Academic writing styles

I am working on two books this summer/fall. I hope both will be done by the end of December, although that may be over-optimistic. As a result of being engaged in these writing processes, questions of academic writing style have been on my mind.

I owe many debts of gratitude to my mentor and frequent coauthor, Rein Taagepera. But the most recent one was his suggestion that every empirical chapter in our new book (Votes from Seats, 2017) start with a presentation of the key result. Don’t drag the reader through prior literature and a bunch of “hypotheses” (a practice he hates, and I tend to agree) before getting to the point. Start with the point, and then explain how you got there, and only then why others did not get there. But the thing is, this almost never works with a journal article (and maybe doesn’t work with books for most scholars not named Shugart or Taagepera), because reviewers impose a standard format that just makes for plodding reading. And writing.

For probably the best demonstrations of our preferred presentation, if you have access to the book, see Chapter 7, which has an overview of “Duverger’s law” near its end, but starts with the Seat Product formula for effective number of seat-winning parties and a graph showing the payoff. Also Chapter 12, in which the previously proposed concept of “proximity” is discussed at the end of a chapter that opens with some data plots showing our preferred “elapsed time“. Other empirical chapters in the book mostly follow this format as well.

Sierra Leone 2018

[See caveat in comments about the electoral rules of the earlier elections. For now, I am not changing the post, even though I should re-do it with averages only from the FPTP elections.]

On Sunday, Sierra Leone held its presidential runoff. Sierra Leone is one of those examples of a relatively rare combination: presidentialism with an assembly elected by plurality in single-seat districts. Some of the other examples of this combo are also found in West Africa, including Ghana and Liberia. In this entry, I will consider the effects of Sierra Leone’s institutions on the party system, applying some of the logical models of Votes from Seats.

The runoff rule used for the presidency is even rarer (unique?). A second round is required if the leading candidate in the first round does not reach 55% of the valid votes (Art. 42.2.e of the constitution of 1991).

Julius Maada Bio of the Sierra Leone People’s Party (SLPP) won 43.3% in the first round on 7 March. The runner up was Samura Kamara of the All People’s Congress (APC), with 42.7%. This was the country’s closest contest thus far since the current democratic institutions were inaugurated in 1996.

Sierra Leone has had one president during this time period who was elected with less than 55%. In 2007, Ernest Bai Koroma of the APC won with just 54.62%. However, this was in the runoff. He had 44.3% (to 38.3% for the runner up) in the first round. And herein lies the real oddity: One might wonder why it is OK to elect a president with just half of the votes, plus one, in a two-candidate runoff, but a total falling between 50% (plus one) and (one vote under) 55% would not be sufficient to win in a single round.

So far Sierra Leone has not had an election in which the first-round leader was in that 50-55% grey zone. Dating to 1996, first-round leaders’ vote percentages have been 35.8, 70.1, 44.3, 58.7, and 43.3

Sunday’s runoff (results for which will not be known for about a week) is to replace outgoing President Koroma, who was elected in 2007 and reelected in 2012.

In the assembly elections, concurrent with the first round of the presidential election, only 90 of the 132 constituencies have been declared so far. (There are also 12 seats reserved for tribal chiefs.) The SLPP has won 47 seats to the APS’s 32. The Coalition for Change has eight, despite its presidential candidate having placed fourth with only 3.5% of the vote. Obviously the Coalition for Change has a regional base, and parties with regional strength can win under FPTP despite having a low nationwide vote total. (National vote totals for assembly are not yet available.) The party of the third-place presidential candidate, who won 6.9%, is called the National Grand Coalition, but evidently it is not. On the other hand, it also is apparently not regional, having won no assembly seats (at least among those declared).

The assembly has been increased in size from the last election, when there were 112 elected seats. This remains slightly undersized for a country with a population around seven million. The Cube Root Law would imply an assembly of around 192.

As for the assembly party system, the current assembly size, S=132 (ignoring the indirectly elected chiefs), and the use of FPTP (M=1) implies an effective number of seat-winning parties, NS=(MS)1/6=2.26. On currently declared seats, we have NS=2.45 (counting each of three independents elected thus far as a “party”). That is only a very minor deviation from expectation.

