Voter Turnout Chile - 2013 Update

We had covered in a previous post the development of voter turnout in Chile since 1870. In this post we update the time series to include the recent elections.

First we have update the population time series from INE and calculated the voting age population as 40% of the 15-19 age band plus all the age band 20+. The result is graphically depicted as follows:





















The ratio of the voting age population as a percentage of total population has increased from 64% in 1990 to 74% in 2013 and is expected to further increase at a somewhat reduced pace to 76% in 2020. It should be noted that the voting age population is not identical with the population permitted to vote as some segment of the voting age population (foreigner with less than five year of residency, persons with criminal records of certain characteristics etc) are not allowed to vote.

Separately, it is well known that the Servel voting registry is inflated and that the Census data contradicts the INE projection. We will come back to this in a future post.

Below updated table of (i) population, (ii) voting age population, (iii) votes and (iv) valid votes since 1870. The sources have all been disclosed in the earlier post.


































































And the voter turnout in graphical format.

Especially the first round of the presidential election seems to be in line with the previous compulsory voting record.

Impact of 1930´s depression on Chile´s Economy

Just re-read a chapter of Reinhart & Rogoff´s "This Time is Different: Eight Centuries of Financial Folly" (obviously I´m aware of the calculation errors, in my view it is still a tremendously valuable book).

The following graph (on page 267) describes the collapse of exports 1929 -1932. From a Chilean perspective the magnitude of the drop is particularly impressive.

Male/Female Ratio for Major Countries

For major countries, the total population and the male/female ratio has been obtained from UN´s: World Population Prospects: The 2012 Revision (dated 2013)

Major countries has been somewhat arbitrarily defined as:
- G20 member
- OECD member above 5 million population
- UN member abover 50 million

Graphically depicted this look as follows (red female surplus, blue make surplus):

The corresponding data in table format:

Copper Aluminium Price Ratio

We had looked at the copper to aluminium price ratio earlier and noted that it had reached a historical maximum. Interestingly the price ratio has more or less less stayed above 4 and recently even moved to 4.3 as can be seen in the following graph. The data has been obtained from OFDP (Open Financial Data Project).

Admittedly, this price development has not been in line with our expectations.

Proportional Voting Systems

There are a handful of different proportional voting and allocation systems, specifically

Quota Methods

The Hare Niemayer or Vinton is the largest remainder method, which is sometimes generalized with the use of different quotas:

The largest remainder method requires the numbers of votes for each party to be divided by a quota representing the number of votes required for a seat (i.e. usually the total number of votes cast divided by the number of seats, or some similar formula). The result for each party will usually consist of an integer part plus a fractional remainder. Each party is first allocated a number of seats equal to their integer. This will generally leave some seats unallocated: the parties are then ranked on the basis of the fractional remainders, and the parties with the largest remainders are each allocated one additional seat until all the seats have been allocated. This gives the method its name.

Hare quota (also called Hamilton): votes/seats 

Droop quota: 1+votes/(1+seats)

Hagenbach-Bischoff quota: votes/(1+seats)

Imperiali quota: votes/(2+seats)

The quota-method can also be used in an iterative approach, which mostly yields in the same result. An other alternative is too allocate all unallocated seats to the largest party.

Divisor Methods

The highest quotient and highest averages methods is defined as follows:

The highest averages method requires the number of votes for each party to be divided successively by a series of divisors. This produces a table of quotients, or averages, with a row for each divisor and a column for each party. The n'th seat is allocated to the party whose column contains the n'th largest entry in this table, up to the total number of seats available

The series of devisors are defined as follows (D'Hondt is also called Jefferson in the US and Hagenbach-Bischoff in Switzerland, Sainte-Lague is also called Webster in the US:

Generally D`Hondt (round-down) favours large parties while Adams (round-up) favours smaller parties while Sainte-Lague (artithmetic avergae), Hill Huntington (geometric mean) and Dean (harmonic mean) or generally almost identical in their outcome.

In a future post we will look at the actual implications.

Net International Investment Position (NIIP) 2011

The Net International Investment Position data for 2011 was retrieved from the IMF.

All countries with a (either positive or negative) balance larger than USD 100 billion are shown graphically:

Positive balance countries (data in USD billion). Top 5 are Japan, China, Germany, Switzerland and Hong Kong.

