Party cohesion in the Italian parliament

June 12, 2013

They might be losing members, but evidently the Movimento 5 Stelle doesn’t have any problem whipping its parliamentarians.

cairo_test

Cohesion score = Rice index = |% Yes – % No| / (%Yes + %No)

ERT: only good compared to other Greek media

June 12, 2013

Yesterday the Greek government — or at least, one part of it — decided unilaterally to shut down the Greek public broadcaster ERT.

This has led to a wave of solidarity with one of Europe’s least watched and least independent public broadcasters which I find difficult to understand.

For a public broadcaster, ERT has an extremely low audience share (circa 12%). One of the reasons ERT performs so poorly is that it has been colonised by the political parties. In my article and book on the independence of public broadcasters, I wasn’t able to find enough information on ERT’s legal status to include in alongside my other proxies of de jure and de facto independence — but the information I did have on tenure suggested that ERT would have been one of the least independent PSBs in my sample.

That’s backed up by a recent expert survey of European media. The responses to that survey show two things.

First, ERT looks good when compared to commercial Greek media. Here’s a graph showing the average level of agreement with the statement, “Public television in [COUNTRY], compared to private television channels, provides more trustworthy information”, on a zero to ten scale, across a range of European countries.

ert_compared_to_commercial_tv

Second, ERT looks bad when respondents are asked to evaluate it in absolute terms. Here’s a graph showing, for public broadcasters only, the average response to the question “how much is the political coverage in the following media outlets influenced by its owners?”, again on a zero to ten scale. (The question asks about owners, since it also applied to commercial stations; but since ERT is 100% owned by the Finance ministry, it is apt).

ert_owninfl

In my book there’s a wonderful quote from a former Rai board member (Franco Cardini) who was disenchanted with the legacy of political colonization of the broadcaster. He suggested the following:

What Rai needs is a relatively long period of real government . . . A period of dictatorship followed by an extremely tough mayor, as ancient Rome and the medieval cities did. A period in which one could truly reform, in the etymological sense of the word: re-­form

It looks like ERT will have that opportunity.

Left-right response scales in the British Candidate Surveys

June 3, 2013

The British Candidate Surveys — of which five (1992, 1997, 2001, 2005, and 2010) have now been completed — are a fantastic resource for students of political recruitment.

How good are these surveys for measures of MPs’ left-right positioning? All respondents to the survey have to fill out a scale, from zero (most left-wing) to ten (most right-wing). But we know that people use scales in different ways. Some people use the full range of values (‘spreaders’); some use a narrower range (‘bunchers’); and some use a fuller or narrower range but shift responses one way or the other (‘shifters’).

More than thirty years ago, Aldrich and McKelvey developed techniques for dealing with spreaders, bunchers and shifters which are applicable provided respondents rate some stimuli in common. If we say that these stimuli just have the one position, then we can use that information to gauge how much people are bunching, or spreading, or shifting. These techniques — which can be used in R with the basicspace package — allow us to place stimuli and respondents in a `common space’, and thus to check the fit between the original placement and the recovered position.

When it works out well — as in the demo data set using voters’ perceptions of candidates together with their own self-positioning in the 1980 US Presidential election, you get a nice chart like this

issues1980

and a nice Spearman correlation (r=0.8) between respondents’ self-positioning and their recovered position.

Unfortunately, it doesn’t work so well on British Candidate Survey data. Let’s take the 2001 survey [all R code], which asked candidates not just for their own left-right position, but also for three common stimuli — the parliamentary party, the leader, and the party’s voters.

If you carry out the scaling procedure for just Labour respondents (subsetting is necessary — there are no cross-party stimuli available), you get a negligible correlation (r=0.18) between respondents’ self-reported position and their recovered position. You also get a large number of respondents with `negative weights’ — cases where the best fit (assuming common stimuli) involving flipping some respondents’ use of the response scale.

