Airbus vs. Boeing, comparison of market forecasts (2016)

Last week, on the first day of Farnborough air show, Airbus released the new figures of the 2016-35 Airbus’ Global Market Forecast (GMF, PDF 2.6 MB). This is good news, as it did so at the same time as Boeing released its Current Market Outlook (see a post here about it) and before it used to do so in September.

In previous years, I have published comparisons (1) of both Airbus’ and Boeing’s forecasts (Current Market Outlook, CMO, PDF 4.1 MB). You can find below the update of such comparison with the latest released figures from both companies.

Comparison of Airbus GMF and Boeing CMO 2016-2035.

Comparison of Airbus GMF and Boeing CMO 2016-2035.

Some comments about the comparison:

  • Boeing sees demand for 12% more passenger aircraft (excluding regional a/c) with a 10% more value (excluding freighters). The gap is higher than in 2015 (similar to 2013 and previous years).
  • In relation to last year studies, Airbus has increased demand by ~650 aircraft whereas Boeing has increased by 1,670.
  • Boeing continues to play down A380 niche potential (66% less a/c than Airbus’ GMF).
  • Both companies’ forecast for the twin aisle segment is nearly identical: ~7,600-7,700 aircraft (Airbus sees demand for about a 100 less aircraft than Boeing, mainly due to Boeing increased figures in relation to 2015). The mix between small and intermediate twins varies, ~300-400 units up and down. However, Boeing’s wide-bodies mix is not to be taken as engraved in stone, see the erratic trend in the last years here.
  • On the other hand, Boeing forecasts about 4,600 single-aisle more than Airbus (the gap has widened in 800 units this year). Boeing doesn’t provide the split between more or less than 175 pax capacity airplanes since its 2015 CMO, this year Airbus hasn’t included it either.
  • In relation to traffic, measured in terms of RPKs (“revenue passenger kilometer”), that is, the number of paying passenger by the distance they are transported, they see a similar future: Airbus forecasts for 2035 ~16.0 RPKs (in trillion, 4.5% annual growth from today) while Boeing forecasts 17.01 RPKs (4.8% annual growth).

The main changes from last year’s forecasts are:

  • Both manufacturers have increased their passenger aircraft forecast in between ~650-1,670 a/c.
  • Both manufacturers have increased the volume (trn$) of the market in these 20 years, by about 300-400 bn$.

Some lines to retain from this type of forecasts:

  • Passenger world traffic (RPK) will continue to grow about 4.5% per year (4.8% according to Boeing). This is, doubling every ~15 years.
  • Today there are about 18,019 passenger aircraft around the world (according to Airbus; 18,190 in Boeing’s CMO), this number is about 700 a/c more than the year before (4% increase) and will more than double over the next 20 years to 37,708 a/c in 2035 (39,750 as seen by Boeing, excluding regional jets).
  • Most deliveries will go to Asia-Pacific, 41% or 13,239 passenger aircraft (according to Airbus).
  • Domestic travel in China will be the largest traffic flow in 2035 with over 1,600 bn RPK (according to Airbus (x 3.7 times more than today’s traffic), or 1,897 bn RPK according to Boeing), or 11% of the World’s traffic.
  • About 12,830 aircraft will be retired to be replaced by more eco-efficient types.
Passenger traffic growth vs. global GPD growth.

Passenger traffic growth vs. global GPD growth.

As I do every year, I strongly recommend both documents (GMF and CMO) which provide a wealth of information of market dynamics. This year, Airbus included as well an excel file with its data, find it here [XLS, 0.3 MB]

(1) Find here the posts with similar comparisons I made with the forecasts of previous years: 2015, 2014, 2013, 2012, 2011, 2010.

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Review of Boeing Current Market Outlook 2016

Last week, on the first day of Farnborough air show, Boeing Commercial published its yearly update of the Current Market Outlook (CMO) for the next 20 years of commercial aircraft market (2016-2035).

I have just compared the figures for passenger aircraft of the last two years’ CMOs:

CMO 2016 vs 2015 comparison

CMO 2016 vs. 2015 comparison.