The combination of FPTP for assembly and a two-round presidential election might be expected to inflate NS due to the expected (and observed) proliferation of presidential candidates seeking votes in the first round. At least it would be so expected if one believes in coattail effects. There were sixteen presidential candidates contesting the first round, and seventeen parties with assembly candidates in at least some districts.

While the effect of the first-round threshold of 55% is not clear, we might expect it to enhance fragmenting effects, relative to a standard majority runoff. Candidates who are unlikely to win might enter anyway, hoping to deny even a strong leading candidate an outright win. Given that an outright win is more difficult in Sierra Leone than in other two-round systems, the effect might be to enhance first-round fragmentation. Under a “coattails” expectation, that fragmentation would carry over into the assembly elections, even with the use of FPTP for those elections, held concurrent with the first round of the presidential contest.

In Votes from Seats, Taagepera and I express some skepticism about coattail effects, at least in terms of their impact on the effective number of parties. In fact, we go so far as to claim that one can deduce the effective number of presidential candidates (NP) from the assembly electoral system. A more direct logical expectation, developed in the book, goes from the assembly voting party system to NP; to the extent that the voting fragmentation (measured by the effective number of vote-earning parties, NV) is over-fragmented, relative to the electoral system expectation, then NP will be inflated as well.

Sierra Leone is thus a good test case for the logical models of Votes from Seats. First of all, it has changed its assembly size twice now, while retaining FPTP. Second, as noted already, it combines the FPTP assembly electoral system with a two-round presidential formula that might tend to increase fragmentation of the presidential contest. If it does so, it may also tend to increase NS and NV, if coattails explain assembly party-system fragmentation. In a table below are the results, showing all three actually observed effective numbers (NSNVNP), where available, and the expected values. The expectations are derived from the seat product (MS) in the case of NS, but for NV, we should use the derivation from observed NS, because if the latter is over expectation, for sure NV will be, too. For NP, the table reports the expectation from NV, which is the more direct route. Again, if NV, is higher than expected (perhaps because so is NS), then NP will be, as well. However, we can also compare the institutionally grounded expectation, derived from MS only.

What we see is that NV was far “too high” in the initial election under the current constitution, given the quite low assembly size. So was NP, and thus it looks like a “win” for the coattails expectation, perhaps because as an initial election before the civil war (starting 1991) was fully settled, many candidates may have entered unsure of who would be viable. The 2002 election, following the settlement of the war, also looks like a case of coattails, as the winner easily dominated the field, leading to very low values of all three effective numbers.

Nonetheless, on average, the institutionally derived expectations perform well. Even with the first election being well off the expectation (and the second, too, albeit less so and in the opposite direction), overall, the ratio of observed NS to actual has been only a little above 1.00; the ratio of expected to observed is 1.153, shown in the bottom line. (If we ignore the anomalously fragmented 1996 election, the mean NS is 2.175, or slightly below the expectation from the assembly sizes used in 2002-2018.)

Given actual NS, the observed NV has been almost exactly as expected, on average, with a ratio of 1.025. And while the slight over-fragmentation of the average assembly election result in Sierra Leone gets magnified when we look at expected NP from MS (i.e., from the assembly electoral system only, for which the ratio is 1.225), the expected NP from observed NV is not too far off, with a ratio of 1.16. Note that the ratio for NP from observed NV is almost the same as the ratio for NS from the assembly seat product.

Thus, even with a presidential electoral formula (super-majority runoff) that theoretically promotes more fragmentation than the assembly electoral system (FPTP), there is scant evidence–beyond 1996–that we are unable to predict the assembly party system from the assembly electoral system. There is also scant evidence that we can’t predict voting fragmentation for both assembly and presidency from the assembly party system. The small over-fragmentation of the assembly party system, on average, gets carried through to the other measures. This over-fragmentation might be due to the fragmenting incentives of the presidential electoral formula, but only in 1996 is the evidence for such an explanation, based on candidate entry and their coattails, compelling. Otherwise, it seems the assembly seat product allows us to get a pretty good handle on the output indices of Sierra Leone’s elections.

The seat product model, based on the assembly electoral system, performs well, even in a new post-war democracy like Sierra Leone, and even given the country’s somewhat unusual combination of institutions.

