вторник, 1 сентября 2015 г.

The Global Competitiveness Report 2014–2015

The Global Competitiveness Report 2014-2015 assesses the competitiveness landscape of 144 economies, providing insight into the drivers of their productivity and prosperity. The Report series remains the most comprehensive assessment of national competitiveness worldwide.

воскресенье, 30 августа 2015 г.

political demography

from brother2:


Вот часто приходиццо слышать - ах мол это европейцы и американцы подожгли Ближний Восток и окрестности и теперь разгребают.

Посмотрим на то, что объёединяет все страны в которых случилсь всякие события:

1) вполдне себе африканская демография - резкий рост населения, более 2/3 - момодёжь - во всех афространах это источник гражданских войн, что же сдерживало эти страны от сьеролеонезации - см. п.2

2) все эти страны были у кого-то на подсосе, даж нефтеЛивия была капитально повязана, как только подача бабла или техпомощи прекращалась, так начинались события. Относительно саимообеспечивиающие страны (Алжир и Марокко, Турция например) довольно быстро погасили кризисы.

3) а как так получилось, что они стали подсосозависимыми: все свергутые лидеры примерно одинаковы - родились при позднем колониализме, как политики состоялись во времена пикового советско-американского противостояния - отсюда и соответствующая психология - дорогой Кремль/БелыйДом дай нам денег или мы уйдём к БеломуДому/Кремлю. Как только противостояние закончилось, потки иссякли, а добывать бабло и жить по средствам они не умели, а тут ещё и мировой кризис. Ну и возраст.

Вот такие вот три источника и три составляющих.
А четвёртый - сословная система во всех этих странах, когда принадлежность к племении/нации/религии определяет сословие и профессию, но демография-то изменилась и прежде всего за счёт роста чистленности низшизх сослловий (а в Сирии сунитское меньшинство перестало быть меньшинством за счёт палестинских беженцев). Кароч движуха была неизбежна.

А что же европеи и американы - они поступили прагматично: не можешь победить - возглавь!
Прикинув соотношения сил сторон и демографические расклады - заявили о поддержке потенциальных победителей.
Кстати с большевистской революцией всё было точно так же.
Естессно, что для русскомыслов всё это выглядело как тщательное поджигание стабильных стран.
ну так они и про нацпроблемы в позднем сесесере ничо не слышали - "дружно ж жили".

10 greatest threats facing the world in 2014

по ЮСтудей проблемы следующие:

The World Economic Forum on Thursday released its Global Risks 2014 report.

"Taking a 10-year outlook, the report assesses 31 risks that are global in nature and have the potential to cause significant negative impact across entire countries and industries if they take place," is how the WEF describes the report in a statement accompanying its release.

"The risks are grouped under five classifications — economic, environmental, geopolitical, societal and technological — and measured in terms of their likelihood and potential impact," the statement says.

The report canvasses the views of 700 experts from around the world. Ten of what the WEF calls the "global risks of highest concern" for 2014 are as follows:


Fiscal crises in key economies


"Fiscal crises feature as the top risk in this year's Global Risks report. Advanced economies remain in danger, while many emerging markets have seen credit growth in recent years, which could fuel financial crises. A fiscal crisis in any major economy could easily have cascading global impacts."

Structurally high unemployment/underemployment


"Unemployment appears second overall, as many people in both advanced and emerging economies struggle to find jobs. Young people are especially vulnerable – youth unemployment is as high as 50% in some countries and underemployment (with low-quality jobs) remains prevalent, especially in emerging and developing markets."

Water crises


"Environmental risks feature prominently on this year's list. Water crises, for instance, rank as the third highest concern, illustrating a continued and growing awareness of the global water crisis as a result of mismanagement and increased competition for already scarce water resources."

Severe income disparity


"Closely associated in terms of societal risk, income disparity is also among the most worrying issues. Concerns have been raised about the squeezing effect the financial crisis had on the middle classes in developed economies, while globalization has brought about a polarization of incomes in emerging and developing economies."

Failure of climate change mitigation and adaptation


"Even as governments and corporations are called upon to speed up greenhouse gas reduction, it is clear that the race is on not only to mitigate climate change but also to adapt. Failure to adapt has the biggest effect on the most vulnerable, especially those in least developed countries."

Greater incidence of extreme weather events (e.g. floods, storms, fires)


"Climate change is the key driver of uncertain and changing weather patterns, causing an increased frequency of extreme weather events such as floods and droughts. The Global Risks 2014 report draws attention to the combined implications of these environmental risks on key development and security issues, such as food security and political and social instability, ranked 8th and 10th respectively."

Global governance failure


"The risk of global governance failure, which lies at the heart of the risk map, was viewed by respondents as one of the risks that is most connected to others. Weak or inadequate global institutions, agreements or networks, combined with competing national and political interests, impede attempts to cooperate on addressing global risks."

