Income distribution

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Income_distribution

Share of income of the top 1% for selected developed countries, 1975 to 2015

In economics, income distribution covers how a country's total GDP is distributed amongst its population. Economic theory and economic policy have long seen income and its distribution as a central concern. Unequal distribution of income causes economic inequality which is a concern in almost all countries around the world.

About

Classical economists such as Adam Smith (1723–1790), Thomas Malthus (1766–1834), and David Ricardo (1772–1823) concentrated their attention on factor income-distribution, that is, the distribution of income between the primary factors of production (land, labour and capital). Modern economists have also addressed issues of income distribution, but have focused more on the distribution of income across individuals and households. Important theoretical and policy concerns include the balance between income inequality and economic growth, and their often inverse relationship.

The Lorenz curve can represent the distribution of income within a society. The Lorenz curve is closely associated with measures of income inequality, such as the Gini coefficient.

Measurement

Income before (green) and after (pink) taxes and Transfer payments for different income groups starting with the lowest quintile. Top 20% people take approximately 45% of the all income.

Main article: Income inequality metrics

The concept of inequality is distinct from that of poverty and fairness. Income inequality metrics (or income distribution metrics) are used by social scientists to measure the distribution of income, and economic inequality among the participants in a particular economy, such as that of a specific country or of the world in general. While different theories may try to explain how income inequality comes about, income inequality metrics simply provide a system of measurement used to determine the dispersion of incomes.

Limitations

There exist some problems and limitations in the measurement of inequality as there is a large gap between the national accounts (which focus on macroeconomic totals) and inequality studies (which focus on distribution).

The lack of a comprehensive measure about how the pretax income differs from the post-tax income makes hard to assess how government redistribution affects inequality.

There is not a clear view on how long-run trends in income concentration are shaped by the major changes in woman's labour force participation.

Income inequality and its causes

Main article: Economic inequality

Income inequality is one aspect of economic inequality. Incomes levels can be studied through taxation records and other historical documents. Capital in the Twenty-First Century (2013) by French economist Thomas Piketty is noted for its systematic collection and review of available data, especially concerning income levels; not all aspects of historical wealth distribution are similarly attested in the available records.

Causes of income inequality and of levels of economic equality/inequality include: labor economics, tax policies, other economic policies, labor union policies, Federal Reserve monetary policies & fiscal policies, the market for labor, abilities of individual workers, technology and automation, education, globalization, gender bias, racism, and culture.

How to improve income inequality

Taxes

The progressive income tax takes a larger percentage of high incomes and a smaller percentage of low incomes. Effectively, the poorest pay the least of their earned incomes on taxes which allows them to keep a larger percentage of wealth. Justification can be illustrated by a simple heuristic: The same dollar amount of money (e.g. $100) has a greater economic impact on only one party—the poor. That same amount has little economic impact on a wealthy individual, so the disparity is addressed by ensuring the richest individuals are taxed a greater share of their wealth. The state then uses the tax revenue to find necessary and beneficial activities for the society at large. Every person in this system would have access to the same social benefits, but the rich pay more for it, so progressive tax significantly reduces the inequality.

In-kind transfers

If a cash is given to a poor person, he or she may not make "the best" choice in case, what to buy for this extra money. Then, there is the solution in form of the food stamps or directly the food as an in-kind transfer to the poorest.

Housing subsidies

The rent and upkeep of housing form a large portion of spending in the lower income families. Housing subsidies were designed to help the poor obtaining adequate housing.

Welfare and Unemployment benefits

This provides actual money to the people with very low or no income and gives them an absolute freedom in decision-making how to use this benefit. This works best if we assume that they are rational and make decisions in their best interest.

Income mobility

Income mobility is another factor in the study of income inequality. It describes how people change their economic well-being, i.e. move in the hierarchy of earning power over their lifetime. When someone improves his economic situation, this person is considered upwardly mobile. Mobility can vary between two extremes: 1) rich people stay always rich and poor stay always poor: people cannot easily change their economic status and inequality then seems as a permanent problem. 2) individuals can easily shift their income class, e.g. from middle earning class to upper class or from lower class to middle class. Inequality is "fluid" and temporary so it does not create a serious permanent problem.

Measuring income mobility

Mobility is measured by the association between parents´ and adult children's socioeconomic standing, where higher association means less mobility. Socioeconomic standing is captured by four different measures:

1. Occupational status: – it is weighted average of the mean level of earnings and education of certain occupations. It has advantages such a collecting important information about parents, which can be reported retrospectively by adult children. It also remains relatively stable in between the occupation career so single measuring provides adequate information of long run standing. On the other hand, it has also limitations for the mobility analyzing. Whereas occupational earning of men usually tends to be higher than by women, by the occupational education it is the other way around.
2. Class mobility: – Classes are instead categorical groupings based on specific occupational assets that determine life chances as expressed in outcomes such as income, health or wealth.
3. Earnings mobility: – Earning mobility evaluates the relationship between two certain generations by means of linear regression (upper math) of the long transformed measure of children's and parents' earnings.
4. Total family income mobility and the mobility of women: – Old economic analysis has been making one mistake, that they did analysis that focused mostly on the father-son pairs and their individual earnings. In the last two decades, they have expanded their research and now they focus more on the mother-daughter pairs as well. Generally earnings provides a stable measure of well-being independently of another financial assets or any kind of transfers.

Distribution measurement internationally

Main article: List of countries by income inequality

Using Gini coefficients, several organizations, such as the United Nations (UN) and the US Central Intelligence Agency (CIA), have measured income inequality by country. The Gini index is also widely used within the World Bank. It is an accurate and reliable index for measuring income distribution on a country by country level. The Gini index measurements go from 0 to 1 for 1 being perfect inequality and 0 being perfect equality. The world Gini index is measured at 0.52 as of 2016.