Colombia 2018: Counter-honeymoon elections and presidential primaries

Colombians have voted today in elections for the two chambers of the congress and in (optional) presidential primaries. I believe Colombia is the only country to hold assembly and presidential-primary elections on the same day. Notably, these are the first elections in which the political party formed by the former guerrilla movement, FARC, is participating.

Colombia is rare among presidential (or semi-presidential) democracies in using counter-honeymoon elections over a long time frame. A counter-honeymoon election is one held late in the presidential term, much closer to the next presidential election.

In fact, I believe that since 1958, only three Colombian congressional elections have not been in the counter-honeymoon: 1970 and 1974 (which were concurrent) and 1991 (which was an early election called by the Constituent Assembly that had been elected the preceding year to create a new constitution).

By the measure of elapsed time between presidential elections, Colombia is about as extreme as can be. The elapsed time of its recent elections, including today’s, has been around 0.95. In other words, when the congress is elected, only 5% of the time between presidential elections remains.

Among all elections from presidential systems in the dataset used for Votes from Seats, the mean elapsed time is 0.268. However, most assembly elections in the wider world of presidential democracies are concurrent. If we eliminate these from the sample, the mean is 0.540. In other words, on average, non-concurrent elections tend to be held around the midterm. But the range is large. The minimum is 0.164 (France 1988; the 2017 honeymoon election France also had a similar value). The maximum is 0.992 (Poland 2005; another near the maximum was El Salvador 2009).

When an election is this late in a presidential term it is likely to be essentially a preliminary round of competition for the upcoming presidential election. I wrote about this effect in Colombia in 2010. That would be the expected effect even if there were no presidential candidates on the ballot, but in Colombia, there are. Parties that choose to hold a presidential primary (consulta) hold them on the same date as the congressional elections. The first such primary was held by the Liberal Party at the same time as the 1990 congressional elections. And most congressional elections since then have featured one or more primaries.

There were two primaries in Colombia today. They were not actually party primaries, but something new for Colombia (and rare anywhere): alliance primaries. There is a right-wing alliance holding a primary among three candidates, including those of the Democratic Center (the party led by former President Alvaro Uribe and strongly opposed to the peace terms the FARC received) and the Conservative Party. Then there is a left-wing alliance holding a primary among two candidates. In addition, there are other parties that already have nominated candidates for the upcoming first round of the presidential contest itself, and thus are not holding primaries. The primaries are “open” in the sense that any voter may request either one of the primary ballots. (See details at AS-COA.)

According to data graphed and analyzed statistically in Votes from Seats, counter-honeymoon elections tend to be more fragmented than those at other points in the term. The Seat Product Model, predicting the effective number of parties (both seat-winning and vote-earning) tends to be quite accurate for assemblies in presidential democracies* except when held with an elapsed time greater than roughly 0.90. Really late-term elections have a tendency to an effective number of parties significantly higher than the Seat Product Model prediction (depicted in Figure 12.1 in the book).

We suspect that is precisely because with the current president’s term almost up, and politicians jockeying for position in the next presidential election, more parties enter and receive votes as a sort of “testing of the waters” prior to the presidential election.

Would holding presidential primaries on the same day dampen this fragmenting effect of the counter-honeymoon? I see no reason why it would. It simply inflates the number of presidential candidates (or “pre-candidates”) testing the waters. Moreover, if the primary is for an alliance, rather than a single party–as is the case in Colombia this year–then the parties have every incentive to run separately and seek to boost their legislative vote as well as their preferred candidate for the presidency.

Thus Colombia’s high fragmentation in recent elections might be explained both by the counter-honeymoon assembly election and the primaries. Moreover, the presidential election itself is a two-round process, and the Senate is a single nationwide district (M=100). That is a lot of things pointing towards a high number of parties!

As for the FARC’s electoral debut, how many seats will it win? I will predict five in each house.***


* Despite more variation overall than is the case in parliamentary democracies.

** This is one of the easier predictions I will ever make. This is what the peace accord guarantees them. They could win more, if they won sufficient votes to elect more. That is highly unlikely.
</small >


The Salvadoran result 2018: The electoral cycle counts!

