打了長達十二年官司，浪費了加拿大納稅千萬元的訴仲開支後，賴昌星終於被遣返中國。他是中國史上最大經濟犯罪案，走私金額八百億元，行賄涉及超過千多名官員，遠華走私集團的幕後主腦。他觸犯中國法律是無可爭議的事實，新聞報導特別是華語媒體， 大多一面倒把他描述為壞人，可是他是否真的是罪有應得，原先的死刑或現在講數後的無期徒刑呢。我想力排罛議為他平反，也許正如他自已所說，不過是政治鬥爭下的犧牲品。

賴昌星並非什麼十惡不赦的壞人，大家不要以為犯了法就一定是壞人，特別是中國不合理的法制。在中國行多不合法的事情，在外國可是天經地義的人權。看賴昌星在遠華走私案的罪行，他的罪名不過是走私汽油、植物油、汽車、香煙，經營紅樓妓院和行賄官員。容大家細聽我的理由，為賴昌星的三宗罪逐一平反，證明他人雖犯中國法律，但道德上他並沒有犯罪，錯的只是中國不合理的法制。

賴昌星的一宗罪是走私逃稅，但他並不是走私害人的軍火毒品，他走私的是一般市民日常生活用的貨品。在一個連外國遊客帶iPad自用，入境也要打稅的國家，可見中國的關稅是多麼的不合理。當政府用其軍政暴力，合法地以稅收為名強搶人民財產，或以國營企業壟斷市場，走私商人是必定應運而生，為人民提供廉價的選擇，賴昌星是經濟定律下的必然產物。有人說會逃稅不對，納稅是人民的義務，但這只適用於經由人民受權，其管治合法性建立在民主之上的政府。美國國父曾說過：No taxation without representation，沒有代表權就不用交稅。中共槍桿子裏出政黨，交了稅也只是落入貪官口袋中，人民完全沒有交稅的義務。賴昌星走私為人民帶來好處，免受政府苛稅的剝削，他是反抗暴政的現代羅賓漢。

他的第二宗罪是開紅樓妓院，色情行業是人類最古老的行業，同樣也是經濟定律下的必然產物。他的紅樓走高檔消費路線，並非黑社會逼良為娼，為買賣雙方你情我願的僱傭關係。在澳洲開妓院是可以掛牌上市的正當行業，中國的官員則只許自已包養情婦，不許民間開妓寨或嫖妓，明顯的雙重標準。

他的最後一宗罪是行賄官員，在一個無官不貪，官員權力和責任完全不受人民監管的國家，不行賄根本不能做生意。賴昌星行賄的金額數目龐大，只不過是因為他的生意太成功，要應付大量前來索取利益的官員，必需所付出的運作成本。可惜他選錯了靠山，後台在政治鬥爭中落敗，才給拿出來祭旗演場反貪戲。若果真的是公正地依法辨事，從上到下中國沒有一個官員不用坐牢。要根治貪污，必需要從政治制度入手，開放言論自由，讓人跟監察官員，並做好好保謢人民財產和權益，不讓官員濫權敲詐勒索人民自肥，否則捉了一個賴昌星，還有千千萬萬個賴昌星，因為這也是經濟定律下的必然產物。

賴昌星是一個不幸的人，他有生意頭腦白手興家，只是出生在一個錯誤的國家。若他生在一個經濟自由，民主開放，政府依法管治的地方，做生意不用依靠官員關係，不行賄也不怕受官員滋擾，賴昌星說不定會成為物流業和色情業大享，光明正大地當上市公司的主席啊。

(刊於蘋果日報2011年8月1日)

說在前頭這篇書評有點膳稿的味道﹐《不方便的通識》的作者謝毅﹐是很少數我從網絡萍水相逢﹐變成變為現實中的朋友。他與我的政治和經濟理念十分相近﹐我們都是古典自由主義的支持者﹐難怪我們一見如故﹐有無數說不盡的話題。可是我的學術水平只是停留在吹水層次﹐人家便已是出版了兩本書的大作家。在香港芸芸眾多左傾的時事評論當中﹐他可是絕無僅有的右派擁躉﹐也算是一個另類聲音。

《不方便的通識》其實有點呃錢﹐這本書結集他在報章專欄﹐和他自己博客的發表過文章。讀者如果想省錢的話﹐大部份文章可以在薯淘同雞的網站觀看﹐不知道這本書是否改錯名﹐我原本以為書店會放在香港評論一欄﹐竟然給放了在中學生參考書一欄﹐與其他通識教育的雞精書放在一起。在此奉勸各位中學生﹐考試時千萬不要引用此書的觀點﹐因為有些事實只能知不能說﹐說出來便被扣上政治不正確的罪名﹐肯定不合改卷員的標準答案。

謝毅文章的觀點在香港的報章評論雖比較少見﹐但其思想脈絡與《經濟學人》的分析大同小異﹐反對大政府凡事都管﹐主張私有化和自由市場﹐反對最低工資﹐支持引入競爭﹐反對共產主義社會主義等等。可能是報紙專欄篇幅有限﹐很多文章只是宣示了立場﹐引用經濟學大師佛利民或海耶克的名言背書﹐外加一兩個粗淺經濟學推論作例子便算。大慨要遷就一般香港讀者的程度﹐實在沒有辨法說深入一點理論。謝毅寫文章有一個口頭襌﹐總愛在結尾時加句反問﹐有點硬銷讀者去讚同他的說法。其實一篇文章理據充份﹐推論嚴緊正確﹐結論自然順理成章﹐那句反問倒像在質疑讀者的智慧。以前在網上逐篇逐篇看不太覺﹐把所有文章放在一起讀﹐那句反問起來便有點刺眼。

網絡上有些人對謝毅不太客氣﹐如果不認識他的人單單閱讀他的文章﹐甚至會懷疑那些文章是否大商家出錢找人代寫﹐好粉飾香港歌舞昇平繼續賺其大錢。謝毅的文章用經濟學為骨幹﹐以分析整體總利益和效率為主﹐不免忽略左派常常強調公義的問題。如果他的文章在強調經濟學的結果之餘﹐還花點篇幅回應左派的攻擊﹐相信文章會更有說服力。除了他支持醫療私營化﹐我則認為醫療應該與警察消防一樣﹐本質上是公共事業外﹐基本上我大致認同謝毅的大部份觀點。

這本書的全部文章﹐我在網絡上早已看過﹐買書純萃是捧朋友場。買書另外還有一個目的﹐就是勉勵自己要發奮向上﹐如果謝毅都可以出書﹐無理由我唔可以出番本書嘛。

Offshore levy sounds like an economical suicide. Protectionism is never the solution. I do agree Andy Grove’s opinion about off source is long term problem as we are losing our technical expertise. My solution is two folds. On technology front, we have to move even even higher tech, use robots and automation to keep the cost advantage. On the political front, we have to change the unfair competition advantage in overseas countries even by overthrowing their government.