2018 World gini Index

The World Inequality Lab at the Paris School of Economics published in December 2017 the World Inequality Report 2018 that provides estimates of global income and wealth inequality.

Trends

Idealized hypothetical Kuznets curve

Standard economic theory stipulates that inequality tends to increase over time as a country develops, and to decrease as a certain average income is attained. This theory is commonly known as the Kuznets curve after Simon Kuznets. However, many prominent economists disagree with the need for inequality to increase as a country develops. Further, empirical data on the proclaimed subsequent decrease of inequality is conflicting.

Across the board, a number of industries are stratified across the genders. This is the result of a variety of factors. These include differences in education choices, preferred job and industry, work experience, number of hours worked, and breaks in employment (such as for bearing and raising children). Men also typically go into higher paid and higher risk jobs when compared to women. These factors result in 60% to 75% difference between men's and women's average aggregate wages or salaries, depending on the source. Various explanations for the remaining 25% to 40% have been suggested, including women's lower willingness and ability to negotiate salary and sexual discrimination. According to the European Commission direct discrimination only explains a small part of gender wage differences.

A study by the Brandeis University Institute on Assets and Social Policy which followed the same sets of families for 25 years found that there are vast differences in wealth across racial groups in the United States. The wealth gap between Caucasian and African-American families studied nearly tripled, from $85,000 in 1984 to $236,500 in 2009. The study concluded that factors contributing to the inequality included years of home ownership (27%), household income (20%), education (5%), and familial financial support and/or inheritance (5%). In an analysis of the American Opportunity Accounts Act, a bill to introduce Baby Bonds, Morningstar reported that by 2019 white families had more than seven times the wealth of the average Black family, according to the Survey of Consumer Finances.

There are two ways of looking at income inequality, within country inequality (intra-country inequality) – which is inequality within a nation; or between country inequality (inter-country inequality) which is inequality between countries.

According to intra-country inequality at least in the OECD countries, a May 2011 report by OECD stated that the gap between rich and poor within OECD countries (most of which are "high income" economies) "has reached its highest level for over 30 years, and governments must act quickly to tackle inequality".

Furthermore, increased inter-country income inequality over a long period is conclusive, with the Gini coefficient (using PPP exchange rate, unweighted by population) more than doubling between 1820 and the 1980s from .20 to .52 (Nolan 2009:63). However, scholars disagree about whether inter-country income inequality has increased (Milanovic 2011), remained relatively stable (Bourguignon and Morrisson 2002), or decreased (Sala-i-Martin, 2002) since 1980. What Milanovic (2005)  calls the “mother of all inequality disputes” emphasizes this debate by using the same data on Gini coefficient from 1950 to 2000 and showing that when countries’ GDP per capita incomes are unweighted by population income inequality increases, but when they are weighted inequality decreases. This has much to do with the recent average income rise in China and to some extent India, who represent almost two-fifths of the world. Notwithstanding, inter-country inequality is significant, for instance as a group the bottom 5% of US income distribution receives more income than over 68 percent of the world, and of the 60 million people that make up the top 1% of income distribution, 50 million of them are citizens of Western Europe, North America or Oceania (Milanovic 2011:116,156).

Larry Summers estimated in 2007 that the lower 80% of families were receiving $664 billion less income than they would be with a 1979 income distribution, or approximately $7,000 per family. Not receiving this income may have led many families to increase their debt burden, a significant factor in the 2007–2009 subprime mortgage crisis, as highly leveraged homeowners suffered a much larger reduction in their net worth during the crisis. Further, since lower income families tend to spend relatively more of their income than higher income families, shifting more of the income to wealthier families may slow economic growth.

In a TED presentation shown here Archived 2014-03-01 at the Wayback Machine, Hans Rosling presented the distribution and change in income distribution of various nations over the course of a few decades along with other factors such as child survival and fertility rate.

As of 2018, Albania has the smallest gap in wealth distribution with Zimbabwe having the largest gap in wealth distribution.

Income distribution in different countries

Thailand

• Thailand has been ranked the world's third most unequal nation after Russia and India, with a widening gap between rich and poor according to Oxfam in 2016. A study by Thammasat University economist Duangmanee Laovakul in 2013 showed that the country's top 20 land owners owned 80 percent of the nation's land. The bottom 20 owned only 0.3 percent. Among those having bank deposits, 0.1 percent of bank accounts held 49 per cent of total bank deposits. As of 2019, Thai per capita income is US$8,000 a year. The government aims to raise it to US$15,000 (498,771 baht) per year, driven by average GDP growth of five to six percent. Under the 20-year national plan stretching out to 2036, the government intends to narrow the income disparity gap to 15 times, down from 20 times in 2018.

United States

Main article: Household income in the United States

Further information: Income inequality in the United States

2011: In the United States, income has become distributed more unequally over the past 30 years, with those in the top quintile (20 percent) earning more than the bottom 80 percent combined.

2019: The wealthiest 10% of American households control nearly 75% of household net worth.

• Post-tax Gini coefficient: 0.39.
• Unemployment rate: 4.4%.
• GDP per capita: $53 632.
• Poverty rate: 11.1%.

Low unemployment rate and high GDP are signs of the health of the U.S. economy. But there is almost 18% of people living below the poverty line and the Gini coefficient is quite high. That ranks the United States 9th income inequal in the world.