[Note: the following has been revised based on updated voting results– 9 March, 17:17 PM PST]

Before the assembly election in El Salvador, I suggested that the FMLN should be expected to win 24.2% of the vote. I hedged, saying I thought the Salvadoran party system probably was still too rigid to allow one of its two leading parties to fall off that far. I should not have hedged, because the preliminary results show that the largest party will be the opposition ARENA, which won 42.3%. The FMLN got 24.4%. How about that. I was off by a tenth of a percentage point in my pre-election prediction!

Well, as nice as that would be as a story, it is more complicated than that…

now realize that I made an error in calculating my expectation of 24.2%. I based the expectation on the fact that the FMLN is the party of the incumbent president, that this election was being held with 80% of the president’s inter-electoral time lapsed, and the president’s own (first-round) vote total (in 2013). It was in the latter factor that I made a mistake, using 39.0%; that was the ARENA total, but the FMLN candidate, Salvador Sánchez Cerén, had 48.9%. Plugging that into the formula (shown below), I should have “expected” the FMLN to get 30.3% of the vote in this past Sunday’s assembly election. So the party actually did a good deal worse than the corrected expectation. And I did worse in my prediction.

Perhaps the party system is no longer so rigid; one of the leading parties can fall below a quarter of the votes after all. Alternatively, as I shall explore here, perhaps I made a second countervailing mistake, which was not to include a coalition partner. If we add the votes of GANA, a center-right party but one that has supported FMLN presidencies since 2010 and, importantly, did not compete against Sánchez Cerén in the presidential contest, we get 35.9%. That’s greater that my (corrected) expectation of 30.3%, but somewhat closer to it than the FMLN’s own vote. I will return to this issue of party vs. alliance later.

The FMLN’s 24.4% is its worst showing in the votes for assembly since its debut election in 1994 (21.4%); that election was concurrent with the presidential election and the party ran just behind its presidential candidate (24.9%) who was a very distant second. Since then, the party has won 33.0%, 35.2%, 34.0%, 39.7%, 42.6%, 36.8%, 37.2%, and now 24.4%.

The party’s high-water mark was 2009, the “counter-honeymoon” election that presaged the leftist, ex-guerrila, party’s first presidential win a few months later.* Then, holding the presidency, it slipped in 2012, an election held with about 60% of the president’s term elapsed. In 2014, it won the presidency again, then held its own in the 2015 election, held with 20% of the new president’s term elapsed.

GANA first appeared, as a split from ARENA, in 2010, just under a year after the election of the first FMLN president. It has now run in three assembly elections staring with 2012, and its votes have been 9.6%, 9.2%, and 11.5%. Interestingly, it gained in 2018 even while the FMLN lost badly. If we add the two parties’ votes together for the last three elections, we get 46.4% (not much less than Sánchez Cerén’s own percentage in 2014), 46.4% (yes, again) in 2015, and 35.9%. That is obviously a sharp decline in the two parties’ combined votes, even if one of the partners did experience an increase. FMLN and GANA will now will have around 40% of the assembly seats, whereas they held half the seats after both the 2012 and 2015 elections.

What led to the sharp decline this time? Many political factors, no doubt. But what really counts is the elapsed time–an election this late in a presidential term tends to be bad for the presidential party–or alliance. The FMLN in 2018 is just the latest example of an effect I first researched in my dissertation (1988) and published about in the APSR in 1995.

Now, via Votes from Seats, we have a formula:


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).

The key question around which this post is based is whether we should mean “party” literally as the party of which the president is nominee, or if we should include supporting parties that do not compete against the candidate. If you think it is cheating to use the alliance, I am being transparent and reporting the party totals. If you think it is OK to use the alliance when the two parties in question do not compete against each for presidency and cooperate in the assembly–despite running separately–we can compute the totals that way, too.

