Its 90 seats is 40.9%. Given 44% of the votes, its advantage ratio is 0.928. Across a subset of electoral systems fitting the criteria I referred to above, this is quite low. In fact, the average for second parties is 1.075. (Subset because my dataset does not currently have second party shares for all elections; there are 147 elections here.)
In this sense, the electoral system’s design did indeed punish the main opposition. So if this was the MPLA goal, mission accomplished. The malapportionment must be a main cause of this, combined with the parallel (non-compensatory) allocation of the national seats. It should be noted as well, however, that with only two big parties, if one is overrepresented even a little bit (as the MPLA was), the second will probably be more underrepresented than would be the case in a multiparty system more typical of PR electoral systems.
Interestingly, much of the disadvantage to UNITA went to the advantage of smaller parties instead of to MPLA. There were three other parties, each of which won 2 seats. Two seats is 0.91% of the assembly; these parties had from 1.14% to 1.02% of the votes apiece. These small parties won only in the national district, where the only threshold was that a party could not win a seat by remainder unless it had already won a seat.2 Given that the national district is 130 seats, it could easily have supported even more parties than the five that won at least 2 seats. The largest party to win no seats had 0.75%. A simple quota for this district would be 0.769%, so this party was below the weak threshold anyway.
The effective numbers of parties were 2.20 by votes and 2.06 by seats–note not much difference there.3 The deviation from proportionality (Gallagher’s “least squares index”) was 4.44%. The latter figure, using again my set of simple non-FPTP systems, is not much different from average (4.87%). So all in all, despite the unusual electoral system, it is not a terribly remarkable result in terms of election indices.
As far as the effective seat product is concerned, for a parallel system I have found the satisfactory method is to take the geometric mean of what we would get if the basic tier were the entire system and what we would get if the system were compensatory. The seat product of the basic tier of this system is straightforward: district magnitude of 5, times tier size of 90 gives us 450. The formula for compensatory based on these parameters (an update and slight modification of a method I have shown here before) would yield an effective seat product of 3844. But because it is actually parallel, we take the geometric average of these values, which is 1315.
An effective seat product of 1315 is in the general range of the simple seat product Norway had (1297) before it adopted a small compensatory tier after 1985, or Peru’s in 1980 or 1985 (1296), and also not much smaller than Switzerland’s (1540).4
The disproportionality we should expect from an effective seat product of of 1315 would be around three percent; the actual 4.4% is thus not too much higher. The seat share of the largest party in this election is about 1.4 times expectation5 from such a seat product and the effective number of seat-winning parties is about 0.62 the expectation. Obviously, this is due to MPLA political dominance. Or perhaps due to unfair vote reporting. That I can’t say. What I can say is that, despite a fairly unusual combination of extreme malapportionment in one tier and a greater than 50% parallel national tier, the impact this electoral system had on the seat allocation and disproportionality was not anything too out of the ordinary.
Finally, an interesting question but one I will not attempt to answer is whether, had UNITA won a narrow plurality of the nationwide vote, could the MPLA have retained a plurality or even majority of the assembly seats? Given the malapportionment and parallel allocation, I will say maybe. However, once again, I will point out that if they had wanted to ensure they could “win by losing,” the design they came up with was perhaps a little too “fair” to really be in their best (presumed to be anti-democratic) interest. On the other hand, if they are open to a gradual transition to democracy, and perhaps losing a fair election in five or ten years’ time, the system isn’t too bad. It plays to the MPLA’s regional strength yet does not overrepresent it greatly, and it creates space for the opposition, both UNITA and other parties, to operate.
MPLA won 4-1 in Cuanza Sul, Moxico, Namibe, Huíla, and Cuando Cubango. It won 5-0 in Cunene (where the votes split 82.9%–14.4%). It is really striking that most of these strong MPLA districts are in the south, where UNITA was most present in the civil war. Meanwhile, the UNITA pluralities are Luanda (the capital and largest by far), Cabinda (the non-contiguous oil-rich enclave in the far north which has had a separatist movement) and Zaire (also in the northwest).
It is not clear to me if this means a party could have won a provincial seat and thus been eligible for a remainder seat in the national district, or it had to have won a quota of nationwide votes. In any case, as all provincial seats were won by MPLA or UNITA, this detail would not have affected the results of this election.
If I knew nothing other than that the effective number of vote-earning parties in some election was 2.2, I would expect the effective number of seat-winning parties to be around 1.72, based on logically derived, and empirically supported, formulas inVotes from Seats.
By comparison, if we used the “as if compensatory” estimate of 3844, we would be in roughly the range of single-tier systems like Finland (3076 in 2019) or another former Portuguese colony, East Timor (4225). Indonesia is also in this seat-product neighborhood (4134), as was the French PR system of 1986 (3174).
A ratio of actual to expected of 1.38 is near the 90th percentile for over a thousand elections, simple and complex, in the dataset (and would be about the same if I looked at just the simple non-FPTP subset).
Was the French 2022 honeymoon election one that defies the usual impact of such election timing? Not to offer a spoiler, but the answer is yes and no.
Back around the time of the presidential runoff, I restated what I often say about elections for assembly held shortly after a presidential election: they are not an opportunity for the voters to “check” the president they have just chosen; presidential and semi-presidential systems just do not work that way. Well, usually. It seems hard to escape the notion that voters did just that–by holding Emmanuel Macron’s allies in Ensemble to less than a majority of seats, and by delivering bigger than expected seat totals to the Mélenchon-led united left (Nupes) and even to Le Pen’s National Rally (RN).
There will not be cohabitation, which was what I really meant in the French context when saying that honeymoon elections were not an opportunity to check the president. The results have not offered up any conceivable assembly majority that would impose its own choice for premier on Macron. I was also generally careful to say that I thought Macron’s allies would win a majority of seats, or close to it. They are relatively close, but considerably farther away that I expected, on about 42%. So, how does this outcome compare to honeymoon elections generally?