By Andy Grove, Jul 1, 2010, Bloomborg

Recently an acquaintance at the next table in a Palo Alto, California, restaurant introduced me to his companions: three young venture capitalists from China. They explained, with visible excitement, that they were touring promising companies in Silicon Valley. I’ve lived in the Valley a long time, and usually when I see how the region has become such a draw for global investments, I feel a little proud.

Not this time. I left the restaurant unsettled. Something didn’t add up. Bay Area unemployment is even higher than the 9.7 percent national average. Clearly, the great Silicon Valley innovation machine hasn’t been creating many jobs of late — unless you are counting Asia, where American technology companies have been adding jobs like mad for years.

The underlying problem isn’t simply lower Asian costs. It’s our own misplaced faith in the power of startups to create U.S. jobs. Americans love the idea of the guys in the garage inventing something that changes the world. New York Times columnist Thomas L. Friedman recently encapsulated this view in a piece called “Start-Ups, Not Bailouts.” His argument: Let tired old companies that do commodity manufacturing die if they have to. If Washington really wants to create jobs, he wrote, it should back startups.

Mythical Moment

Friedman is wrong. Startups are a wonderful thing, but they cannot by themselves increase tech employment. Equally important is what comes after that mythical moment of creation in the garage, as technology goes from prototype to mass production. This is the phase where companies scale up. They work out design details, figure out how to make things affordably, build factories, and hire people by the thousands. Scaling is hard work but necessary to make innovation matter.

The scaling process is no longer happening in the U.S. And as long as that’s the case, plowing capital into young companies that build their factories elsewhere will continue to yield a bad return in terms of American jobs.

Scaling used to work well in Silicon Valley. Entrepreneurs came up with an invention. Investors gave them money to build their business. If the founders and their investors were lucky, the company grew and had an initial public offering, which brought in money that financed further growth.

Intel Startup

I am fortunate to have lived through one such example. In 1968, two well-known technologists and their investor friends anted up $3 million to start Intel Corp., making memory chips for the computer industry. From the beginning, we had to figure out how to make our chips in volume. We had to build factories; hire, train and retain employees; establish relationships with suppliers; and sort out a million other things before Intel could become a billion-dollar company. Three years later, it went public and grew to be one of the biggest technology companies in the world. By 1980, which was 10 years after our IPO, about 13,000 people worked for Intel in the U.S.

Not far from Intel’s headquarters in Santa Clara, California, other companies developed. Tandem Computers Inc. went through a similar process, then Sun Microsystems Inc., Cisco Systems Inc., Netscape Communications Corp., and on and on. Some companies died along the way or were absorbed by others, but each survivor added to the complex technological ecosystem that came to be called Silicon Valley.

As time passed, wages and health-care costs rose in the U.S., and China opened up. American companies discovered they could have their manufacturing and even their engineering done cheaper overseas. When they did so, margins improved. Management was happy, and so were stockholders. Growth continued, even more profitably. But the job machine began sputtering.

U.S. Versus China

Today, manufacturing employment in the U.S. computer industry is about 166,000 — lower than it was before the first personal computer, the MITS Altair 2800, was assembled in 1975. Meanwhile, a very effective computer-manufacturing industry has emerged in Asia, employing about 1.5 million workers — factory employees, engineers and managers.

The largest of these companies is Hon Hai Precision Industry Co., also known as Foxconn. The company has grown at an astounding rate, first in Taiwan and later in China. Its revenue last year was $62 billion, larger than Apple Inc., Microsoft Corp., Dell Inc. or Intel. Foxconn employs more than 800,000 people, more than the combined worldwide head count of Apple, Dell, Microsoft, Hewlett-Packard Co., Intel and Sony Corp.

10-to-1 Ratio

Until a recent spate of suicides at Foxconn’s giant factory complex in Shenzhen, China, few Americans had heard of the company. But most know the products it makes: computers for Dell and HP, Nokia Oyj cell phones, Microsoft Xbox 360 consoles, Intel motherboards, and countless other familiar gadgets. Some 250,000 Foxconn employees in southern China produce Apple’s products. Apple, meanwhile, has about 25,000 employees in the U.S. — that means for every Apple worker in the U.S. there are 10 people in China working on iMacs, iPods and iPhones. The same roughly 10-to-1 relationship holds for Dell, disk-drive maker Seagate Technology, and other U.S. tech companies.

You could say, as many do, that shipping jobs overseas is no big deal because the high-value work — and much of the profits — remain in the U.S. That may well be so. But what kind of a society are we going to have if it consists of highly paid people doing high-value-added work — and masses of unemployed?

Since the early days of Silicon Valley, the money invested in companies has increased dramatically, only to produce fewer jobs. Simply put, the U.S. has become wildly inefficient at creating American tech jobs. We may be less aware of this growing inefficiency, however, because our history of creating jobs over the past few decades has been spectacular — masking our greater and greater spending to create each position.

Tragic Mistake

Should we wait and not act on the basis of early indicators? I think that would be a tragic mistake because the only chance we have to reverse the deterioration is if we act early and decisively.

Already the decline has been marked. It may be measured by way of a simple calculation: an estimate of the employment cost- effectiveness of a company. First, take the initial investment plus the investment during a company’s IPO. Then divide that by the number of employees working in that company 10 years later. For Intel, this worked out to be about $650 per job — $3,600 adjusted for inflation. National Semiconductor Corp., another chip company, was even more efficient at $2,000 per job.

Making the same calculations for a number of Silicon Valley companies shows that the cost of creating U.S. jobs grew from a few thousand dollars per position in the early years to $100,000 today. The obvious reason: Companies simply hire fewer employees as more work is done by outside contractors, usually in Asia.

Alternative Energy

The job-machine breakdown isn’t just in computers. Consider alternative energy, an emerging industry where there is plenty of innovation. Photovoltaics, for example, are a U.S. invention. Their use in home-energy applications was also pioneered by the U.S.

Last year, I decided to do my bit for energy conservation and set out to equip my house with solar power. My wife and I talked with four local solar firms. As part of our due diligence, I checked where they get their photovoltaic panels — the key part of the system. All the panels they use come from China. A Silicon Valley company sells equipment used to manufacture photo-active films. They ship close to 10 times more machines to China than to manufacturers in the U.S., and this gap is growing. Not surprisingly, U.S. employment in the making of photovoltaic films and panels is perhaps 10,000 — just a few percent of estimated worldwide employment.

Advanced Batteries

There’s more at stake than exported jobs. With some technologies, both scaling and innovation take place overseas. Such is the case with advanced batteries. It has taken years and many false starts, but finally we are about to witness mass- produced electric cars and trucks. They all rely on lithium-ion batteries. What microprocessors are to computing, batteries are to electric vehicles. Unlike with microprocessors, the U.S. share of lithium-ion battery production is tiny.

That’s a problem. A new industry needs an effective ecosystem in which technology knowhow accumulates, experience builds on experience, and close relationships develop between supplier and customer. The U.S. lost its lead in batteries 30 years ago when it stopped making consumer-electronics devices. Whoever made batteries then gained the exposure and relationships needed to learn to supply batteries for the more demanding laptop PC market, and after that, for the even more demanding automobile market. U.S. companies didn’t participate in the first phase and consequently weren’t in the running for all that followed. I doubt they will ever catch up.