The U.S. has the highest level of income inequality among its (post-)industrialized peers. When measured for all households, U.S. income inequality is comparable to other developed countries before taxes and transfers, but is among the highest after taxes and transfers, meaning the U.S. shifts relatively less income from higher income households to lower income households. In 2016, average market income was $15,600 for the lowest quintile and $280,300 for the highest quintile. The degree of inequality accelerated within the top quintile, with the top 1% at $1.8 million, approximately 30 times the $59,300 income of the middle quintile.

The economic and political impacts of inequality may include slower GDP growth, reduced income mobility, higher poverty rates, greater usage of household debt leading to increased risk of financial crises, and political polarization. Causes of inequality may include executive compensation increasing relative to the average worker, financialization, greater industry concentration, lower unionization rates, lower effective tax rates on higher incomes, and technology changes that reward higher educational attainment.

United Kingdom

Inequality in the UK has been very high in the past, and did not change much until the onset of industrialization. Incomes used to be remarkably concentrated pre-industrial evolution: up to 40% of total income went into the pockets of the richest 5%. In the more recent years income distribution is still an issue. The UK experienced a large increase in inequality during the 1980s—the incomes of the highest deciles increase while everyone else was stagnant. Uneven growth in the years leading up to 1991 meant further increases in inequality. Throughout the 1990s and 2000s, more even growth across the distribution meant little changes in inequality, with rising incomes for everybody. In sight of Brexit, there is more predicted income distribution discrepancies between wages.

2019: The United Kingdom was doing a lot to reduce one of the widest gap between rich and poor citizens, what has led to getting on the 13th place in the ranking of income inequality in the world.

• Post-tax Gini coefficient: 0.35.
• Unemployment rate: 4.3%.
• GDP per capita: $39 425.
• Poverty rate: 11.1%.

Russia

• Post-tax Gini coefficient: 0.38.
• Unemployment rate: 5.2%.
• GDP per capita: $24 417.
• Poverty rate: NA.

Occupying the 11th place in the ranking of income inequality in the world. USA TODAY stated: "Russia has a Corruption Perceptions Index score of 28 – tied for the worst among OECD member states and affiliates and one of the lowest in the world. " The cause of the income gap are the close connections of Russian oligarchs and the government, thanks to these relationships oligarchs get lucrative business deals and earn more and more money.

South Africa

• Post-tax Gini coefficient: 0.62.
• Unemployment rate: 27.3%.
• GDP per capita: $12 287.
• Poverty rate: 26.6%.

The highest income inequality is in the South Africa, based on 2019 data. It is due to the recent policy of apartheid. There were huge differences between white and the other people, not only in wages, but also in the place they can enter and so on.

Development of income distribution as a stochastic process

It is difficult to create a realistic and not complicated theoretical model, because the forces determining the distribution of income (DoI) are varied and complex and they continuously interact and fluctuate.

In a model by Champernowne, the author assumes that the income scale is divided into an enumerable infinity of income ranges, which have uniform proportionate distribution. The development through time of the DoI between ranges is regarded to be a stochastic process. The income of any person in one year may depend on the income in the previous year and on a chance of progress. Assuming that to every "dying" income receiver, there is an heir to his or her income in the following year, and vice versa. This implies that the number of incomes is constant through time.

Under these assumptions any historical development of the DoI can be described by the following vectors and matrices.

• ${\displaystyle X_r(0)}$ ... number of the income receivers in range r = 1, 2, ... in the initial year ${\displaystyle Y_0}$
• ${\displaystyle p_{rs}^{\prime }(t)}$ ... matrix, that contains proportions of the occupants of r-th range in the year ${\displaystyle Y_t}$ shifted to the s-th range in the following year ${\displaystyle Y_{t+1}}$

The vector of the DoI can be expressed as

${\displaystyle X_s(t+1)=\sum _{r=0}^{\mathrm{\infty }}{X}_r(t)p_{rs}^{\prime }(t).}$

The elements of proportion matrices can be estimated from historical data.

Dot-com bubble

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Dot-com_bubble

The NASDAQ Composite index spiked in 2000 and then fell sharply as a result of the dot-com bubble.

Quarterly U.S. venture capital investments, 1995–2017

The dot-com bubble (or dot-com boom) was a stock market bubble that ballooned during the late-1990s and peaked on Friday, March 10, 2000. This period of market growth coincided with the widespread adoption of the World Wide Web and the Internet, resulting in a dispensation of available venture capital and the rapid growth of valuations in new dot-com startups.

Between 1995 and its peak in March 2000, investments in the NASDAQ composite stock market index rose 800%, only to fall 78% from its peak by October 2002, giving up all its gains during the bubble.

During the dot-com crash, many online shopping companies, notably Pets.com, Webvan, and Boo.com, as well as several communication companies, such as Worldcom, NorthPoint Communications, and Global Crossing, failed and shut down. Others, like Lastminute.com, MP3.com and PeopleSound remained through its sale and buyers acquisition. Larger companies like Amazon and Cisco Systems lost large portions of their market capitalization, with Cisco losing 80% of its stock value.

Background

Historically, the dot-com boom can be seen as similar to a number of other technology-inspired booms of the past including railroads in the 1840s, automobiles in the early 20th century, radio in the 1920s, television in the 1940s, transistor electronics in the 1950s, computer time-sharing in the 1960s, and home computers and biotechnology in the 1980s.

Overview

Low interest rates in 1998–99 facilitated an increase in start-up companies. Although a number of these new entrepreneurs had realistic plans and administrative ability, most of them lacked these characteristics but were able to sell their ideas to investors because of the novelty of the dot-com concept.

