Wednesday, March 30, 2016

My Current Reading - 香港治與亂: 2047的政治想像

It's Wednesday, which mean it's library day after work. Out of this kid-friendly neighborhood library which consists of mostly children's books (and very few foreign language books), I stumbled across this one.

The title looked interesting but the synopsis seemed a bit boastful  (這是一本「講真話」的書), I was a bit skeptical but checked it out (borrowed it) anyway.

Fast forward to one hour after flipping through the first page, I'm almost quarter-way through already! I didn't expect this to be a quick-and-easy read - especially with my proficiency in Chinese and on such serious topics, but the writing style is definitely a big factor.  The well-organized structure (great parallelism), the meticulous diction, and the matter-of-fact tone of the writing make the book a very enjoyable read.

I'm glad that I didn't judge a book by its cover (the synopsis is on the back of the cover). All I have to say is that the content is great and the context is even better. I highly recommend this to anyone who wants a neutral tone and an analytical approach in thoroughly explaining the cause-and-effect of the current issues, and is open-minded enough listening to some unbiased forecast for the future.

Back to reading!!

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About the book

簡介 
本書以2014年「佔領運動」和2015年特首普選制度本地立法失敗為開篇,解析了香港政治之所以走入當前困局的心理、社會、政治和歷史脈絡,這包括:香港社會對於「一國兩制」方針所存在的觀念偏差和在國家政治認同方面所面臨的困難處境,「港人治港」投入實踐之後所面臨的政治隱憂,以及在高度自治原則下,作為中國的特殊政治邊陲,香港在管治上面臨的結構性困難。
當五十年不變的期限來臨之際,2047年的香港何去何從,將直接取決於接下來的二三十年間,中央政府與香港社會之間是否能夠重建政治信任。
本書作者畢業於北京大學和哈佛大學,現任教於香港大學,兼具政治學者和中國年輕一代知識菁英的雙重身份,以其理性和敏銳的筆觸,為所有關懷香港未來的人打開全新的政治想像空間。

作者簡介
閻小駿,哈佛大學政治學博士,北京大學法學學士、碩士。現任香港大學政治與公共行政學系副教授,主要從事當代中國政治、比較政治制度與政府改革方面的研究。2012年,閻小駿博士關於中國農民企業家的研究榮獲全球中國研究權威學術期刊、英國《中國季刊》(The China Quarterly)年度最具原創性論文獎。2012年入選香港特別行政區科研資助局首屆傑出青年學者計劃。2013年榮獲香港大學傑出教學獎。其學術成果曾發表於英國《中國季刊》、澳大利亞《中國學刊》、美國《當代中國研究》、英國《政治與政策》、美國《後共產主義問題》等知名英文學術期刊。他亦曾為《南方日報》、《戰略與管理》、《財經》等中文報刊撰稿,其譯著曾由香港大學出版社及香港中文大學出版社出版。

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Link

閻小駿:我為什麼要寫《香港治與亂》?

熟悉香港本地政治討論話語的人士,一定早已經發現自說自話乃是香港政治的一個獨特景觀。在香港政治問題的討論中,本地不同派別人士基本上都擁有各不相同的政治觀點、論述方式和預期讀者群,相沿成習;但他們共通的一點則是對於北京治港政策的隔膜。