Job Creation

Scaling isn’t easy. The investments required are much higher than in the invention phase. And funds need to be committed early, when not much is known about the potential market. Another example from Intel: The investment to build a silicon manufacturing plant in the 1970s was a few million dollars. By the early 1990s, the cost of the factories that would be able to produce the new Pentium chips in volume rose to several billion dollars. The decision to build these plants needed to be made years before we knew whether the Pentium chip would work or whether the market would be interested in it.

Lessons we learned from previous missteps helped us. Years earlier, when Intel’s business consisted of making memory chips, we hesitated to add manufacturing capacity, not being sure about the market demand in years to come. Our Japanese competitors didn’t hesitate: They built the plants. When the demand for memory chips exploded, the Japanese roared into the U.S. market and Intel began its descent as a memory-chip supplier.

Intel Experience

Though steeled by that experience, I remember how afraid I was as I asked the Intel directors for authorization to spend billions of dollars for factories to make a product that didn’t exist at the time for a market we couldn’t size. Fortunately, they gave their OK even as they gulped. The bet paid off.

My point isn’t that Intel was brilliant. The company was founded at a time when it was easier to scale domestically. For one thing, China wasn’t yet open for business. More importantly, the U.S. hadn’t yet forgotten that scaling was crucial to its economic future.

How could the U.S. have forgotten? I believe the answer has to do with a general undervaluing of manufacturing — the idea that as long as “knowledge work” stays in the U.S., it doesn’t matter what happens to factory jobs. It’s not just newspaper commentators who spread this idea.

Offshore Production

Consider this passage by Princeton University economist Alan S. Blinder: “The TV manufacturing industry really started here, and at one point employed many workers. But as TV sets became ‘just a commodity,’ their production moved offshore to locations with much lower wages. And nowadays the number of television sets manufactured in the U.S. is zero. A failure? No, a success.”

I disagree. Not only did we lose an untold number of jobs, we broke the chain of experience that is so important in technological evolution. As happened with batteries, abandoning today’s “commodity” manufacturing can lock you out of tomorrow’s emerging industry.

Our fundamental economic beliefs, which we have elevated from a conviction based on observation to an unquestioned truism, is that the free market is the best economic system — the freer, the better. Our generation has seen the decisive victory of free-market principles over planned economies. So we stick with this belief, largely oblivious to emerging evidence that while free markets beat planned economies, there may be room for a modification that is even better.

No. 1 Objective

Such evidence stares at us from the performance of several Asian countries in the past few decades. These countries seem to understand that job creation must be the No. 1 objective of state economic policy. The government plays a strategic role in setting the priorities and arraying the forces and organization necessary to achieve this goal.

The rapid development of the Asian economies provides numerous illustrations. In a thorough study of the industrial development of East Asia, Robert Wade of the London School of Economics found that these economies turned in precedent- shattering economic performances over the 1970s and 1980s in large part because of the effective involvement of the government in targeting the growth of manufacturing industries.

Consider the “Golden Projects,” a series of digital initiatives driven by the Chinese government in the late 1980s and 1990s. Beijing was convinced of the importance of electronic networks — used for transactions, communications and coordination — in enabling job creation, particularly in the less developed parts of the country. Consequently, the Golden Projects enjoyed priority funding. In time, they contributed to the rapid development of China’s information infrastructure and the country’s economic growth.

Job-Centric Economy

How do we turn such Asian experience into intelligent action here and now? Long term, we need a job-centric economic theory — and job-centric political leadership — to guide our plans and actions. In the meantime, consider some basic thoughts from a onetime factory guy.

Silicon Valley is a community with a strong tradition of engineering, and engineers are a peculiar breed. They are eager to solve whatever problems they encounter. If profit margins are the problem, we go to work on margins, with exquisite focus. Each company, ruggedly individualistic, does its best to expand efficiently and improve its own profitability. However, our pursuit of our individual businesses, which often involves transferring manufacturing and a great deal of engineering out of the country, has hindered our ability to bring innovations to scale at home. Without scaling, we don’t just lose jobs — we lose our hold on new technologies. Losing the ability to scale will ultimately damage our capacity to innovate.

Blade Didn’t Drop

The story comes to mind of an engineer who was to be executed by guillotine. The guillotine was stuck, and custom required that if the blade didn’t drop, the condemned man was set free. Before this could happen, the engineer pointed with excitement to a rusty pulley, and told the executioner to apply some oil there. Off went his head.

We got to our current state as a consequence of many of us taking actions focused on our own companies’ next milestones. An example: Five years ago, a friend joined a large VC firm as a partner. His responsibility was to make sure that all the startups they funded had a “China strategy,” meaning a plan to move what jobs they could to China. He was going around with an oil can, applying drops to the guillotine in case it was stuck. We should put away our oil cans. VCs should have a partner in charge of every startup’s “U.S. strategy.”

Financial Incentives

The first task is to rebuild our industrial commons. We should develop a system of financial incentives: Levy an extra tax on the product of offshored labor. (If the result is a trade war, treat it like other wars — fight to win.) Keep that money separate. Deposit it in the coffers of what we might call the Scaling Bank of the U.S. and make these sums available to companies that will scale their American operations. Such a system would be a daily reminder that while pursuing our company goals, all of us in business have a responsibility to maintain the industrial base on which we depend and the society whose adaptability — and stability — we may have taken for granted.

I fled Hungary as a young man in 1956 to come to the U.S. Growing up in the Soviet bloc, I witnessed first-hand the perils of both government overreach and a stratified population. Most Americans probably aren’t aware that there was a time in this country when tanks and cavalry were massed on Pennsylvania Avenue to chase away the unemployed. It was 1932; thousands of jobless veterans were demonstrating outside the White House. Soldiers with fixed bayonets and live ammunition moved in on them, and herded them away from the White House. In America! Unemployment is corrosive. If what I’m suggesting sounds protectionist, so be it.

Choice Is Simple

Every day, that Palo Alto restaurant where I met the Chinese venture capitalists is full of technology executives and entrepreneurs. Many of them are my friends. I understand the technological challenges they face, along with the financial pressure they are under from directors and shareholders. Can we expect them to take on yet another assignment, to work on behalf of a loosely defined community of companies, employees, and employees yet to be hired? To do so is undoubtedly naive. Yet the imperative for change is real and the choice is simple. If we want to remain a leading economy, we change on our own, or change will continue to be forced upon us.