I have prepared an updated version of a graph I have shared before. An earlier version appears in Votes from Seats, as Figure 12.2. The x-axis is elapsed time, E, defined as the share of the period between presidential elections at which the assembly election occurs. The y-axis is the presidential seat ratio, RP, calculated by dividing the vote share of the party (or pre-electoral alliance) supporting the president by the president’s own vote share in the first or sole round. The diagonal line is a regression best fit on the nonconcurrent elections (those with E>0), and is RP=1.2–0.7E.
I added the France 2022 data point and label a little larger than the others, to call attention to it. The most notable thing is that this is the only case of a really extreme honeymoon–defined loosely as those with E<.05 but E>0–to have a value of RP<1.00. So in that sense, it is a poor performance. There are other honeymoons for which E≤0.1 that are below RP=1.00, including Chile 1965 and Poland 2001. In the Chilean case, the result obtains simply because the right did not present its own presidential candidate, but ran separately in the congressional election. Although this post is focused on honeymoon and other nonconcurrent elections, I also added labels to the two cases of concurrent elections (E=0) that have unusually low presidential vote ratios. Note that on average, RP in concurrent elections tends to be a bit below 1.00, as a combination of strategic voting and small-party abstention from the presidential contest leads assembly voting to be more fragmented than presidential voting, hence lowering RP. However, in very early term elections, the president’s party/alliance almost always gains. So France 2022 is unusual, but not a massive outlier. In fact, in terms of distance from the regression line, it is about equivalent to France 1997 or El Salvador 2006 (labelled).
We see that the 2022 election also features the lowest RP of any of France’s six honeymoon elections to date. The 2002 election (Chirac) produced an especially huge boost, whereas the 2017 election, when Macron had just been elected the first time, is almost on the regression line. (The regression does not include elections after 2015 because the dataset was collected around then; I added these more recent ones to the graph directly.) I also want to call attention to Volodomyr Zelenskyy’s 2019 honeymoon result in Ukraine for Servants of the People, as it is also among the most extreme honeymoon vote surges recorded anywhere as expected, perhaps aided by how uninstitutionalized that country’s party system has been. (If I wanted to be provocative, I’d say that factor also has been present in France, given frequent realignments on the right, the emergence of Macron, etc.)
(As an aside, I was somewhat surprised that an outlier, the one case of E>0.6 to have RP>1 is the French late-midterm election of 1986. This is remembered as the election that produced the first cohabitation of the French Fifth Republic. But the vote share of the Socialists was still considerably higher than Mitterrand’s own vote share in the presidential first round of 1981, when the Communists had presented their own candidate.1)
So much for the votes. I was wondering what happens if we look at seats? Strangely I had never done this before (at least with this dataset). This graph has as its y-axis the seat share of the president’s party (or alliance) divided by the president’s own first or sole-round votes, which I will call RPs. The x-axis is the same. In addition to plotting a best fit line, the diagonal, I also added the 95% confidence intervals from the regression estimates to this graph. There is also a lowess (local regression) plotted as the very thin grey line. Note how flat it is for a long portion of the term, a fact related to a point I will come to at the end (and also suggesting a more complex than linear fit may be more accurate, but I want to keep it simple for now).
The regression line here is very close to RPs=1.5–E, which is a wonderfully elegant formula! It says that at a midterm election, a president’s party’s seat share would be, all else equal, the same as his or her own vote share half a term earlier. At a truly extreme honeymoon election–imagine one held the day after the president was elected, but with the result known–the seat share would be about 1.5 times the president’s vote share. At an extreme counter-honeymoon it would drop to around 0.5. So where did Macron’s Ensemble come out in the election just concluded? His RPs=1.52! So the party actually did about what the average trend says to expect. It was his 2017 surge that was higher than we perhaps should have expected (although, again, not as high as Chirac’s in 2002).
The result in the second figure is obviously holding constant the electoral system, so it should be taken with a grain of salt, given the importance of variation in electoral systems in shaping the size of the largest party (which is usually the president’s party, at least until we get to midterms and beyond).
What I find particularly elegant about the equation is its suggestion that midterm elections are no-effect elections, in terms of seat share for the president’s party. This was presumably what major party leaders were going for in the Dominican Republic when they shifted to the world’s only ever case (to my knowledge) of an all-midterm cycle. Both president and congress were elected to four-year terms, each at the halfway point of the other. (Actual outcomes during were not always no-effect, though on average they were close2; they have since changed back to their former concurrent elections.) This may seem a surprise to readers who know the American system and its infamous midterm decline, but actually the midterm-election median in the US is 0.969. In an almost pure two-party system, anything below 1.00 might look bad, and be both politically consequential and also somewhat over-interpreted. But 0.969 is not really that much below 1.00! Okay I am cheating just a little by reporting the median. The mean is 0.943; it is brought down by a few major “shellackings” like 2010 (0.891), although 1990 was worse (0.719, in this case because G.H.W. Bush had won such a big landslide of his own).3
In concurrent elections, the regression suggests also that on average, RPs is around 1.00. For the US, the median is 0.979, and the mean is 1.009. Note how it is higher than the midterm average, but perhaps not as much as one might expect.4
At this point, both these equations are just empirical regression best fits, not logical models. There is logic behind the general effects of electoral cycles on a presidential party’s performance, but not a logical basis for the specific parameters observed. I would very much like to have such a logical basis, but I have not hit upon it. Yet.
(Considerably nerdier and some rather half-baked stuff the rest of the way.) Such a logical model may be closer now that there is a simple and elegant empirical connection between presidential votes and seats. Seat shares are more directly connected to parameters of the electoral system than votes shares are–even vote shares for assembly parties, but vote shares for presidential candidates are a good deal more remote from the assembly electoral system. Nonetheless, in Votes from Seats we do derive a predictive formula for the effective number of presidential candidates, based on the assembly’s seat product. A regression reported in the book confirms its plausibility, but with rather low R2. From that formula one could get an expected relationship for the leading presidential candidate’s vote total, vp. It would be vp = 2–3/8[(MS)1/4 +1]–1/4. We already have, for the seat share of the largest party, s1=(MS)–1/8. It so happens that these return the same value at around MS=175. Expectations of vp<s1 or s1<vp would then depend on whether MS (mean district magnitude times assembly size) is higher or lower than 175; for most presidential systems it is a good deal higher (the median in this sample of elections, including semi-presidential, is 480). Tying this observation to the one about midterm elections (E=0.5) yielding actual (not predicted) sp=vp and accepting for simplification that the president’s party seat share (sp) is also the largest party seat share, at least in elections that are not after the midterm, might be a path towards a model. But that may take a while yet. Below I will copy a table of what the formulas for vp and s1 yield at various values of seat product, MS, for simple systems. These values of s1 are without regard to elapsed time when the assembly election takes place.