香港政治說到底是在中國政治大框架下運行的一個子系統。國家級政治的變遷,對香港政治的影響不但是深刻的,而且是決定性的。北京對香港的政策,則基本上確定了香港政治在不同時期的主旋律,也不斷勾勒出「一國兩制」在香港具體落實的型態。隨著時代發展而不斷與時俱進的北京對港政策,對香港社會來說實際上是最重要的制度資源;但恰恰在這一點上,香港人往往也是最陌生的。我以為,要改變「自說自話」式的香港政治討論,首先就要瞭解「一國兩制」這個故事在香港以外的另一面。
「自說自話」式的香港政治帶來的危害是多方面的。因為不瞭解和隔膜,使得香港社會與北京之間長期溝通和交流失靈,雙方「雞同鴨講」,以至於誤解日深。在行動上,香港社會──從建制到泛民──也往往是僅僅憑著自己對北京的模糊的、常常不真實的印象而做出研判,其結果如何可想而知。特別是打出與北京「溝通」大旗的政黨和智庫,細細考究起來,其實內裏也無人對中央政府的政治運行有何瞭解。這樣的溝通其實又有什麼實際效果?「自說自話」式的香港政治帶來的是整個政治局面「刻舟求劍」式的嚴重落伍。當北京政治以一日千里的速度向前發展的時候,香港各方政治人物還在以前朝舊事為依憑憧憬未來虛妄的政治圖景;「盲人騎瞎馬、夜半臨深池」,這樣的香港政治發展下去,孰能不危乎殆哉?
「自說自話」式的香港政治模式成因是多方面的。但過去十年中央政府在處理香港問題時的柔性取態──特別是「二十三條」立法、2010年政改和反國民教育運動──三件事上的讓步有莫大關係。這三次讓步,使得香港社會形成了較為固定的心理預期,即:只要自己能夠動員民眾、能夠「企硬」,即便自說自話,北京也必定是最後讓步的那一方。這種「大鬧大解決、小鬧小解決、不鬧不解決」的工作方式,確實鼓勵了香港政治中「自說自話」傾向的發展。
在如此情形下,在香港看來,一切瞭解、交流和溝通都無必要,總之「會哭的孩子有奶吃」,只要自己堅持立場,最後勝利一定屬於自己。但香港社會尚未深刻意識到的是,這樣的工作方式,是不能套用到新的政治時代的。2013年2月,新擔任中共中央總書記的習近平在政治局集體學習時就專門指出,「不能讓那種大鬧大解決、小鬧小解決、不鬧不解決現象蔓延開來」。這是充分反映中國新領導階層在處理政治和社會矛盾時將採用的、不同以往的工作方式的重要表態。這個指導原則,在北京處理2014年香港「雨傘運動」問題時已被充分貫徹。
就香港而言,今天,適用於過往的政治定式顯然不再具有可延續性和可操作性。在新的時代,香港社會瞭解中國政治運作、瞭解北京的「一國兩制」觀之最新發展就顯得尤其重要。回歸以來北京對於香港政局、香港社會和「一國兩制」落實狀況的觀察、分析和研判實際上是經歷了較長和複雜過程的,其中也有演變、反覆和自我反思。深入了解在新的「自信年代」,北京對港政策的流變,是所有關心香港政治未來人們的必備知識。
《香港治與亂:2047的政治想像》正是在經歷了2014年佔領運動和2015年政改爭端之後,我對香港政治的總體反思以及對新時代北京對港政策的分析和梳理,再加上對「一國兩制」未來不同結局的合理展望。我在書裡第一次詳盡分析了香港政治緣何走入今天的亂局,以及系統提出了香港該如何走出政治困局的辦法。總的來說,這本書試圖系統講述的是在「一國兩制」實施過程中香港人所不熟悉的、另一面的觀念、認知和故事,也試圖把香港政治中最具爭議的政治和政策問題還原到其本來狀態。
《香港治與亂:2047的政治想像》聚焦於政治信任,詳細討論了香港和北京之間如何失去政治信任,而未來政治信任又該如何重建。瞭解另一面的故事,就是希望香港政治能夠擺脫「自說自話」式的話語和操作習慣,而轉向互相瞭解、互相信任和互相合作的新的道路。
荀子說,「不積跬步、無以至千里」;我希望建設未來良性的香港政治能夠從閱讀這本書並瞭解北京的「一國兩制」觀開始。

Friday, March 25, 2016

RIP Johann Cruijff

Zijn jij een van de beste Oranje spelers; jij had voor altijd de spelen en de historie van het Nederlandse voetbal veranderden. Hartelijk dank.


