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Top crypto app downloads rise over 15% following SVB collapse

Following a shakeup in the U.S. banking system over the past week, crypto exchanges and wallets gained momentum as some look for bankless alternatives….

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Following a shakeup in the U.S. banking system over the past week, crypto exchanges and wallets gained momentum as some look for bankless alternatives.

The top 10 crypto applications for exchanges and wallets have risen about 15% since Silicon Valley Bank’s stock fell 60% last week, according to a chart from real-time app data provider Apptopia. The top 10 crypto apps were defined as Coinbase, Crypto.com, Trust, Binance, Bitcoin and Crypto DeFi Wallet, Blockchain.com, KuKoin, Kraken, eToro and BitPay.

Chaos in US banks could push crypto industry toward decentralization

Meanwhile, the top 10 traditional banks and top 10 “digital first” bank app downloads have fallen during the same time frame about 5% and 3%, respectively. The top 10 banking apps include Capital One, Chase, Bank of America, Wells Fargo, Discover, Citi and U.S. Bank, among others. The top 10 digital first apps were Chime, Dave, Albert, Empower, Varo, MoneyLion, Current, Aspiration, Sable and Oxygen.

Image Credits: Apptopia (opens in a new window)

The divergence in downloads points to general concern across the U.S. from customers amid the recent banking crisis.

Last week, Silvergate Capital, Silicon Valley Bank and Signature Bank all shut down or were closed, which resulted in crypto companies and investors and traditional users alike scrambling to move their assets.

The shuttering of these banks brought on bigger questions around where people and companies should park assets and which banks they can (or can’t) trust.

Other midsize and regional banks, including First Republic, have been under pressure following SVB’s collapse. First Republic had the third-highest rate of uninsured U.S. deposits behind SVB and Signature with about $119.5 billion in uninsured deposits, according to Reuters.

The crypto market is showing a “positive contagion” after the SVB collapse, similar to what transpired in 2020 when investors fled traditional markets during the COVID-19 pandemic in favor of alternative assets, Stefan Rust, CEO of inflation data aggregator Truflation and former CEO of Bitcoin.com, previously said to TechCrunch+.

In the wake of all this chaos, bitcoin and ether, the biggest cryptocurrencies by market cap, had a seven-day increase of about 15% and 9%, respectively, at the time of publication, according to CoinMarketCap data. The global market cap for all cryptocurrencies also increased 8.3% during the same time period to about $1.1 trillion, slightly down from a weekly high of $1.14 trillion on Tuesday, the data showed.

The market madness has seemingly created a bullish sentiment in the crypto economy; as traders responded positively to the news, the overall market cap rose on the week and crypto app downloads increased.

Read more about SVB's 2023 collapse on TechCrunch

Top crypto app downloads rise over 15% following SVB collapse by Jacquelyn Melinek originally published on TechCrunch

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New research reveals gut microbiota link to colitis: intestinal epithelial axin1 deficiency offers protective effects

A groundbreaking study conducted by Jun Sun’s research team at the University of Illinois Chicago has revealed a new and critical role of Axin1 in regulating…

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September 22, 2023

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A groundbreaking study conducted by Jun Sun’s research team at the University of Illinois Chicago has revealed a new and critical role of Axin1 in regulating intestinal epithelial development and microbial homeostasis. The research, published in the journal Engineering, highlights the potential therapeutic strategies for human inflammatory bowel disease (IBD).

Credit: Shari Garrett et al.

A groundbreaking study conducted by Jun Sun’s research team at the University of Illinois Chicago has revealed a new and critical role of Axin1 in regulating intestinal epithelial development and microbial homeostasis. The research, published in the journal Engineering, highlights the potential therapeutic strategies for human inflammatory bowel disease (IBD).

IBD, a chronic inflammatory disorder affecting the gastrointestinal tract, has been a significant health concern worldwide. The study focused on understanding the role of Axin1, a negative regulator of Wnt/β-catenin signaling, in maintaining gut homeostasis and host response to inflammation.