I’ve checked this for Labour, the Conservatives, and Lib Dems across two waves (2001, 2005), and only the Lib Dems in 2001 and 2005 show moderate correlation (0.55) between self-reported position and recovered space — perhaps because they were so acutely aware of tensions in their strategy of equidistance.

I don’t know how much to make of this. My gut feeling is that party voters, party leader, and parl’y party are just too close together for them to be good anchor stimuli, and so whilst we might have concerns about scale use, we can’t act on them.

P.S. In all of the results, candidates thought that their party voters were to their preferred wing — Labour candidates thought party voters were pulling them left, Conservative candidates thought party voters were pulling them right. Are they nuts?

My last word on Italian polling in 2013

May 31, 2013

I’ve finally written a short note on the accuracy of Italian polling in the 2013 election. Here’s the abstract:

This note examines polling for the 2013 Italian general election. Polling was not accurate when compared to the election outcome. I argue that half of this inaccuracy is due to the long (15 day) embargo period. Polling is much more accurate when pre-embargo polling is compared to the most likely levels of support for each of the main parties on the day the embargo came into force. I estimate this counterfactual level of support using a model which simultaneously pools polls and estimates house effects.

Here’s the key table:

Company MAE v. result RMSE v. result Rank (MAE) MAE v. embargo day RMSE v. embargo day Rank (MAE) MAE from house fx RMSE from house effects Rank (MAE)
SWG spa 2.17 3 (1) 0.83 1.08 (1) 0.78 0.93 (4)
IPR Marketing 2.4 3.65 (2) 0.98 1.23 (3) 0.74 0.99 (3)
Euromedia Research 2.48 4.24 (3) 1.47 1.9 (9) 1.24 1.55 (10)
Demopolis 2.62 3.55 (4) 0.95 1.09 (2) 0.6 0.73 (1)
Ipsos 2.66 4.06 (5) 1.21 1.64 (5) 1.24 1.71 (9)
Tecnè 2.68 3.95 (6) 1.18 1.4 (4) 0.63 0.9 (2)
Lorien Consulting 2.83 4.3 (7) 1.36 1.86 (6) 0.92 1.24 (8)
Datamonitor 2.87 4.47 (8) 1.38 1.98 (8) 0.86 1.03 (6)
ISPO 2.91 4.72 (9) 1.64 2.4 (11) 0.89 1.16 (7)
EMG Srl 2.98 4.43 (10.5) 1.49 1.96 (10) 0.81 1.17 (5)
SpinCon 2.98 5.29 (10.5) 1.81 2.87 (12) 1.36 1.95 (12)
Demos 3.08 4.26 (12) 1.38 1.67 (7) 1.3 1.61 (11)
Istituto Piepoli 5.68 7.37 (13) 3.66 4.31 (13) 1.81 2.3 (13)
Average 2.95 4.41 1.49 1.95 1.01 1.33

A mean absolute error (MAE) of 2.95 flatters the pollsters because it’s based on all parties which secured representation, and it’s much easier to secure smaller errors with small parties.

Which are the best performing government departments?

May 25, 2013

On Friday at 5pm (which was an excellent time to bury bad news) the government released the first report of the Major Projects Authority. The MPA has given traffic light codes to a range of “Major projects”.

Hearteningly, the data for this exercise are available (in bits and pieces) online. If we take all the project codes, and assign numbers to them (Red = 1; Red/Amber = 2; Amber = 3; Amber/Green = 4; Green= 5), then how do government departments fare?

If you just take the average, you get something like this:

Dept. Score
NS&I 2
HMT 2.5
DCMS 2.8
ONS 2.8
CO 3.2
DCLG 3.25
DWP 3.33
HO 3.42
MOD 3.46
DfT 3.47
BIS 3.5
DEFRA 3.5
DfE 3.5
MoJ 3.5
FCO 3.67
HMRC 3.67
DoH 3.71
DfID 4
DECC 5

But of course the first and last in class are only there because they’ve just managed one project which went well (or badly) respectively.