在買「經濟殺手的告白」前﹐早已在網絡上看這本書的評論。全部也極力推介此書﹐說此書讓我們認識清楚美國的黑暗。書評亦不忘加兩插句反資本主義﹐反西方以發展為名剝削第三世界的感想。經濟殺手為跨國企業工作收受豐厚酬勞﹐運用各種正當或不正當的政治和經濟手段﹐在背後操控影響第三世界的獨裁者﹐讓他們淪為美國的經濟附庸國。經濟殺手和顧用他們的跨國企業﹐暗地裏為美國政府處理不方便正式出面辨的事情。美國政府和跨國企業關係千絲萬縷﹐合組成一個龐大的經濟利益複合體﹐在全球各地推動美國的經濟帝國主義。

此書的作者早年曾經濟殺手﹐退休後自己開設能源公司﹐亦受惠於跨國企業的關係網。晚年良心發現決心要寫這本書﹐揭發﹐美國政府與跨國企業的陰謀。我滿懷期望地閱讀這本書﹐想看看當年有什麼驚人內幕﹐經濟殺手如何呼風喚雨﹐左右一國之命運。豈料這本書只是一本自憐式的自傳﹐並附加充滿偏見的歷史課。作者一心要漂白自己的過去﹐不斷說自己一面當經濟殺手享受榮華富貴﹐一面看見落後國家人民生活貧困良心受責。不知是作者天真還是有意誤導讀者﹐他除了把自己包裝成經濟殺手污流中的清源﹐還把曾與他打交道的第三世國獨裁者﹐寫成一心一意要為國為民的大好人﹐美國政府和跨國企業則是貪婪自私的壞人﹐書中的世界黑白分明得讓我以為在看童話故事。

我原本以為經濟殺手的工係充滿刺激﹐是現實世界中的經濟占士邦。作者曾經做過的所謂壞事﹐不過是把經濟預測跨大﹐向落後國家的獨裁者行賄兼色誘﹐讓所屬的工程公司贏取發展合同。那年代貪污橫行﹐不作這些臺底交易﹐根本不可能做成生意。發達國家與落後國家做生意的人﹐豈不是每個都是經濟殺手。作者批評美國向落後國提供援助和借貸﹐而些金錢最終又流回美國的工程公司口袋中﹐當地的窮人沒有分到任何得益﹐國家卻背上了龐大債務﹐從此要用天然資源的收益去還債。虧作者還自稱是首席經濟顧問﹐他連經濟學的根本也搞錯﹐錢只是不過交易媒介﹐難道要向貧民派錢才算是援助。美國工程公司在當地興建的基建和發展﹐做完後又沒有帶走運回美國﹐那不就是美國政府的援助和借貸的結果。不過也很難責怪他不懂經濟學﹐因為他根本不是讀經濟出身﹐他的寫經濟報告也只是按上頭意思做假作數字。

若果他只是做數騙獨裁者也算了﹐想不到他亂作數據的習性不改﹐竟然在書中也做數騙讀者﹐好增加他美國陰謀論的說服力。第三十四章說厄瓜多爾淪為美國經濟傀儡後﹐貧窮人口大幅從50%上升至70%﹐失業率更高達嚇人的70%。我上Google核對資料﹐厄瓜多爾最近十年的失業率徘徊在10%﹐貧窮人口則下跌至36%。作者說厄瓜多爾外債增加倒是事實﹐不過恐怕相對於同期美國外債的增幅﹐厄瓜多爾的外債只是小意思。作者還批評世界貧富懸殊日益加劇﹐美國的經濟市國主義要負上全部責任。可是他忘記了計算過去三十年﹐發達國家人口平穩﹐落後國家的人口則大幅增長。落後國家沒有好好控制人口﹐不負責任地生育分薄人均資源﹐難道又是發達國家的錯。

作者不只經濟數據有問題﹐他的政治理念也很有問題。不知道是否他運氣不好﹐他曾到印尼﹐巴拿馬﹐沙地阿拉伯和厄瓜多爾當經濟殺手﹐那些國家到今天是第三世界的落後國家。反觀當年同樣是美國經濟附庸國的亞洲國家﹐日本﹐台灣﹐南韓﹐星加坡﹐今天已階身發達國家的行例﹐經濟實力之強足以和美國一較高下。到底是美國剝削第三世界讓他們走不出貧窮的困局﹐還是那些國家自己沒有好好把握美國提供的發展機會。作者中左派思想的毒太深﹐彷徘認定有錢便是原罪﹐發達國有義務無條件幫助窮國。發達國幫助窮國的義務﹐僅只於向他們提攜教育﹐讓窮國學習發達國進步之道。並不是窮國人什麼也不需要做﹐便要給他們餵飽飯食。作者甚至有點精神分裂﹐一邊控訴美國在落後國發展破壞當地的原始文化﹐另一邊又想落後國脫貧踏上小康之路。為什麼他不想想當地的原始文化﹐正正是落後國貧窮的原因嗎﹖看看亞洲國家與美國經濟接軌﹐三十年間便從一窮二白擠身經濟強國之例﹐甚至吸收了美國的文化後﹐加以改良反出口回美國去。

作者寫這本書﹐大慨認為讀者看完﹐會認定美國剝削窮國不公義。可是我卻看到另外的一種不公義﹐窮國不事生產持窮為惡﹐反過來剝削發達國家的不公義。書中提及巴拿馬和沙特阿拉伯﹐正好是不公義最明顯的例子。巴拿馬運河當年是美國出資興建﹐運河每年為巴拿馬人民帶來龐大經濟收益﹐可是巴拿馬政府還不知足﹐竟想把運河收歸國有侵佔全部收益﹐美國為保障自己的投資利益﹐派兵把諾列加趕下台也無可厚非。沙特阿拉伯坐擁大半中東石油﹐國家抬高石油價格坑發達國家錢﹐國庫的錢多到水浸。沙特國民從出生便不用工作﹐國家會養他們一生一世。書中說沙特人的文化很懶﹐過份到連順手把街上的垃圾捨起丟進垃圾筒﹐也認為是有失身沙特人份的事情。沙特人自己不事生產﹐卻霸佔著世界經濟命脈的石油﹐正如大地主的二世祖﹐自己不工作卻搾取辛勤工作農民的租金。發達國家賺回沙特的石油收益﹐不過是取回原本屬於他們的金錢。中國近年經濟起飛慢慢趕上發達國家﹐也許中國也要開始學習經濟殺手之道﹐保障天然資源的供應發展所需﹐不要被那些不事生產的落後國家﹐憑著手上天然資源開天殺價﹐剝削中國的努力成果。

相对优势永不消失
2003年12月22日
一位在攻读理工专业的同学，最近接二连三给我长信，声称自己发现了一个“没学过经济学就能发现、却长期被人忽视的”经济原理。

是的，时不时就会遇上这样的朋友。我以前公司的火头军，业余时间都泡在图书馆，撰写关于修筑连接深圳和珠海的大坝、藉此增加淡水供应的可行性报告。这几年，又有几个说自己创造了什么经济理论体系的找上门来。这些朋友喜欢闭门造车，有锲而不舍的精神。不是说他们的东西必定没有价值，只是机会不高。

回头说那位理工科的同学。我给他回信说：“读到第二行，我就决定不读下去了，因为你说一个国家的相对优势会消失。相对优势是永远不会消失的。为什么？你随便找本教科书琢磨琢磨，把自己的理解，用一百字写出来再说吧。”