In 2000, the dot-com bubble burst, and many dot-com startups went out of business after burning through their venture capital and failing to become profitable. However, many others, particularly online retailers like eBay and Amazon, blossomed and became highly profitable. More conventional retailers found online merchandising to be a profitable additional source of revenue. While some online entertainment and news outlets failed when their seed capital ran out, others persisted and eventually became economically self-sufficient. Traditional media outlets (newspaper publishers, broadcasters and cablecasters in particular) also found the Web to be a useful and profitable additional channel for content distribution, and an additional means to generate advertising revenue. The sites that survived and eventually prospered after the bubble burst had two things in common: a sound business plan, and a niche in the marketplace that was, if not unique, particularly well-defined and well-served.

In the aftermath of the dot-com bubble, telecommunications companies had a great deal of overcapacity as many Internet business clients went bust. That, plus ongoing investment in local cell infrastructure kept connectivity charges low, and helped to make high-speed Internet connectivity more affordable. During this time, a handful of companies found success developing business models that helped make the World Wide Web a more compelling experience. These include airline booking sites, Google's search engine and its profitable approach to keyword-based advertising, as well as eBay's auction site and Amazon.com's online department store. The low price of reaching millions worldwide, and the possibility of selling to or hearing from those people at the same moment when they were reached, promised to overturn established business dogma in advertising, mail-order sales, customer relationship management, and many more areas. The web was a new killer app—it could bring together unrelated buyers and sellers in seamless and low-cost ways. Entrepreneurs around the world developed new business models, and ran to their nearest venture capitalist. While some of the new entrepreneurs had experience in business and economics, the majority were simply people with ideas, and did not manage the capital influx prudently. Additionally, many dot-com business plans were predicated on the assumption that by using the Internet, they would bypass the distribution channels of existing businesses and therefore not have to compete with them; when the established businesses with strong existing brands developed their own Internet presence, these hopes were shattered, and the newcomers were left attempting to break into markets dominated by larger, more established businesses.

The dot-com bubble burst in March 2000, with the technology heavy NASDAQ Composite index peaking at 5,048.62 on March 10 (5,132.52 intraday), more than double its value just a year before. By 2001, the bubble's deflation was running full speed. A majority of the dot-coms had ceased trading, after having burnt through their venture capital and IPO capital, often without ever making a profit. But despite this, the Internet continues to grow, driven by commerce, ever greater amounts of online information, knowledge, social networking and access by mobile devices.

Prelude to the bubble

See also: 1990s United States boom

The 1993 release of Mosaic and subsequent web browsers during the following years gave computer users access to the World Wide Web, popularizing use of the Internet. Internet use increased as a result of the reduction of the "digital divide" and advances in connectivity, uses of the Internet, and computer education. Between 1990 and 1997, the percentage of households in the United States owning computers increased from 15% to 35% as computer ownership progressed from a luxury to a necessity. This marked the shift to the Information Age, an economy based on information technology, and many new companies were founded.

At the same time, a decline in interest rates increased the availability of capital. The Taxpayer Relief Act of 1997, which lowered the top marginal capital gains tax in the United States, also made people more willing to make more speculative investments. Alan Greenspan, then-Chair of the Federal Reserve, allegedly fueled investments in the stock market by putting a positive spin on stock valuations. The Telecommunications Act of 1996 was expected to result in many new technologies from which many people wanted to profit.

The bubble

As a result of these factors, many investors were eager to invest, at any valuation, in any dot-com company, especially if it had one of the Internet-related prefixes or a ".com" suffix in its name. Venture capital was easy to raise. Investment banks, which profited significantly from initial public offerings (IPO), fueled speculation and encouraged investment in technology. A combination of rapidly increasing stock prices in the quaternary sector of the economy and confidence that the companies would turn future profits created an environment in which many investors were willing to overlook traditional metrics, such as the price–earnings ratio, and base confidence on technological advancements, leading to a stock market bubble. Between 1995 and 2000, the Nasdaq Composite stock market index rose 400%. It reached a price–earnings ratio of 200, dwarfing the peak price–earnings ratio of 80 for the Japanese Nikkei 225 during the Japanese asset price bubble of 1991. In 1999, shares of Qualcomm rose in value by 2,619%, 12 other large-cap stocks each rose over 1,000% in value, and seven additional large-cap stocks each rose over 900% in value. Even though the Nasdaq Composite rose 85.6% and the S&P 500 rose 19.5% in 1999, more stocks fell in value than rose in value as investors sold stocks in slower growing companies to invest in Internet stocks.

An unprecedented amount of personal investing occurred during the boom and stories of people quitting their jobs to trade on the financial market were common. The news media took advantage of the public's desire to invest in the stock market; an article in The Wall Street Journal suggested that investors "re-think" the "quaint idea" of profits, and CNBC reported on the stock market with the same level of suspense as many networks provided to the broadcasting of sports events.

At the height of the boom, it was possible for a promising dot-com company to become a public company via an IPO and raise a substantial amount of money even if it had never made a profit—or, in some cases, realized any material revenue. People who received employee stock options became instant paper millionaires when their companies executed IPOs; however, most employees were barred from selling shares immediately due to lock-up periods. The most successful entrepreneurs, such as Mark Cuban, sold their shares or entered into hedges to protect their gains. Sir John Templeton successfully shorted many dot-com stocks at the peak of the bubble during what he called "temporary insanity" and a "once-in-a-lifetime opportunity". He shorted stocks just before the expiration of lockup periods ending six months after initial public offerings, correctly anticipating many dot-com company executives would sell shares as soon as possible, and that large-scale selling would force down share prices.