Interesting, if we perform an ANOVA on this, taking the scores as continuous, then we wouldn’t be able to conclude that there are significant differences in departments (F(18,151)=0.613; p = 0.885).*

Given the strong idea of the generalist civil servant, that’s perhaps to be expected. But these scores are definitely going to be a useful resource for future students of public administration who might be able to coax a bit more out of the data.

* This is also true if you run an ordered probit.

Italian polling update, May 2013

May 19, 2013

Graphs below. Click on the links to show trend-lines for different parties.

PDL | PD | M5S | Lega | SEL | Scelta Civica

Infrequently asked questions

Where do these polling figures come from? Here and here.

What are these trend lines? They’re estimates from a model which treats latent party support as something which evolves smoothly over time, and is made manifest through particular potentially biased polling snapshots.

Why are some trend lines way above the polls? Evidence from the last elections showed polling companies consistently under/over-estimated some parties. These biases are included in the model.

How long might a Letta government last?

April 30, 2013

tl:dr version: a standard model of cabinet duration predicts the Letta government should last about 400 days.

Enrico Letta’s government was supposed to be a governo di scopo — a government that would take a number of targeted measures to reduce the cost of politics and increase the ease of governing.

Letta’s address to the Camera yesterday promised much more than that. This was true even for matters of institutional and electoral reform: the bicameral commission on constitutional reform — the fourth in thirty years — would take eighteen months (or rather, Letta would step in and possibly dissolve parliament if it hadn’t completed its work by then).

Given the ambitious nature of Letta’s announced programme, it’s fair to ask: how long might such a government last?

I’ve made a number of predictions about government duration in the past. All of these predictions have been based on statistical models, and some of them have performed reasonably well (Berlusconi). Here are some of the time-varying factors we can include in the model, which is taken from Strøm, Kaare; Müller, Wolfgang C. and Bergman, Torbjörn, eds. (2008). Cabinets and Coalition Bargaining: the Democratic Life Cycle in Western Europe:

Majority government:
the cabinet has a clear majority, so that works in its favour;
Minimal winning:
the cabinet is not minimal winning, because it includes a surplus party (Scelta Civica), which does make it…
Minimal connected:
the cabinet is ideologically connected (i.e., there are no gaps when the parties are lined up left to right)
Maximum Banzhaf score:
the cabinet includes the party with the largest Banzhaf score
Coalition:
it’s a coalition, rather than a single-party government, which counts against it
Eff. num. parl parties:
here, I’ve taken the effective number of parties in Camera, at 3.51 (but you could take the number in the Senate, or 3.92)
Conservative:
conservative parties don’t have a majority (conservative governments are longer-lived)

Add to this a number of factors which are constant (Opposition influence, positive parliamentarism, cabinet unanimity, PM dissolution powers (or lack thereof), bicameralism, lack of semipresidentialism), and what kind of prediction do we get?

The figure below plots the predicted probability of survival for days after formation. The probability dips below 0.5 after 396 days — which means that we should predict Letta’s government falling at the end of May next year. If we bear in mind that the 2014 European Parliament elections will, shortly after that point, provide a useful signal of parties’ electoral support, we might expect the government to fall after that point.

letta_durat

Note that the definition of cabinet termination used in the academic literature includes changes of PM and changes of party composition. A change of parties in the government — due to a PD split or Scelta Civica withdrawing — means a `new’ cabinet. Note also that the model doesn’t tell us anything about the causes of termination — the approach is to assume that causes come along (`events, dear boy, events’) and structural attributes modify governments’ ability to weather them.

R source code available as a GitHub Gist.

Update: This Oxford Analytica talk with David Hine gives slightly different estimates: 50% probability lasting until autumn, and only 20 to 25% chance of lasting until next spring. The reasoning is that Berlusconi will pull the plug as soon as he thinks that the gap between PDL and PD in the polls is sufficient to win a majority.