Wednesday, March 23, 2016

Thoughts on AlphaGo vs Lee Sedol - What does Artificial Intelligence mean to our future?


I followed the recent matches of AlphaGo (by Google DeepMind) vs Lee Sedol, and even though I am not a Go player nor a computer scientist, I was genuinely intrigued by the complexity of the game, the intensity of the battle, and the capability of machine learning. AlphaGo is a prototype program that was created 2 years ago, it learned to play Go by playing against top players and itself over and over in order to learn from its mistakes. Since last year, it had defeated Fan Hui, a European Champion Go player, with five straight wins. Before that, computer programs had little success in defeating human players because of the large number of possibilities in the game and the finite playing time. Thus this is a well-anticipated battle to show the improvement and advancement in the latest development of machine learning. Lee, a Korean 9-dan (highest ranking - Divinity) Go master, was often regarded as one of the best players in the world today, played 5 matches against AlphaGo. He had faced tremendous pressure during each game and did not feel like he had any lead at all at any point. By the end of the game 3, he was losing to AlphaGo 0-3. The result caused a lot of emotional responses from the public, which some believed that it is about time that AI is more intelligent than us, and that it will eventually rule the world. Most people started to root for Lee and hoped that he would defend us human beings against machine, and when he won game 4, the world cheered. This got me thinking, is this really a battle between human and machine? Are we trying to draw to a black-and-white conclusion here that the winner (machine) reigns supreme?

After giving it some thoughts, and understanding how powerful machine learning is and what it can do, it is still probably too soon to be worried that AI will take over our world. However, its capability is a wonderful tool for us as it can empower us in an innovative way, and I think this is rather the meaning behind these games.

First of all, the battle is merely in the game of Go. It is only meant to demonstrate the capability of machine learning, and how it is capable to improve itself by learning from others and itself. Then in combination of its uncanny speed in calculating probabilities in each possibility, would be able to solve complex problems and complete very difficult tasks - to the point that it can be better than humans.

However, in real life, there are so much more complex tasks that would still require human inputs in order to be carried out and accomplished. For example, think of our roles in creating arts, performing arts, negotiations, relationship buildings etc. Even though AI can have very high intelligence quotient in solving problems, it lacks emotion quotient (EQ), and this is what makes human input/interaction meaningful and crucial. A lot of times connections and emotions are the keys to getting the jobs done. For example, doing business requires solid relationships/partnerships - people like to do business with those they feel comfortable with and are able to feel connected to; performing the Chopin concertos require deep emotional understanding of the composer and the meaning of the masterpiece etc. All of which would not be achieved without the human part. Our civilization is much broader than just 'intelligence': there are emotions, values, virtues, manner, morale, spirits, religions etc, those are essential part of the civilization which AI does not possess (at least not today).

Furthermore, with the discovery and advancement of machine learning, we should utilize it as a way to assist us to look into things that we might have missed. As the developers in AlphaGo stated, machine learning might even be able to assist the healthcare providers in some day, by identifying problems that we have neglected to observe from individual incidents and cases, and by enough repetitions that translate to learning, coming up with information and ideas on what we should pay further attention to in order to reduce errors and improve the quality of healthcare.

So after all, although there was a clear 'winner' in the battle, it is not a competition between human and AI, but a demonstration of the possibilities and capabilities in machine learning. What can we do instead, is to take this opportunity to reflect on ourselves as human being, on how we can make the best out of AI. We need to have a solid understanding of what we are doing, what we are capable of, and then determine what are the things that we can delegate to AI to make our life easier. We can optimize the strength of AI as a way to make us better human beings by allowing us to achieve more than we could do before with better awareness or resources; then maximize our uniqueness (the human aspect) to innovate, to change, and to accomplish more great things for the world.

Another takeaway from the success of AlphaGo is its ability to "learn and master" the game by playing itself over millions of times through trial and error. It is a good example and a reminder for us that the old saying "Practice Makes Perfect" is still the key to success. Although we might not be able to do the same things a million times, with failure and willingness to succeed, we will gain wisdom and our possibilities are still endless.