Food crises


"One of the top societal risks in the report, food crises occur when access to appropriate quantities and quality of food and nutrition becomes inadequate or unreliable. Food crises are strongly linked to the risk of climate change and related factors."

Failure of a major financial mechanism/institution


"Over five years after the collapse of Lehman Brothers, the failure of a major financial mechanism or institution also features among the risks that respondents are most concerned about, as uncertainty about the quality of many banks' assets remains."

Profound political and social instability


"At number 10 is the risk that one or more systemically critical countries will experience significant erosion of trust and mutual obligations between states and citizens. This could lead to state collapse, internal violence, regional or global instability and, potentially, military conflict."

The World’s Biggest Problems

The World’s Biggest Problems portal has a simple, clear mission: educating people all around the world about the biggest problems facing humanity.These problems have two criteria, they must be global in scope, and have the potential to rapidly escalate into severe crises.
  1. Economic Collapse : Fragilities in the current global economy could tip the developed world into conditions not seen since the 1920s.
  2. Peak Oil : Petroleum has powered the modern world for almost 100 years; today, many industry insiders say that we may be reaching a permanent peak in oil production. 
  3. Global Water Crisis : Over the last 50 years the human population has nearly tripled, while industrial pollution, unsustainable agriculture, and poor civic planning have decreased the overall water supply. 
  4. Species Extinction : Certain species that human beings depend upon for our food supply are going extinct; if their numbers fall too low we may face extinction ourselves. 
  5. Rapid Climate Change : While the debate rages on about the causes of climate change, global warming is an empirical fact. The problem is both a curse and blessing, in that people from different cultures will either have to work together or face mutual destruction

Issues on the Global Issues

Issues on the Global Issues web site
This web site has numerous articles categorized into various issues. Some articles can of course be in more than one issue as many are inter-related:

  1. Aid (6)
  2. Arms Control (7)
  3. Arms Trade—a major cause of suffering (10)
  4. Biodiversity (9)
  5. Causes of Poverty (14)
  6. Climate Change and Global Warming (32)
  7. Conflicts in Africa (14)
  8. Consumption and Consumerism (14)
  9. Corporations (13)
  10. Environmental Issues (50)
  11. Fair Trade (5)
  12. Food Dumping [Aid] Maintains Poverty (3)
  13. Food and Agriculture Issues (26)
  14. Foreign Policy — Projecting Power (8)
  15. Free Trade and Globalization (14)
  16. G8: Too Much Power? (4)
  17. Genetically Engineered Food (10)
  18. Geopolitics (45)
  19. Health Issues (15)
  20. Human Population (7)
  21. Human Rights Issues (11)
  22. International Criminal Court (6)
  23. Iraq Crisis (3)
  24. Links and resources for more information (20)
  25. Mainstream Media (9)
  26. Middle East (19)
  27. Natural Disasters (6)
  28. Nuclear Weapons (5)
  29. Palestine and Israel (6)
  30. Sustainable Development (13)
  31. Third World Debt Undermines Development (11)
  32. Trade, Economy, & Related Issues (67)
  33. War on Terror (13)
  34. World Hunger and Poverty (4)

“Bad ideas flourish because they are in the interest of powerful groups.” — Paul Krugman

Global problems according to the UN

глобальные проблемы в представлении ООН:
все согласны?
на мой взгляд: салат из винигрета

четверг, 11 сентября 2014 г.

time series

(This article was first published on Google Open Source Blog, and kindly contributed to R-bloggers)
How can we measure the number of additional clicks or sales that an AdWords campaign generated? How can we estimate the impact of a new feature on app downloads? How do we compare the effectiveness of publicity across countries?

In principle, all of these questions can be answered through causal inference.

In practice, estimating a causal effect accurately is hard, especially when a randomised experiment is not available. One approach we've been developing at Google is based onBayesian structural time-series models. We use these models to construct a synthetic control — what would have happened to our outcome metric in the absence of the intervention. This approach makes it possible to estimate the causal effect that can be attributed to the intervention, as well as its evolution over time.

We've been testing and applying structural time-series models for some time at Google. For example, we've used them to better understand the effectiveness of advertising campaigns and work out their return on investment. We've also applied the models to settings where a randomised experiment was available, to check how similar our effect estimates would have been without an experimental control.

Today, we're excited to announce the release of CausalImpact, an open-source R package that makes causal analyses simple and fast. With its release, all of our advertisers and users will be able to use the same powerful methods for estimating causal effects that we've been using ourselves.

Our main motivation behind creating the package has been to find a better way of measuring the impact of ad campaigns on outcomes. However, the CausalImpact package could be used for many other applications involving causal inference. Examples include problems found in economics, epidemiology, or the political and social sciences.