Some comments to it:

  • You can see that the total number of new aircraft delivered has slightly increased from 37,130 to 38,690, a 4.2%, which is consistent with the 4.8% traffic increase (1) that Boeing predicts (2).
  • The volume (Bn$) increases by a larger percentage, 7.2% (380Bn$) up to 5.66 Trn$… this is due mainly to the increase in (3):
    • single-aisle aircraft expected sales in volume (8%, +230M$) and aircraft (+1,410), and
    • small wide-body segment with 220 more aircraft (+5%) and an increase in volume of 80 Bn$ (+7%).
  • Three years ago, I wrote about a sudden change between CMO 2013 and CMO 2012 of the mix in wide-bodies; in this respect, CMO 2015 is consistent with last year’s one, showing simply an  increase in demand for both sub-segments.
  • It is interesting to note how Boeing continues to downplay the large aircraft segment at the moment when a A380 is discussed, however this year’s figures are increased in relation to CMO 2014 in terms of both aircraft and volume.

This year study’s figures and presentation focus again on single-aisle (737 MAX 8, “Medium-size aircraft are at heart of single-aisle market“) and small wide-bodies (787, “opening new markets”), the products to be pushed by the sales force.

Find below the nice infographic [PDF, 464 KB] that the guys from Boeing have put up together:

Boeing Commercial Aviation Market Forecast 2016-2035 infographic.

Boeing Commercial Aviation Market Forecast 2016-2035 infographic.

As always, I recommend going through the CMO, as you can learn a lot about the business: from global numbers, to growth, traffic figures, fleet distributions, forecasts, etc… You may find the presentation [PDF, 4.7 MB], a file [XLS, 0.6 MB] with all the data or the full CMO report [PDF, 4.1 MB].

This year again, together with the CMO, Boeing provides two interesting papers from a couple of years ago: Key Findings on Airplane Economic Life [PDF, 0.3MB, dating from August 2013] and A Discussion of the Capacity Supply -Demand Balance within the Global Commercial Air Transport Industry [PDF, 0.6MB, dating from August 2013].

(1) Traffic increased measured in RPKS (revenue passenger kilometers) in billions.

(2) These two ratios, 4.2% fleet demand and 4.8% traffic growth, point to an implicit increase in the average size of the aircraft in fleet and / or a higher utilization of the aircraft (higher availability).

(3) These two segments (single-aisle and small wide-body) saw as well the largest increases in number of aircraft and volumes in the CMO of 2015 in relation to 2014.

(4) Find the reviews I wrote comparing 2015 CMO with 2014 CMO2014 CMO with 2013 CMO and 2013 CMO with 2012 CMO.

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What I Talk About When I Talk About Running (book review)

MurakamiHaruki Murakami is Japanese writer of World fame. Murakami happens to be a consistent runner since the early 1980s, about the same time as he went full-time with the process of becoming a professional writer. “What I Talk About When I Talk About Running” (2007) is an autobiographical book in which the author not only explains what running means to him but also how he turned from running a bar to becoming a writer, from being a rather sedentary person to training about 60 km weekly, running at least a marathon a year for over 25 years, etc.

Murakami draws some parallels between running and writing:

  • Stop right at the point when you feel you can do more, both when writing and running. As he says to keep going you have to keep the rhythm, the most difficult part being starting and setting the pace.
  • The most important qualities for a novelist after talent: focus (“the ability to concentrate all your limited talents on whatever’s critical at the moment”) and endurance. These two can be applicable to practically every profession (e.g. “The Focused Leader” by Daniel Goleman at HBR).

There are some other passages that drew my attention while reading the book that I want to share:

Nobody remembers what stupid things I might have said back then, so they’re not about to quote them back at me”. (Think now about today’s social media)

“I’m struck by how, except when you’re young, you really need to prioritize in life, figuring out in what order you should divide up your time and energy. If you don’t get that sort of system by a certain age, you’ll lack focus and your life will be out of balance.”