Table of expected values of presidential vote shares (pv) and largest assembly party seat share (s1)
Note how we would expect president’s parties to have a seat share greater than the president’s own vote share at low MS due to system disproportionality, but higher as MS increases beyond 175, presumably because of strategic behavior being different around the majoritarian presidential election and the more permissive assembly electoral system. The smallest MS observed in this dataset for a (semi-)presidential system is 124 (Sierra Leone, 2002, 2007). The largest is 202,500 (Ukraine, 2006, 2007). For nonconcurrent elections, the minimum MS is 240 (Chile, 1997, 2001).
Also, Mitterand himself had finished second in the first round, with 25.9% of the votes (the incumbent, Giscard, had 28.3%). The Communist candidate had 15.4%. In the 1986 election, Socialists won 31% of the votes, for RP=1.2. (I am not counting the Communists as part of Mitterrand’s alliance by then, as he had fired the Communist ministers that were in his initial cabinet.)
The values for RPs in these Dominican elections were: 0.587 in 1998, 0.975 in 2002, 0.945 in 2006, and 1.067 in 2010. So other than that first run, if the no-effect was what they wanted, they basically got it.
[Added, 21 June.] I somehow forgot that my first publication on this topic, in the APSR in 1995, also used seats as its outcome of interest–but it was change in seat percentage for the president’s party from the prior assembly election (with president’s vote share as a control). Looking back on that pub, I see that my regression there would agree with my updated analysis here in suggesting that midterm elections, all else constant, are no-effect elections. The regression line clearly passes very near the change=0, E=0.5 point in the article’s Figure 1. And, yes, in that article I commented on this as a “particularly striking feature” (p. 332).
The way I set up the regression, its constant term would be the RPs when E=0, a concurrent election. This constant is actually 0.95, but its 95% confidence interval includes 1.00 (it is 0.844–1.057). The coefficient on the nonconcurrent dummy is 0.552, from which I get the approximation, 1.5, in the equation in the second figure (summing this coefficient and the constant). The coefficient on E is –1.072. R2=0.215.
The first round of the French 2022 National Assembly election is on 12 June. As readers of this blog recognize, this is an extreme honeymoon election, owing to the short time that has elapsed since the presidential election. In that two-round contest in April, Emmanuel Macron was reelected, winning 27.9% of the vote in the first round and 58.6% in the runoff.
The runner-up in the presidential contest was Marine Le Pen of the extremist National Rally, with 23.2% in the first round and 41.5% in the runoff. In a close third place was the leftist Jean-Luc Mélenchon, with 22.0%. In the period since the runoff results were known, Mélenchon has led the formation of a left alliance known as the New Ecologic and Social People’s Union (NUPES). (See the series of very helpful comments from Wilf at an earlier post, where he shared news stories about the coalition bargaining as it was taking place.) Mélenchon has not been shy about his goal, proclaiming that he is running to be premier. If this happened, it could usher in a period of cohabitation, defined as president and premier from opposing parties and the president’s party not in the cabinet. (I say “could usher in” because there’s always the possibility Macron’s party would be in a cabinet headed by Mélenchon, although if the latter actually were premier–and especially if NUPES won a majority of seats–that would be rather unlikely.)
As readers of this space will know, I find such an outcome extremely unlikely. Honeymoon elections do not work that way. They are not a second chance for voters to “check” the president. They confirm the mandate the voters have just conferred on the new (or newly reelected) president. Or do they? Maybe this will be a special case. That is what I am setting out to explore in this post.
Regarding “normal” honeymoon elections, see the post on France that I wrote in 2017, just before the presidential runoff, suggesting that Macron’s then-new party would get around 29% of the vote, and be the largest party. It actually won almost exactly that, 28.2%, and given both allies and the majoritarian two-round electoral system, Macron ended up with a large assembly majority. See the graph in that post, which also appears in Votes from Seats, and shows how nearly all elections early in a presidential term result in rather significant surges for the president’s party. The graph shows something called “Presidential Ratio” graphed against “Elapsed Time.” The ratio, RP, is simply the vote share of the president’s party, divided by the president’s own (first or sole round) vote share in the preceding presidential election. The elapsed time, E, is the percentage of the time between presidential elections at which the assembly election takes place.
For all non-concurrent elections, a best fit shows a steep slope starting at about 1.2 if the honeymoon election is immediately after the presidential election, and dropping steadily as assembly elections occur later in the period between presidential elections. It crosses the 1.00 line (indicating identical assembly and presidential vote shares) at around E=0.28, or just past the quarter mark, then drops to around 0.84 when E=0.5, encompassing the well known midterm-decline phenomenon. Given that for France in 2022 (as in 2017 and some previous cycles), E=0.017, we expect RP=1.19. Taking Macron’s first-round vote of 27.9%, his party should win around 33.1% of the votes. Presumably that would be a plurality and would again be sufficient to win a majority (or close to it) in the assembly when the two-round process is all said and done. Or should we be sure that would be a plurality this time? Let’s see.
Please remember that the equation of this line for presidential vote ratio is not a logical model (like the Seat Product Model or the Cube Root Law), and in any case, even logical model predictions get tripped up by real politics at times! Maybe this honeymoon election will be different. Macron won many voters in the runoff who would have preferred Mélenchon but felt they had to vote to stop Le Pen. There may be much more energy on the side of NUPES than is normal for an alliance that backed a loser.