Youtube recordings of the 5 matches played by AlphaGo vs Lee Sedol






Tuesday, March 22, 2016

Avoid making these mistakes in facial masks!

I love caring for my skin, and I started at very young age.  I always loved facial masks as well, it's sort of a skin care boost to detox, remove impurities, and nourish the skin with 'nutrition'. During weekends I can easily do 3-5 a day! I have used over 50 different masks from various brands, in cream or cloth form, from pharmacy to high-end department store brands.  In retrospect, I have purchased some based on marketed benefits, promotions, or positive reviews, without thinking too much about the ingredients, but I choose them more carefully. (For product ingredients and the benefits of skincare ingredients, feel free to visit ewg.org or paulaschoices.com for individual produce reviews)

In my opinion, facial masks are not absolutely necessary but it is a great way to address specific skin concerns.  However, using facial masks incorrectly will result in wasting the products and your money, or worse, making your skin worse! So whether you're looking to do a deep cleaning or adding some hydration to your face, be sure to avoid these mistakes:

1. Not looking at the product labels - read the labels carefully to make sure that you are not allergic to the products' ingredients

2. Buying the 'natural' marketed labels - Don't get me wrong. I love natural products and try to avoid certain chemical ingredients as much as possible.  But poison ivy is natural but it isn't good for the skin, and ingredients like Retinol (Vitamin A), Hyaluronic Acid (or Sodium Hyaluronate), or Glycerin might sound foreign to you, can be good or even essential for the skin

3. Not cleaning your face thoroughly - Clogged pores and dirt prevent you from getting the most out of the facial masks. Even if you're using a cleansing mask, it's still a good habit to remove the dirt from the surface and let the mask absorbs the impurities from your pores


4. Opting for cream mask because it seems to be cheaper and lasts longer - Cloth mask also does wonders.  When you leave it on your face, it seals the ingredients onto the skin.  For cream masks, apply generously onto your skin, you do need a good amount (more than the daily moisturizer amount) in order for your skin to absorb the essence.

Not following instructions
5.  Leaving the mask on for too long (except for overnight/sleeping masks) - This is a huge mistake.  Cleaning mask with clay and charcoal can dry up your skin quickly.  When your skin is too dry, it can become flaky and cause peeling, or worse, form fine lines!  Even if you are doing a hydrating mask, some masks have intensive formulas that you shouldn't leave it on for more than 5-10.  After the recommended time the ingredients could irritate your skin. So the longer isn't always better.

5b. Using your facial/eye masks as a substitute to your regular skincare products. Facial masks ingredients are formulated for special skin concerns and provide a boost to the skin, but they don't provide the same protection as the regular skincare products (SPF, seed oils for antioxidants)

6. Not rinsing/wiping/rubbing properly - If it says "wipe off excess", use a facial tissue to gently wipe off any residues on your face; for rinsing, use lukewarm water to rinse off completely.  If it says massage onto your skin, use your fingertips to rub the essence onto your face in circular motions.  Be sure to follow the regular skincare routine as instructed.

7.  Talking/Laughing/Eating - Try to relax as much as you can.  Your skin will relax too and absorb the ingredients better.  In addition, if the ingredients are drying, intensive motion on your face will pull your skin and can create fine lines.

8.  Using only one facial masks - I would switch with a few products, or at least try something else and then go back to your favorite.  Once your skin is used to the ingredients, the products will become less effective.

9. Picking one that is colorful and smells like its marketed ingredients - If you care about the ingredients, try to stay away from the colorful ones or the ones that really smell like the ingredients (like 'rose' or 'cucumber').  A lot of times they contain synthetics colors and scents to make the products more 'believable' and don't add any benefits to your skin.  I prefer not having Green-3, Yellow-3, CI-xxxxx (artificial colors) and fragrance/parfum (could be made of synthetics) added to my skincare boost.