Spending tendencies of dot-com companies

dot-com companies spent most of their investments in marketing efforts. Left: A promotional music CD for the Modo pager, Right: The Pets.com sock puppet

Most dot-com companies incurred net operating losses as they spent heavily on advertising and promotions to harness network effects to build market share or mind share as fast as possible, using the mottos "get big fast" and "get large or get lost". These companies offered their services or products for free or at a discount with the expectation that they could build enough brand awareness to charge profitable rates for their services in the future.

The "growth over profits" mentality and the aura of "new economy" invincibility led some companies to engage in lavish spending on elaborate business facilities and luxury vacations for employees. Upon the launch of a new product or website, a company would organize an expensive event called a dot-com party.

Bubble in telecom

In the five years after the American Telecommunications Act of 1996 went into effect, telecommunications equipment companies invested more than $500 billion, mostly financed with debt, into laying fiber optic cable, adding new switches, and building wireless networks. In many areas, such as the Dulles Technology Corridor in Virginia, governments funded technology infrastructure and created favorable business and tax law to encourage companies to expand. The growth in capacity vastly outstripped the growth in demand. Spectrum auctions for 3G in the United Kingdom in April 2000, led by Chancellor of the Exchequer Gordon Brown, raised £22.5 billion. In Germany, in August 2000, the auctions raised £30 billion. A 3G spectrum auction in the United States in 1999 had to be re-run when the winners defaulted on their bids of $4 billion. The re-auction netted 10% of the original sales prices. When financing became hard to find as the bubble burst, the high debt ratios of these companies led to bankruptcy. Bond investors recovered just over 20% of their investments. However, several telecom executives sold stock before the crash including Philip Anschutz, who reaped $1.9 billion, Joseph Nacchio, who reaped $248 million, and Gary Winnick, who sold $748 million worth of shares.

Bursting the bubble

See also: Early 2000s recession

Historical government interest rates in the United States

Nearing the turn of the 2000s, spending on technology was volatile as companies prepared for the Year 2000 problem. There were concerns that computer systems would have trouble changing their clock and calendar systems from 1999 to 2000 which might trigger wider social or economic problems, but there was virtually no impact or disruption due to adequate preparation. Spending on marketing also reached new heights for the sector: Two dot-com companies purchased ad spots for Super Bowl XXXIII, and 17 dot-com companies bought ad spots the following year for Super Bowl XXXIV.

On January 10, 2000, America Online, led by Steve Case and Ted Leonsis, announced a merger with Time Warner, led by Gerald M. Levin. The merger was the largest to date and was questioned by many analysts. Then, on January 30, 2000, 12 ads of the 61 ads for Super Bowl XXXIV were purchased by dot-coms (sources state ranges from 12 up to 19 companies depending on the definition of dot-com company). At that time, the cost for a 30-second commercial was between $1.9 million and $2.2 million.

Meanwhile, Alan Greenspan, then Chair of the Federal Reserve, raised interest rates several times; these actions were believed by many to have caused the bursting of the dot-com bubble. According to Paul Krugman, however, "he didn't raise interest rates to curb the market's enthusiasm; he didn't even seek to impose margin requirements on stock market investors. Instead, [it is alleged] he waited until the bubble burst, as it did in 2000, then tried to clean up the mess afterward". Finance author and commentator E. Ray Canterbery agreed with Krugman's criticism.

On Friday March 10, 2000, the NASDAQ Composite stock market index peaked at 5,048.62. However, on March 13, 2000, news that Japan had once again entered a recession triggered a global sell off that disproportionately affected technology stocks. Soon after, Yahoo! and eBay ended merger talks and the Nasdaq fell 2.6%, but the S&P 500 rose 2.4% as investors shifted from strong performing technology stocks to poor performing established stocks.

On March 20, 2000, Barron's featured a cover article titled "Burning Up; Warning: Internet companies are running out of cash—fast", which predicted the imminent bankruptcy of many Internet companies. This led many people to rethink their investments. That same day, MicroStrategy announced a revenue restatement due to aggressive accounting practices. Its stock price, which had risen from $7 per share to as high as $333 per share in a year, fell $140 per share, or 62%, in a day. The next day, the Federal Reserve raised interest rates, leading to an inverted yield curve, although stocks rallied temporarily.

Tangentially to all of speculation, Judge Thomas Penfield Jackson issued his conclusions of law in the case of United States v. Microsoft Corp. (2001) and ruled that Microsoft was guilty of monopolization and tying in violation of the Sherman Antitrust Act. This led to a one-day 15% decline in the value of shares in Microsoft and a 350-point, or 8%, drop in the value of the Nasdaq. Many people saw the legal actions as bad for technology in general. That same day, Bloomberg News published a widely read article that stated: "It's time, at last, to pay attention to the numbers".

On Friday, April 14, 2000, the Nasdaq Composite index fell 9%, ending a week in which it fell 25%. Investors were forced to sell stocks ahead of Tax Day, the due date to pay taxes on gains realized in the previous year. By June 2000, dot-com companies were forced to reevaluate their spending on advertising campaigns. On November 9, 2000, Pets.com, a much-hyped company that had backing from Amazon.com, went out of business only nine months after completing its IPO. By that time, most Internet stocks had declined in value by 75% from their highs, wiping out $1.755 trillion in value. In January 2001, just three dot-com companies bought advertising spots during Super Bowl XXXV. The September 11 attacks accelerated the stock-market drop. Investor confidence was further eroded by several accounting scandals and the resulting bankruptcies, including the Enron scandal in October 2001, the WorldCom scandal in June 2002, and the Adelphia Communications Corporation scandal in July 2002.

By the end of the stock market downturn of 2002, stocks had lost $5 trillion in market capitalization since the peak. At its trough on October 9, 2002, the NASDAQ-100 had dropped to 1,114, down 78% from its peak.