So how surprising would a good performance be? I decided the best way to put a potential answer to this question in context was to go back to my dataset and augment it with votes data from runners-up and third-place presidential candidates. I have never looked into this before! So here we go…
First, let’s see what it looks like for the party of the candidate who finished second in the second or sole round of presidential voting.
We see that honeymoon elections are really bad for your party if you just lost the presidential election as the runner-up! All data points are below the 1.00 line until nearly E=0.3. The dashed curve is just a lowess (local regression) curve. I did not continue it much past the midterm, because the data get rather sparse late in the term. Not because there are no such elections (again, see the graph for presidential parties), but because the farther you go into the term, the more likely the runner-up’s party does not exist in a recognizable form. Presidential and semi-presidential systems can be that way.
In France 2022, it was Le Pen who finished second, and I do not think anyone would be surprised if her party got less than two thirds of what she won (in other words, around 15%). In fact, it will probably be much worse than that for her.
The topic of interest here, though, is the third presidential candidate’s party. Here is what that graph looks like:
Interestingly, the party backing the candidate who came in third quite often increases its support in a honeymoon election. In most cases, that probably comes predominantly at the expense of the second candidate’s party. But there is probably no reason why it could not come from the winner’s, in a case where there was a good deal of strategic voting in the presidential election (or specifically, in a runoff).
The curve is pretty level until E=0.2, with a mean of almost 1.5. Given how sparse the data are–there are lots of presidential elections with no third candidate or where the third had no party–I would not draw too much of a conclusion from this. However, note that 1.5 times Mélenchon’s vote would reach 33%, or almost exactly what we “predict” for Macron’s La République En Marche! (The exclamation point is in the party name, although you should be as excited about this convergence of their potential shares as I am!) If one were to add in the votes of the other presidential candidates whose parties since have joined NUPES, perhaps we would “predict” a voting plurality for Mélenchon.
So, while I still do not think Mélenchon is going to become premier, this data exploration has led me to believe it would not be as shocking a development as I initially assumed. It could be that this is the honeymoon election that has the ideal convergence of factors to generate an upset. And make no mistake, if a just-reelected president were to be forced to appoint as premier someone opposed to him, it would be an upset. On the other hand, polls do show it will indeed be close, at least in the first round.
I still think Emmanuel Macron will win reelection, but it is going to be a closer fight than most prognosticators expected before this past Sunday’s first round. In the results of that vote, Macron has the expected plurality, and it was a few percentage points higher than he got in 2017 (27.8% vs. 24.0%). His runoff opponent in both 2017 and later this month, Marine Le Pen, also improved a bit over last time (23.3% vs. 21.3%). What is new–or really accelerating a trend that was already there–is the total collapse of older established parties. The Republican (mainstream right) got 20% in 2017 but only 4.8% this time, fifth place. The Socialists were already in dire shape in 2017 with 6.4%, but did even worse this time, 1.75%, despite (or because of?) running the mayor of Paris, a seemingly high-quality candidate. Jean-Luc Mélenchon of La France Insoumise, a far left group, made the race for a runoff slot pretty close this time, coming third with just under 22% (19.6% last time, fourth place). Given just over 7% for the far-far-right Eric Zenmour, one could say there was a majority for extremes of one sort or another.
While the Economist’s forecast model still has Macron’s win probability at around 80%, it was just short of 100% as recently as 21 March. An extreme right candidate actually has a roughly 20% chance of being the next president of France.
It is never a good thing for democracy when the fate of the republic hinges on one person. But it is hard to exaggerate how absolutely essential it is that Macron win. France has been running a decades-long experiment in whether a highly presidentialized system would eventually destroy the party system. The French party system held up pretty well, despite the adoption of a relatively strong presidency with the 1958 constitution and direct election to that office in 1965. The party system did indeed become presidentialized in ways that David Samuels and I document in our 2010 book, Presidents, Parties, and Prime Ministers. Parties reorganized themselves internally around the goal of advancing their presidential candidate, rather than emphasizing their parliamentary party organization. This presidentialization was only further enhanced by the decision in 2002 to make assembly elections follow immediately after presidential, with both elected for five-year terms. The party system’s left and right blocs, starting from the 1960s, came to be dominated by whichever party could present the successful presidential candidate–the identity of these parties changed over time on the right, but presidentialization allowed the Socialists to surpass the Communists on the left. However, with the demise of the old right and left, there is not much remaining to the party system other than presidential aspirations. Macron himself is the perfect demonstration of presidentialization–having no party at all till he was on the cusp of the presidency, and then creating one that swept into power on the heels of his own win.
The combination of direct election of a politically powerful presidency, honeymoon election of the assembly, and majoritarian electoral rules is toxic. It means that someone from outside the party system potentially can win the presidency and then, in short order, a majority in the assembly. If you get lucky with this combination, you get a Macron. If you get unlucky, you get a Le Pen (or potentially a Mélenchon).
Make no mistake. Honeymoon elections, with majoritarian rules, are the real deal. If Le Pen manages to win the runoff, there will be no “second chance” at which voters can check her with a majority opposed to her in a cohabitation via the assembly. Presidential and semi-presidential democracies just do not work that way. If she wins the runoff, we can expect her National Rally to win around 28% of the vote in the first round of the assembly (see the just-linked post or the one from 2017), and that to be a plurality. Could a broad alliance form to block her candidates, given the two-round majority-plurality system? Sure. Just don’t count on it. Do count on her getting support from various other anti-system forces and being in a much stronger position going into the second round of the assembly election than that 28% estimate implies.
Do I think this is the most likely outcome? No, I do not. I think Macron will win, and go on to win a large majority of the assembly. However, it is a bad situation for French democracy–and the world–to be dependent on this one man not slipping up in some way in the final days before the presidential runoff–especially with a major war going on in the extended neighborhood and related economic difficulties at home. France is in dangerous territory in these moments with its toxic institutional combo, and the overly high stakes that combo generates.