Negative balance countries (data in USD billion). Bottom 5 are United States, Spain, Australia, Brazil, Italy (surprising to see commodity exporters like Australia and Brazil with such negative balances).

Complete table (data in USD billion). The data is not consistent in itself as the total is about USD 1.5 trillion negative (a number of countries have no data but it is highly unlikely that they would add USD 1.5 trillion).



PS Chile has a balance of negative 24 billion.

Employment Population Ratio 15-64 for OECD and BRICS countries

We have retrieved the employment participation rate from the OECD site and plotted the following five graphs:

• Ranking of countries (all OECD countries with more than 5 million population plus BRICS) by total employment to population rate (15-64 age cohort) in 2011
• Ranking of countries by male employment to population rate (15-64 age cohort) in 2011
• Ranking of countries by female employment to population rate (15-64 age cohort) in 2011
• Ranking of countries by difference of male to female employment to population rate (15-64 age cohort) in 2011
• Change of employment to population rate (15-64 age cohort) between 2011 and 2001 (data for India is not available)

Large (more than 50 million population) OECD countries are colored green, medium (5 to 50 million population) blue and BRICS countries red. Countries are shown with their two digit ISO 3166-1 alpha-2 codes.

Top 3: Switzerland, China, Netherlands

Bottom 3: South Africa, Turkey, India

Top 3: Switzerland, China, Japan

Bottom 3: South Africa, Hungary, Spain

Top 3: Switzerland, Sweden, Denmark

Bottom 3: Turkey, India, South Africa

Top 3: Finland, Sweden, Denmark

Bottom 3: India, Turkey, Mexico

Top 3: Chile, Germany, Poland

Bottom 3: US, Portugal, China

Surprises:

• Switzerland with highest employment to population to population ratios by a wide margin also for females
• Hardly any change in terms of employment to population ratio in Greece or Spain during the last ten years

From Chile´s perspective it is nice to see big improvement in the last ten year, but still much to be done with current ranked in the third quartile in terms of male employment and bottom quartile regarding female employment.

Finally a word of caution: employment data is normally survey based and significant differences with other data sources (say social security) are likely.

Business English

Following a blog post in the Economist, I stumbled across another post from the same publication and finally came across an EF publication which compares English proficiency across many countries. Results are in line with expectation with Scandinavia ranked very high (including the Dutch as honorary Scandinavians) and Central Eastern Europe as high (including also Singapore and Malaysia). Chile is not doing very well, I must say, with very low English proficiency (ranked 39 out of 54).

Copper Price Forecasting (2013 Update)

In a 2012 post we looked at the copper price forecasts of Cochilco since 2005. To do so we looked at the "Informe Trmestral del Mercado de Cobre" which is published on a quarterly basis.

The following graph shows the development of the forecasted copper price (or rather the deviation from the ex-post price) as a function of the number of days before the end of the period for which the forecast was made.

Separately we show an update of the graph we already showed in last year´s post comparing the deviation of the forecasted price made 18 months before the end of the forecasted period with the spot price at the forecasting date.

2012 was a relatively good year with a relatively small forecasting error, undoubtedely assited by relatively low volatility of copper price and the absence of large price movements

Metal and Ore Exports (as a percentage of exports) 1988 to 2010

The Worldbank has nifty page allowing to plot numerous trade related data points:

The World Integrated Trade Solution (WITS) is a software developed by the world Bank, in close collaboration and consultation with various International Organizations including United Nations Conference on Trade and Development (UNCTAD), International Trade Center (ITC), United Nations Statistical Division (UNSD) and World Trade Organization (WTO). WITS gives you access to major international trade, tariffs and non-tariff data compilations:

• The UN COMTRADE database maintained by the UNSD: Exports and imports by detailed commodity and partner country
• The TRAINS maintained by the UNCTAD: Imports, Tariffs, Para-Tariffs & Non-Tariff Measures at national tariff level
• The IDB and CTS databases maintained by the WTO: MFN Applied, Preferential & Bound Tariffs at national tariff level

WITS is a data consultation and extraction software with simulation capabilities. WITS is a free software. However, access to databases themselves can be fee-charging or limited depending on your status. WITS is a system that is still evolving and we will be adding more features. In subsequent releases of WITS we plan to provide additional features including coupling with ITC's MACMAP system.

We used WITS to plot the share of metals and ore exports as a percentage of total exports for the ten largest copper exporters. Zambia followed by Chile and Peru lead this metric through the whole period (1988 to 2010).