他没理会，继续长篇大论。我倒是出于好奇，自己试了一下，把自己所理解的相对优势原理写出来。果然一百字就够了，没有为难他。是这样：“每个人的资源和时间有限，用来生产此，就不能生产彼。‘顾此’的成本就是‘失彼’；选择‘失彼’最小的‘顾此’，就是这个人的相对优势。由于这始终是自己跟自己比的结果，所以任何人都永远具有相对优势。”

这是说，没有人会在每一种工作上都是成本最高或成本最低的。想来真奇妙：即使别人样样都比我出色，但只要我跟他共处，只要我们有交换的自由，那么我就不可能一无是处。换言之，只要我从事与自己相比成本较低的工作，然后与他交换，那么双方就都会得益。成本的概念是要点。成本就是放弃了的最好机会。即使盖茨写程序比我快，做饭也比我香，但只要我跟他住一屋，他就会让我做饭（尽管没他做得香）。并不是因为我做饭比他好，而是因为他做饭的成本是放弃了的程序——他做饭的成本比我的高得多。

讓我這個經濟外行人﹐試試用一百字解釋相對優勢為什麼會消失。“如果一個地方負生產力﹐生產不足以扺賞最低生存所需消耗﹐那就沒有任何相對優勢了。可以想像沒有天然資源﹐又戰亂﹐又愛滋﹐又天災又飢荒的非洲小國﹐他們憑什麼和其他國家交易呢﹖用學術點的口吻來說﹐交易成本比生產力高時﹐相對優勢便不存在了。”噢~用了一百一十四個字﹐不過馬馬虎虎也算數喇。

用他文章的例子來解釋﹐如果我做飯不單只是不夠蓋茨香﹐而是我做出來的飯難吃到會食死人﹐蓋茨寧可寫少幾行程式自己煮飯﹐也不會和我交易讓我替他煮飯吧。又或者蓋茨間屋很大﹐他的房間離我房間很遠。他行過來我房吃飯所需的時間﹐比自己求其煮點東西吃的時間長﹐那他便不會行過來吃我煮的飯了。大慨這位經濟學博士﹐未見識過什麼是負生產力﹐沒有讀過張五常﹐竟然忘記考慮交易成本這個重要因素。

那網頁上的另外兩篇文章﹐經濟理論也同樣有根本性的致命毛病。讀者有興趣的話﹐可以玩找錯處遊戲﹐不過估中無獎。

The lefties always love trashing economy theories being the slave of the all evil capitalism. Maybe this article from the Economist, the stronghold from the right, would deliver debate ammo to the lefties, if they choose to misinterpret it for their convenience.

Jul 16th 2009 – The Economist
Although the crisis has exposed bitter divisions among economists, it could still be good for economics. Our first article looks at the turmoil among macroeconomists. Our second (see article) examines the foundations of financial economics

ROBERT LUCAS, one of the greatest macroeconomists of his generation, and his followers are “making ancient and basic analytical errors all over the place”. Harvard’s Robert Barro, another towering figure in the discipline, is “making truly boneheaded arguments”. The past 30 years of macroeconomics training at American and British universities were a “costly waste of time”.

To the uninitiated, economics has always been a dismal science. But all these attacks come from within the guild: from Brad DeLong of the University of California, Berkeley; Paul Krugman of Princeton and the New York Times; and Willem Buiter of the London School of Economics (LSE), respectively. The macroeconomic crisis of the past two years is also provoking a crisis of confidence in macroeconomics. In the last of his Lionel Robbins lectures at the LSE on June 10th, Mr Krugman feared that most macroeconomics of the past 30 years was “spectacularly useless at best, and positively harmful at worst”.

These internal critics argue that economists missed the origins of the crisis; failed to appreciate its worst symptoms; and cannot now agree about the cure. In other words, economists misread the economy on the way up, misread it on the way down and now mistake the right way out.

On the way up, macroeconomists were not wholly complacent. Many of them thought the housing bubble would pop or the dollar would fall. But they did not expect the financial system to break. Even after the seizure in interbank markets in August 2007, macroeconomists misread the danger. Most were quite sanguine about the prospect of Lehman Brothers going bust in September 2008.

Nor can economists now agree on the best way to resolve the crisis. They mostly overestimated the power of routine monetary policy (ie, central-bank purchases of government bills) to restore prosperity. Some now dismiss the power of fiscal policy (ie, government sales of its securities) to do the same. Others advocate it with passionate intensity.

Among the passionate are Mr DeLong and Mr Krugman. They turn for inspiration to Depression-era texts, especially the writings of John Maynard Keynes, and forgotten mavericks, such as Hyman Minsky. In the humanities this would count as routine scholarship. But to many high-tech economists it is a bit undignified. Real scientists, after all, do not leaf through Newton’s “Principia Mathematica” to solve contemporary problems in physics.

They accuse economists like Mr DeLong and Mr Krugman of falling back on antiquated Keynesian doctrines—as if nothing had been learned in the past 70 years. Messrs DeLong and Krugman, in turn, accuse economists like Mr Lucas of not falling back on Keynesian economics—as if everything had been forgotten over the past 70 years. For Mr Krugman, we are living through a “Dark Age of macroeconomics”, in which the wisdom of the ancients has been lost.

What was this wisdom, and how was it forgotten? The history of macroeconomics begins in intellectual struggle. Keynes wrote the “General Theory of Employment, Interest and Money”, which was published in 1936, in an “unnecessarily controversial tone”, according to some readers. But it was a controversy the author had waged in his own mind. He saw the book as a “struggle of escape from habitual modes of thought” he had inherited from his classical predecessors.

That classical mode of thought held that full employment would prevail, because supply created its own demand. In a classical economy, whatever people earn is either spent or saved; and whatever is saved is invested in capital projects. Nothing is hoarded, nothing lies idle.

Keynes appreciated the classical model’s elegance and consistency, virtues economists still crave. But that did not stop him demolishing it. In his scheme, investment was governed by the animal spirits of entrepreneurs, facing an imponderable future. The same uncertainty gave savers a reason to hoard their wealth in liquid assets, like money, rather than committing it to new capital projects. This liquidity-preference, as Keynes called it, governed the price of financial securities and hence the rate of interest. If animal spirits flagged or liquidity-preference surged, the pace of investment would falter, with no obvious market force to restore it. Demand would fall short of supply, leaving willing workers on the shelf. It fell to governments to revive demand, by cutting interest rates if possible or by public works if necessary.

The Keynesian task of “demand management” outlived the Depression, becoming a routine duty of governments. They were aided by economic advisers, who built working models of the economy, quantifying the key relationships. For almost three decades after the second world war these advisers seemed to know what they were doing, guided by an apparent trade-off between inflation and unemployment. But their credibility did not survive the oil-price shocks of the 1970s. These condemned Western economies to “stagflation”, a baffling combination of unemployment and inflation, which the Keynesian consensus grasped poorly and failed to prevent.

The Federal Reserve, led by Paul Volcker, eventually defeated American inflation in the early 1980s, albeit at a grievous cost to employment. But victory did not restore the intellectual peace. Macroeconomists split into two camps, drawing opposite lessons from the episode.