“Have you ever run sixty-two miles in a single day? […] I doubt I’ll try again, but who knows what the future may hold. Maybe someday, having forgotten my lesson, I’ll take up the challenge of an ultramarathon again” (No need to tell me that)

“[…] Thus the seasons come and go, and the years pass by. I’ll age one more year, and probably finish another novel. One by one. I’ll face the tasks before me and complete them the best I can. Focusing on each stride forward, but at the same time taking a long-range view scanning the scenery as far ahead as I can. I am, after all, a long-distance runner.”

If you are a frequent runner it is quite easy to relate to the author in several passages (1). In my case, it has been from the races he has taken part in (New York or Athens marathons), to the experiences lived in a 100 km ultra marathon, the thoughts or lack of them while running, the balance found in training, etc.

The book is rather light (about 180 pages in the version I have) and makes for a good reading, however, if he ever wins the literature Nobel prize it won’t be for this book.:-)

(1) I guess that for a professional writer there may be several parts easy to relate to as well.

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A380: 747 production rate throughout history

Back in 2013, I wrote a post comparing the orders of the Airbus A380 compared to those of the Boeing 747 Jumbo taking different references for the comparison. As I explained then, the idea for the post was triggered by a conversation with my friend Jose. A year later, in 2014 I wrote an update of that comparison (here).

This post is yet again triggered by another point raised by Jose (1) in another conversation a few months ago, when Airbus announced that it has reached the unit break even point for the A380 programme in 2015 with 27 deliveries. In that news it was already mentioned that the company sought to lower the number of aircraft for breaking even on any given year. The point became more relevant since Airbus confirmed, this week at Farnborough air show, that it would slow down its production pace to a monthly rate of 1 aircraft per month from 2018.

In our conversation, Jose looked at how the Boeing 747 production rate had evolved throughout history. Taking the figures from the 747 article in the Wikipedia (here), you can see the results in the graphic below. The bars show yearly deliveries. The lines the monthly production rate and its 3-year rolling average. I took this average to smooth the curve even if it is very similar to the year-by-year data (1).

747 rate

Some comments on the 747 production rates (taken from its yearly deliveries):

  • The average monthly production rate since its first delivery back in 1969 has been: 2.7 airplanes per month (above 2.25 for A380 in 2015).
  • During the first about 30-35 years (till ~2002-3) the rate fluctuated between 2 and 5 deliveries per month.
  • Since 2003 the rate has averaged 1.3.
  • For the first 10 years of the 747 programme (as the A380 is just about to complete that first decade of deliveries), its production rate averaged 2.9 aircraft per month.
  • Even if not reflected in the graphic, for information, Boeing has announced that it would decrease production rate down to 0.5 airplanes per month (6 a year) from September 2016.

Time will tell if the rate for the A380 is sustainable and whether its market rebounds.

(1) I took 3 years to make the rolling average as the fact of confirming in 2016 a delivery rate decrease to be effective from 2018 may give an idea of lead times.

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The penalty shoot-outs are a lottery

Recently, the 2016 UEFA Champions League final (between Real Madrid and Atletico de Madrid) was decided in a penalty shoot-out, so was the 2016 Copa America Centenario final (Chile – Argentina) and so have already been a couple of matches in the round of 16 and quarter finals of the ongoing UEFA Euro 2016 (Switzerland – Poland and yesterday’s Poland-Portugal). You could expect one or two more matches in that competition to be decided in such a way.

“The penalty shoot-outs are a lottery”

This is a mantra repeated once and again each time the extra time of a football match comes to an end and the score is still a draw. Yet penalty shoot-outs are not a lottery. However, asking TV or radio football commentators to describe this aspect of the game as “two-person zero-sum game that meets von Neumann’s Minimax theorem” would be too much.

Years ago, while reading the book “Soccernomics“, by Simon Kuper and Stefan Szymanski (book review here), I came to know a couple of papers on penalties and penalty shoot-outs published by the Spanish economist Ignacio Palacios Huerta (at the London School of Economics).

