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What is Reed’s law, and why does it matter in the crypto space?
Reed’s Law highlights exponential growth from diverse communities, crucial in crypto for innovation, DeFi and decentralized governance.
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Reed’s Law highlights exponential growth from diverse communities, crucial in crypto for innovation, DeFi and decentralized governance.
Understanding Reed’s Law
The concept of network effects is extended by Reed’s Law, which was developed by Harvard professor David P. Reed in 1999 and emphasizes the importance of communities and subgroups within a network.
Reed’s Law states that the value of a network increases exponentially with the number of potential subgroups that users can establish within the network, in contrast to Metcalfe’s Law, which states that a network’s value is proportional to the square of its number of users.
Reed’s Law considers the combinatorial explosion of potential groups in contrast to Metcalfe’s Law, which emphasizes the total number of connections among users. While Reed’s Law implies an exponential rise, emphasizing the importance of smaller, more niche groups, Metcalfe’s Law suggests a quadratic growth in value regarding the number of users.
Using the formula 2^n, where “n” stands for the number of potential subgroups within the network, Reed’s Law determines the value of a network. This formula emphasizes the ability of communities to produce and distribute value by showing that as the number of potential subgroups grows, the value of the network expands at an astounding rate.
A classic example illustrating Reed’s Law is in online social networks. Users can create a variety of specialized groups on websites like Facebook and LinkedIn based on shared interests, occupations or hobbies. Each subgroup creates its own community, and as these communities grow, the network’s overall value grows exponentially because of the different ways these groups can communicate and exchange information, not just linearly with the number of users.
Reed’s Law has numerous applications in digital networks, including file-sharing networks where users can build and join various file-sharing communities, each specializing in a particular type of material or set of interests. Reed’s Law applies to traditional networks in situations like professional associations or academic societies where members can form specialized committees or groups, increasing the network’s worth exponentially as these subgroups multiply.
How Reed’s Law impacts the growth and value of cryptocurrencies
By highlighting the exponential increase in value as communities and applications within the cryptocurrency networks proliferate, Reed’s Law has a profound impact on the growth and value of cryptocurrencies.
Here’s how Reed’s Law influences cryptocurrencies:
Community building and adoption
Community participation is key for cryptocurrencies. According to Reed’s Law, the number of potential communities and subgroups inside the crypto ecosystem grows exponentially as more people join the network. For instance, Bitcoin (BTC) and Ether (ETH), among other cryptocurrencies, have experienced exponential growth in their respective communities, which has facilitated global adoption and value appreciation.
Decentralized applications (DApps)
Ethereum’s smart contracts enable DApps, embodying Reed’s Law. As these applications multiply, the network’s value grows exponentially. Reed’s Law emphasizes the exponential increase in value as diverse communities and applications within Ethereum’s network expand, underscoring the power of decentralized ecosystems.
Niche and use case-specific cryptocurrencies
Some cryptocurrencies are created for particular businesses or use cases. When these cryptocurrencies attract communities relevant to their particular applications, Reed’s Law is evident. For instance, the Brave browser has Basic Attention Tokens (BAT), a cryptocurrency that aims to transform digital advertising. Users, advertisers and content producers make up the BAT community, forming a variety of subgroups that increase the currency’s usefulness and overall worth.
Role of Reed’s Law in shaping tokenomics strategies
Reed’s Law serves as a foundation for tokenomics initiatives by highlighting the exponential growth potential that may be achieved through the emergence of several subgroups and communities.
Reed’s Law plays a pivotal role in the development of tokenomics strategies as well as the planning and execution of blockchain initiatives. The economic model that underpins cryptocurrencies, known as tokenomics, leverages this principle by promoting the creation of a variety of use cases and stimulating active community interaction.
As Reed’s Law emphasizes the possibility of an exponential increase in a project’s value as new communities and subgroups emerge, tokenomics techniques can take advantage of this law by motivating users and programmers to develop applications, thereby boosting the ecosystem’s overall usefulness and allure. Demand for the native token increases as specialized subgroups form, favorably affecting the token’s value.
Additionally, Reed’s Law underlines how crucial it is to promote relationships between these sub-groups. Interconnectedness guarantees a thriving ecosystem where the network’s worth dramatically rises through cooperative efforts. As a result, tokenomics models encourage activities that promote interactions among communities, resulting in a network effect that increases the project’s overall value.