How the package works
The CausalImpact R package implements a Bayesian approach to estimating the causal effect of a designed intervention on a time series. Given a response time series (e.g., clicks) and a set of control time series (e.g., clicks in non-affected markets, clicks on other sites, or Google Trendsdata), the package constructs a Bayesian structural time-series model with a built-in spike-and-slab prior for automatic variable selection. This model is then used to predict the counterfactual, i.e., how the response metric would have evolved after the intervention if the intervention had not occurred.

As with all methods in causal inference, valid conclusions require us to check for any given situation whether key model assumptions are fulfilled. In the case of CausalImpact, we are looking for a set of control time series which are predictive of the outcome time series in the pre-intervention period. In addition, the control time series must not themselves have been affected by the intervention. For details, see Brodersen et al. (2014).

A simple example
The figure below shows an application of the R package. Based on the observed data before the intervention (black) and a control time series (not shown), the model has computed what would have happened after the intervention at time point 70 in the absence of the intervention (blue).

The difference between the actual observed data and the prediction during the post-intervention period is an estimate of the causal effect of the intervention. The first panel shows the observed and predicted response on the original scale. The second panel shows the difference between the two, i.e., the causal effect for each point in time. The third panel shows the individual causal effects added up in time.
The script used to create the above figure is shown in the left part of the window below. Using package defaults means our analysis boils down to just a single line of code: a call to the functionCausalImpact() in line 10. The right-hand side of the window shows the resulting numeric output. For details on how to customize the model, see the documentation.
How to get started
The best place to start is the package documentation. The package is hosted on Github and can be installed using:

install.packages("devtools")
library(devtools)
devtools::install_github("google/CausalImpact")
library(CausalImpact)

By Kay H. Brodersen, Google

To leave a comment for the author, please follow the link and comment on his blog: Google Open Source Blog.
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2Boxplotsmapsanimation), programming (RStudioSweaveLaTeXSQL,EclipsegithadoopWeb Scraping) statistics (regressionPCAtime seriestrading) and more...

среда, 23 октября 2013 г.

not sure

тут (это из ФБгр) много лирики и эмоции, но одна вещь, имхо, подмечена верно: немедицинские критерии Зурабова. Насколько понимаю, он оказался первым немедицинским министром, хотя и из страховой части, но по некоторым показаниям: программист.
Что происходит в современной медицине имеет "ноги" из Минздрава со времен страховщика-министра М. Зурабова. Он ввел безумный норматив пребывания больных в стационаре, которые противоречат всем патофизиологическим и патанатомическим показателям! Это привело к резкому увеличению смертности и инвалидности населения. Напрочь сметены такие понятия, как "лечить больного, а не болезнь", реабилитация инфарктных и постинсультных больных! Мне больно это говорить, но это так! В основу здравоохранения легли принципы ЭКОНОМИИ средств. В Итоге мы потеряли массу людей трудоспособного возраста, в связи с чем потери оказались гораздо большими.
А сейчас о небольших зарплатах врачей и среднего медперсонала! После выхода постановления правительства о расширении прав руководителей 50% и более фонда зарплаты ЛПУ уходит управленческому аппарату, а что останется - это вам, дорогие наши труженники. Надо добиться отмены этого постановления, т.к. оно преждевременно из-за абсолютной неготовности наших руководителей к справедливому распределению фонда зарплаты!!! А больные здесь НЕПРИЧЁМ !!! Мы должны соблюдать клятву Гиппократа, относиться к больным, как к себе и близким вам людям! И ваше добро и теплое, профессиональное отношение к больному не останется не замеченным и не вознагражденным! Удачи вам, дорогие коллеги!!! И боритесь за свои права всеми правовыми способами!
в этой же ветке есть ссылка на годовой давности статью Балласт в Снобе, -- год прошёл, и стало хуже

ещё из той же ветки -- мед тезис, объясняющий разницу между статистическим глазом и медицинским:
Olga Demicheva Ася Джатдоева, вот Вы пишете: " У нас все врачи - выгоревшие..."
Вы ушли из медицины и медицинской науки. Но Вы никогда не отречётесь от своего медицинского образования. Это часть Вас. 
Позвольте, как старший коллега, открою Вам одну истину. Когда Вы характеризуете личностные качества людей, самое опасное слово - это слово "ВСЕ".
Вы ушли из медицины и медицинской науки. Но Вы никогда не отречётесь от своего медицинского образования. Это часть Вас. Позвольте, как старший коллега, открою Вам одну истину. Когда Вы характеризуете личностные качества людей, самое опасное слово - это слово "ВСЕ".

Redefining this blog

Нумерология поскольку не очень пошла, а появился проект с политикой здоровья, который хочу воплотить в секцию валентеевских чтений 15 года -- буду этот блог пользовать для обдумывания предполагаемого мероприятия. Название менять не буду, поскольку, скорее всего, и 15 год удастся пережить (плюнул через плечо 3(три) раза:).
Буду тут собирать разные вещи вокруг тэга ВЧ15.