The research team analyzed Axin1 expression in human inflammatory bowel disease datasets and found increased Axin1 expression in the colonic epithelium of IBD patients. To further investigate the effects and mechanism of intestinal Axin1 in regulating intestinal homeostasis and colitis, the team generated new mouse models with Axin1 conditional knockout in intestinal epithelial cells (Axin1ΔIEC) and Paneth cells (Axin1ΔPC).

The results showed that Axin1ΔIEC mice exhibited altered goblet cell spatial distribution, Paneth cell morphology, reduced lysozyme expression, and an enriched presence of Akkermansia muciniphila (A. muciniphila) in the gut microbiota. Importantly, the absence of intestinal epithelial and Paneth cell Axin1 led to decreased susceptibility to dextran sulfate sodium-induced colitis in vivo.

Furthermore, when Axin1ΔIEC and Axin1ΔPC mice were cohoused with control mice, they became more susceptible to dextran sulfate sodium (DSS)-colitis, suggesting the protective role of Axin1 in the presence of a healthy gut microbiota. Treatment with A. muciniphila further reduced the severity of DSS-colitis, highlighting its potential as a therapeutic target.

Interestingly, antibiotic treatment did not change the proliferation of intestinal epithelial cells in the control mice. However, in Axin1ΔIEC mice with antibiotic treatment, the intestinal proliferative cells were significantly reduced, indicating the non-colitogenic effects driven by the gut microbiome.

These findings demonstrate the novel role of Axin1 in mediating intestinal homeostasis and the microbiota. The loss of intestinal Axin1 protects against colitis, likely through the regulation of epithelial Axin1 and Axin1-associated A. muciniphila. Further mechanistic studies using specific Axin1 mutations will be crucial in elucidating how Axin1 modulates the microbiome and host inflammatory response, paving the way for new therapeutic strategies for human IBD.

Jiaming Wu, editor of the subject of medicine and health of Engineering, commented, “This study provides valuable insights into the development of inflammatory bowel disease and offers potential therapeutic strategies for its treatment. By understanding the intricate interactions between Axin1, the gut microbiota, and host immunity, researchers can develop targeted interventions to restore intestinal homeostasis and alleviate the symptoms of IBD.”

The research team’s findings have significant implications for the field of gastroenterology and hold promise for the development of novel treatments for IBD. As further studies are conducted, the scientific community eagerly awaits the potential therapeutic breakthroughs that may arise from this research.

The paper “Profiling the Antimalarial Mechanism of Artemisinin by Identifying Crucial Target Proteins”, authored by Shari Garrett, Yongguo Zhang, Yinglin Xia, Jun Sun. Full text of the open access paper: https://doi.org/10.1016/j.eng.2023.06.007. For more information about the Engineering, follow us on Twitter (https://twitter.com/EngineeringJrnl) & like us on Facebook (https://www.facebook.com/EngineeringPortfolio).

 

About Engineering

Engineering (ISSN: 2095-8099 IF:12.8) is an international open-access journal that was launched by the Chinese Academy of Engineering (CAE) in 2015. Its aims are to provide a high-level platform where cutting-edge advancements in engineering R&D, current major research outputs, and key achievements can be disseminated and shared; to report progress in engineering science, discuss hot topics, areas of interest, challenges, and prospects in engineering development, and consider human and environmental well-being and ethics in engineering; to encourage engineering breakthroughs and innovations that are of profound economic and social importance, enabling them to reach advanced international standards and to become a new productive force, and thereby changing the world, benefiting humanity, and creating a new future.

Journal

Engineering

DOI

10.1016/j.eng.2023.06.007

Article Title

Intestinal Epithelial Axin1 Deficiency Protects Against Colitis via Altered Gut Microbiota

Article Publication Date

25-Jul-2023

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The New York Fed DSGE Model Forecast— September 2023

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE)…

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41 mins ago

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September 22, 2023

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Marco Del Negro, Pranay Gundam, Donggyu Lee, Ramya Nallamotu, and Brian Pacula

This post presents an update of the economic forecasts generated by the Federal Reserve Bank of New York’s dynamic stochastic general equilibrium (DSGE) model. We describe very briefly our forecast and its change since June 2023. As usual, we wish to remind our readers that the DSGE model forecast is not an official New York Fed forecast, but only an input to the Research staff’s overall forecasting process. For more information about the model and variables discussed here, see our DSGE model Q & A.