Penalties

In a first paper, Professionals Play Minimax (2002, and its annex) [PDF, 335 KB and 342 KB], by analyzing over 1,400 penalty kicks, he came to confirm that professionals do play Minimax, a game theory rule decision model in which they try to minimize the worst outcome not knowing the strategy of their opponent.

The object of the paper itself is to try to find a natural setting in which von Neumann’s theorem implication can be tested. Penalty kicks turns out to be such a natural setting, the reasons enabling the game to be so are: there are few strategies available to the players (basically shooting left or right for the kickers, or jumping to his left or right for the keepers), it is a two-player zero-sum game and the outcome of the game (goal or no goal) is immediate after a strategy is chosen.

Studying those over a thousand penalties and in particular those of 42 players (kickers and keepers) who have been each one involved in over 30 penalties in the time span of the study (1995-2000), the author came to the following findings:

  • Kickers have practically the same probability of scoring with different mix of strategies (being a strategy alternating between shooting left or right by a given proportion).
  • Players are capable of generating truly random sequences of choices (left – right). This is remarkable, as humans, when asked to produce a random sequence, normally over do it and shy away from what would be truly random.
  • Some figures: players shoot to their natural side (with the interior of the feet, shooting left to a right footed) just above 50% of the times, keepers jump to the natural side of the kicker slightly more often.
  • When the keeper “guesses” the side to which the kicker is shooting, the scoring probability greatly differs depending on whether it was the kicker’s “natural side”, 71%, or the non-natural side, 55%. When the keeper jumps to the wrong side the scoring probability is about 95% with no big difference between natural or non-natural side.
  • During a match the average scoring rate is about 80%, with the rate decreasing as the match comes to an end (73% for penalties in the last 10 minutes).
  • Some players during the years of the study (1995-2000) had significantly better scores; in particular Mendieta (91% and no matter whether he kicked to his natural (68% of the times) or non-natural side (32%)), Del Piero and Juninho (especially strong on their natural side (94%) and above average in their non-natural (87%)) or Bergkamp (91% and 88%).
  • Strategies between players varied greatly. As I said Mendieta had a 68/32 (natural / non-natural), whereas Batistuta had a 81/19 and Baggio a 45/55, all with above average scoring success. Other players like Zidane, Mihajlovic or Chiesa managed an undistinguishable 50/50.

See a couple of interesting tables below:

Minimax table 1

Minimax table 2

Even more interesting is his second paper.

Penalty shoot-outs

In a second paper, “Psychological Pressure in Competitive Environments: Evidence from a Randomized Natural Experiment” (2009, with Jose Apesteguia) [PDF, 342 KB], Palacios Huerta wants to find out how emotions play a major effect on performance and to do so he takes a look at penalty shoot-outs from major football competitions.

For this study he reviewed over 2,800 penalty kicks in about 270 penalty shoot-outs. He divides the observations in two blocks, before and after FIFA changed the rules governing the shoot-outs in 2003. Before that date, the team of the captain winner of a toss of a coin started kicking first; after the change in the rules, the captain winner of the toss of a coin chooses which team kicks first.

Before 2003, the fact of kicking first or not was random, and after 1,343 kicks in 129 shoot-outs, the authors found out that the first in kicking in the sequence win the penalty shoot-out 60.5 percent of the time. (1)

As part of his study, Palacios Huerta made a survey questioning over 200 football players and coaches in Spain, professionals and amateurs, what would they choose if they had won the toss of a coin to decide which team kicks first in a penalty shoot-out. The results offer not doubt: over 95% of the cases chose to kick first. When asked why they would choose that option they indicated “to put pressure on the rivals”.

Experience matched the survey. After the change of FIFA rules in 2003, Palacios Huerta gathered data of another 140 penalty shoot-outs up to 2008 (just before writing his paper). Those were the first 140 penalty shoot-outs in which the winner of the toss of a coin had to choose whether he wanted his team to kick first or his opponent to kick first. In just a single case did the winner of the toss of a coin choose to let the opponent to kick first: Gianluigi Buffon playing for Italy the quarter-final of the Euro cup in 2008 against Spain, with the result that Spain won the penalty shoot-out and went to win the Euro, starting a streak of 3 consecutive major competitions at national level (Euro 2008, World Cup 2010 and Euro 2012).