The purists, known as “freshwater” economists because of the lakeside universities where they happened to congregate, blamed stagflation on restless central bankers trying to do too much. They started from the classical assumption that markets cleared, leaving no unsold goods or unemployed workers. Efforts by policymakers to smooth the economy’s natural ups and downs did more harm than good.
Illustration by Brett Ryder

America’s coastal universities housed most of the other lot, “saltwater” pragmatists. To them, the double-digit unemployment that accompanied Mr Volcker’s assault on inflation was proof enough that markets could malfunction. Wages might fail to adjust, and prices might stick. This grit in the economic machine justified some meddling by policymakers.

Mr Volcker’s recession bottomed out in 1982. Nothing like it was seen again until last year. In the intervening quarter-century of tranquillity, macroeconomics also recovered its composure. The opposing schools of thought converged. The freshwater economists accepted a saltier view of policymaking. Their opponents adopted a more freshwater style of modelmaking. You might call the new synthesis brackish macroeconomics.
Pinches of salt

Brackish macroeconomics flowed from universities into central banks. It underlay the doctrine of inflation-targeting embraced in New Zealand, Canada, Britain, Sweden and several emerging markets, such as Turkey. Ben Bernanke, chairman of the Fed since 2006, is a renowned contributor to brackish economics.

For about a decade before the crisis, macroeconomists once again appeared to know what they were doing. Their thinking was embodied in a new genre of working models of the economy, called “dynamic stochastic general equilibrium” (DSGE) models. These helped guide deliberations at several central banks.

Mr Buiter, who helped set interest rates at the Bank of England from 1997 to 2000, believes the latest academic theories had a profound influence there. He now thinks this influence was baleful. On his blog, Mr Buiter argues that a training in modern macroeconomics was a “severe handicap” at the onset of the financial crisis, when the central bank had to “switch gears” from preserving price stability to safeguarding financial stability.

Modern macroeconomists worried about the prices of goods and services, but neglected the prices of assets. This was partly because they had too much faith in financial markets. If asset prices reflect economic fundamentals, why not just model the fundamentals, ignoring the shadow they cast on Wall Street?

It was also because they had too little interest in the inner workings of the financial system. “Philosophically speaking,” writes Perry Mehrling of Barnard College, Columbia University, economists are “materialists” for whom “bags of wheat are more important than stacks of bonds.” Finance is a veil, obscuring what really matters. As a poet once said, “promises of payment/Are neither food nor raiment”.

In many macroeconomic models, therefore, insolvencies cannot occur. Financial intermediaries, like banks, often don’t exist. And whether firms finance themselves with equity or debt is a matter of indifference. The Bank of England’s DSGE model, for example, does not even try to incorporate financial middlemen, such as banks. “The model is not, therefore, directly useful for issues where financial intermediation is of first-order importance,” its designers admit. The present crisis is, unfortunately, one of those issues.

The bank’s modellers go on to say that they prefer to study finance with specialised models designed for that purpose. One of the most prominent was, in fact, pioneered by Mr Bernanke, with Mark Gertler of New York University. Unfortunately, models that include such financial-market complications “can be very difficult to handle,” according to Markus Brunnermeier of Princeton, who has handled more of these difficulties than most. Convenience, not conviction, often dictates the choices economists make.

Convenience, however, is addictive. Economists can become seduced by their models, fooling themselves that what the model leaves out does not matter. It is, for example, often convenient to assume that markets are “complete”—that a price exists today, for every good, at every date, in every contingency. In this world, you can always borrow as much as you want at the going rate, and you can always sell as much as you want at the going rate.

Before the crisis, many banks and shadow banks made similar assumptions. They believed they could always roll over their short-term debts or sell their mortgage-backed securities, if the need arose. The financial crisis made a mockery of both assumptions. Funds dried up, and markets thinned out. In his anatomy of the crisis Mr Brunnermeier shows how both of these constraints fed on each other, producing a “liquidity spiral”.

What followed was a furious dash for cash, as investment banks sold whatever they could, commercial banks hoarded reserves and firms drew on lines of credit. Keynes would have interpreted this as an extreme outbreak of liquidity-preference, says Paul Davidson, whose biography of the master has just been republished with a new afterword. But contemporary economics had all but forgotten the term.
Fiscal fisticuffs

The mainstream macroeconomics embodied in DSGE models was a poor guide to the origins of the financial crisis, and left its followers unprepared for the symptoms. Does it offer any insight into the best means of recovery?

In the first months of the crisis, macroeconomists reposed great faith in the powers of the Fed and other central banks. In the summer of 2007, a few weeks after the August liquidity crisis began, Frederic Mishkin, a distinguished academic economist and then a governor of the Fed, gave a reassuring talk at the Federal Reserve Bank of Kansas City’s annual symposium in Jackson Hole, Wyoming. He presented the results of simulations from the Fed’s FRB/US model. Even if house prices fell by a fifth in the next two years, the slump would knock only 0.25% off GDP, according to his benchmark model, and add only a tenth of a percentage point to the unemployment rate. The reason was that the Fed would respond “aggressively”, by which he meant a cut in the federal funds rate of just one percentage point. He concluded that the central bank had the tools to contain the damage at a “manageable level”.

Since his presentation, the Fed has cut its key rate by five percentage points to a mere 0-0.25%. Its conventional weapons have proved insufficient to the task. This has shaken economists’ faith in monetary policy. Unfortunately, they are also horribly divided about what comes next.

Mr Krugman and others advocate a bold fiscal expansion, borrowing their logic from Keynes and his contemporary, Richard Kahn. Kahn pointed out that a dollar spent on public works might generate more than a dollar of output if the spending circulated repeatedly through the economy, stimulating resources that might otherwise have lain idle.

Today’s economists disagree over the size of this multiplier. Mr Barro thinks the estimates of Barack Obama’s Council of Economic Advisors are absurdly large. Mr Lucas calls them “schlock economics”, contrived to justify Mr Obama’s projections for the budget deficit. But economists are not exactly drowning in research on this question. Mr Krugman calculates that of the 7,000 or so papers published by the National Bureau of Economic Research between 1985 and 2000, only five mentioned fiscal policy in their title or abstract.

Do these public spats damage macroeconomics? Greg Mankiw, of Harvard, recalls the angry exchanges in the 1980s between Robert Solow and Mr Lucas—both eminent economists who could not take each other seriously. This vitriol, he writes, attracted attention, much like a bar-room fist-fight. But he thinks it also dismayed younger scholars, who gave these macroeconomic disputes a wide berth.

By this account, the period of intellectual peace that followed in the 1990s should have been a golden age for macroeconomics. But the brackish consensus also seems to leave students cold. According to David Colander, who has twice surveyed the opinions of economists in the best American PhD programmes, macroeconomics is often the least popular class. “What did you learn in macro?” Mr Colander asked a group of Chicago students. “Did you do the dynamic stochastic general equilibrium model?” “We learned a lot of junk like that,” one replied.

