The Diminishing Returns of Productivity Culture

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In 2006, Karen Ho was an anthropology student at Princeton. She wanted to study the culture of Wall Street, and she understood that the easiest way to gain real access was to work there herself. She had virtually no qualifying experience, but because she was a student at Princeton — one of the handful of schools that Wall Street firms deem acceptable in their search for the ‘best of the best’ — she was able to finagle a low level position.

With time, she built enough connections and trust that dozens of bankers agreed to sit with her for an interview. The resultant book, Liquidated: An Ethnography of Wall Street, came out in 2009. There’s a passage from one of Ho’s interviews that, as the kids say, lives in my mind rent-free. She’s talking to a banker about his preference for the sort of work ethic you find on Wall Street:

If you go to the outside world and you start working with people, people just are not motivated in the same way. It is just a pain in the ass to get anything done in the real world. People leave work at five, six p.m. People take one-hour lunch breaks, and people do this and that and whatever.

Believe me, it makes a big deal, because if you are working with people who all work real hard to do whatever it takes to get things done, it just makes things so much easier. And doing things is what makes people feel good about their life and makes them feel important. This is the whole self-worth thing — to complete and do things.

He talks a little about how he thinks workers in big corporations and the academy just aren’t as motivated — they lack ambition, or:

I think in the old days, back in the fifties or sixties, people kind of just had a set pattern of life. They went to work, climbed the ladder slowly, and did whatever they were told. I think now that people are so seduced by the capabilities that you can jump ahead and how much difference you can make, how important you can feel or whatever it is that gets you off…

He’s referring to the ‘Organization Man’ approach to work — made possible, at least for white men, by the middle-class security of the post-war period. Who needs manic ambition when you’re not terrified of falling from your class position? But then he finishes with:

It feels like now, you can get a lot done, be really productive, and it is seductive. And that is why people who have more than enough money…more than enough respect, still are involved in this at the expense of their families because they need to feel needed. And there is nothing better than to complete thing on a regular basis.

There’s something great about this dude with so much confidence in his approach to life that he doesn’t have to dress up what he gives him self-worth (“completing and doing things”) and his addiction to it. Productivity is what gets him off. Everyone else just doesn’t understand the thrill of completing things on a regular basis……

Continue reading….

By: Anne Helen Petersen

Source: The Diminishing Returns of Productivity Culture

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More Than Half Of All Bitcoin Trades Are Fake

Within the emerging and turbulent market for cryptocurrencies, where there are no fewer than 10,000 tokens, bitcoin, is the great granddaddy, the blue-chip, representing 40% of the $1 trillion in crypto assets outstanding. Bitcoin is crypto’s gateway drug.

An estimated 46 million adult Americans already own it according to New York Digital Investment Group, and an increasing number of institutional investors and corporations are warming to the nascent alternative asset. But can you trust what your crypto exchange or e-brokerage reports about trading in the most important digital currency?

One of the most common criticisms of bitcoin is pervasive wash trading (a form of fake volume) and poor surveillance across exchanges. The U.S. Commodity Futures Trading Commission defines wash trading as “entering into, or purporting to enter into, transactions to give the appearance that purchases and sales have been made, without incurring market risk or changing the trader’s market position.”

The reason why some traders engage in wash trading is to inflate the trading volume of an asset to give the appearance of rising popularity. In some cases trading bots execute these wash trades in tokens, increasing volume, while at the same time insiders reinforce the activity with bullish remarks, driving up the price in what is effectively a pump and dump scheme.

Wash trading also benefits exchanges because it allows them to appear to have more volume than they actually do, potentially encouraging more legitimate trading.

There is no universally accepted method of calculating bitcoin daily volume, even among the industry’s most reputable research firms. For instance, as of this writing, CoinMarketCap puts the latest 24-hour trading of bitcoin at $32 billion, CoinGecko at $27 billion, Nomics at $57 billion and Messari at $5 billion.

Adding to the challenges are persistent fears about the solvency of crypto exchanges, underscored by the public collapses of Voyager and Celsius. In an exclusive interview with Forbes in late June, FTX CEO Sam Bankman-Fried commented that there are many exchange bankruptcies yet to come.

A significant repercussion of this lack of faith in its underlying markets is the Security and Exchange Commission’s refusal to approve a spot bitcoin ETF.

Unfortunately for the bitcoin ETF hopefuls, many of these fears and criticisms are valid. As part of Forbes research into the crypto ecosystem using 2021 data, we ranked the 60 best exchanges in March. More recently we conducted a deeper-dive into the bitcoin trading markets to answer a few pressing questions:

  1. Where is bitcoin traded?
  2. How much bitcoin gets traded every day?
  3. How is bitcoin traded?

Our study evaluated 157 crypto exchanges across the world. Here are our main findings:

  1. More than half of all reported trading volume is likely to be fake or non-economic. Forbes estimates the global daily bitcoin volume for the industry was $128 billion on June 14. That is 51% less than the $262 billion one would get by taking the sum of self-reported volume from multiple sources.
  2. Tether, the world’s largest stablecoin, continues to be a dominant player in the crypto trading economy, especially when it comes to trades against bitcoin. Its current market capitalization is $68 billion, despite questions about its reserves.
  3. In terms of how much bitcoin activity takes place at these firms, 21 crypto exchanges generate $1 billion or more in daily trading activity, while the next 33 exchanges had volume between $200 million and $999 million across all contract types, spot, futures and perpetuals. Perpetual futures, or perpetual swaps as they are also known, are futures contracts that don’t require investors to roll over their positions. Binance is the clear leader, with a 27% market share, followed by FTX. Looking only at spot bitcoin, the top position is shared by Binance, FTX, and OKX. Chicago-based CME Group is the market leader in bitcoin futures trading.
  4. The biggest problem areas regarding fake volume are firms that tout big volume but operate with little or no regulatory oversight that would make their figures more credible, notably Binance, MEXC Global and Bybit. Altogether, the lesser regulated exchanges in our study account for approximately $89 billion of the true volume (they claim $217 billion).
  5. The creation of new trading assets and products such as stablecoins and perpetual futures adds complications for national authorities seeking to regulate crypto markets. Major U.S. exchanges hardly utilize these instruments or contracts in any of their trading. However, offshore exchanges make significant use of them as ways to synthetically create U.S. dollar liquidity on their platforms (they cannot get U.S. bank accounts).
  6. In the Western world and particularly in the U.S., it is tempting to think of bitcoin only trading against either the U.S. dollar or the euro and British pound. But some of the largest trading pair activity occurs against fiat currencies like the Japanese yen and Korean won and against major stablecoins like Binance U.S. dollar and the USD coin.
  7. 573 million people visit crypto exchange websites on a monthly basis.

We hope that this report builds on top of the important work done by other digital asset researchers such as Bitwise, which estimated in a March 2019 white paper that 95% of CoinMarketCap’s bitcoin trading volume was fake and/or non-economic.