The formula above expects Rp=0.620 because E=0.80 for this election. Using only the FMLN assembly vote only, observed Rp=0.244/0.489=0.489. Using the FMLN+GANA vote, observed Rp=0.359/0.489=0.734. With the expected Rp=0.620, we get the previously mentioned expectation of 0.303 for the president’s alliance vote share. Obviously the president’s own vote does not change with these calculations, because any GANA-aligned voters who voted for the FMLN candidate are already included. This is why I think it makes sense to use the combined votes–not only because it makes the formula “work” better. (Honest! But F&V readers get to do peer review here!)**

This is the second nonconcurrent assembly election I have watched closely since Rein Taagepera and I developed the formula for our book (published in October, 2017). The other was in France. In April, 2017, I “predicted” that the brand new party of Emmanuel Macron would win around 29% of the vote. This was the day after the first round, and assuming he would win the second round (which he did, easily). At the time, much media commentary was of a hand-wringing character: Macron would be weak, maybe even face cohabitation, because he didn’t have any party to speak of. I said no, the electoral cycle will ensure he gets a good boost in votes in the assembly election. An elapsed time (E) of 0.017, an extreme “honeymoon” election, would almost guarantee it.

In fact, the election resulted in Macron’s party winning 32% of the vote. (And, a large majority of seats, due to the disproportional electoral system.)

So, that’s two elections in the past year called (more or less) correctly, within a few percentage points, based only on the elapsed time and the president’s own initial vote share.

I still hesitate to call this a prediction, because the parameters in the formula (1.20 and 0.725, above) are not themselves based on deductive logic. And perhaps I also should hesitate because of the ambiguity over party vs. alliance, as discussed in this post. But there just may be something to these electoral cycle effects, after all.

[Note: lightly edited since posting.]

______ Notes
* The 2009 presidential election featured only two candidates. So the party’s presidential vote was inflated due to the abstention of all but the two big parties from the presidential race that year. This is the only time smaller parties have not contested the first round. As I said at the time, the decision by the then-ARENA majority to shift from a concurrent to counter-honeymoon assembly election that year converted the assembly election into a “de-facto first round of the presidential election”. The right got spooked, perhaps, by the strong showing of the FMLN, and did not want to risk a division, even in the two-round election. The left followed suit and, with a sole candidate, narrowly won.

** In the 2015 election, based on the new president’s 48.9% of the (first round) vote in 2014 and elapsed time, E=0.20, we would have expected a votes ratio Rp=1.055. That would mean an assembly vote percentage of 51.6%. The FMLN itself won only 37.2%, but if we include GANA, as noted, we get 46.4% (Rp=0.949), which is a small under-performance. (Consequential, of course, as they failed to get the majority predicted.) How about one election farther back in the cycle? In 2012, GANA existed, but that party had not existed at the time the then-incumbent president of the FMLN was elected. So we certainly can’t include it in the calculation for 2012! For that election E=0.60, and so expected Rp=0.765. The president had won 51.3%, so we’d expect the FMLN to have won 39.2%. It actually won 36.8% (observed Rp=0.719), so it did only a little worse than the formula suggests it could have expected.



This could be a pre-election post on Italy, where the subject line would fit. But it is not.

It is about a really annoying error I just noticed in Votes from Seats. The heading for Table 3.5 is WRONG.

Obviously, Japan uses MMM, not MMP. Not only do I know that (as does my coauthor, Rein Taagepera), but we say so in the text just below this table (not shown in the image). So this made me want to check the document that we submitted to the press for production.

Pretty clearly we had it right! The error was introduced in a later stage. Perhaps partly due to confusion with the preceding table, 3.4, which shows an example from MMP (New Zealand, 2008), and is titled correctly.

I post this not to shame the press. These things happen. It is a lesson in checking proofs, and re-checking them. Do it. Carefully. Of course, we did. Both of us. And still this got through. It happens. Publishing is imperfect. But errors like this in the final print version are so very annoying.

Chile 2017: Meet your new seat product

As discussed previously, Chile has changed its electoral system for assembly elections (and for senate). The seat product (mean district magnitude times assembly size) was increased substantially. Now that the 2017 Chilean election results are in, did the result come close to the Seat Product Model (SPM) predictions?

The old seat product was 240 (2 x 120). The new seat product is 852.5 (5.5 x 155). This should yield a substantially more fragmented assembly, according to the SPM (see Votes from Seats for details).