Take a look at the following graphics and tables that let you read how the probabilities of scoring each penalty in a shoot-out evolve depending on previous outcomes (whether the team is behind, even or ahead) and the probability of winning the shoot-out (hence qualifying to the next phase or winning the competition) evolve.

ScoringProbabilitiesperRound

PenaltyShootOut_ScoringProbabilities

I highlighted in the previous table in blue and yellow the scoring probability for each kick and the winning percent of the shoot-out for a shoot-out in which both teams go about scoring each of the penalties. It is interesting, if not dramatic, to see how while the scoring probability for the first team is always between 72 and 78% (2), for the second team it drops from 82% to 62-66% for rounds 3 to 5. Similarly, the winning probability decreases for the second team down to 21-23% just before attempting kicks 3 and 4 if all previous penalties have been scored.

See below that 2008 penalty shoot-out between Spain and Italy.

After having commented on these two papers and its conclusions, let me share a few comments and anecdotes:

MILAN, ITALY - MAY 28: Cristiano Ronaldo of Real Madrid scores the winning penalty during the UEFA Champions League Final match between Real Madrid and Club Atletico de Madrid at Stadio Giuseppe Meazza on May 28, 2016 in Milan, Italy. (Photo by Shaun Botterill/Getty Images)

MILAN, ITALY – MAY 28: Cristiano Ronaldo of Real Madrid scores the winning penalty during the UEFA Champions League Final. (Photo by Shaun Botterill/Getty Images)

Toss of a coin. Both 2016 Copa America Centenario final and UEFA Champions League final were won by the team which kicked the first penalty, Chile and Real Madrid, respectively. In the draw, using the toss of a coin, to decide which team kicked first Chile chose to kick first (see here the video). However, in the Champions League final, Atletico de Madrid’s captain Gabi chose to let Real Madrid kick first. Apparently, he chose that as they had kicked second in the round of 16 of that same competition against PSV Eindhoven and passed. Somehow he tried to repeat the sequence thinking that this would bring them luck. Well, with that decision he put his team against about 60-40% odds backed by over 30 years of recorded experience and about 270 shootouts. Not a clever move. See this article “La buena mala suerte del Churu” by Manuel Jabois discussing this toss of a coin (in Spanish). See here the video.

“[…] we find a systematic first-mover advantage. Further, professionals are self-aware of their own psychological effects and, when given the chance, they rationally react by systematically taking advantage of these effects.” (Palacios-Huerta)

1024x1024As reflected above, in the paper, Palacios-Huerta indicates that between 2003 and 2008 only once in 140 samples did the winner of the toss chose to let the opponent kick first. That is why it was striking what Gabi did and why it called the attention of some football fans. Well, yesterday, during the first match of the Euro 2016 quarter finals between Poland and Portugal, we had yet another such example, another anomaly. This time it was Robert Lewandowski, the Polish captain, the perpetrator. He won the toss of the coin and chose that Portugal kicked first. I can imagine how Cristiano Ronaldo might have felt at that moment, the second time in just 6 weeks that he was being handed such a present. Portugal won the shoot-out.

Palacios Huerta and other analysts receive requests for dedicated reports about kicking patterns, records and data of different teams when playing knock-out phases. In Soccernomics, Simon Kuper and Stefan Szymanski, describe how that happened during the 2008 UEFA Champions League final between Manchester United and Chelsea. Palacios Huerta had given Chelsea some tips on Manchester kickers and keeper (van der Saar): “Van der Sar tends to dive to the kicker’s natural side”, “most of the penalties that Van der Sar stops are mid-height, thus is better to shoot low or high”, “if Cristiano Ronaldo stops half-way in the run-up to the ball chances are 85% that he shoots to his natural side”…, it is quite interesting to actually see that penalty shoot-out and how the different players acted. See below the video. Apparently Van der Saar saw how Cech, Chelsea’s keeper had some paper in his hands and also noticed how kickers were shooting to their non-natural side, until at the 7th penalty (~9’30” in the video) he defies Anelka by pointing to Anelka’s non-natural side, like saying “I know you have the tip to kick there”, then…

For the record, the final was won by Manchester, first in kicking.