Our Approach

Forbes uses quantitative and qualitative analyses to adjust trading volume reported by the exchanges. Unlike other methods that carry out tests on transactional data (and can also be duped), Forbes grades a firm’s credibility by evaluating no fewer than five datasets that together inspire or diminish confidence in a firm’s self-reported data. Data comes from four crypto media firms, CoinMarketCap, CoinGecko, Nomics and Messari, as well as multiple exchanges and two other third-party data providers.

We apply volume discounts based on a proprietary methodology that relies on 10 factors such as an exchange’s home regulator if any and volume metrics based on an exchange’s web traffic and estimated workforce size. We also use the number and quality of crypto licenses as proxy to gauge the sophistication of each crypto exchange in matters pertaining to regulation and trade surveillance.

If a firm shows a commitment to transparency by conducting token proofs of reserve or by participating in Forbes crypto exchange surveys, it qualifies for a “transparency credit” that lowers any discount that may otherwise apply.

Many of these factors were also present in Forbes’ crypto exchange ranking formula. We divided them into three categories:

Group 1: 48 crypto exchanges that were assigned discounts of 0-25% generated $39 billion of real bitcoin trading activity across all markets–spot, derivatives and futures–on June 14.

Group 2: 73 exchanges with volume discounts of 26% to 79% generated $81 billion in transactional activity (vs. $158 billion claimed)

Group 3: The remaining 36 firms were penalized with a high discount rate (80-99%) and traded $7.7 billion out of $59 billion claimed.

Despite crypto’s global nature, spot bitcoin trading activity is centered around relatively few currency pairs and stablecoins. Stablecoin USDT is the biggest, followed by the U.S. dollar. The next biggest fiat assets are the yen and won.

BTC-US DOLLAR Daily Volume

Group 1 exchanges, many of which are based in the U.S., provide $24.3 billion in daily USD-BTC liquidity, and Group 2 exchanges add $17.3 billion. The prominence of Group 1 exchanges as the main source of BTC-USD occurs across spot, perpetuals, and futures contracts. CME Group is the leading provider of bitcoin futures globally, with $2.1 billion of USD-BTC futures changing hands daily. There are at least 27 crypto exchanges–12 in Group 1–that have daily BTC-USD liquidity greater than $5 million.

BTC – U.S. TETHER Daily Volume

At $71.4 billion daily volume, bitcoin-tether (BTC-USDT) activity exceeds that of BTC-USD by 57%, with 79% generated by Group 2 crypto exchanges and 5% by those in Group 3. There are 77 exchanges–44 in Group 2, 12 in Group 1–with daily bitcoin-tether volume above $5 million. Tether is prominent across spot and perpetual futures markets, less so among the regulated futures industry, which is largely absent outside of the U.S.

BTC – U.S. DOLLAR COIN Daily Volume

U.S. dollar coin (USDC) is gaining adoption in the stablecoin arena. Daily liquidity for bitcoin-USDC was $2.15 billion, with Groups 1 and 2 splitting that total 39% and 60%, respectively. An interesting observation is that Group 2 exchanges use USDC actively in the spot bitcoin market whereas Group 1 exchanges do so with perpetuals. This different use could suggest that Group 2 exchanges may be open to the idea of supporting an alternative to tether’s dominance in the stablecoin market.

USDT and Binance USD (BUSD) each generate more volume than USDC, but the latter now has 26 crypto exchanges (17 in Group 2) with daily trading volume of $5 million or more, versus 77 exchanges for USDT and five with BUSD. If tether’s prominence begins to wane, USDC could be the stablecoin most likely to pick up its crown.

Bitcoin Trading Volume by Exchange Group

The top-10 Group 1 crypto exchanges by volume originate from across the world, with three from the U.S. (CME Group, Coinbase, Kraken), one from Singapore (, one from Europe (LMAX Digital), four from financial offshore centers (FTX, OKX,, BitMEX), and one from Central America (Deribit).

Among Group 1 firms, FTX is the largest and growing at a fast clip. It wasn’t until mid 2021 when institutional funding fueled a transformation of FTX operations from a midsized unregulated exchange focused on offshore crypto derivatives to a global group of exchanges today regulated in the U.S., Japan, Europe and elsewhere. In addition to derivatives, FTX trades in crypto spot, tokenized stocks and has recently added equities.

Group 2 crypto exchanges tend to be large and possess wide product offerings. They primarily focus on growth and tend to have much less interest in being regulated where they operate. They also generally lack robust ways to track and deter wash trading. Binance is by far the largest crypto exchange in Group 2, with $34.2 billion of daily trading activity followed by Bybit with $8.9 billion. The majority of these exchanges are based in offshore havens such as the Seychelles and British Virgin Islands.

Group 3 consists of 36 crypto exchanges which, with few exceptions, are unregulated and small. Their huge self reported volume and tiny visitor number cast doubt on the possibility that a limited audience could indeed generate that much trading activity. A case in point is BitCoke, which CoinMarketCap identifies as a Hong Kong-based, Cayman Island-domiciled exchange that purportedly generated $14 billion daily–mostly from BTC-USDT perpetuals.

SimilarWeb, however, indicates that the exchange’s domain receives less than 10,000 monthly visitors–with 53% coming from Argentina alone. The discrepancies in volume versus traffic plus lack of regulatory credentials result in Forbes discounting this firm’s volume by 95% to $702 million.

As discussed above, BTC/USD and BTC/USDT are by far the biggest spot pairs for bitcoin, but there are a few other pairs worth mentioning. The next largest are BTC-KWR, BTC-JPY, BTC-USDC, and BTC-EUR. An exchange’s decision to offer base assets across bitcoin, especially when it comes to fiat, usually comes down to the local fiat currency used by an exchange’s client base. Each of the companies trading bitcoin against the won or yen are based in South Korea or Japan respectively.

USDC, by nature of its blockchain-based DNA, is easier to cross national-boundaries. Readers may notice that Kraken, Binance or Coinbase are not based in Europe, though they each have a series of licenses to operate in certain countries. They each offer euro trading as a way to onboard new users, but unlike the South Korea or Japan-based exchanges, the euro is not their most dominant base asset for trading.

However, while eight pairs by volume garner the majority of bitcoin volume, there are dozens of other varieties trading at obscure exchanges uncounted even in our present study. For example, it is difficult to find the amount of BTC-NGN (Nigerian naira) volume traded in Nigeria because crypto data firms like Nomics, CoinMarketCap and CoinGecko generally do not track it.

One can safely assume that local crypto exchanges not widely known outside of Nigeria capture most BTC-NGN liquidity, which is likely true for many other exchanges operating in emerging markets.

These observations are largely true when it comes to perpetual futures as well. However, the won and the yen do not appear to have gained significant market share in this area.Finally, when it comes to the traditional futures markets, such as those that offer regular monthly expirations, the only two pairs that seem to matter are BTC-USD and BTC-USDT.