Furthermore, Reed’s Law emphasizes the value of community-driven initiatives. Tokenomics strategies frequently set aside a portion of tokens for community development, promoting the emergence of varied communities. These groups participate in governance processes, offer support, and create apps that benefit the ecosystem. The project’s resilience and sustainability are improved by such active participation, ensuring long-term benefits.
Potential pitfalls in applying Reed’s Law to crypto networks
While Reed’s Law provides useful insights into the development of cryptocurrency networks, managing the complexity of various subgroups, foreseeing their success, maintaining engagement, managing expectations, and ensuring security and privacy are crucial challenges that must be addressed when applying this principle to cryptocurrency ecosystems.
One significant drawback is the difficulty of managing numerous subgroups. Coordinating interactions and creating a seamless user experience get more challenging as the number of communities increases. To avoid division and conflicts among subgroups, it is necessary to have robust governance systems, which can be challenging in decentralized networks.
The complexity of precisely anticipating what subgroups will gain traction creates a further problem. A crypto network’s value will not always be created equally by all of its communities. It can be difficult and involve a lot of trial and error to determine what subgroups are the most beneficial and sustainable, which results in an ineffective use of resources.
Additionally, Reed’s Law’s exponential growth prediction can be difficult to maintain over the long run. Maintaining the same degree of connection and involvement within each subgroup as the network grows is challenging. Subgroups may experience activity stagnation or decline, which will impact the value proposition of the network as a whole.
Furthermore, there is a chance of overestimating the network’s potential worth, particularly if the expansion of subgroups differs from early projections. Unrealistic predictions may leave consumers and investors feeling let down, which could contribute to market instability.
Finally, dealing with numerous subgroups can raise privacy and security issues. It is crucial to ensure the security of user identities, data and transactions within these communities. Concerns regarding user safety can impede the growth potential anticipated by Reed’s Law and lower network value if security measures are not strong.
How will Reed’s Law shape the future of crypto space?
Reed’s Law is set to revolutionize the crypto industry by fostering exponential growth through varied, interconnected communities, driving innovation and democratizing finance and governance.
The concept of Reed’s Law, which emphasizes the exponential value created through different, specialized communities, will encourage the growth of creative DApps and networks as blockchain technology develops. This potential for exponential expansion promotes the creation of original, user-centered solutions across a variety of industries, including banking, gaming, healthcare and government.
Decentralized autonomous organizations (DAOs), nonfungible tokens (NFTs), and decentralized finance (DeFi) highlight the importance of Reed’s Law in driving collaborative ecosystems. Moreover, the law will have an impact on governance models, allowing for less centralization and more inclusive decision-making procedures.
A synergistic environment will be created by connected networks of communities as blockchain interoperability advances, greatly enhancing the general utility and adoption of cryptocurrencies. The application of Reed’s Law will foster the development of active, diverse crypto communities as well as the democratization of finance, innovation and governance, resulting in a decentralized future for the crypto industry.
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Homes listed for sale in early June sell for $7,700 more
New Zillow research suggests the spring home shopping season may see a second wave this summer if mortgage rates fall
The post Homes listed for sale in…
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- A Zillow analysis of 2023 home sales finds homes listed in the first two weeks of June sold for 2.3% more.
- The best time to list a home for sale is a month later than it was in 2019, likely driven by mortgage rates.
- The best time to list can be as early as the second half of February in San Francisco, and as late as the first half of July in New York and Philadelphia.
Spring home sellers looking to maximize their sale price may want to wait it out and list their home for sale in the first half of June. A new Zillow® analysis of 2023 sales found that homes listed in the first two weeks of June sold for 2.3% more, a $7,700 boost on a typical U.S. home.
The best time to list consistently had been early May in the years leading up to the pandemic. The shift to June suggests mortgage rates are strongly influencing demand on top of the usual seasonality that brings buyers to the market in the spring. This home-shopping season is poised to follow a similar pattern as that in 2023, with the potential for a second wave if the Federal Reserve lowers interest rates midyear or later.
The 2.3% sale price premium registered last June followed the first spring in more than 15 years with mortgage rates over 6% on a 30-year fixed-rate loan. The high rates put home buyers on the back foot, and as rates continued upward through May, they were still reassessing and less likely to bid boldly. In June, however, rates pulled back a little from 6.79% to 6.67%, which likely presented an opportunity for determined buyers heading into summer. More buyers understood their market position and could afford to transact, boosting competition and sale prices.