Earliest National Day Celebration Events

In case you ever wanted to know which countries celebrate the earliest events in their national holiday, here is a list for those countries commemorating events which occurred before 1800 (source mostly Wikipedia).

Year	Country	Celebrated Event
660 BC	Japan	Coronation Day First Emperor Jimmu
301	San Marino	Independence from the Roman Empire
461	Ireland	Death of St. Patrick
1291	Switzerland	Alliance against the Holy Roman Empire
1492	Spain	Columbus Discovers America
1523	Sweden	Election of Gustav Vasa as King of Sweden
1580	Portugal	Death of National Poet Luís de Camões
1776	United States	Declaration of Independence from Great Britain
1788	Australia	Founding of Sydney
1789	France	Storming of the Bastille
1791	Poland	Constitution of the Polish–Lithuanian Commonwealth

The list does not include sub-national territories where Scotland (70), England (303), Wales (589), Faroe Islands (1030), Minorca (1287), Catalonia (1714) and Sardinia (1794) also celebrate events before 1800.

Apologies if I have missed any event in the above list.

Chilean Lottery (Polla) Numbers for 2011

We looked at the financial numbers for 2011 and 2010 for Polla Chilena, one of the two official lotteries in Chile.

The basic numbers look as follows (in thousand CLP):

* Lottery Revenues can be categorized in the various games as follows (most of the revenues are from traditional lotto):

** From the Payouts there is a 2% fee going to the Handling Agent and a 15% tax on lottery winnings.

*** The Various Beneficiaries are detailed as follows

This gives the following overview on where the revenues go (handling agent fee added to administration cost, all taxes and state beneficiary summed up):

The following comments can be made when comparing these metrics to other lotteries:

• low winner payout (typically in the 40-50% range)
• high administration cost (normally less than 10%)
• high take by the state (normally less than 20%, if that)
• very low distribution to good causes (even when including the amount given to the "Instituto Nacional del Deporte", normally above 30%)

Reader comments as always welcome.

Chile´s Gini Coefficient (calculated from tax records)

Chile tax authority (Servicio de Impuestos Internos, SII) provides an annual statistics of the number of tax payers and taxable income by tax bracket (here).

This information looks as follows (this information includes all types of taxable incomes):

With this information on hand the following Lorenz curve can be constructed, which looks as follows:

Assuming (not entirely realistically) linear income distribution within each tax bracket, the Gini coefficient can be calculated. The following should be noted:

• calculation is based on individuals and not households
• calculation only incorporates taxable income and not other forms of income (i.e. state transfer, tax deductions, undeclared incomes)

Also the Gini coefficient was calculated for the after tax income and assuming the tax intake was equally distributed among all taxpayers after redistribution. The effect is actually minimal, which should not be surprising given that despite high marginal rates (40%) only 0.28% of all taxpayer (24'400 individuals) were paying 58.73% of all income taxes in 2012. This should be kept in mind if higher marginal tax rates would ever be suggested as a policy instruments for higher equality (keeping in mind that the fairest taxes are those with a large tax base but low tax rates).

Interestingly despite the shortcomings of the calculation (see above) the results are close do the numbers published in other sources (0.521 for 2009 according to the Worldbank):

German Billionaires: Data Reconciliation

We  looked at the billionaire's lists available from Forbes and MM (Manager Magazin behind paywall, the 2010 list is available in Wikipedia) and compared the entries. To convert the numbers in Manager Magazin we used a exchange rate of EURUSD = 1.30.

Most strikingly the Forbes list is much smaller (55 entries with a total of USD 251.3 billion) than the MM list (156 entries with a total of 482.4 billion)

The differences in more detail are as follows:

• Five entries with a total wealth of USD 12.1 billion (according to Forbes) are not recorded in the MM billionaire list:
• Three entries (Schoeller, von Opel, Thurn und Taxis) appear in MM but significantly below the USD 1 billion threshold
• Ludwig Merckle is recorded with with USD 5.3 billion in Forbes, while there is significant valuation uncertainty after the near collapse of the group in 2008/2009, the group has successfully deleveraged und is probably worth above USD 1 billion
• Finally Vladimir Iorich (according to Forbes Russian born, German nationality and Swiss residence) is neither recorded by MM nor by the Bilanz list of billionaires resident in Switzerland)
• The Herz family is recorded with five entries in Forbes (Michael, Wolfgang, Günter, Daniela, Ingeburg), while MM only has the two family entries (one for Günter and Daniela and another one for Ingeburg and her children)
• 109 entries with a total wealth of USD 248.6 billion (according to MM) are not recorded in the Forbes list:
• Two entries with a net worth of more than USD 10 billion (Dieter Schwarz with Lidl and Kaufland, Reimann family with Reckitt Benckiser and Coty)
• Six entries with a net worth between USD 5 and 10 billion (Oetker family with Oetker Group, Braun family with B. Braun Melsungen, Jacobs family with Barry Callebaut and Adecco, Knauf family with Knauf Gips, Peter Thiel with early investments in Paypal, Facebook, Zynga and Linkedin, Liebherr family with Liebherr Group)
• 32 entries with a net worth between USD 2 and 5 billion
• 69 entries with a net worth netween USD 1 and 2 billion
• Finally 47 names are recorded on both lists (Forbes and MM) with a total wealth of USD 233.8 billion according to MM and USD 239.2 billion according to Forbes. Despite total wealth for these entries matching nicely, for individual records the differences are more significant as shown in the graph below:

Obviously putting together billionaire lists is a difficult tasks especially when it comes to valuation of private companies. Nevertheless the overall differences are quite striking. When German billionaires are recorded at 156 instead of 55, the number of German billionaires exceeds those of China or Russia and its per capita number increases from 6.4 to 18.3 (exceeding the US level of 13.2) billionaires per 10 million population.

In a future post we will look the billionaires resident in Switzerland, where Bilanz has 131 entries (USDCHF exchange rate 0.95) compared to Forbes with only nine entries. Obviously one major source of differences for this list can be easily explained in terms of Forbes' nationality criteria versus Bilanz residency criteria.

90-Year Precipitation and Temperature Data for Santiago de Chile (Quinta Normal Measuring Station)

We have looked at the meteorological/climatological yearbooks (Anuarios Meteorologicos 1920-1996/Anuario Climatologico 1997-2010) available for the period of 1920 to 2010 at the website of the Chilean Metearological Services (Dirección Meteorological de Chile). The data is unfortunately only available in pdf format, so we had to get through each report and retrieve the data manually. The datapoints for 1930 and 1962 were omitted as for the former, the 1931 reports was posted and for the latter data was not available for the Quinta Normal measuring station (we pondered whether to replace with Cerillos measuring station for 1962).

The following shows the time series for precipitation and temperature:

 

The correlation matrix looks as follows. No surprises: temperature is correlated with AMO annd precipitacion with ENSO.

The temperature in Santiago (Quinta Normal) and AMO track each other quite closely. The increase in temperature was roughly 0.008 °C per year during the observation time.

Correlation between precipitacion and ENSO is not so strong, but it is still visible from the following graph that high precipitation years typically go together with negative SOI values and vice versa. 2012 was a neutral year in terms of the ENSO cycle and a below average year in terms of precipitation.

Major Foreign Holders of US Treasury Securities

The US treasury produces a handy list of major foreign holders of US securities which can be found here. As  of September 30, 2012 the total was USD 5.5 trillion up from USD 5.0 trillon on December 31, 2012.

The distribution between the major foreign holders is shown in the following graph (total USD 5.5 trillion):

The countries fall within one or more of the following categories:

• financial centers
• strong export nations
• participant in competitive quantitative easing and currency devaluation

When looking at the change for the first three quarters in 2012 against the absolute value the following picture emerges (Asian countries in green and Latin American countries in yellow).

The increase of Switzerland and Japan are notable while China and the Oil Exporters remained at a stable level.

Voter Turnout Chile 1870 to 2012

The recent municipal election in Chile, saw a dramatically reduced voter turnout. This was mostly triggered by a change from compulsory to voluntary voting.

The following post briefly addresses the history of Chilean voter turnout from 1870 to present (2012). The period from 1870 to 1973 has been covered by Patricio Navia in a paper in the Revista de Ciencia Política (Journal of Political Science) from which the following table is extracted. The data is actually extracted from two books, namely:

• Meller, Patricio. 1996. Un Siglo de Economía Política Chilena. 1980-1990. Santiago: Andrés Bello.
• Cruz-Coke, Eduardo. 1984. Historia electoral de Chile, 1925-1973. Santiago: Editorial Jurídica de Chile.