Bitcoin may just be the beginning of the problem. If reported trading volumes for bitcoin, the most regulated and closely-watched crypto asset around the world, are untrustworthy, then metrics for even smaller assets should be taken with even greater grains of salt. At its best, trading volume is one of the most measurable signs of investor interest, but it can be easily manipulated to convince novice investors that it has much more demand than it actually does.

Binance remains the 800-lb elephant in the room. Even after a 45% discount on its volume, Binance still generates the equivalent of 27.3% of all “real” trading volume. There is no other crypto exchange that can match its market power, and it’s been that way for the past two years. That said, while Binance has been saying all of the right things about cooperating with regulators – it has started getting licenses around the world and is promising to announce a global headquarters – questions remain about its operational controls. Unless regulators can get comfortable with Binance’s legitimacy, it may be difficult to envision a spot ETF getting approved anytime soon.

Tether remains “Too Big To Fail” – for now: This study invites more questions about the true use and value of two of the largest stablecoins – USDT and BUSD. Say what you will about Tether, and people have, it has found product-market fit in a big way. But that is the exact problem in the minds of many so-called Tether Truthers, who do not believe that the $68 billion is actually backed by reserves. It is hard to imagine what would happen to markets if traders stopped trusting tether – and to be fair there is little evidence that this is happening – and none of its competitors were willing to take its place.

Areas For Future Study

The role of stablecoins in market manipulation. We did not see any evidence that tether-based trading pairs were any more prone to fraud than other assets. However, this area is worth looking into further, especially if tether begins to deviate again from its $1 peg or other algorithmic stablecoins begin to gain traction in large spot-market trading. An ostensibly stable base asset that has higher-than-expected volatility can always lead to both legitimate arbitrage opportunities as well as openings for fraud.

The potential of perpetual futures to be manipulated. Through our research, including first-person interviews with direct market participants, we did not see any evidence that perpetual futures are more prone to wash trading and other forms of manipulation than conventional futures or spot contracts. However, given the relatively novel nature of this product (it was created in 2016), as well as its dominance in crypto trading, it is well worth deeper study.

The future of DEXS in market manipulation. This report did not focus on decentralized exchanges (DEXs), in large part due to the fact that they are not major players in bitcoin trading. To the contrary, when it comes to spot markets most of the major players have separated themselves from the major centralized exchanges by specializing in novel ways to provide liquidity in long-tail assets that are not financially worthwhile for many traditional exchanges to offer.

That said, the market share of DEXs has slowly been creeping up to that of spot–there are even days where Uniswap, the largest DEX, has more trading volume than Coinbase.The Forbes methodology for discounting bitcoin trading volume follows a series of steps.

Regulation. We identify crypto licenses and from what regulatory body that each exchange possesses and use that as proxy to gauge their level of sophistication and intent to deter wash trades and publishing fake volume.

Third-party input. We considered the work of select third parties such as volume data from CoinMarketCap, CoinGecko, Nomics and Messari. Messari’s volume statistics are less extensive by pairs, and it has fewer exchanges than its peers, but it has its own real-volume calculations. Forbes tracked in recent months how Messari applied a volume discount ranging from 40% to 65% to Binance volume, compared with the averages reported by CoinMarketCap, CoinGecko and Nomics at the time.

Messari also discounts the trading volume of FTX by a lesser percentage (less than 20%) and that of Kraken by 99%. With regards to this latter, Forbes doesn’t share the view of applying a heavy discount to a firm that is among the most regulated crypto exchanges in the world. Most exchanges going through the Messari real volume analysis, however, lack any type of volume discount.

Web traffic. Forbes employs third-party data from web analytics firm SimilarWeb to heavily discount the volume of firms claiming a high trading volume without having sufficient crypto licenses and web traffic to generate such volume.

Forbes interviews. Forbes has conducted dozens of interviews of senior executives at major crypto exchanges to supplement quantitative information on a firm’s profile.

I write about digital assets trends and am a leading creator of the Forbes Digital Assets tools and functionality our viewers require. I support the generation of relevant, curated investor

Source: More Than Half Of All Bitcoin Trades Are Fake

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Over 50% of all Bitcoin trades on exchanges are fake, new analysis reveals Finance in Bold

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How eBay Turned The Internet Into a Marketplace

The story of the modern web is often told through the stories of Google, Facebook, Amazon. But eBay was the first conqueror. One weekend in September 1995, a software engineer made a website. It wasn’t his first. At 28, Pierre Omidyar had followed the standard accelerated trajectory of Silicon Valley: he had learned to code in seventh grade, and was on track to becoming a millionaire before the age of 30, after having his startup bought by Microsoft. Now he worked for a company that made software for handheld computers, which were widely expected to be the next big thing.

But in his spare time, he liked to tinker with side projects on the internet. The idea for this particular project would be simple: a website where people could buy and sell. Buying and selling was still a relatively new idea online. In May 1995, Bill Gates had circulated a memo at Microsoft announcing that the internet was the company’s top priority. In July, a former investment banker named Jeff Bezos launched an online storefront called, which claimed to be “Earth’s biggest bookstore”. The following month, Netscape, creator of the most popular web browser, held its initial public offering (IPO).

By the end of the first day of trading, the company was worth almost $3bn – despite being unprofitable. Wall Street was paying attention. The dot-com bubble was starting to inflate. If the internet of 1995 inspired dreams of a lucrative future, the reality ran far behind. The internet may have been attracting millions of newcomers – there were nearly 45 million users in 1995, up 76% from the year before – but it wasn’t particularly user-friendly. Finding content was tricky: you could wander from one site to another by following the tissue of hyperlinks that connected them, or page through the handmade directory produced by Yahoo!, the preferred web portal before the rise of the modern search engine.

And there wasn’t much content to find: only 23,500 websites existed in 1995, compared to more than 17m five years later. Most of the sites that did exist were hideous and barely usable. But the smallness and slowness of the early web also lent it a certain charm. People were excited to be there, despite there being relatively little for them to do. They made homepages simply to say hello, to post pictures of their pets, to share their enthusiasm for Star Trek. They wanted to connect. Omidyar was fond of this form of online life. He had been a devoted user of the internet since his undergraduate days, and a participant in its various communities. He now observed the rising flood of dot-com money with some concern.

The corporations clambering on to the internet saw people as nothing more than “wallets and eyeballs”, he later told a journalist. Their efforts at commercialisation weren’t just crude and uncool, they also promoted a zombie-like passivity – look here, click here, enter your credit card number here – that threatened the participatory nature of the internet he knew. “I wanted to do something different,” Omidyar later recalled, “to give the individual the power to be a producer as well as a consumer.” This was the motivation for the website he built in September 1995. He called it AuctionWeb. Anyone could put up something for sale, anyone could place a bid, and the item went to the highest bidder. It would be a perfect market, just like you might find in an economics textbook.