So that's it for now! Don't forget to  Happy Masking!

Wednesday, February 3, 2016

Gender Wage Gap - Discussion on Descriptive Statistics

Bernie Sanders is probably celebrating how close the gap was between him and Clinton in the Iowa Caucus last night. The senator, who aims to fight inequalities in minorities (people of color, women, LGBT, disabilities) and the welfare of the youth and the elderly, has been gaining support steadily. Anyone can visit his official campaign website to read more about where he stands on issues. There's one issue, particularly the 'facts' and its descriptive statistics, even as female (and somewhat of a feminist) I cannot bring myself to totally agree with it.

This issue is the endless 'gender wage gap" that politicians have been debating over for decades.
Does it exist? I believe so
Are the statistics correct? Most likely.
Are politicians fighting the anti-pay gap making a case based on statistics? Yes
So, they must be right? Not necessarily.

First, take a look at where Sanders stands on Gender Wage Gap from his issue on "Fighting for Women's Right" (Reference: https://berniesanders.com/issues/fighting-f...womens-rights/)

AS PRESIDENT, SENATOR BERNIE SANDERS WILL:

1. FIGHT FOR PAY EQUITY FOR WOMEN.
It is a national disgrace that women only earn 79 cents for every dollar a man earns.1 The gender pay gap is even worse for women of color. Today, African American women earn just 64 cents for every dollar a white male earns, while the figure for Hispanic women is just 54 cents. As president, Sen. Sanders will sign the Paycheck Fairness Act into law to end wage discrimination based on gender.

5. INCREASE THE MINIMUM WAGE TO $15 AN HOUR BY 2020.
According to the most recent statistics, women make up two-thirds of all minimum wage workers. Increasing the minimum wage to $15 an hour would significantly boost the wages of more than 15 million women and help close the gender wage gap.

6. RAISE THE TIPPED MINIMUM WAGE TO $15 AN HOUR BY 2023.
The federal tipped minimum wage of just $2.13 an hour hasn’t been raised since 1991. More than two-thirds of tipped workers are women. Increasing the tipped minimum wage to $15 an hour by 2023 would lift millions of women out of poverty and significantly reduce the gender pay gap.

Skipped #2-#4 as they were irrelevant to wage gap (they were about reproductive rights and childcare)

See any problem there with the descriptions? Most might say "Well it's just the median, so the extreme outliers won't skew the median". Well, true...but here are the considerations:

- Are the female minimum wage worker and the tipped minimum wage worker groups large enough so that the median salary includes their pay rates?
- Are the male minimum wage worker and the tipped minimum wage worker groups small enough so that the median salary does NOT include their pay rates?
If both answers to the questions above are yes, then sure, increasing the minimum wage would help. However, the fact is that it is inaccurate. Based on government data (Bureau of Labor Statistics), 'Hourly rate' (not limited to minimum wage) workers represent 58.7% of all wage and salary workers, and only 4% of those hourly rate workers are making minimum wage or below. So we can conclude that raising minimum wage is good for certain workers, but will NOT close the gender wage gap.

Now, one can argue this way: if the minimum wage increases, wouldn’t the wage of other non-minimum wage jobs increase as well? Yes, the cost of doing business would increase, however in order to generate positive returns or to merely break-even, businesses would mark up the prices of goods and services, which means the cost is transferred and absorbed by the customers. When price level goes up, it becomes inflation, and non-minimum wage workers would demand high wages in return. In the long run, everything would be adjusted but will also return to equilibrium. So is increasing minimum wage the answer to solve gender wage gap? Or is it more of a campaign tactic that Sanders is using in order to gain supports from the many lower wage workers? I would like to think it’s the latter.

Descriptive statistics, if used properly, can properly identify issues/problem/inefficiencies/inequality, and provide insights on what is or isn’t working. However, the misuse of descriptive statistics is misleading and deceptive, and can even cause the ill-informed to think/act based on incomplete information and biased messages. Unfortunately, politicians and the media often unintentionally or deliberately interpret statistics, make inferences, and draw conclusions only to their advantages.