Finally, ever since coming to know all this information I have enjoyed penalty shootouts more than before. I now entertain myself seeing the strategy taken by the keepers and kickers, whether the keeper jumps to the natural side of the kicker more or less than in 60% of the shots, if he changes his strategy depending on whether the kicker is left or right-footed, whether kickers shoot more or less than 60% of the shots to their natural side, etc.

Les grandes personnes aiment les chiffres“, Le Petit Prince.

(1) At the time of the Copa de America Centenario final, the Spanish journalist Alexis Sanchez (better know by his profile @2010MisterChip), expert in providing all kind of football statistics, tweeted that Chile, being the first in kicking in the penalty shootout against Argentina had a 55% chance of winning the tournament. Thus, it may be the case that he has a larger (not public) database including more penalty shootout.

(2) Note how probabilities in shoot-outs decrease from the average of 80% of penalties during the match.

 

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El sistema de reparto D’Hondt es justo

“El sistema de reparto D’Hondt es justo”

Un clásico de los análisis tras unas elecciones es criticar el sistema de reparto o “ley” D’Hondt (1), y sin embargo, ésta fue la conclusión, contraria a la crítica general, a la que llegaba un amigo después de que hace un par de semanas pasamos un rato haciendo los números y comparando cómo era la distribución de escaños mediante dicho sistema de reparto y un reparto proporcional. (2)

Para ello, cogimos el ejemplo de la circunscripción de la provincia de Sevilla en las elecciones generales de 2011 (3). Sevilla, entonces y a día de hoy, elige 12 diputados. En 2011 y con el sistema de reparto D’Hondt los resultados fueron los siguientes:

  • PSOE: 6 escaños.
  • PP: 5 escaños.
  • IU: 1 escaño.

Para repartir escaños según el sistema D’Hondt se dividen los votos de cada uno de los partidos, que haya superado el mínimo establecido (3% por circunscripción), entre los números enteros 1, 2, 3… y se van adjudicando escaños a los cocientes mayores. En el caso de Sevilla en 2011, el último escaño asignado fue el sexto al PSOE, para un cociente de 73.610 votos. Todo ello se puede ver en la tabla de debajo.

Para llegar a lo que sería un reparto proporcional habría que dividir el número total de votos válidos entre el número de escaños (12 en el caso de Sevilla) y se obtiene el ratio “Votos / escaño”. Después, habría que dividir el número de votos de cada partido entre dicho ratio “Votos / escaño”. Del resultado, se separa del cociente la parte entera de la parte decimal (resto). Los enteros se traducen en escaños directamente, mientras que los escaños pendientes se adjudicarían a los restos superiores. En este caso irían a PP y a UPyD.

Es ese escaño que se adjudica a UPyD, en vez de al PSOE (que sería el sexto que tiene según el sistema D’Hondt), el que hace que se diga que el sistema D’Hondt perjudica a los partidos pequeños, que favorece mayorías, que no es proporcional o que es “injusto”. Mientras que las tres primeras afirmaciones son factuales, la cuarta (“es injusto”) es un juicio de valor. Para valorar este juicio se puede hacer otro pequeño ejercicio, consistente en calcular los ratios de votos obtenidos entre escaños adjudicados por un sistema u otro.

Haciendo dicho cálculo se obtiene que el ratio para el PSOE con los 6 escaños obtenidos según el sistema D’Hondt (73.610) es superior al que hubiese obtenido UPyD de haber obtenido un escaño según un sistema proporcional (58.415). Por tanto, un observador imparcial podría llegar a la conclusión de que, de hecho, el sistema D’Hondt es justo.

DHondt vs proporcional

(1) En círculos donde la gente ha hecho o leído análisis más profundos, se apunta a la división en circunscripciones y los diputados asignados a cada una de ellas.