Through the miracle of competition, supply and demand would meet to discover the true price of a commodity. One precondition of perfect markets is that everyone has access to the same information, and this is exactly what AuctionWeb promised. Everything was there for all to see. The site grew quickly. By its second week, the items listed for sale included a Yamaha motorcycle, a Superman lunchbox and an autographed Michael Jackson poster. By February 1996, traffic had grown brisk enough that Omidyar’s web hosting company increased his monthly fee, which led him to start taking a cut of the transactions to cover his expenses. Almost immediately, he was turning a profit. The side project had become a business.

But the perfect market turned out to be less than perfect. Disputes broke out between buyers and sellers, and Omidyar was frequently called upon to adjudicate. He didn’t want to have to play referee, so he came up with a way to help users work it out themselves: a forum. People would leave feedback on one another, creating a kind of scoring system. “Give praise where it is due,” he said in a letter posted to the site, “make complaints where appropriate.” The dishonest would be driven out, and the honest would be rewarded – but only if users did their part. “This grand hope depends on your active participation,” he wrote.

The value of AuctionWeb would rely on the contributions of its users. The more they contributed, the more useful the site would be. The market would be a community, a place made by its members. They would become both consumers and producers, as Omidyar hoped, and among the things they produced would be the content that filled the site. By the summer of 1996, AuctionWeb was generating $10,000 a month. Omidyar decided to quit his day job and devote himself to it full-time. He had started out as a critic of the e-commerce craze and had ended up with a successful e-commerce company. In 1997, he renamed it eBay. Ebay was one of the first big internet companies. It became profitable early, grew into a giant of the dot-com era, survived the implosion of the dot-com bubble, and still ranks among the largest e-commerce firms in the world.

But what makes eBay particularly interesting is how, in its earliest incarnation, it anticipated many of the key features that would later define the phenomenon commonly known as the “platform”. Ebay wasn’t just a place where collectors waged late-night bidding wars over rare Beanie Babies. In retrospect, it also turned out to be a critical hinge in the history of the internet. Omidyar’s site pioneered the basic elements that would later enable Google, Facebook and the other tech giants to unlock the profit potential of the internet by “platformising” it.

None of the metaphors we use to think about the internet are perfect, but “platform” is among the worst. The term originally had a specific technical meaning: it meant something that developers build applications on top of, such as an operating system. But the word has since come to refer to various kinds of software that run online, particularly those deployed by the largest tech firms. The scholar Tarleton Gillespie has argued that this shift in the use of the word “platform” is strategic. By calling their services “platforms”, companies such as Google can project an aura of openness and neutrality. They can present themselves as playing a supporting role, merely facilitating the interactions of others.

Their control over the spaces of our digital life, and their active role in ordering such spaces, is obscured. “Platform” isn’t just imprecise. It’s designed to mystify rather than clarify. A more useful metaphor for understanding the internet, one that has guided its architects from the beginning, is the stack. A stack is a set of layers piled on top of one another. Think of a house: you have the basement, the first floor, the second floor and so on, all the way up to the roof. The things that you do further up in a house often depend on systems located further down. If you take a shower, a water heater in the basement warms up the cold water being piped into your house and then pipes it up to your bathroom.

The internet also has a basement, and its basement also consists largely of pipes. These pipes carry data, and everything you do further up the stack depends on these pipes working properly. Towards the top of the stack is where the sites and apps live. This is where we experience the internet, through the pixels of our screens, in emails or tweets or streams. The best way to understand what happens on these sites and apps – on what tech companies call “platforms” – is to understand them as part of the broader story of the internet’s privatisation.

The internet started out in the 1970s as an experimental technology created by US military researchers. In the 80s, it grew into a government-owned computer network used primarily by academics. Then, in the 90s, privatisation began. The privatisation of the internet was a process, not an event. It did not involve a simple transfer of ownership from the public sector to the private, but rather a more complex movement whereby corporations programmed the profit motive into every level of the network. A system built by scientists for research was renovated for the purpose of profit maximisation. This took hardware, software, legislation, entrepreneurship. It took decades. And it touched all of the internet’s many pieces.

The process of privatization started with the pipes, and then worked its way up the stack. In April 1995, only five months before Omidyar made the website that would become eBay, the government allowed the private sector to take over control of the network’s plumbing. Households and businesses were eager to get online, and telecoms companies made money by helping them access the internet. But getting people online was a small fraction of the system’s total profit potential. What really got investors’ capital flowing was the possibility of making money from what people did online. In other words, the next step was figuring out how to maximize profit in the upper floors, where people actually use the internet. The real money lay not in monetizing access, but in monetizing activity.

This is what Omidyar did so effectively when he created a place where people wanted to buy and sell goods online, and took a cut of their transactions. The dot-com boom began with Netscape’s explosive IPO in August 1995. Over the following years, tens of thousands of startups were founded and hundreds of billions of dollars were invested in them. Venture capital entered a manic state: the total amount of US venture-capital investment increased more than 1,200% from 1995 to 2000. Hundreds of dot-com companies went public and promptly soared in value: at their peak, technology stocks were worth more than $5tn.

When eBay went public in 1998, it was valued at more than $2bn on the first day of trading; the continued ascent of its stock price over the next year made Omidyar a billionaire. Yet most of the startups that attracted huge investment during these years didn’t actually make money. For all the hype, profits largely failed to materialize, and in 2000 the bubble burst. From March to September, the 280 stocks in the Bloomberg US Internet Index lost almost $1.7tn. “It’s rare to see an industry evaporate as quickly and completely,” a CNN journalist remarked. The following year brought more bad news. The dot-com era was dead.

Today, the era is typically remembered as an episode of collective insanity – as an exercise in what Alan Greenspan, during his contemporaneous tenure as chair of the Federal Reserve, famously called “irrational exuberance”., a startup that sold pet supplies online, became the best-known symbol of the period’s stupidity, and a touchstone for retrospectives ever since. Never profitable, the company spent heavily on advertising, including a Super Bowl spot; it raised $82.5m in its IPO in February 2000 and imploded nine months later.

Arrogance, greed, magical thinking and bad business decisions all contributed to the failure of the dot-com experiment. Yet none of these were decisive. The real problem was structural. While their investors and executives probably wouldn’t have understood it in these terms, dot-com companies were trying to advance the next stage of the internet’s privatisation – namely, by pushing the privatization of the internet up the stack. But the computational systems that could make such a push feasible were not yet in place. Companies still struggled to turn a profit from user activity.

In his analysis of capitalist development, Karl Marx drew a distinction between the “formal” and “real” subsumption of labour by capital. In formal subsumption, an existing labour process remains intact, but is now performed on a capitalist basis. A peasant who used to grow his own food becomes a wage labourer on somebody else’s farm. The way he works the land stays the same. In real subsumption, by contrast, the labour process is revolutionised to meet the requirements of capital. Formerly, capital inherited a process; now, it remakes the process. Our agricultural worker becomes integrated into the industrialised apparatus of the modern factory farm.