Without turning this into a political debate, let’s focus on the main issue here. If gender wage gap exists, how should we properly measure this based on the data that we have? The answer is not as easy as we think.

What are the challenges?
The 79% (Refer to pg. 7 of the link provided below)
This is a very quick but rough comparison. It is inclusive of all workers, regardless of job function, location, skills (hard and soft) competency, tenure at the job, years of relevant work experience, age, education, licenses, and certification etc. The distribution of these attributes could vary based on gender but the comparison does not distinguish any of them. Also, the research report did not disclose the profile of the median earnings of female and male.

Comparison by state (pg. 9)
This is better, but it only helps a little by taking into consideration the diverse cost of living among states.

Comparison by age group, education (pg. 14, 15)

These comparisons are bit more convincing, at least they show that we are seeing gaps in every age group/education level. The difficult part would be to validate some of the soft facts, such as whether women are taking jobs that are as aligned to their education as their male counterpart; whether women are leaving the workforce at some point to start a family and returning years later; or have their male counterpart been switching jobs more often and negotiating salary more aggressively. These factors could be an explanation for some of the differences, rather than concluding it as a discrimination that women are hitting so-called glass ceiling that limits their earning potential.

Comparison by specific job title (pg. 17)
This seems to be the better comparison, but again the challenge is still there – as the other attributes/factors could still play a significant role in driving the differences in the measured result.

It is extremely difficult and complicated to properly show the accurate earnings gap between genders, if we have to take into account all factors that can be attributed to earnings. Even if all factors are being accounted for, ceteris paribus, still shows the gaps, our analysis would provide accuracy and granularity, but lose credibility.

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1 all figures are median earning based on AAUW's published result (http://www.aauw.org/files/2015/09/The-Simple-Truth-Fall-2015.pdf) the information published in this report is often used as the gender wage gap debate. It’s worthwhile to take a deep look for anyone who is interested. The report has better analysis and argument to explain the differences in the numbers than how the main-stream media with political biases choose to interpret them.

Thursday, January 7, 2016

Oil Price: an example of Game Theory

Drivers have been enjoying low gasoline price thanks to the cheapest oil price in over 7 years. While some of the reasons of low price stem from a weaker global economy which results in lower demand for oil, and the recent conflict between Saudi Arabia and Iran, the true reason behind the steep decline in oil price is fueled by the price competition between the largest oil producing countries, largely between the OPEC (Organization of the Petroleum Exporting Countries) and US Shale producers. The control of supply, the discrepancy in break-even cost of production amongst individual oil producers, and the political strategy in this battle demonstrated a great example of Game Theory.

The OPEC (led by Saudi Arabia, other major producing countries including UAE, Iran, Iraq etc) was once the largest oil producer. Since the past two decades, with the increasing demand which resulted in rising oil price, and the drive to cut back on the dependence on oil imports, Russia, the US, as well as other countries resumed researches and investments for alternative/renewable energy and different methods of extracting oil. This fueled the rise of the oil shale industry, which involves mining and processing of oil from shale rocks. However, at higher cost in producing each barrel, the only incentive for shale producers to generate supply is when both the demand and the price of oil are high.

The shale producers run a lucrative business when the price is at the highest and supply as much as possible, but their counterparts in OPEC extracting oil from offshore have the same interest as well. However, they could not both achieve optimization by adopting the same strategy and enjoy the maximum profit. Thus the leaders in OPEC planned a way to regain the market by adopting the game theory model: price war - to compete at a cost of its own profits in order to drive down oil price and to undermine competing producers. This was a favorable strategy for OPEC (mainly Saudi Arabia) as it only costs $25-$30 USD per barrel to extract conventional oil from the Persian Gulf, as opposed to about $55-60 USD per barrel from shale oil production. Hence, as long as the oil price remains below mid 50s, shale producers would find themselves unprofitable and eventually be forced out of the market (note: Many shale producers are partnership funded by investors, and investors focus on dividends and returns from private business periodically)