Ages of Italian deputies from 1946 onwards

April 28, 2013

One of the more benign consequences of having being invaded by Napoleon lies in generally having very good administrative records in certain areas. This is certainly true of the Italian parliament, which has a wonderful collection of linked data available to download.

I’ve spent too great a part of my day getting to grips with querying the SPARQL endpoint in order to find out about the ages of Italian legislators over time. The effort spent on learning SPARQL somewhat exceeds the reward in terms of the graph below, but still, blah blah blah transferable skills blah blah blah semantic web blah.

Anyway, here’s a plot which shows the mean and median ages of legislators from the constituent assembly to the 16th Legislature (the one which recently ended rather than the one which was recently elected), upon the start of their mandate.
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Electoral reform in Italy: what’s the PD’s current proposal?

April 25, 2013

If the Letta government is confirmed next week, it will have to reform the electoral system, either by reforming the electoral law, or by amending the Constitution to end Italy’s perfect bicameralism, whereby the government must have the confidence of both the Chamber and the Senate.

The PD’s current proposal for electoral reform, presented at the end of last month, is a resubmission of the proposal they made during the last parliamentary term. It proposes the following for the Camera:

  • 433 single-member districts, elected in two rounds if no candidate wins 50% in the first round, with all candidates polling over 10% progressing to the second round
  • 173 seats allocated using party-list proportional representation using the existing 26 circoscrizionali.
  • 12 seats allocated in a national constituency using the vote totals for party lists
  • A strong link between the two tiers: voters will only have one vote, which will be valid for both single-member and proportional tiers
  • Compensatory allocation of seats in the proportional tier: votes cast for a party in the single-member districts will be subtracted from their total before seats are allocated in the proportional tier.

For the Senate, the proposal is similar, except that 216 seats are elected in single member districts, and the remaining 93 seats are allocated using party-list proportional representation in the regions.

This is similar to the system used between 1994 and 2001, in that it is a mixed-member proportional system.

It is different, and more majoritarian in its likely effects, in that (a) it is harder for parties to avoid their votes being subtracted in the proportional element (there are no problems with the scorporo), and (b) the allocation of seats in 26 circoscrizioni creates a very high effective threshold.

It is different, and less majoritarian in its likely effects, in that (a) the two round system allows small parties to either try their luck in the first round, and possibly sneak through to the second round, or to negotiate stand-down pacts with other bigger parties and secure seats that way.

If, as Napolitano’s wise men have suggested, the size of both chambers must be reduced, then this system will become even more majoritarian in its likely effects.

Of course, just because the PD has proposed this reform does not mean that any eventual reform will bear any relationship to this proposal.

The formation of theLetta government: is 60-odd days too long?

April 24, 2013

Suppose the Letta government receives a vote of confidence next Monday. That will mean that the coalition took 63 days to form, counting from the day of the election. Is that more than might reasonably have been expected?

If we use Sona Golder’s data, then we can say that it’s certainly more than the average for Western Europe (23 days), and more than the average for Italy (29 days). It’s certainly much more than the average for post-electoral formation exercises in Western Europe (12 days).

One response to that is to say that this time round was different. We can use Golder’s Cox survival model to make a prediction based on specific features of Italy in 2013. The main features are:

  • the number of legislative parties: here, I’ve taken the effective number of parties in the Senate (4.29)
  • the degree of polarization: here, lacking a left-right position for the M5S, I’ve taken the mean for Italy
  • positive parliamentarism: governments must face an investiture vote
  • continuation rules (governments can continue in office during electoral periods): Golder has Italy as lacking a continuation rule, strangely, but I’ve followed her usage
  • majority party: no majority party here.

With this set of features (and ignoring interactions with time necessary to maintain the proportional hazards assumption), we’d predict that the median time to formation would be 33 days, with 95% confidence interval of [30,40].

So government formation this time round was almost 100% longer than we would have predicted. Why?

Two obvious suggestions: first, a President had to be elected. Parties had to negotiate on two levels. Second, there was a new anti-system party. Ascertaining that party’s intentions took time.

R code here.

 
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