The way he works completely changes: his daily rhythms bear little resemblance to those of his peasant predecessors. And the new arrangement is more profitable for the farm’s owner, having been explicitly organised with that end in mind. This is a useful lens for thinking about the evolution of the internet, and for understanding why the dot-coms didn’t succeed. The internet of the mid-to-late 1990s was under private ownership, but it had not yet been optimised for profit. It retained too much of its old shape as a system designed for researchers, and this shape wasn’t conducive to the new demands being placed on it. Formal subsumption had been achieved, in other words, but real subsumption remained elusive.

Accomplishing the latter would involve technical, social and economic developments that made it possible to construct new kinds of systems. These systems are the digital equivalents of the modern factory farm. They represent the long-sought solution to the problem that consumed and ultimately defeated the dot-com entrepreneurs: how to push privatisation up the stack. And eBay offered the first glimpse of what that solution looked like.Ebay enlisted its users in its own creation. They were the ones posting items for sale and placing bids and writing feedback on one another in the forum. Without their contributions, the site would cease to exist.

Omidyar was tapping into a tradition by setting up eBay in this way. In 1971, a programmer named Ray Tomlinson invented email. This was before the internet existed: Tomlinson was using its precursor, Arpanet, a cutting-edge network that the Pentagon created to link computers across the country. Email became wildly popular on Arpanet: just two years after its invention, a study found that it made up three-quarters of all network traffic. As the internet grew through the 1980s, email found an even wider reach. The ability to exchange messages instantaneously with someone far away was immensely appealing; it made new kinds of collaboration and conversation possible, particularly through the mailing lists that formed the first online communities.

Email was more than just a useful tool. It helped humanize the internet, making a cold assemblage of cables and computers feel inhabited. The internet was somewhere you could catch up with friends and get into acrimonious arguments with strangers. It was somewhere to talk about politics or science fiction or the best way to implement a protocol. Other people were the main attraction. Even the world wide web was made with community in mind. “I designed it for a social effect – to help people work together,” its creator, Tim Berners-Lee, would later write.

Community is what Omidyar liked best about the internet, and what he feared the dot-com gold rush would kill. He wasn’t alone in this: one could find dissidents railing against the forces of commercialisation on radical mailing lists. But Omidyar was no anti-capitalist. He was a libertarian: he believed in the liberating power of the market. He didn’t oppose commercialisation as such, just the particular form it was taking. The companies opening cheesy digital storefronts and plastering the web with banner ads were doing commercialisation poorly. They were treating their users as customers. They didn’t understand that the internet was a social medium.

Ebay, by contrast, would be firmly rooted in this fact. From its first days as AuctionWeb, the site described itself as a community, and this self-definition became integral to its identity and to its operation. For Omidyar, the point wasn’t to defend the community from the market but rather to recast the community as a market – to fuse the two. No less a figure than Bill Gates saw the future of the internet in precisely these terms. In 1995, the same year that Omidyar launched AuctionWeb, Gates co-authored a book called The Road Ahead. In it, the Microsoft CEO laid out his vision for the internet as “the ultimate market”: “It will be where we social animals will sell, trade, invest, haggle, pick stuff up, argue, meet new people, and hang out.

Think of the hustle and bustle of the New York Stock Exchange or a farmers’ market or of a bookstore full of people looking for fascinating stories and information. All manner of human activity takes place, from billion-dollar deals to flirtations.” Here, social relationships have merged so completely with market relationships as to become indistinguishable. The internet is the instrument of this union; it brings people together, but under the sign of capital. Gates believed his dream was at least a decade from being realised. Yet by the time his book came out, AuctionWeb was already making progress toward achieving it.

Combining the community with the market was a lucrative innovation. The interactions that occurred in the guise of the former greatly enhanced the financial value of the latter. Under the banner of community, AuctionWeb’s buyers and sellers were encouraged to perform unpaid activities that made the site more useful, such as rating one another in the feedback forum or sharing advice on shipping. And the more people participated, the more attractive a destination it became. More people using AuctionWeb meant more items listed for sale, more buyers bidding in auctions, more feedback posted to the forum – in short, a more valuable site.

This phenomenon – the more users something has, the more valuable it becomes – is what economists call network effects. On the web, accommodating growth was fairly easy: increasing one’s hosting capacity was a simpler and cheaper proposition than the brick-and-mortar equivalent. And doing so was well worth it because, at a certain size, network effects locked in advantages that were hard for a competitor to overcome. A second, related strength was the site’s role as a middleman. In an era when many dot-coms were selling goods directly – paid a fortune on postage to ship pet food to people’s doors – Omidyar’s company connected buyers and sellers instead, and pushed the cost of postage on to them.

This enabled it to profit from users’ transactions while remaining extremely lean. It had no inventory, no warehouses – just a website. But AuctionWeb was not only a middleman. It was also a legislator and an architect, writing the rules for how people could interact and designing the spaces where they did so. This wasn’t in Omidyar’s plan. He initially wanted a market run by its members, an ideal formed by his libertarian beliefs. His creation of the feedback forum likely reflected an ideological investment in the idea that markets were essentially self-organising, as much as his personal interest in no longer having to mediate various disputes.

Contrary to libertarian assumptions, however, the market couldn’t function without the site’s ability to exercise a certain kind of sovereignty. The feedback forum is a good example: users started manipulating it, leaving praise for their friends and sending mobs of malicious reviewers after their enemies. The company would be compelled to intervene again and again. It did so not only to manage the market but also to expand it by attracting more buyers and sellers through new categories of goods and by expanding into new countries – an imperative that shareholders imposed after eBay went public in 1998.

“Despite its initial reluctance, the company stepped increasingly into a governance role,” writes the sociologist Keyvan Kashkooli, in his study of eBay’s evolution. Increasing profitability required managing people’s behaviour, whether through the code that steered them through the site or the user agreements that governed their activities on it. Thanks to network effects, and its status as both middleman and sovereign, eBay easily turned a profit. When the crash of 2000–01 hit, it survived with few bruises. And in the aftermath of the crash, as an embattled industry, under pressure from investors, tried to reinvent itself, the ideas that it came up with had much in common with those that had formed the basis for eBay’s early success.

For the most part, eBay’s influence was neither conscious nor direct. But the affinities were unmistakable. Omidyar’s community market of the mid-1990s was a window into the future. By later standards it was fairly primitive, existing as it did within the confines of an internet not yet remodelled for the purpose of profit maximisation. But the systems that would accomplish that remodelling, that more total privatisation of the internet, would do so by elaborating the basic patterns that Omidyar had applied. These systems would be called platforms, but what they resembled most were shopping malls.