Aftermath

See also: List of companies affected by the dot-com bubble

After venture capital was no longer available, the operational mentality of executives and investors completely changed. A dot-com company's lifespan was measured by its burn rate, the rate at which it spent its existing capital. Many dot-com companies ran out of capital and went through liquidation. Supporting industries, such as advertising and shipping, scaled back their operations as demand for services fell. However, many companies were able to endure the crash; 48% of dot-com companies survived through 2004, albeit at lower valuations.

Several companies and their executives, including Bernard Ebbers, Jeffrey Skilling, and Kenneth Lay, were accused or convicted of fraud for misusing shareholders' money, and the U.S. Securities and Exchange Commission levied large fines against investment firms including Citigroup and Merrill Lynch for misleading investors.

After suffering losses, retail investors transitioned their investment portfolios to more cautious positions. Popular Internet forums that focused on high tech stocks, such as Silicon Investor, Yahoo! Finance, and The Motley Fool declined in use significantly.

Job market and office equipment glut

Layoffs of programmers resulted in a general glut in the job market. University enrollment for computer-related degrees dropped noticeably. Aeron chairs, which retailed for $1,100 each, were liquidated en masse.

Legacy

As growth in the technology sector stabilized, companies consolidated; some, such as Amazon.com, eBay, and Google gained market share and came to dominate their respective fields. The most valuable public companies are now generally in the technology sector.

In a 2015 book, venture capitalist Fred Wilson, who funded many dot-com companies and lost 90% of his net worth when the bubble burst, said about the dot-com bubble:

A friend of mine has a great line. He says "Nothing important has ever been built without irrational exuberance." Meaning that you need some of this mania to cause investors to open up their pocketbooks and finance the building of the railroads or the automobile or aerospace industry or whatever. And in this case, much of the capital invested was lost, but also much of it was invested in a very high throughput backbone for the Internet, and lots of software that works, and databases and server structure. All that stuff has allowed what we have today, which has changed all our lives... that's what all this speculative mania built.

Irrational exuberance

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Irrational_exuberance

"Irrational exuberance" is the phrase used by the then-Federal Reserve Board chairman, Alan Greenspan, in a speech given at the American Enterprise Institute during the dot-com bubble of the 1990s. The phrase was interpreted as a warning that the stock market might be overvalued.

Origin

Greenspan's comment was made during a televised speech on December 5, 1996 (emphasis added in excerpt):

Clearly, sustained low inflation implies less uncertainty about the future, and lower risk premiums imply higher prices of stocks and other earning assets. We can see that in the inverse relationship exhibited by price/earnings ratios and the rate of inflation in the past. But how do we know when irrational exuberance has unduly escalated asset values, which then become subject to unexpected and prolonged contractions as they have in Japan over the past decade?

— "The Challenge of Central Banking in a Democratic Society", 1996-12-05

The Tokyo market was open during the speech and immediately moved down sharply after this comment, closing off 3%. Markets around the world followed.

Greenspan wrote in his 2008 book that the phrase occurred to him in the bathtub while he was writing a speech.

The irony of the phrase and its aftermath lies in Greenspan's widely held reputation as the most artful practitioner of Fedspeak, often known as Greenspeak, in the modern televised era. The speech coincided with the rise of dedicated financial TV channels around the world that would broadcast his comments live, such as CNBC. Greenspan's idea was to obfuscate his true opinion in long complex sentences with obscure words so as to intentionally mute any strong market response.

The phrase was also used by Yale professor Robert J. Shiller, who was reportedly Greenspan's source for the phrase. Shiller used it as the title of his book, Irrational Exuberance, first published in 2000, where Shiller states:

Irrational exuberance is the psychological basis of a speculative bubble. I define a speculative bubble as a situation in which news of price increases spurs investor enthusiasm, which spreads by psychological contagion from person to person, in the process amplifying stories that might justify the price increases, and bringing in a larger and larger class of investors who, despite doubts about the real value of an investment, are drawn to it partly by envy of others' successes and partly through a gamblers' excitement.

Shiller is associated with the CAPE ratio and the Case–Shiller Home Price Index popularized during the housing bubble of 2004–2007. He is frequently asked during interviews whether markets are irrationally exuberant as asset prices rise. There was some speculation for many years whether Greenspan borrowed the phrase from Shiller without attribution, although Shiller later wrote that he contributed "irrational" at a lunch with Greenspan before the speech but "exuberant" was a previous Greenspan term and it was Greenspan who coined the phrase and not a speech writer.

Continued use

By the mid-to-late 2000s the dot-com losses were recouped and eclipsed by a combination of events, including the 2000s commodities boom and the United States housing bubble. However, the recession of 2007 onward wiped out these gains. The second market slump brought the phrase back into the public eye, where it was much used in hindsight, to characterize the excesses of the bygone era. In 2006, upon Greenspan's retirement from the Federal Reserve Board, The Daily Show with Jon Stewart held a full-length farewell show in his honor, named An Irrationally Exuberant Tribute to Alan Greenspan.

This combination of events caused the phrase at present to be most often associated with the 1990s dot-com bubble and the 2000s US housing bubble although it can be linked to any financial asset bubble or social frenzy phenomena, such as the tulip mania of 17th century Holland.

The phrase is often cited in conjunction with criticism of Greenspan's policies and debate whether he did enough to contain the two major bubbles of those two decades. It is also used in arguments about whether capitalist free markets are rational.

Robert J. Shiller, Nobel Prize Laureate and author of the seminal book Irrational Exuberance, called Bitcoin the best current example of a speculative bubble.