The old logic was that sellers could earn a premium by listing in late spring, when search activity hit its peak. Now, with persistently low inventory, mortgage rate fluctuations make their own seasonality. First-time home buyers who are on the edge of qualifying for a home loan may dip in and out of the market, depending on what’s happening with rates. It is almost certain the Federal Reserve will push back any interest-rate cuts to mid-2024 at the earliest. If mortgage rates follow, that could bring another surge of buyers later this year.
Mortgage rates have been impacting affordability and sale prices since they began rising rapidly two years ago. In 2022, sellers nationwide saw the highest sale premium when they listed their home in late March, right before rates barreled past 5% and continued climbing.
Zillow’s research finds the best time to list can vary widely by metropolitan area. In 2023, it was as early as the second half of February in San Francisco, and as late as the first half of July in New York. Thirty of the top 35 largest metro areas saw for-sale listings command the highest sale prices between May and early July last year.
Zillow also found a wide range in the sale price premiums associated with homes listed during those peak periods. At the hottest time of the year in San Jose, homes sold for 5.5% more, a $88,000 boost on a typical home. Meanwhile, homes in San Antonio sold for 1.9% more during that same time period.
| Metropolitan Area | Best Time to List | Price Premium | Dollar Boost |
| United States | First half of June | 2.3% | $7,700 |
| New York, NY | First half of July | 2.4% | $15,500 |
| Los Angeles, CA | First half of May | 4.1% | $39,300 |
| Chicago, IL | First half of June | 2.8% | $8,800 |
| Dallas, TX | First half of June | 2.5% | $9,200 |
| Houston, TX | Second half of April | 2.0% | $6,200 |
| Washington, DC | Second half of June | 2.2% | $12,700 |
| Philadelphia, PA | First half of July | 2.4% | $8,200 |
| Miami, FL | First half of June | 2.3% | $12,900 |
| Atlanta, GA | Second half of June | 2.3% | $8,700 |
| Boston, MA | Second half of May | 3.5% | $23,600 |
| Phoenix, AZ | First half of June | 3.2% | $14,700 |
| San Francisco, CA | Second half of February | 4.2% | $50,300 |
| Riverside, CA | First half of May | 2.7% | $15,600 |
| Detroit, MI | First half of July | 3.3% | $7,900 |
| Seattle, WA | First half of June | 4.3% | $31,500 |
| Minneapolis, MN | Second half of May | 3.7% | $13,400 |
| San Diego, CA | Second half of April | 3.1% | $29,600 |
| Tampa, FL | Second half of June | 2.1% | $8,000 |
| Denver, CO | Second half of May | 2.9% | $16,900 |
| Baltimore, MD | First half of July | 2.2% | $8,200 |
| St. Louis, MO | First half of June | 2.9% | $7,000 |
| Orlando, FL | First half of June | 2.2% | $8,700 |
| Charlotte, NC | Second half of May | 3.0% | $11,000 |
| San Antonio, TX | First half of June | 1.9% | $5,400 |
| Portland, OR | Second half of April | 2.6% | $14,300 |
| Sacramento, CA | First half of June | 3.2% | $17,900 |
| Pittsburgh, PA | Second half of June | 2.3% | $4,700 |
| Cincinnati, OH | Second half of April | 2.7% | $7,500 |
| Austin, TX | Second half of May | 2.8% | $12,600 |
| Las Vegas, NV | First half of June | 3.4% | $14,600 |
| Kansas City, MO | Second half of May | 2.5% | $7,300 |
| Columbus, OH | Second half of June | 3.3% | $10,400 |
| Indianapolis, IN | First half of July | 3.0% | $8,100 |
| Cleveland, OH | First half of July | 3.4% | $7,400 |
| San Jose, CA | First half of June | 5.5% | $88,400 |
The post Homes listed for sale in early June sell for $7,700 more appeared first on Zillow Research.
federal reserve pandemic home sales mortgage rates interest ratesUncategorized
February Employment Situation
By Paul Gomme and Peter Rupert The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000…
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By Paul Gomme and Peter Rupert
The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000 average over the previous 12 months. The payroll data for January and December were revised down by a total of 167,000. The private sector added 223,000 new jobs, the largest gain since May of last year.
Temporary help services employment continues a steep decline after a sharp post-pandemic rise.
Average hours of work increased from 34.2 to 34.3. The increase, along with the 223,000 private employment increase led to a hefty increase in total hours of 5.6% at an annualized rate, also the largest increase since May of last year.
The establishment report, once again, beat “expectations;” the WSJ survey of economists was 198,000. Other than the downward revisions, mentioned above, another bit of negative news was a smallish increase in wage growth, from $34.52 to $34.57.