The first modern shopping mall was built in Edina, Minnesota, in 1956. Its architect, Victor Gruen, was a Jewish socialist from Vienna who had fled the Nazis and disliked American car culture. He wanted to lure midcentury suburbanites out of their Fords and into a place that recalled the “rich public social life” of a great European city. He hoped to offer them not only shops but libraries and cinemas and community centres. Above all, his mall would be a space for interaction: an “outlet for that primary human instinct to mingle with other humans”. Unlike in a city, however, this mingling would take place within a controlled setting. The chaos of urban life would be displaced by the discipline of rational design.

As Gruen’s invention caught on, the grander parts of his vision fell away. But the idea of an engineered environment that paired commerce with a public square remained. Gruen’s legacy would be a kind of capitalist terrarium, nicely captured by what urban planners call a “privately owned public space”. The systems that dominate life at the upper end of the stack are best understood, to borrow an insight from the scholar Jathan Sadowski, as shopping malls. The shopping malls of the internet – Google, Facebook, Amazon – are nothing if not privately owned public spaces. Calling themselves platforms, they are in fact corporate enclosures, with a wide range of interactions transpiring inside of them.

Just like in a real mall, some of these interactions are commercial, such as buying clothes from a merchant, while others are social, such as hanging out with friends. But what distinguishes the online mall from the real mall is that within the former, everything one does makes data. Your clicks, chats, posts, searches – every move, however small, leaves a digital trace. And these traces present an opportunity to create a completely new set of arrangements. Real malls are in the rental business: the owner charges tenants rent, essentially taking a slice of their revenues. Online malls can make money more or less the same way, as eBay demonstrated early on, by taking a cut of the transactions they facilitate.

But, as Sadowski points out, online malls are also able to capture another kind of rent: data rent. They can collect and make money from those digital traces generated by the activities that occur within them. And since they control every square inch of the enclosure, and because modifying the enclosure is simply a matter of deploying new code, they can introduce architectural changes in order to cause those activities to generate more traces, or traces of different kinds. These traces turn out to be very valuable. So valuable, in fact, that amassing and analysing them have become the primary functions of the online mall. Like Omidyar’s community market, the online mall facilitates interactions, writes the rules for those interactions, and benefits from having more people interacting with one another.

But in the online mall, these interactions are recorded, interpreted and converted into money in a range of ways. Data can help sell targeted advertising. It can help build algorithmic management systems that siphon more profit out of each worker. It can help train machine learning models in order to develop and refine automated services like chatbots, which can in turn reduce labour costs and open new revenue streams. Data can also sustain faith among investors that a tech company is worth a ton of money, simply because it has a ton of data. This is what distinguishes online malls from their precursors: they are above all designed for making, and making use of, data. Data is their organizing principle and essential ingredient.

Data is sometimes compared to oil, but a better analogy might be coal. Coal was the fuel that powered the steam engine. It propelled the capitalist reorganization of manufacturing from an artisanal to an industrial basis, from the workshop to the factory, in the 19th century. Data has played a comparable role. It has propelled the capitalist reorganization of the internet, banishing the remnants of the research network and perfecting the profit engine. Very little of this vastly complex machinery could be foreseen from the vantage point of 1995.

But the arrival of AuctionWeb represented a large step toward making it possible. The story of the modern internet is often told through the stories of Google, Facebook, Amazon and the other giants that have come to conquer our online life.  But their conquests were preceded and prefigured by another, one that started as a side project and stumbled into success by coming up with the basic blueprint for making a lot of money on the internet.


Source: ‘Wallets and eyeballs’: how eBay turned the internet into a marketplace | eBay | The Guardian

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eBay, Inc. 2021 Annual Report (Form 10-K)”. U.S. Securities and Exchange Commission.

Global Trade: 1. Finding International Items On eBay”

Skype and PayPal – A Different Set of Rules”.

PayPal Spinoff Day Has Arrived — What Does It Mean for Investors?”.

The Perfect Store.

How did eBay start?”

The perfect store

The eBay Business Model”

The Myths of Innovation

Ebay Enters The NFT Space, Launches First NFT Collection

“EBay Founder Pierre Omidyar Steps Down From Board”.

“Brand New: eBay Settles for Lowest Bid”

eBay selling fees”.

Ebay’s history – know your roots!”.

eBay Guides – Tickets Buying Guide”.

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eBay Inc. – eBay Inc. Outlines Global Business Strategy”

The brand that auctioned the www: eBay

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Facing Shortfalls, Pension Managers Turn to Risky Bets

The graying of the American employee is a math drawback for Farouki Majeed. It’s his job to take a position his means out. Mr. Majeed is the funding chief for an $18 billion Ohio college pension that gives retirement advantages to greater than 80,000 retired librarians, bus drivers, cafeteria staff and different former staff. The issue is that this fund pays out extra in pension checks yearly than its present staff and employers contribute. That hole helps clarify why it’s billions in need of what it must cowl its future retirement guarantees.

“The bucket is leaking,” he mentioned. The answer for Mr. Majeed—in addition to different pension managers throughout the nation—is to tackle extra funding threat. His fund and plenty of different retirement programs are loading up on illiquid belongings resembling personal fairness, personal loans to corporations and actual property.

So-called “various” investments now comprise 24% of public pension fund portfolios, in response to the latest knowledge from the Boston School Middle for Retirement Analysis. That’s up from 8% in 2001. Throughout that point, the quantity invested in additional conventional shares and bonds dropped to 71% from 89%. At Mr. Majeed’s fund, alternate options had been 32% of his portfolio on the finish of July, in contrast with 13% in fiscal 2001.

This technique is paying off in Ohio and throughout the U.S. The median funding return for all public pension programs tracked by the Wilshire Belief Universe Comparability Service surged to almost 27% for the one-year interval ending in June. That was one of the best consequence since 1986. Mr. Majeed’s retirement system posted the identical 27% return, which was its strongest-ever efficiency primarily based on information courting again to 1994. His private-equity belongings jumped almost 46%.

A majority of these blockbuster positive aspects aren’t anticipated to final for lengthy, nevertheless. Analysts anticipate public pension-fund returns to dip over the subsequent decade, which is able to make it tougher to cope with the core drawback dealing with all funds: They don’t have sufficient money to cowl the guarantees they made to retirees. That hole narrowed in recent times however remains to be $740 billion for state retirement programs, in response to a fiscal 2021 estimate from Pew Charitable Trusts.

This public-pension predicament is the results of many years of underfunding, profit overpromises, unrealistic calls for from public-employee unions, authorities austerity measures and three recessions that left many retirement programs with deep funding holes. Not even the 11-year bull market that ended with the pandemic or a fast U.S. restoration in 2021 was sufficient to assist pensions dig out of their funding deficits utterly.

Demographics didn’t assist, both. Prolonged lifespans brought about prices to soar. Wealthy early-retirement preparations and a wave of retirees world-wide additionally left fewer lively staff to contribute, widening the distinction between the quantity owed to retirees and belongings available.