Theories of poverty

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Theories_of_poverty

Theories on the causes of poverty are the foundation upon which poverty reduction strategies are based.

While in developed nations poverty is often seen as either a personal or a structural defect, in developing nations the issue of poverty is more profound due to the lack of governmental funds. Some theories on poverty in the developing world focus on cultural characteristics as a retardant of further development. Other theories focus on social and political aspects that perpetuate poverty; perceptions of the poor have a significant impact on the design and execution of programs to alleviate poverty.

Causes of poverty in the United States

Poverty as a personal failing

See also: individualism and Infrahumanisation

When it comes to poverty in the United States, there are two main lines of thought. The most common line of thought within the U.S. is that a person is poor because of personal traits. These traits in turn have caused the person to fail. Supposed traits range from personality characteristics, such as laziness, to educational levels. Despite this range, it is always viewed as the individual's personal failure not to climb out of poverty. This thought pattern stems from the idea of meritocracy and its entrenchment within U.S. thought. Meritocracy, according to Katherine S. Newman is "the view that those who are worthy are rewarded and those who fail to reap rewards must also lack self-worth." This does not mean that all followers of meritocracy believe that a person in poverty deserves their low standard of living. Rather the underlying ideas of personal failure show in the resistance to social and economic programs such as welfare; a poor individual's lack of prosperity shows a personal failure and should not be compensated (or justified) by the state.

Poverty as a structural failing

Rank, Yoon, and Hirschl (2003) present a contrary argument to the idea that personal failings are the cause of poverty. The argument presented is that poverty in the United States is the result of "failings at the structural level." Key social and economic structural failings which contribute heavily to poverty within the U.S. are identified in the article. The first is a failure of the job market to provide a proper number of jobs which pay enough to keep families out of poverty. Even if unemployment is low, the labor market may be saturated with low-paying, part-time work that lacks benefits (thus limiting the number of full-time, good paying jobs). Rank, Yoon and Hirschl examined the Survey of Income and Program Participation (SIPP), a longitudinal study on employment and income. Using the 1999 official poverty line of $17,029 for a family of four, it was found that 9.4% of persons working full-time and 14.9% of persons working at least part-time did not earn enough annually to keep them above the poverty line.

One study showed that 29% of families in The United States could go six months or longer during a hardship with no income. Over 50% of respondents said around two months with no income and another 20% said they could not go longer than two weeks. Low minimum wage, combined with part-time jobs which offer no benefits, have contributed to the labor market's inability to produce enough jobs which can keep a family out of poverty is an example of an economic structural failure.

Rank, Yoon and Hirschl point to the minimal amount of social safety nets found within the U.S. as a social structural failure and a major contributor to poverty in the U.S. Other industrialized nations devote more resources to assisting the poor than the U.S. As a result of this difference poverty is reduced in nations which devote more to poverty reduction measure and programs. Rank et al. use a table to drive this point home. The table shows that in 1994, the actual rate of poverty (what the rate would be without government interventions) in the U.S. was 29%. When compared to actual rates in Canada (29%), Finland (33%), France (39%), Germany (29%), the Netherlands (30%), Norway (27%), Sweden (36%) and the United Kingdom (38%), the United States rate is low. But when government measures and programs are included, the rate of reduction in poverty in the United States is low (38%). Canada and the United Kingdom had the lowest reduction rates outside of the U.S. at 66%, while Sweden, Finland and Norway had reduction rates greater than 80%.

Additionally, filial responsibility laws are usually not enforced, resulting in parents of adult children remaining more impoverished than otherwise.

Causes of poverty in developing nations

Poverty as cultural characteristics

Development plays a central role to poverty reduction in third world countries. Some authors feel that the national mindset itself plays a role in the ability of a country to develop and to thus reduce poverty. Mariano Grondona (2000) outlines twenty "cultural factors" which, depending on the culture's view of each, can be indicators as to whether the cultural environment is favorable or resistant to development. In turn Lawrence E. Harrison (2000) identifies ten "values" which, like Grondona's factors, can be indicative of the nation's developmental environment. Finally, Stace Lindsay (2000) claims the differences between development-prone and development-resistant nations is attributed to mental models (which, like values, influence the decisions humans make). Mental models are also cultural creations. Grondona, Harrison and Lindsay all feel that without development-orientated values and mindsets, nations will find it difficult if not impossible to develop efficiently, and that some sort of cultural change will be needed in these nations in order to reduce poverty.

In "A Cultural Typology of Economic Development", from the book Culture Matters, Mariano Grondona claims development is a matter of decisions. These decisions, whether they are favorable to economic development or not, are made within the context of culture. All cultural values considered together create "value systems". These systems heavily influence the way decisions are made as well as the reactions and outcomes of said decisions. In the same book, Stace Lindsay's chapter claims the decisions individuals make are a result of mental models. These mental models influence all aspects of human action. Like Grondona's value systems, these mental models which dictate a nations stance toward development and hence its ability to deal with poverty.

Grondona presents two ideal value systems (mental models), one of which has values only favoring development, the other only with value which resist development. Real value systems fluctuate and fall somewhere between the two poles, but developed countries tend to bunch near one end, while undeveloped countries bunch near the other. Grondona goes on to identify twenty cultural factors on which the two value systems stand in opposition. These factors include such things as the dominant religion; the role of the individual in society; the value placed on work; concepts of wealth, competition, justice and time; and the role of education. In "Promoting Progressive Cultural Change", also from Culture Matters, Lawrence E. Harrison identifies values, like Grondona's factors, which differ between "progressive" cultures and "static" cultures. Religion, value of work, overall justice and time orientation are included in his list, but Harrison also adds frugality and community as important factors.