French election season is upon us. In four rounds of elections over the next three months France will choose their President and National Assembly. The presidency is elected by two-round majority (10 and 24 April), followed closely by the assembly using two-round majority-plurality (12 and 19 June). Predictably, the news media are already starting to suggest that President Emmanuel Macron, while likely to be reelected, might be at risk of losing his assembly majority (e.g., The Economist). Will he?
What is almost as predictable as the media expressing this outcome as a real possibility is that presidents–just elected or reelected–see their parties do really well in honeymoon assembly elections. You can’t get much more honeymoon-ish than the French cycle. The assembly election occurs with approximately 1/60 of the time between presidential elections having elapsed. It just so happens that we have a formula for this.
where Rp is the “presidential vote ratio”– vote share of the president’s party in the assembly election, divided by the president’s own vote share (in the first round, if two-round system)–and E is the elapsed time (the number of months into the presidential inter-electoral period in which the assembly election takes place, divided by the total months comprising that period).
In 2017, there were actually news reports suggesting that because Macron at the time he was elected did not yet have a true political party, he would face cohabitation. That would mean an opposition majority, which under French institutions would also mean a premier (head of cabinet) from parties opposed to the president. This was, even at the time, obviously hogwash.
The formula suggested that, once we knew Macron’s first-round vote percentage, we could estimate his (proto-) party’s first-round assembly vote percentage–assuming he would go on to win his own runoff (which was never seriously in doubt). Given that Macron had won 24% of the vote in his own first round, that implied 29% of the vote for the party in the first round for assembly.
What did his party, branded by then La République En Marche!, get? The answer would be… 28.2%. Not too bad for a political science formula. Not too surprising, either. It does not sound impressive as a vote percentage, but when you have the plurality of the vote in a multiparty field with a two-round majority-plurality electoral system, it can be pretty helpful in terms of seats won. Even more when you are a center party, and your opponents are split between left, right, and farther right (and we should not leave out farther left, too). After the second round, LREM ended up with about 54% of the seats. When combined with a pre-election ally, Democratic Movement, the seat total was over 60% (the two parties had combined for about a third of the first-round votes and got 49% of second-round votes).
The Economist article I linked to in the first paragraph was published in the March 5 edition. I want to check how plausible its claim was, using the Economist’s own election forecast model. As of a few days before March 5, that model was basing its forecast on aggregated polls that averaged about 27% of expected first-round vote for Macron himself. In other words, a few percentage points higher than he ended up winning in the first round in 2017. The model also gave Macron at the time an 88% chance of winning the presidency. Thus on the basis of information available at the time–including the Shugart-Taagepera formula for expected presidential-party vote share–we should conclude that LREM would win about 32% of the vote in the first-round assembly election. Assuming this would be the plurality share–a very safe assumption–that would again imply a strong chance of a single-party majority of seats. Not a loss of the majority, or even the need to forge a post-electoral coalition.
Now, since that article was published, Macron has been enjoying quite a surge in the polls. As of today, the forecast model at The Economist has his odds of winning the presidency above 95%. His polling aggregate as of March 12 is up to 31% (Marine Le Pen, his runoff opponent in 2017, is a distant second with 18%). From this we could estimate the first-round assembly vote share is up to 38%.
I will caution that the formula is not a logical model. It is empirical. There is good logical basis behind the general idea of honeymoon surge (and midterm decline, for countries with such cycles). But the specific parameters of the formula do not have a logical basis. At least yet. The graph of the relationship that is shown in Chapter 12 of Votes from Seats (and also included in the 2017 “predictive” post on France) shows a couple honeymoon elections in various countries that have defied the expected surge. However, only one has an elapsed time of less than 0.1 (the specific example of a relatively early honeymoon decline was Chile 1965, in an election held at 0.083 of the presidential inter-election period.1)
So I can’t predict what LREM will get in June. But it would be a surprise if it was worse than around a third of the vote, even if Macron’s own polling surge does not hold. Given the fragmentation of the party system–which looks even higher now than it was in 2017–and the majoritarian nature of the electoral system, anything short of a majority of seats for Macron would be a surprise at this point.
The notion that voters will come out and vote to “check” a just-elected president that they maybe were not all that enthusiastic about is a hard notion for the news media (not only The Economist) to shake. But there just is not much evidence that politics in presidential and semi-presidential systems works like that.2
____ 1. This election saw the Christian Democratic Party of newly elected President Eduardo Frei win a very strong plurality, 43.6%, but Frei himself had won 56%. The problem–for the formula–is that there were only two serious candidates and three total in the presidential election, whereas the PR-elected legislature featured many parties, including allies of the president running separately. The formula implicitly assumes that all parties contest both elections. This is one of the reasons I can’t call it a logical model, because such conditions have not been incorporated, and perhaps can’t be without making it too complicated to be useful. It is pretty useful as it is, even with its oversimplification and lack of true logical basis!
(By the way, in the next Chilean assembly election, held with 75% of the term elapsed, the party’s vote percentage fell to 31%. The formula suggests 37%, but given that we already know the party did worse than “expected” at the honeymoon, we should just use the expected drop from what it actually had. That would “predict” about 25% of the vote at the late-term election. So they did better than expected, actually.)
2. On this point, let me shout out a just-published article by some recent UC Davis Ph.D.s Carlos Algara, Isaac Hale, and Cory L. Struthers on the Georgia (US) Senate runoffs. Even I was skeptical that honeymoon logic could apply to those elections. And in fact it did not turn out as a Dem surge, but there was clearly no evidence of “checking the president” behavior by voters.
Costa Rica recently (6 Feb.) held its presidential and national assembly elections. In the case of the presidency, it was the first round; a runoff will be needed (3 April), as no candidate came close to the 40% required for a first-round victory. The result shows a continuation of the impressive degree of fragmentation that has occurred in recent elections, following a prolonged period of dominance by two major parties.
I will focus first on the assembly election. The largest party in the new assembly will be the National Liberation Party (PLN), one of those formerly major two parties, but in this election it won only 24.5% of the votes for assembly party lists and 18 of the 57 seats, or 31.6%. That is a one seat gain from what it had in the outgoing assembly, elected in 2018, when it was also the largest party. No other party broke 15%. Six parties have won at least one seat, and a large number of parties obtained vote shares of around 2% or less but no seats.