Low rates of interest made the pension-funding drawback much more tough to unravel as a result of they modified long-held assumptions about the place a public system might place its cash. Pension funds pay advantages to retirees via a mixture of funding positive aspects and contributions from employers and staff. To make sure sufficient is saved, plans undertake long-term annual return assumptions to mission how a lot of their prices can be paid from earnings. These assumptions are at present round 7% for many funds.

There was a time when it was potential to hit that concentrate on—or larger—simply by shopping for and holding investment-grade bonds. Not anymore. The extremely low rates of interest imposed by central banks to stimulate development following the 2008-09 monetary disaster made that just about inconceivable, and shedding even just a few share factors of bond yield hindered the purpose of posting regular returns.

Pension officers and authorities leaders had been left with a vexing resolution. They may shut their funding gaps by decreasing advantages for current staff, chopping again public companies and elevating taxes to pay for the bulging obligations. Or, since these are all tough political decisions and courts have a tendency to dam any efforts to chop advantages, they may take extra funding threat. Many are selecting that possibility, including dollops of actual property and private-equity investments to the once-standard guess of bonds and shares.

This shift might repay, because it did in 2021. Beneficial properties from private-equity investments had been an enormous driver of historic returns for a lot of public programs within the 2021 fiscal yr. The efficiency helped enhance the combination funded ratio for state pension plans, or the extent of belongings relative to the quantity wanted to satisfy projected liabilities, to 85.5% for the yr via June, Wilshire mentioned. That was a rise of 15.4 share factors.

These bets, nevertheless, carry potential pitfalls if the market ought to fall. Illiquid belongings resembling personal fairness usually lock up cash for years or many years and are far more tough to promote throughout downturns, heightening the danger of a money emergency. Various belongings have tripped up cities, counties and states prior to now; Orange County famously filed for chapter in 1994 after losses of greater than $1.7 billion on dangerous derivatives that went bitter.

The heightened concentrate on various bets might additionally end in heftier administration charges. Funds pay about two-and-one-half share factors in charges on various belongings, almost 5 occasions what they pay to spend money on public markets, in response to analysis from retired funding marketing consultant Richard Ennis. Some funds, consequently, are avoiding various belongings altogether. One of many nation’s best-performing funds, the Tampa Firefighters and Police Officers Pension Fund, limits its investments to publicly traded shares and bonds. It earned 32% within the yr ending June 30.

It took some convincing for Mr. Majeed, who’s 68 years outdated, to change the funding mixture of the Faculty Workers Retirement System of Ohio after he turned its chief funding officer. When he arrived in 2012, there was a plan below technique to make investments 15% of the fund’s cash in one other kind of other asset: hedge funds. He mentioned he thought such funds produced lackluster returns and had been too costly. Altering that technique would require a feat of public pension diplomacy: Convincing board members to roll again their hedge-fund plan after which promote them on new investments in infrastructure initiatives resembling airports, pipelines and roads—all below the unforgiving highlight of public conferences. “It’s a tricky room to stroll into as a CIO,” mentioned fund trustee James Rossler Jr., an Ohio college system treasurer. It wasn’t Mr. Majeed’s first expertise with politicians and fractious boards.

He grew up in Sri Lanka because the son of a distinguished Sri Lanka Parliament member, and his preliminary funding job there was for the Nationwide Growth Financial institution of Sri Lanka. He needed to consider the feasibility of factories and tourism initiatives. He got here to the U.S. in 1987 along with his spouse, received an M.B.A. from Rutgers College and shortly migrated to the world of public pensions with jobs in Minneapolis, Ohio, California and Abu Dhabi. In Orange County, Calif., Mr. Majeed helped persuade the board of the Orange County Workers Retirement System to cut back its reliance on bonds and put more cash into equities—a problem heightened by the county’s 1994 chapter, which occurred earlier than he arrived.

His 2012 transfer to Ohio wasn’t Mr. Majeed’s first publicity to that state’s pension politics, both; he beforehand was the deputy director of investments for one more of the state’s retirement programs within the early 2000s. This time round, nevertheless, he was in cost. He mentioned he spent a number of months presenting the board with knowledge on how current hedge-fund investments had lagged behind expectations after which tallied up how a lot the fund paid in charges for these bets. “It was not a reasonably image at that time,” he mentioned, “and these paperwork are public.” Trustees listened. They lowered the hedge-fund goal to 10% and moved 5% into the real-estate portfolio the place it might be invested in infrastructure, as Mr. Majeed needed.

What cemented the board’s belief is that portfolio then earned annualized returns of 12.4% over the subsequent 5 years—greater than double the return of hedge funds over that interval. The board in February 2020 signed off on one other request from Mr. Majeed to place 5% of belongings in a brand new kind of other funding: personal loans made to corporations. “Again once I first received on the board, in case you would have instructed me we had been going to have a look at credit score, I might have instructed you there was no means that was going to occur,” Mr. Rossler mentioned. The private-loan guess paid off spectacularly the next month when determined corporations turned to non-public lenders amid market chaos sparked by the Covid-19 pandemic. Mr. Majeed mentioned he added loans to an airline firm, an plane engine producer and an early-childhood schooling firm impacted by the widespread shutdowns. For the yr ended June 30, the newly minted mortgage portfolio returned almost 18%, with greater than 7% of that coming in money the fund might use to pay advantages.

The system’s whole annualized return over 10 years rose to 9.15%, effectively above its 7% goal. These positive aspects closed the yawning hole between belongings available and guarantees made to retirees, however not utterly. Mr. Majeed estimates the fund has 74% of what it wants to satisfy future pension obligations, up from 63% when he arrived. Mr. Majeed is now eligible to attract a pension himself, however he mentioned he finds his job too absorbing to think about retirement simply but. What he is aware of is that the pressures forcing a cutthroat seek for larger returns will make his job—and that of whoever comes subsequent—exponentially tougher. “I believe it’s going to be very robust.”