Stace Lindsay also presents "patterns of thought" which differ between nations that stand at opposite poles of the developmental scale. Lindsay focuses more on economic aspects such as the form of capital focused upon and market characteristics. Key themes which emerge from these lists as characteristic of developmental cultures are: trust in the individual with a fostering of individual strengths; the ability for free thinking in an open, safe environment; importance of questioning/innovation; law is supreme and holds the power; future orientated time frame with an emphasis on achievable, practical goals; meritocracy; an autonomous mindset within the larger world; strong work ethic is highly valued and rewarded; a microeconomic focus; and a value that is non-economic, but not anti-economic, which is always wanting. Characteristics of the ideal non-developmental value system are: suppression of the individual through control of information and censorship; present/past time orientation with emphasis on grandiose, often unachievable, goals; macroeconomic focus; access to leaders allowing for easier and greater corruption; unstable distribution of law and justice (family and its connections matter most); and a passive mindset within the larger world.

Grondona, Harrison, and Lindsay all feel that at least some aspects of development-resistant cultures need to change in order to allow under-developed nations (and cultural minorities within developed nations) to develop effectively. According to their argument, poverty is fueled by cultural characteristics within under-developed nations, and in order for poverty to be brought under control, said nations must move down the development path.

Poverty as a label

Various theorists believe the way poverty is approached, defined, and thus thought about, plays a role in its perpetuation. Maia Green (2006) explains that modern development literature tends to view poverty as agency filled. When poverty is prescribed agency, poverty becomes something that happens to people. Poverty absorbs people into itself and the people, in turn, become a part of poverty, devoid of their human characteristics. In the same way, poverty, according to Green, is viewed as an object in which all social relations (and persons involved) are obscured. Issues such as structural failings (see earlier section), institutionalized inequalities, or corruption may lie at the heart of a region's poverty, but these are obscured by broad statements about poverty. Arjun Appadurai writes of the "terms of recognition" (drawn from Charles Taylor's 'points of recognition'), which are given the poor and are what allows poverty to take on this generalized autonomous form. The terms are "given" to the poor because the poor lack social and economic capital, and thus have little to no influence on how they are represented and/or perceived in the larger community. Furthermore, the term "poverty" is often used in a generalized matter. This further removes the poor from defining their situation as the broadness of the term covers differences in histories and causes of local inequalities. Solutions or plans for reduction of poverty often fail precisely because the context of a region's poverty is removed and local conditions are not considered.

The specific ways in which the poor and poverty are recognized frame them in a negative light. In development literature, poverty becomes something to be eradicated, or, attacked. It is always portrayed as a singular problem to be fixed. When a negative view of poverty (as an animate object) is fostered, it can often lead to an extension of negativity to those who are experiencing it. This in turn can lead to justification of inequalities through the idea of the deserving poor. Even if thought patterns do not go as far as justification, the negative light poverty is viewed in, according to Appadurai, does much to ensure little change in the policies of redistribution.

Poverty as restriction of opportunities

The environment of poverty is one marked with unstable conditions and a lack of capital (both social and economical) which together create the vulnerability characteristic of poverty. Because a person's daily life is lived within the person's environment, a person's environment determines daily decisions and actions based on what is present and what is not. Dipkanar Chakravarti argues that the poor's daily practice of navigating the world of poverty generates a fluency in the poverty environment but a near illiteracy in the environment of the larger society. Thus, when a poor person enters into transactions and interactions with the social norm, that person's understanding of it is limited, and thus decisions revert to decisions most effective in the poverty environment. Through this a sort of cycle is born in which the "dimensions of poverty are not merely additive, but are interacting and reinforcing in nature."

According to Arjun Appadurai (2004), the key to the environment of poverty, which causes the poor to enter into this cycle, is the poor's lack of capacities. Appardurai's idea of capacity relates to Albert Hirschman's ideas of "voice" and "exit" which are ways in which people can decline aspects of their environment; to voice displeasure and aim for change or to leave said aspect of environment. Thus, a person in poverty lacks adequate voice and exit (capacities) with which they can change their position. Appadurai specifically deals with the capacity to aspire and its role in the continuation of poverty and its environment. Aspirations are formed through social life and its interactions. Thus, it can be said, that one's aspirations are influenced by one's environment. Appadurai claims that the better off one is, the more chances one has to not only reach aspirations but to also see the pathways which lead to the fulfillment of aspirations. By actively practicing the use of their capacity of aspiration the elite not only expand their aspiration horizon but also solidify their ability to reach aspirations by learning the easiest and most efficient paths through said practice. On the other hand, the poor's horizon of aspiration is much closer and less steady than that of the elite.

Thus, the capacity to aspire requires practice, and, as Chakravarti argues, when a capacity (or decision making process) is not refined through practice it falters and often fails. The unstable life of poverty often limits the poor's aspiration levels to those of necessity (such as having food to feed ones family) and in turn reinforces the lowered aspiration levels (someone who is busy studying, instead of looking for ways to get enough food, will not survive long in the poverty environment). Because the capacity to aspire (or lack thereof) reinforces and perpetuates the cycle of poverty, Appadurai claims that expanding the poor's aspiration horizon will help the poor to find both voice and exit. Ways of doing this include changing the terms of recognition (see previous section) and/or creating programs which provide the poor with an arena in which to practice capacities. An example of one such arena may be a housing development built for the poor, by the poor. Through this, the poor are able to not only show their abilities but to also gain practice dealing with governmental agencies and society at large. Through collaborative projects, the poor are able to expand their aspiration level above and beyond tomorrow's meal to the cultivation of skills and the entrance into the larger market.