The benchmark macroeconomic model, though not junk, suffers from some obvious flaws, such as the assumption of complete markets or frictionless finance. Indeed, because these flaws are obvious, economists are well aware of them. Critics like Mr Buiter are not telling them anything new. Economists can and do depart from the benchmark. That, indeed, is how they get published. Thus a growing number of cutting-edge models incorporate one or two financial frictions. And economists like Mr Brunnermeier are trying to fit their small, “blackboard” models of the crisis into a larger macroeconomic frame.

But the benchmark still matters. It formalises economists’ gut instincts about where the best analytical cuts lie. It is the starting point to which the theorist returns after every ingenious excursion. Few economists really believe all its assumptions, but few would rather start anywhere else.

Unfortunately, it is these primitive models, rather than their sophisticated descendants, that often exert the most influence over the world of policy and practice. This is partly because these first principles endure long enough to find their way from academia into policymaking circles. As Keynes pointed out, the economists who most influence practical men of action are the defunct ones whose scribblings have had time to percolate from the seminar room to wider conversations.

These basic models are also influential because of their simplicity. Faced with the “blooming, buzzing confusion” of the real world, policymakers often fall back on the highest-order principles and the broadest presumptions. More specific, nuanced theories are often less versatile. They shed light on whatever they were designed to explain, but little beyond.

Would economists be better off starting from somewhere else? Some think so. They draw inspiration from neglected prophets, like Minsky, who recognised that the “real” economy was inseparable from the financial. Such prophets were neglected not for what they said, but for the way they said it. Today’s economists tend to be open-minded about content, but doctrinaire about form. They are more wedded to their techniques than to their theories. They will believe something when they can model it.

Mr Colander, therefore, thinks economics requires a revolution in technique. Instead of solving models “by hand”, using economists’ powers of deduction, he proposes simulating economies on the computer. In this line of research, the economist specifies simple rules of thumb by which agents interact with each other, and then lets the computer go to work, grinding out repeated simulations to reveal what kind of unforeseen patterns might emerge. If he is right, then macroeconomists, like zombie banks, must write off many of their past intellectual investments before they can make progress again.

Mr Krugman, by contrast, thinks reform is more likely to come from within. Keynes, he observes, was a “consummate insider”, who understood the theory he was demolishing precisely because he was once convinced by it. In the meantime, he says, macroeconomists should turn to patient empirical spadework, documenting crises past and present, in the hope that a fresh theory might later make sense of it all.

Macroeconomics began with Keynes, but the word did not appear in the journals until 1945, in an article by Jacob Marschak. He reviewed the profession’s growing understanding of the business cycle, making an analogy with other sciences. Seismology, for example, makes progress through better instruments, improved theories or more frequent earthquakes. In the case of economics, Marschak concluded, “the earthquakes did most of the job.”

Economists were deprived of earthquakes for a quarter of a century. The Great Moderation, as this period was called, was not conducive to great macroeconomics. Thanks to the seismic events of the past two years, the prestige of macroeconomists is low, but the potential of their subject is much greater. The furious rows that divide them are a blow to their credibility, but may prove to be a spur to creativity.

我大學時代讀過幾科經濟學﹐張五常那套經濟學書也看了幾遍﹐加上其他零星的經濟學課外讀物﹐《臥底經濟學家》一書裏面的知識﹐我應該全部懂得明白﹐當然記不記得是另一回事。這本書的經濟學深入淺出﹐沒有圖表沒有方程式﹐不過是基本的經濟定律﹐就足以讓我們理解處身的世界是如何運作。作者從火車站的咖啡店的價錢牌說起﹐討論供求問題和議價能力﹐解釋為什麼地主一定會加租。從超市商品價格的差異﹐討論供求彈性和格價的策略。用駕車帶來的塞車和污染來討論界外效應﹐而二手車市場和保險則討論資訊成本和資訊不對等。第六章理性的瘋狂是全書最精彩一章﹐講述在股市中每一個人作出理性選擇﹐但把他們作為一個群體綜合起來﹐結果就會變成的非理性選擇﹐投資股票時要切記這章的教訓。最後幾章講市場帶來價格訊息的重要﹐全球化的好處和窮國為什麼貧窮﹐而最後則以分析中國改革開放以來的經濟奇蹟作為全書終結。

與其他高談經濟學理論的書不同﹐這本書從現實中的現象出發﹐解釋我們身邊發生的事物為什麼會是這樣發生。作者是一個說故事的能手﹐他沒有一開始抬出經濟理論嚇死讀者﹐而是抽絲剝繭一步一步去推論﹐與讀者一起找出穩藏在事物背後的經濟定律。事中那些現實的例子很有趣﹐引起讀者想一探究竟的好奇心﹐亦幫助讀者把經濟理論牢記腦中。學懂了書中的經濟理論﹐像武林密笈的內功心法般﹐一理通百理明應用任何地方﹐可以自己他也當一個臥底經濟學家﹐分析日常社會現象的前因後果。像近期熱門的社會議題﹐如最低工資﹐的士減價﹐派消費卷等﹐若我們透過經濟學家的眼光去看﹐就不會只看到表面的民粹口號﹐而看到背後市場失衝的真正問題。

Quote from The Economist Feb 1st 2001 “Debating the Minimum Wage”
that the minimum-wage increase left the overall number of workers employed roughly the same, but reduced their hours. (Not implausible, given that most workers in the fast-food business are part-timers.) Then it would be true that the wage rise reduced the demand for (hours of) labour, as the standard model says; but at the same time it could also be true, as advocates of the minimum wage say, that the incomes of the affected workers went up, thanks to the combination of fewer hours at work and the higher wage rate. In which case the policy could be judged a success, even though it had “reduced employment”.

簡單來說﹐最低工資的結果﹐將會是工資上升﹐工時需求下降﹐但就業人數大致不變。經濟理論指出工資上升﹐工作的需求會下降﹐只不過下降的不是工人需求的數目﹐而是工時需求的數目。 換一句話說﹐最低工資逼工人增加工作效率﹐去補償工資上升帶來的開支。不論是最低工資的支持者還是反對者﹐大家圍著就業人數這個數字原地打轉。工作需求除了可以用人頭來計數﹐還可以有其他的計算方法﹐如工時需求啊﹗

右派與左派的政治思想﹐其中一個最大的分別﹐是在於如何去介定何謂公平。究竟生產力高收入高是公平﹐還是人人收入均等才叫公平呢。最低工資支持者認為﹐工人收入低就是不公平。可是若果有最低工資﹐工人生產力多寡與收入脫勾﹐這又是否公平呢。有些工作的薪金過低是事實﹐可是這些工作可能真的生產力很低﹐低到不足以抵消工人的生活開支。工作時間長甚至勤力﹐並不等同生產力﹐生產出來的商品或服務不一定有人要﹐若有人要也不一定買到出足夠生活的金錢。試想象一個古代的農村經濟﹐有些農夫生產很多糧食﹐可以有多餘的糧食去和其他人交換物件。可是有些農夫生產糧食很少﹐有時連自己也餵不飽﹐那個農夫要挨餓又是否不公平。還是有多餘糧食的農夫﹐要無條件去餵飽其他吃不飽的農夫才叫公平。當然站在人道立場﹐我們也不希望見到其他人挨餓﹐把自己多餘的分給別人﹐只是這叫作善心而不是叫公平。