By: Heather Gillers

Heather Gillers is a reporter on The Wall Street Journal’s investing team. She writes about pensions, municipal bonds and other public finance issues. She previously worked at the Chicago Tribune, the Indianapolis Star, and the (Aurora, Ill.) Beacon-News. She can be reached at (929) 384 3212 or



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“Location Selector”. Willis Towers Watson. “Asset Management 2020 – A Brave New World” (PDF). Retrieved March 3, 2021. OECD For examples, see “Local Government Law Library”. Archived from the original on 6 September 2012. Retrieved 15 May 2011. “The 20 largest pension funds of the globe”. 27 October 2017. Retrieved 2018-03-11. [1] Top 100 Largest Public Pension Rankings by Total Assets Budget of the United States Government, FY2022, published May 28, 2021. Value as of September 30, 2020 Office of Management and Budget Retrieved June 13, 2021 Superannuation Statistics, March 2021. Value as of June 1, 2021. Retrieved June 1, 2021 2020年度第3四半期運用状況 GPIF “Annual Survey of Large Pension Funds and Public Pension Reserve Funds” (PDF). OECD. 2016-04-21. Retrieved 2016-10-28. Budget of the United States Government, FY2022, published May 28, 2021. Value as of September 30, 2020. Office of Management and Budget Retrieved June 13, 2021 Budget of the United States Government, FY2022, published May 28, 2021. Value as of September 30, 2020. Office of Management and Budget Retrieved June 13, 2021 Financial Statements of the Thrift Savings Fund December 31, 2020 and 2019. As of December 31, 2020. Thrift Savings Fund. Retrieved May 14, 2021 “Default”. Retrieved 2020-07-04. “CPP Fund Totals $317 Billion at 2017 Fiscal Year-End”. Retrieved 2018-02-24. “Page d’accueil”. Caisse de dépôt et placement du Québec | Investisseur institutionnel de long terme | Gestionnaire d’actif. “CalPERS Reports Preliminary 4.7% Investment Return for Fiscal Year 2019-20”. Retrieved 2021-03-03. “The world’s 300 largest pension funds – year end 2014”. Willis Towers Watson. “Performance – Ontario Teachers’ Pension Plan”. “Current Investment Portfolio –”. Retrieved 2021-03-03. Asher, Mukul (22 January 2021). “How the EPFO can improve as India’s largest social security provider”. Moneycontrol. “Annual Announcement of Financial Statements 2020”. “OMERS – 2020 Annual Report Highlights”. Retrieved 2021-03-03. Official WebSite of PREVI – English Version“STRS Ohio’s Impact”. “Assets Under Management & No.of Subscribers | NPS Trust”. “FRR 2012 Annual Report” (PDF). “NPRF”. Archived from the original on 2017-02-10. Retrieved 2020-05-03. “Choose an Industry SuperFund”. Industry Super. Official Website of PREVI “ΜΕΤΟΧΙΚΟ ΤΑΜΕΙΟ ΠΟΛΙΤΙΚΩΝ ΥΠΑΛΛΗΛΩΝ | Μ.Τ.Π.Υ.”“Official website of Mandatory Provident Fund Schemes Authority”. EPFPFRDA[2]Archived November 2, 2010, at the Wayback Machinehttp://www.csspp.ro“Armed Forces Pension Fund”. 29 USC § 1002 – Definitions | Title 29 – Labor | U.S. Code | LII / Legal Information Institute. Retrieved 2013-07-18. Federal Reserve Statistical Release, Financial Accounts of the United States, Fourth Quarter 2016Archived 2018-01-04 at the Wayback Machine, see pp.94-99. Values as of December 31, 2016. Federal Reserve Board of Governors. Reported March 9, 2017. Retrieved May 18, 2017

IRS Provides Tax Relief for Victims of Hurricane Ida

Hurricane Ida, which began on August 26, barreled through the state of Louisiana and has left millions without power and much of Louisiana in a state of disaster. If you were impacted by Hurricane Ida we want you to know TurboTax is here for you, and we want to keep you up to date with important tax relief information that may help you in this time of need.

The Federal Emergency Management Agency (FEMA) declared the recent events as a disaster and the IRS announced that victims of the hurricane that occurred in Louisiana now have until January 3, 2022 to file various individual and business tax returns and make certain tax payments. Currently, this includes the entire state of Louisiana, but taxpayers in Ida-impacted localities designated by FEMA in neighboring states will automatically receive the same filing and payment relief.

What are the extended tax and payment deadlines for victims of Hurricane Ida?

The tax relief postpones various tax filing and payment deadlines that occurred starting on August 26, 2021. As a result, affected individuals and businesses will have until January 3, 2022 to file returns and pay any taxes that were originally due during this period. These include:

Your resource on tax filing
Tax season is here! Check out the Tax Center on AOL Finance for all the tips and tools you need to maximize your return.
  • 2020 Individual and Business Returns with Valid Extensions: Individuals that had a valid extension to file their 2020 return due to run out on October 15, 2021 will now have until January 3, 2022 to file. Businesses with extensions also have until January 3, 2022 including, among others, calendar-year corporations whose 2020 extensions run out on October 15, 2021. The IRS noted that because tax payments related to 2020 returns were due on May 17, 2021, those payments are not eligible for an extension.
  • 2020 Quarterly Estimated Tax Payments: 2021 quarterly estimated tax payments with a deadline of September 15, 2021 have been extended until January 3, 2022.
  • Quarterly Payroll and Excise Tax Returns: Quarterly payroll and excise tax returns that are normally due on November 1, 2021, are also extended until January 3, 2022. In addition, penalties on payroll and excise tax deposits due on or after August 26 and before September 10 will be abated as long as the deposits were made by September 10, 2021.

Calendar-year tax-exempt organizations, operating on a calendar-year basis that have a valid 2020 tax return extension due to run out on November 15, 2021 also qualify for the extra time.

What do I need to do to claim the tax extension?

The IRS automatically provides filing and penalty relief to any taxpayer with an IRS address of record located in the disaster area. Taxpayers do not need to contact the IRS to get this relief. However, if an affected taxpayer receives a late filing or late payment penalty notice from the IRS that has an original or extended filing, payment or deposit due date falling within the postponement period, the taxpayer should call the number on the notice to have the penalty abated.

The current list of eligible localities is always available on the disaster relief page on

Do surrounding areas outside of Louisiana qualify for an extension?

The IRS will work with any taxpayer who lives outside the disaster area but whose records necessary to meet a deadline occurring during the postponement period are located in the affected area. Taxpayers qualifying for relief who live outside the disaster area need to contact the IRS at 866-562-5227. This also includes workers, assisting the relief activities, who are affiliated with a recognized government or philanthropic organization.

How can I claim a casualty and property loss on my taxes if impacted?

Individuals or businesses who suffered uninsured or unreimbursed disaster-related casualty losses can choose to claim them on either the tax return for the year the loss occurred (in this instance, the 2021 return filed in 2022), or the loss can be deducted on the tax return for the prior year (2020). Individuals may also deduct personal property losses that are not covered by insurance or other reimbursements. Be sure to write the FEMA declaration number – 4611 − for Hurricane Ida in Louisiana on any return claiming a loss.

The tax relief is part of a coordinated federal response to the damage caused by the harsh storms and is based on local damage assessments by FEMA. For information on disaster recovery, visit

If you are not a victim, but you are looking to help those in need, this is a great opportunity to donate or volunteer your time to legitimate 501(c)(3) not-for-profit charities who are providing relief efforts for storm victims.

Check back with the TurboTax blog for more updates on disaster relief. For more tax tips in 5 minutes or less, subscribe to the Turbo Tips podcast on Apple Podcasts, Spotify and iHeartRadio



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Source: IRS Provides Tax Relief for Victims of Hurricane Ida


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