I will use the effective number of parties (seats and votes) based on alliances. The reason for this choice is that it is a list PR system, and the electoral system works on the lists, taking their votes in each district and determining each list’s seats. Lists are open, and typically presented by pre-election alliances, and the candidates on a list typically come from different parties. But the question of which parties win the seats is entirely a matter of the intra-list distribution of preference votes (the lists are open), and not an effect of the electoral system’s operation on the entities that it actually processes through seat-allocations formula–the lists. However, I will include the calculation by sub-alliance parties, too, for comparison purposes.

The predicted values with the new system, for effective number of seat-winning lists (NS) and effective number of vote-earning lists (NV), given a seat product of 825.5, are:

NS=3.08 (SPM, new system)

NV=3.45 (SPM, new system).

The actual result, by alliance lists, was:



So the Chamber of Deputies is almost exactly as fragmented as the SPM predicts! In the very first election under the new system! The voting result is somewhat more fragmented than expected, but not wide of the mark (about 14%). It is not too surprising that the votes are more off the prediction than the seats; voters have no experience with the new system to draw on. However, the electoral system resulted in an assembly party system (or more accurately, alliance system) fully consisted with its expected “mechanical” effect. The SPM for NS is derived from the constraints of the number of seats in the average district and the total number of seats, whereas the SPM for NV makes a potentially hazardous assumption about how many “pertinent” losers will win substantial votes. We can hardly ask for better adjustment to new rules than what we get in the NS result! (And really, that Nresult is not too shabby, either.)

Now, if we go by sub-alliance parties, the system seems utterly fragmented. We get NS=7.59 and NV=10.60. These results really are meaningless, however, from the standpoint of assessing how the electoral system constrains outcomes. These numbers should be used only if we are specifically interested in the behavior of parties within alliances, but not for more typical inter-party (inter-list) electoral-system analysis. It is a list system, so in systems where lists and “parties” are not the same thing, it is important to use the former.

To put this in context, we should compare the results under the former system. First of all, what was expected from the former system?

NS=2.49 (SPM, old system)

NV=2.90 (SPM, old system).

Here is the table of results, for which I include Np, the effective number of presidential candidates, as well as NV and Ns on both alliance lists and sub-alliance parties.

By alliance By sub-list party
year NS NV NP NS (sub) NV (sub)
1993 1.95 2.24 2.47 4.86 6.55
1997 2.06 2.54 2.47 5.02 6.95
2001 2.03 2.33 2.19 5.94 6.57
2005 2.02 2.36 3.01 5.59 6.58
2009 2.17 2.56 3.07 5.65 7.32
mean 2.05 2.41 2.64 5.41 6.79

We see that the old party (alliance) system was really much more de-fragmented than it should have been, given the electoral system. The party and alliance leaders, and the voters, seem to have enjoyed their newfound relative lack of mechanical constraints in 2017!

Can the SPM also predict NP? In Votes from Seats, we claim that it can. We offer a model that extends form NV  to NP; given that we also claim to be able to predict NV from the seat product (and show that this is possible on a wide range of elections), then we can also connect NP to the seat product. We offer this prediction of NP from the seat product as a counterweight to standard “coattails” arguments that assume presidential candidacies shape assembly fragmentation. Our argument is the reverse: assembly voting, and the electoral system that indirectly constraints it, shapes presidential fragmentation.

There are two caveats, however. The first is that NP is far removed from, and least constrained by, assembly electoral systems, so the fit is not expected to be great (and is not). Second, we saw above that NV in this first Chilean election under the new rules was itself more distant from the prediction than NS was.

Under the old system, we would have predicted Np=2.40, so the actual mean for 1993-2009 was not far off (2.64). Under the new system, the SPM predicts 2.62. In the first round election just held, NP=4.17. That is a good deal more fragmented than expected, and we might not expect future elections to feature such a weak first candidate (37% of the vote). It is unusual to have NP>NV, although in the book we show that Chile is one of the countries where it has happened a few times before. Even the less constraining electoral system did not end this unusual pattern, at least in 2017.

In fact, that the assembly electoral system resulted in the expected value of NS, even though NP was so high, is pretty good evidence that it was not coattails driving the assembly election. Otherwise, Ns should have overshot the prediction to some degree. Yet it did not.