In terms of effective numbers, for votes this works out to 8.3. Yes, eight point three! That is up there with the world’s highest observed values. In seats, the effective number is 5.02, which is also high but less remarkably so in world comparative terms. For comparison, the 99th percentile of effective number of vote-earning parties from over a thousand elections in the dataset I use is 8.6. On the other hand, Costa Rica’s value for seats in this election is just above the 75th percentile (which is 4.77). Another way of stating this is that Costa Rica is experiencing an unusually large gap between effective numbers of parties by votes and seats. This is not the first time, as the values in 2018 were, respectively, 7.79 and 4.78.
The precise reasons for why the votes are fragmenting so much would require someone versed in Costa Rican politics, which I certainly am not. However, it is obvious that the electoral system is struggling to accommodate the voting fragmentation that is being fed into it, and at at the same time, voters are no longer coordinating their votes around what the electoral system can sustain. That leads to a lot of wasted votes.
This is a new phenomenon for Costa Rica. Over the entire period of the current electoral system, which has been in place since 1962 (the year the current assembly size and the current mean district magnitude (8.14) went into effect), the mean effective number of vote-earning parties has been 3.67, and the mean effective number of seat-winning parties has been 2.97. The mean largest party vote share has been 0.413. The mean seat share for the largest party has been 0.453. So the recent two elections (and to some notable degree those since 2006) have been quite a break with the old “textbook” Costa Rican party system.
A point I wish to emphasize is that the old party system was what we should expect of an electoral system like Costa Rica’s. It is a proportional representation (PR) system, but one with a modest seat product. Its seat product (mean district magnitude times assembly size) is only 464, or a little higher than that of the USA (435). So it should be expected to have a party system with two major parties, one of which averages close to a majority of seats, plus some smaller parties–as indeed the USA should have! And that is what Costa Rica had. The expected outcomes of this system, from the seat product model, would be a mean effective number of seat winning parties of 2.78 (barely below the observed fifty-year mean of 2.97). For votes we should expect 3.17 (not far below the long term observed mean, 3.67). For largest party seat share, we expect 0.464 (nearly matching the observed mean of 0.453); for vote share, 0.421 (actual mean 0.413).
In other words, the longterm party system of Costa Rica is basically what we should expect to see, given the modest value of its seat product. We do not need to invoke a presidential electoral rule that allegedly supports a two-party system, as some scholars have done in the past (hey, including me!). In fact, it is not even clear that the presidential electoral system–40% or runoff–should support two-candidate competition. In some past works I classified it as close enough to plurality, which some folks allege supports two-party systems. Of course, it does. Except when it does not. And the runoff provision makes that “except when it does not” even more accurate a description of the systemic effect. Sure, if 40% in within reach for a leading contender, others may have incentive to coordinate and try to beat the leader to 40% When the PLN was politically dominant, that was exactly what the game was. But when expectations are that no one will get to 40%, all bets are off, because to a significant degree political forces can coordinate between rounds, rather than before the first one.
In Votes from Seats (2017), Taagepera and I showed that we can actually predict presidential vote fragmentation from the assembly seat product better than we can predict it from either the rule used to elect the presidentor the actual number of competitors in the presidential election. And Costa Rica was, until recently, a great demonstration of that effect, with (as noted) an assembly party system that was a near perfect fit for the assembly electoral system’s seat product. The presidential party system followed right along, as expected, with a mean effective number of presidential candidates of 2.5 since 1962. The predictive model Taagepera and I propose in our 2017 book suggests that with Costa Rica’s seat product, the effective number of presidential candidates should average 2.49–so there was basically perfect prediction of Costa Rican presidential competitiveness. However, something clearly has upset the old equilibrium.
In this election, the effective number of presidential candidates was 6.15! For comparison, this is almost the 99th percentile of over 200 presidential elections from around the world in the dataset (6.25). [Update: see my own first comment below.] The leading candidate, José María Figueres had only 27.3%. His opponent in the upcoming runoff, Rodrigo Chaves Robles of Social Democratic Program, won 16.7%, and three other candidates had between 12% and 14.8%. The party of outgoing President Carlos Alvarado, Citizens Action, collapsed, with its candidate getting only 0.66% of the presidential vote (and 2.2% of the assembly vote, and no seat–in 2018, despite winning the presidency it had won only 10 seats, good for third place; further, presidents are not eligible for immediate reelection in Costa Rica).
The level of fragmentation of the presidential vote in 2022 is an increase over 2018, when the effective number of presidential candidates was 5.51, and the leading candidate (who lost the runoff) had just under 25%. It is the third election in a row in which no candidate broke 31%. (In 2010, the leading candidate who was from the PLN, won without a runoff, getting just under 47%.)
While on average, the seat product model leads us to expect presidential systems to have assembly party systems similar to what their seat product predicts, and a mean presidential competition also predictable from the seat product, individual elections can upset this. That is, short term presidential politics–who is entering competition and who is seen as a viable presidential candidate–can shock the assembly party system, due to a “coattail” effect. So we generally get longterm predictability from the assembly electoral system’s seat product, but short term disruptions from “presidentialization” of competition. This is now Costa Rica’s third consecutive election with effective number of seat-winning parties over 4.5. That seems unsustainable, based on the electoral system. But at some point maybe a short-term shock settles down and becomes the new normal. I guess we will have to wait till at least 2026 to see if the seat product reasserts itself, or if fragmentation really is the norm. And not just any fragmentation, but an exceptionally high level by world standards, particularly in the votes for both assembly and president.
The majority of seats obtained by the Socialist Party (PS) in the recent general election in Portugal was seen as a surprise. Polling generally had not shown a majority as within reach and indeed showed a likely close result. However, Portugal has had relatively frequent parliamentary majorities over the years, despite its proportional representation (PR) system. How unusual was the 2022 outcome?