In basic economic fundamentals, when supply exceeds demand, price goes down. Controlling the supply was exactly how the OPEC drove down the price of oil. Since the middle of 2014, OPEC decided to remain or even to increase production despite weaker demands due to slowing global economic growth. This caused a sharp decline in oil price, from $115 in July 2014 to $59 in December 2014. In 2015 OPEC continued to over-produce, which caused many shale producers to halt dividends and discontinue investments and projects. The downward momentum in price persisted into late 2015 when the price finally tumbled below $40, leaving not only shale producers to exit the business, but the revenues of many major oil producing countries also drastically reduced. With the cost of oil production, countries like Russia, Nigeria, Mexico, Canada, and Brazil are not be able to break-even and any production is operating under negative profit margin.

A simple table below explains the price war in Game Theory:

Profit/bbl: OPEC, Shale Producers
OPEC OPEC
Maximize Production Control Production
Shale Producers Maximize Production Price: $35

$5, $-25
Price: $75

$45, $15
Shale Producers Control Production Price: $65

$35, $5
Price: $115

$85, $55


For countries with oil export as a large source of revenue, the price war can turn the economies into deficits or even on verges of collapses. Even for Saudi Arabia, as the country had been spending heavily for the war in Yemen as well as addressing its own issues in the country, the tumbling oil price will only hurt the economy further. In the end, did Saudi Arabia win in the price war and eliminate competitions? Yes; but the bigger question is: when 80% of the country’s revenue comes from oil sales, is this the best strategy to adopt?

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Update Jan 21 2016

Some updates on the continuation of the oil price turmoil:

Saudi Arabia
‧ Reported second quarters of trade deficits at -$8bil USD, albeit favorable comparing to the previous quarter of -$11bil USD
‧ Plans an IPO of Aramco, the state-owned oil giant, in order to find capitals for its exploration and production assets
‧ Plans to issue debt for the first time to fund budget deficit
‧ In talks with the two largest Chinese petroleum companies, China National Petroleum Corp (PetroChina) and China Petroleum & Chemical Corp (Sinopec) to invest in projects to build refineries in China.

Iran
‧ Sanctions have been lifted and Iran can return to the world oil market; plans to ramp up production to 500K barrels a day

Venezuela
‧ Requested an emergency OPEC meeting to discuss plans to curb productions in order to drive prices back upward
‧ As petroleum represents more than 95% of the country’s exports and 38% of total GDP, at current rate the export will generate $27bil in this year, down from $75bil two years before
‧ The country owes over $10 bil in debt payments and is on the brink of going to default
‧ With high inflations and shrinkage, the government can’t pay to import basic food items

United States
‧ As of Jan 15, inventories rose to a record level of 485.2 million
‧ 40 companies have filed for bankruptcy
‧ Oil boomtowns like Pearsall, TX., and Fargo, ND. have turn into ghost towns
‧ Output is expected to reduce drastically

Europe
‧ Oil giant Royal Dutch Shell saw profits tumbled 40%, has reduced 7,500 jobs last year and plans for additional reductions.
‧ Competitor BP plans to eliminate 4,000 positions exploration and production jobs, in additions to 4,000 job cuts from previous year

As price drops below the psychological significant level of $30, producers are getting gloomier at the potential recovery and shutting down production as current contracts are fulfilled. The turmoil also sends the currencies of the petrostates (petroleum as a large % of state revenue) to record low against the USD. IMO, Saudi's plan to continue draining reserves, producing at an 80% discount in order to dominate market share to the point of borrowing to fund budget deficit, is an imbecile move. I suspect that they will have trouble getting great rates: given the country's budget dependency (or lifeline) on a commodity that they are willing to drain and destroy the price at anytime. Think about it this way, who wants to buy Apple's stock if the company willingly discounts its iphone price by 80% anytime just to start a price war with other phone makers?