有些最低工資支持者會說﹐工人要賺到足夠基本生活需要的人工才算公平。好吧﹐讓先假設我們接受這個公平的定義﹐看看會申引出什麼問題。最低工資支持者看來忘記了一點﹐失業工人和領綜援的人也是人﹐若果工人要有足夠基本生活需要的才算公平﹐言下之意是否沒有工作的人就不需要基本生活需要。這算不算歧視沒有工作比低收入工人更貧窮的那群人﹐不用理會他們的基本生活需要﹐任由他們餓死呢。好吧﹐讓他們修改公平的定義﹐改為每個人也要有足夠基本生活需要的入息才算公平。用這個新的公平定義沒有雙重標準﹐不過又會帶出另一個更嚴重的問題。若最低工資等於基本生活需要的話﹐綜援金額也要增加至最低工資的水平﹐才算付合公平的原則。咦~ 最低工資等於綜援金額﹐做又三十六﹐唔做又三十六﹐白痴也看到有問題。唯一可能的解釋﹐就是最低工資支持者說謊﹐最低工資其實比基本生活需要為高。至於最低工資能否為貧窮劃上句號﹐大慨只有全部人有工做﹐零失業率的情況下才做到﹐基本上即是沒有可能發生。說最低工資可以為貧窮劃上句號﹐又算不算是跨大效益﹐刻意誤導市民呢﹖

人類是理性動物﹐為自己爭取最大利益無可厚非。在最低工資有人工加的基層是直接受益者﹐他們支持最低工資不難理解﹐天下間那有不想加人工的打工仔。另一邊廂請工人的老闆反對最低工資也很正常﹐那有老闆會想成本上漲影響生意。可是有些最低工資的支持者﹐基本上他們人工高加薪沒有份﹐他們支持最低工資的理由就很令人費解。若他們以為最低工資的成本全數由老闆支付﹐他們未免太過天真﹐簡直是向老闆與虎謀皮。若他們明知最低工資會導致消費開支增加﹐那麼支持最低工資豈不是與自己荷包作對。 或許他們有些人特別有正義感﹐認為工人有公平的收入比商品服務便宜重要。若他們真的這麼想﹐認為工人薪金過低工不合理﹐他們不用等最低工資立法﹐他們在購物或使用服務時﹐大可以給服務員大額小費﹐彌補市場價格與他們心中認為公平人工的差額﹐用實際行動去支持最低工資。可是綜觀支持最低工資的人﹐看不到有人主動支付差額的小費﹐莫非他們在講一套做一套﹐到真正付鈔時就打鼓退堂的偽善者﹖

怪不得最低工資的支持者口號叫得漂亮﹐卻找不到什麼合理的理由﹐去推翻反對最低工資者的質疑。支持者可以完全無視最低工資理論內的重重矛盾﹐非理性地盲目支持﹐要與他們說道理分析最低工資的利弊﹐大慨比說服老闆接受最低工資還困難。

先說那是工作需要最低工資﹐當然不會是高薪厚職的專業人仕﹐ 也不會是自負盈虧的大中小商人﹐需要特別知識的技工也不大可能。最低工資影響的工作﹐多數是低技術的體力勞動工作。若果工作要求有一定程度的技術﹐又或者需要多年相關工作經驗﹐工人本身的知識是生產力的重要因素﹐顧主轉換工人要付出額外成本﹐工資必定在高於最低工資。只有手板眼見的工作﹐顧主可以輕易替換工人﹐工人淪為純萃販賣勞動力的商品﹐顧主才可以以低於最低工資請人。這些工作通常在服務性行業﹐ 例如保安﹐清潔﹐收銀﹐待應﹐地盤﹐打雜等。從報紙所見那些工人的平均時薪只有十多元﹐而支持立法的團體提倡的最低工資大約三十元﹐人工的升幅接近一倍。推行最低工資﹐工人收入增加﹐ 我們需要問的第一個問題﹐到底加人工的錢從何來﹖

很多支持最低工資的人﹐很多一廂情願地以為那些顧主在剝削工人﹐加人工的錢自然在顧主的營利中扣除。沒有顧主會自願損失盈利﹐反正其他顧主的人工成本也同樣上升﹐不怕其他競爭對手割價拎生意﹐大可以把人工成本完全轉嫁消費者。推行最低工資﹐大慨所有服務會全線加價﹐加人工的成本最終由消費者負擔﹐亦是即基本上等於全港市民。除了直接受惠最低工資收入增加的工人外﹐甚他市民的生活質素恐怕會有所下降。收入高於最低工資的市民或許還可以擔負得起﹐最多只是減少服務減少消費。可是比基層工人生活還貧困的綜援人士﹐恐怕在百物騰貴物格高漲下﹐生活開支會百上加斤。最低工資影響物價帶來通漲﹐就算不計有可能增加的失業人口﹐綜援金額也要提升才能夠保持生活質素﹐這一來政府開支必然增加﹐恐怕要加稅才能收支平衡。最低收入的工人大慨不用納稅﹐稅收自然從其他人工較高市民的荷包而來﹐進一步打擊他們的消費意欲。我不知道市民的生活開支會上升多少﹐會不會帶來經濟放緩甚至衰退﹐最終令最低工資工作的需求減少﹐增加最低工作工人的失業率形成惡性循環。這個問題要經濟學家去回答﹐但在最低工資立法前﹐支持者有責任給香港市民一個明確答案。

也許最壞情況不會出現﹐人工只是經營成本的一部份﹐租金維持不變﹐原料也只是運費的部份上升﹐市民開支不會增加太多。可是我們也要考慮﹐最低工資對不同類型的企業的不同影響。最低工資對高技術高資本的企業影響不大﹐反正也沒有多少員工需要加人工去付合最低工資。低技術勞動力密集的企業﹐將會是最低工資的重災區﹐他們的經營成本很可能會大幅跳升。就算人工開支只佔10%﹐最低工資後人工支出倍增 ﹐經營成本就一下子升10%。那些企業可能只有幾個百份點的利潤﹐原本勉強有賺倒過變成蝕錢。高技術企業受到影響較少﹐在最低工資下有相對優勢﹐加價幅度可以定得比低技術企業低﹐能夠主動出擊搶佔市場。低技術企業受到成本上升和收低下降兩面夾攻﹐恐怕會有很多會難逃被市場淘汰的命運。若低技術企業挨不下去唯有關門大吉﹐那些低技術工人只好加入失業大軍。高技術企業市場佔有率增加﹐技術人材和機械的需求上升﹐帶動整個新興科技產業的發展﹐說不定反而有利香港經濟。雖然與最低工資的原意背道而馳﹐但簡接推動科技發展也不是壞事。