The household survey shows that the labor force increased 150,000, a drop in employment of 184,000 and an increase in the number of unemployed persons of 334,000. The labor force participation rate held steady at 62.5, the employment to population ratio decreased from 60.2 to 60.1 and the unemployment rate increased from 3.66 to 3.86. Remember that the unemployment rate is the number of unemployed relative to the labor force (the number employed plus the number unemployed). Consequently, the unemployment rate can go up if the number of unemployed rises holding fixed the labor force, or if the labor force shrinks holding the number unemployed unchanged. An increase in the unemployment rate is not necessarily a bad thing: it may reflect a strong labor market drawing “marginally attached” individuals from outside the labor force. Indeed, there was a 96,000 decline in those workers.
Earlier in the week, the BLS announced JOLTS (Job Openings and Labor Turnover Survey) data for January. There isn’t much to report here as the job openings changed little at 8.9 million, the number of hires and total separations were little changed at 5.7 million and 5.3 million, respectively.
As has been the case for the last couple of years, the number of job openings remains higher than the number of unemployed persons.
Also earlier in the week the BLS announced that productivity increased 3.2% in the 4th quarter with output rising 3.5% and hours of work rising 0.3%.
The bottom line is that the labor market continues its surprisingly (to some) strong performance, once again proving stronger than many had expected. This strength makes it difficult to justify any interest rate cuts soon, particularly given the recent inflation spike.
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Mortgage rates fall as labor market normalizes
Jobless claims show an expanding economy. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.
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Everyone was waiting to see if this week’s jobs report would send mortgage rates higher, which is what happened last month. Instead, the 10-year yield had a muted response after the headline number beat estimates, but we have negative job revisions from previous months. The Federal Reserve’s fear of wage growth spiraling out of control hasn’t materialized for over two years now and the unemployment rate ticked up to 3.9%. For now, we can say the labor market isn’t tight anymore, but it’s also not breaking.
The key labor data line in this expansion is the weekly jobless claims report. Jobless claims show an expanding economy that has not lost jobs yet. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.
From the Fed: In the week ended March 2, initial claims for unemployment insurance benefits were flat, at 217,000. The four-week moving average declined slightly by 750, to 212,250
Below is an explanation of how we got here with the labor market, which all started during COVID-19.
1. I wrote the COVID-19 recovery model on April 7, 2020, and retired it on Dec. 9, 2020. By that time, the upfront recovery phase was done, and I needed to model out when we would get the jobs lost back.
2. Early in the labor market recovery, when we saw weaker job reports, I doubled and tripled down on my assertion that job openings would get to 10 million in this recovery. Job openings rose as high as to 12 million and are currently over 9 million. Even with the massive miss on a job report in May 2021, I didn’t waver.
Currently, the jobs openings, quit percentage and hires data are below pre-COVID-19 levels, which means the labor market isn’t as tight as it once was, and this is why the employment cost index has been slowing data to move along the quits percentage.
3. I wrote that we should get back all the jobs lost to COVID-19 by September of 2022. At the time this would be a speedy labor market recovery, and it happened on schedule, too
Total employment data
4. This is the key one for right now: If COVID-19 hadn’t happened, we would have between 157 million and 159 million jobs today, which would have been in line with the job growth rate in February 2020. Today, we are at 157,808,000. This is important because job growth should be cooling down now. We are more in line with where the labor market should be when averaging 140K-165K monthly. So for now, the fact that we aren’t trending between 140K-165K means we still have a bit more recovery kick left before we get down to those levels.
From BLS: Total nonfarm payroll employment rose by 275,000 in February, and the unemployment rate increased to 3.9 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, in government, in food services and drinking places, in social assistance, and in transportation and warehousing.
Here are the jobs that were created and lost in the previous month:
In this jobs report, the unemployment rate for education levels looks like this:
- Less than a high school diploma: 6.1%
- High school graduate and no college: 4.2%
- Some college or associate degree: 3.1%
- Bachelor’s degree or higher: 2.2%
Today’s report has continued the trend of the labor data beating my expectations, only because I am looking for the jobs data to slow down to a level of 140K-165K, which hasn’t happened yet. I wouldn’t categorize the labor market as being tight anymore because of the quits ratio and the hires data in the job openings report. This also shows itself in the employment cost index as well. These are key data lines for the Fed and the reason we are going to see three rate cuts this year.
recession unemployment covid-19 fed federal reserve mortgage rates recession recovery unemployment
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