From 1976 to 2019, the mean seat share for the largest party in Portugal has been 0.478–not a majority, but pretty close. In this election the PS obtained 117 of 230 seats, which is 0.509. (The total includes the four seats for Portuguese abroad.) This is the fifth absolute majority won in 16 Portuguese assembly elections since 1976. Thus in terms of Portugal’s electoral history, the result was not so unusual. How unusual is it relative to what is expected from Portugal’s PR system?
Portugal’s electoral system has a seat product of around 2400. This is a modest seat product by standards of proportional representation, stemming from a moderate assembly size, S (currently 230; 250 before 1991), and a middle-range district magnitude, M (currently 10.5 on average), yielding a seat product, MS=2415. For such a seat product, the expected largest party seat share is 0.378, derived from the formula expecting this share to be (MS)–1/8. Thus Portugal’s actual largest party seat share has averaged 1.26 times the seat product model prediction.1 This indicates that while Portugal’s electoral system is not expected to produce a high degree of fragmentation (38% of the seats is a decent sized largest party2), actual Portuguese politics supports a more de-fragmented party system–at least so far–than what its electoral system could sustain.
As for votes, the associated formula of the seat product model implies we should expect the largest to have 35.4% of the votes, but the average has been 41.8% instead. In this election the PS won 41.7%. So, whatever people expected, it was a pretty ordinary voting result by the standard of Portuguese electoral history. There was a somewhat higher boost for the largest party, however, than the norm. The average advantage ratio (%seats/%votes) has been 1.14; in this election it was 1.22. I would guess that this larger seat bonus for the largest party comes in significant part from the main rival for national power, the Social Democrats (PSD, actually a center-right party) losing votes to a farther right-wing/nationalist party, CHEGA. The latter party was the big gainer in votes and seats in the election, as it had only one seat from 2019 but won 12 in this election. However, it had a very low advantage ratio, with its 5.31% of seats coming on 7.15% of votes, for a ratio of 0.74. Its votes thus did not translate efficiently into seats, which may have helped the PS harvest more seats than normally would be the case for a party with just over 41% of the votes given Portuguese electoral laws.3
The mean actual largest party seat share in a sample of 634 simple electoral systems is only 1.048 times the model prediction; for PR systems the model is even better, with a ratio of 1.033. So a ratio of 1.26 indicates a strong degree of politics being needed in addition to institutions to explain an outcome. Less than a quarter of PR elections have ratios that high or higher.
The mean largest party seat share for the sample of 280 PR elections in parliamentary (or semi-presidential) democracies that I am working with happens to be 38.2%.
Relative punishment of smaller parties is an inherent feature of the system’s moderate seat product. For instance, in this election the significantly smaller Liberal Initiative won 3.5% of seats on just under 5% of votes. The wasted votes by smaller parties have to go somewhere; given that Portugal uses the D’Hondt formula, the result will tend to be generally more favorable to the largest party than it would be with other PR formulas, for a given seat product. (This is not unusual; more than two thirds of all simple PR systems use D’Hondt.) Still, for a party in its range of vote percentage, CHEGA’s advantage ratio is quite low. For instance, in 2019, the Left Bloc and Unitary Democratic Coalition, with 9.5% and 6.3% of votes, respectively, had advantage ratios of 0.86 and 0.82. So CHEGA must have had an unusually inefficient geographic spread for a party of its approximate size. Indeed, skimming the table the Wikipedia page offers for district-level results, it is easy to spot districts where CHEGA received above its nationwide vote share yet won no seats. As a final note on CHEGA, I will add that its single seat in 2019 was won in Lisbon, where the district magnitude is 48, on 2% of the vote.
I am not sure Michael has made the correct choice here–minority representation provisions are part of the electoral system, after all–but I am also not sure this is incorrect. The system really is challenging to classify and quantify. I note in particular his decision to count its assembly size–and therefore, its district magnitude, given there are no district divisions unless we count the ethnic reservation/guarantee as separate “districts”–as 100 before 2014 but as the full 120 since then. Here, for reference, are the indices he reports in the main part of the document:
The unusual nature of the system is what results in the effective number of seat-winning parties (NS) sometimes being higher than the effective number of vote-earning parties (NV), something that is otherwise rare, and certainly should not happen in a single-district nationwide proportional system. As I noted in the earlier discussion, in 2021 it was even the case that a single party list won a majority of votes, but did not win a majority of the full 120 seats. Because I assume all legislators are equal, and that a government needs a majority of the 120, and not just the 100, I think it is incorrect to treat assembly size as not including the 20 ethnic representatives. Gallagher’s data from 2014 do include them, and I think that should be the case for the earlier years as well.
The question of how to calculate the indices is indeed a vexing one. Gallagher very helpfully explains his choices and what would change if we use a different assumption about what “counts.” This allows the researcher using his valuable resource the ability easily to make his or her own decision. But this researcher still is not sure which decision to make with respect to this system!
I am not comfortable with the idea of counting these various ethnic guarantees as additional “districts” even though I see the case for it (which Henry made in a comment to the previous planting). That lack of comfort is not solely because these “districts” overlay the main one. That is, after all, the case of the Maori districts in New Zealand (each of which encompasses the territory of several general electorates). For that matter, it is also the case with any two-tier system. Rather, the conceptual difficulty is that a given party list may win seats in either component of the system–the general 100 or the set-aside for their ethnic group–if they qualify for additional seats beyond their ethnic group’s reservation/guarantee.
However we conceptualize the system, I believe all these parties should be taken into account in calculating the effective number of parties (votes and seats). The question of whether we count them for deviation from proportionality is less clear to me.
I think I need to count this as a non-simple system (by the criteria used on Votes from Seats), giving us a unique case of what could be called a single nationwide district PR system that is nonetheless complex. For countries whose electoral system has just a few ethnic set-asides (like Colombia or Croatia), I tend to ignore the reserved seats when thinking of whether they are “simple” districted or national-district systems. But when such seats are a sixth of the total, they are clearly a complicating feature, as the unusual outcomes reveal.
This seems like a trick question. Of course, free-list has all sorts of complex features. In such a system, the typical rules are that any voter may cast up to M votes (M being the district magnitude) for individual candidates, even across different lists (panachage). A vote for any candidate on a list counts as a vote for that list for purposes of determining proportional seat allocation across lists, as well as for the candidate in competition among other candidates on that list.