The period from 1988 to 2001 is covered in a second table basing itself on the INE (for Population data) and two government sites covering the current and previous (since 1989) elections.

We have completed the data from 2001 to 2012. We added the population data back to 1988 and the voting age population data back to 1992 using INE's population projection. For the voting age population we took all the 20+ age cohorts and 40% of the 15-19 age cohort (rounded to values of 50'000). Note that the 2012 population data point (17.402 million) is significantly higher than the census data (16.572 million, see our previous post on the subject) and the 2012 voting age population data point (12.750 million) is significantly lower than the electoral registry data (13.404 million).

The census data and the electoral registry are just horribly inconsistent, as shown is the following side by side table (note that the age cohorts for census data have been extrapolated from the total using the ratio of 0.7333 in terms of voting age population to total population as observed in the INE projection data, for the electoral registry the total population has been extrapolated using the same ratio). Given that some persons should appear in the census, but not in the electoral registry (foreigners with less than five years of residence, prisoners etc), the data of either the census or the electoral registry (or most likely both) seems indeed quite flawed.

The voter turnout (voters as a percentage of voting age population) can be graphically summarized as follows:

Copper, Gold and Silver Price Changes after Quantitative Easing Announcements

Following a post of ZeroHedge ("Spot the Odd One Out") we were curious to see how copper price reacted to the various QE announcements in the last couple of years. The complement the picture we also looked at gold and silver.

Price data we have downlaoded from Wikiposit (front contracts): Copper, Gold and Silver.

According to our count we have five FOMC announcement with QE characteristics:

1. November 25, 2008
2. March 18, 2009
3. November 3, 2010
4. September 13, 2012
5. December 12, 2012

In order to capture the entire price change due to the announcement we have looking at the closing prices at the day before the announcement (t-1) and after the announcement (t+1) and obtained the following results:

Data is here.

Update on Analysis Program

We have now had the pleasure to blog for one full year and would like to recapitulate our most successful posts in the three categories Copper, Chile and General Interest:

Copper
3. Relationship between Copper Price and Copper Production / Consumption
4. Copper Substitution by Aluminium
6. Top Copper Producing Countries
9. Copper Price Forecasting
10. Relationship between Copper and Chilean Peso Series (1 of 3) (2 of 3) (3 of 3)
12. Peak Copper
        Copper Volume Forecasting
        Relative Conductivity of Ag, Al, Au and Cu
        Copper to Aluminium Price Ratio
        Copper Use in Energy Generation
        Relationship between Copper Price Change and S&P 500 Total Return
        Copper Inventories with Producers

Chile:
7. Voter Turnout Chile 1870 to 2012
10. Relationship between Copper and Chilean Peso Series (1 of 3) (2 of 3) (3 of 3)
        Chile's Export Destination and Products
        Chile's Population (2012 Census)

General Interest:
1. World Population, GDP and GDP per Capita Growth 1820-2020
2. GDP per Capita Time Series for Spanish Speaking Countries
5. Peak Lithium
8. GDP Per Capita Time Series 1820-2008 (Western Europe)
11. Luxury Car Ownership per Capita Series (1 of 2) (2 of 2)
        World Population Data 1820-2008
        Earliest National Day Celebration Events

For 2013 we plan to keep the number of monthly posts at two, more or less equally distributed between the three topics of Copper, Chile and General Interest. We are also happy to include topics suggested by our readers (please use comments).

For the more successful posts and where appropriate we will do updates including the data which will have become available in the course of 2013. We will also try to address the questions which remained unanswered from our initial analysis program:

Have copper prices actually been a good indicator of turning points in the global economy? Do do so we will assess historical time series of world GDP (possibly also US, China and Chile), copper production volume and copper price. We will also look at the question whether copper prices are early, concurrent and lagging indicators and address the question whether the relationship (provided we find one) has changed over time.

What developments will challenge or strengthen the predictive power of copper prices? We name just a few which we aim to discuss in much more detail:

• Substitution of copper usage (we have heard about Dean Lumber and Dr. Aluminium)

• Monetization and off exchange warehouse storage, i.e. dark inventory (for wealth preservation and finance / securitization purposes)

• Increasing recycling rates (copper doesn't degrade and the copper reservoir is significant)

• Peak copper (lower production and lower grades) compensated by increased copper usage

• New uses of copper (antibacterial, renewable energy)

• More efficient design specifications lowering copper content