(2) En la página web de la Wikipedia que explica el sistema D’Hondt también se ofrece una comparación entre dicho sistema y el sistema de reparto proporcional o método del resto mayor.

(3) Este ejemplo permite valorar los sistemas de reparto sin el calor de la actualidad. Invito al lector a coger cualquier otra provincia, los resultados de las elecciones del 26J de 2016 y repetir el ejercicio. Los resultados de Sevilla se pueden ver en este enlace de la web del Ministerio del Interior.

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Mi pronóstico de las elecciones generales de España del 26J 2016

De nuevo, con la ocasión de las elecciones generales en España el próximo domingo 26 de junio, quería aprovechar para hacer un pronóstico de las mismas como ejercicio de aprendizaje (1) y para ver si el acierto que tuve con las del 20 de diciembre (2) fue flor de un día.

La metodología es simple: me he construido una pequeña base de datos con los porcentajes de voto por partido y provincia a partir de los resultados de las últimas 2 elecciones generales (2015 y 2011) y de las últimas 2 elecciones autonómicas (2015, 2012-2011). Y, a partir de esos resultados, viendo las tendencias, he intentado pronosticar el porcentaje de voto de cada partido en cada provincia, lo que después, haciendo uso del sistema de reparto D’Hondt, proporciona los escaños.

Para hacer ese pronóstico me he basado principalmente en mi “gut feeling” y para pocas provincias he mirado a ver qué decían las encuestas (y en algunos de esos casos ha sido para reafirmarme en mis números contra los otros… veremos). Debo aclarar que el ejercicio no se trata de una encuesta (no he ido llamando a nadie), ni de una media de encuestas (3).

Generalmente, cuando una encuesta a nivel nacional nos dice “el PP va a conseguir un 29% y entre 118-125 escaños” nos da un resultado que se compone de la suma de muchas provincias, que no nos sirve para ver qué va a pasar en nuestra provincia en particular. El CIS, sin embargo, ofrece una encuesta con más de 17 mil encuestados, donde indica su estimación de reparto de escaños por provincias y de porcentajes de voto globales (4). Y esa visión, mucho más completa, es la misma que quiero replicar con mi pronóstico.

Como recordatorio: en España tenemos 52 circunscripciones (provincias más Ceuta y Melilla) que aportan desde 1 diputado (Ceuta y Melilla) a 36 (Madrid) (5). El total son 350 y la mayoría absoluta se consigue con 176 escaños.

Dicho esto, la tabla y la gráfica siguientes resumen todo el trabajo:

Como quedaría el arco parlamentario.

Cómo quedaría el arco parlamentario.

Pronóstico detallado.

Pronóstico detallado.

Esta vez quería dejar, acompañando el pronóstico en escaños de arriba, también la tabla origen con los porcentajes debajo (para los 4 grandes partidos). Esta tabla, en combinación con la de escaños, permite al lector ver cómo de cerca están uno u otro partido según el pronóstico, y qué porcentaje de voto más tendría que sacar un partido para obtener ese último escaño que se lleva otro. (6)

Porcentajes pronosticados por provincia.

Porcentajes pronosticados por provincia.

Una vez compartido el pronóstico, no voy a hacer ningún análisis del mismo, dado que puede estar muy o poco equivocado; mejor esperar a tener los resultados reales.

(1) Ya en 2011, tras las elecciones generales hice el ejercicio de repartir con distintos métodos (proporcional vs D’Hondt, circunscripciones provinciales vs única…) y el ejercicio me resultó útil.

(2) Ver aquí un análisis de lo acertado de mi pronóstico para el 20D de 2015 con los resultados finales.

(3) Ver por ejemplo los que hace Kiko Llaneras aquí.

(4) Ver más abajo las tablas del CIS. La fuente aquí.

(5) En estas elecciones León pierde un escaño en favor de Valencia.

(6) Esta tabla puede tener muchos errores parciales (pequeñas desviaciones del porcentaje del resultado) sin que ello necesariamente haga que el pronóstico de escaños sea incorrecto.

CIS 26J tabla escanos

CIS 26J tabla resumen

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