However, this system handles votes and seats for lists just like any other list-PR system: It is designed to allocate seats to lists first, and only then to candidates. It thus is “simple” on the inter-party dimension, unlike SNTV or MNTV or STV (where candidate votes do not count towards aggregate party vote totals and seats are allocated based only on candidate votes).
My general definition of a “simple” electoral system is one that is a single-tier, single-round, party-vote system. The free-list could be said to violate that last part of the definition, in that “party vote” maybe should mean a single party vote per voter. My instinct is to keep free list in, because it remains “simple” in terms of how it processes the votes across lists. But I could be convinced otherwise, given that effectively every voter can vote for more than one list–a “dividual vote” in Gallagher’s terms.1
In Votes from Seats, Taagepera and I kept at least three free-list systems in our dataset: Honduras (since 2005), Luxembourg, and Switzerland. The issue came back to my mind because of my consideration of including some smaller countries and non-independent territories in a dataset for some further analysis of key questions. One of the smaller countries that could be added to the data is Liechtenstein, which I believe uses a free-list PR system. My gut says “yes, include” but now I wonder if we already violated our own criteria2 in having those free-list systems in the prior analysis. To be clear, none of our results would be changed if we had dropped them.3 It is just a matter of consistency of criteria.
Questions like this always nag comparative analysis, or science more generally. What things are part of the set being analyzed? It is not always clear-cut.
Note that there is no question regarding standard open-list PR: Even if there are multiple candidate preference votes cast per voter, as in Peru, only a single list vote is registered per voter.
In fact, on p. 31 of Votes from Seats, we say “Only categorical ballots and a single round of voting are simple, by our definition.” A free-list ballot is dividual and thus not categorical. However, the reason we give for limiting the coverage to categorical ballots is that “other ballot formats… may violate a basic criterion for simplicity in the translation of votes into seats: the rank-size principle” (emphasis in original). For example, the party with the most aggregate votes in a district may not have the most seats allocated in the district (or at least tied for most with the second-most voted party). This violation of the rank-size principle can occur with SNTV, STV, and MNTV, but as noted above it can’t occur in free-list PR (per my understanding, anyway). I note that in a later work, Party Personnel, my coauthors and I seem to adopt a stricter definition. On p. 53 of that book, we say that simple means “a voter votes once, and this vote counts for the entire party list of candidates.” Yet the conceptual point there is somewhat different, in that we are referring to “simple vote” not simple electoral system, and we remove open-list PR from the standard of simple vote because they permit differentiation of candidates within a list in the same district. But as for the vote counting for the entire list, free list still meets that part of the criterion. (A reminder that “voting system” is not a synonym for “electoral system”!)
Although I did not think of this possible issue with free lists at the time, I definitely ran robustness-check regressions with Switzerland dropped. I did so mainly because of its multiparty alliance feature, which also is a complex feature for reasons discussed in the book (mainly with reference to Finland and Chile). Doing so did not affect the results, so we left the case in. There are not enough elections from the other free-list cases, nor are they observably different on our outcomes of interest, that they could affect results. (Switzerland is observably different–far more fragmented than expected for its seat product, and that seems to be mostly due to alliances, even above the impact of its ethnic fragmentation–see p. 269 of Votes from Seats. But the inclusion or exclusion fo the case is immaterial for the overall results.)
I am pleased to announce the publication of a new article, “The Party Personnel Datasets: Advancing Comparative Research in Party Behavior and Legislative Organization Across Electoral Systems” in Legislative Studies Quarterly (open access), coauthored with Matthew E. Bergman (first author), Cory L. Struthers, Robert J. Pekkanen, and Ellis Krauss.
The article introduces the datasets used in the recently published book, Party Personnel Strategies(Oxford, 2021). The data include more countries and many more variables than were covered in the research reported in the book. The datasets themselves are available at the Dataverse.
Here is the article abstract:
This paper introduces eight country-level datasets with >50,000 observations that can be used to analyze novel comparative questions concerning party personnel strategies—how parties recruit candidates and allocate members across party, legislative, and cabinet positions. We make these datasets public to inspire comparative research, especially from an electoral systems perspective; electoral systems shape constituency representation and influence how parties recruit candidates and organize members in legislative and government bodies. In this paper, we first briefly review the relevant literature on electoral nomination and post-election appointment and then describe our motivations for constructing multi-country datasets that can be used to further comparative research. To illustrate the possibilities in these new datasets, we show how recruitment and placement of parliamentarians with particular personal characteristics correlates with their placement onto specific committees and cabinet posts. A conclusion identifies other areas of research that might benefit from using the party personnel datasets.
No reason here to doubt that the logical model, NS = s1–4/3, applies equally well to two-tier systems as it does to simple, single-tier systems. This was a question I raised in the earlier planting on the revision of the extended Seat Product Model (incorporating two-tier systems without an empirical constant).
Thus any deviations of regression output from the precise predictions of the models–as reported in that earlier post–are not caused by some systematic difference in this relationship for two-tier systems. Such deviations are just noise. For instance, the regression intercept on these 472 elections is significantly greater than zero. Yet a nonzero intercept is impossible. It can’t be that the effective number of parties is any different from 1.0 (the log of which is 0) if the largest party has 100% of the seats.* More to the point for the question I had, the regression shows no significant difference in slope (or intercept for that matter) between single-tier and two-tier systems. They behave the same in this sense, meaning that when the compensation tier increases the effective number of parties and reduces the seat share of the largest, it does so while preserving NS = s1–4/3, on average. And, by the way, for those who care about such things, the R2=0.899.
Bottom line: there is no statistically significant difference between single-tier and two-tier electoral systems in how the effective number of parties is related to the size of the largest.
* If I suppress the constant (while also eliminating the binary for “simple”) the coefficient is –1.341, or almost precisely the logically required –4/3. When run with the constant, it is –1.235, but the 95% confidence interval includes –1.333.