The New York Fed model forecasts use data released through 2023:Q2, augmented for 2023:Q3 with the median forecasts for real GDP growth and core PCE inflation from the Survey of Professional Forecasters (SPF), as well as the yields on ten-year Treasury securities and Baa-rated corporate bonds based on 2023:Q3 averages up to August 30. Moreover, starting in 2021:Q4, the expected federal funds rate between one and six quarters into the future is restricted to equal the corresponding median point forecast from the latest available Survey of Primary Dealers (SPD) in the corresponding quarter. The current projection can be found here.

The change in the forecast relative to June reflects the fact that the economy remains resilient in spite of the increasingly restrictive stance of monetary policy. Output growth is projected to be almost 1 percentage point higher in 2023 than forecasted in June (1.9 versus 1.0 percent) and somewhat higher than June for the rest of the forecast horizon (1.1, 0.7, and 1.2 percent in 2024, 2025, and 2026, versus 0.7, 0.4, and 0.9 in June, respectively). The probability of a not-so-soft recession, as defined by four-quarter GDP growth dipping below -1 percent by the end of 2023, has become negligible at 4.6 percent, down from 26 percent in June. According to the model, much of the resilience in the economy so far stems from the surprising strength in the financial sector, which counteracts the effects of the tightening in monetary policy. Inflation projections are close to what they were in June: 3.7 percent for 2023 (unchanged from the previous forecast), 2.2 percent for 2024 (down from 2.5 percent), and 2.0 percent for both 2025 and 2026 (down from 2.2 and 2.1 percent, respectively). The model still sees inflation returning close to the FOMC’s longer-run goal by the end of next year.

The output gap is projected to be somewhat higher over the forecast horizon than it was in June, consistent with the fact that the surprising strength of the economy is mainly driven by demand factors such as financial shocks, as opposed to supply factors. As in the June forecast, the gap gradually declines from its current positive value to a slightly negative value by 2025. The real natural rate of interest is estimated at 2.5 percent for 2023 (up from 2.2 percent in June), declining to 2.2 percent in 2024, 1.9 percent in 2025, and 1.6 percent in 2026. 

Forecast Comparison

Forecast Period2023202420252026
Date of ForecastSep 23Jun 23Sep 24Jun 24Sep 25Jun 25Sep 26Jun 26
GDP growth
(Q4/Q4)		1.9
 (0.2, 3.6) 		1.0
 (-1.9, 4.0) 		1.1
 (-4.0, 6.3) 		0.7
 (-4.2, 5.7) 		0.7
 (-4.4, 5.8) 		0.4
 (-4.7, 5.5) 		1.2
 (-4.2, 6.6) 		0.9
 (-4.5, 6.3) 
Core PCE inflation
(Q4/Q4)		3.7
 (3.4, 3.9) 		3.7
 (3.3, 4.2) 		2.2
 (1.5, 3.0) 		2.5
 (1.6, 3.3) 		2.0
 (1.1, 2.9) 		2.2
 (1.2, 3.1) 		2.0
 (1.0, 3.0) 		2.1
 (1.1, 3.2) 
Real natural rate of interest
(Q4)		2.5
 (1.3, 3.7) 		2.2
 (1.0, 3.5) 		2.2
 (0.8, 3.7) 		1.8
 (0.3, 3.2) 		1.9
 (0.3, 3.4) 		1.5
 (-0.1, 3.0) 		1.6
 (-0.0, 3.3) 		1.3
 (-0.4, 3.0) 
Source: Authors’ calculations.
Notes: This table lists the forecasts of output growth, core PCE inflation, and the real natural rate of interest from the September 2023 and June 2023 forecasts. The numbers outside parentheses are the mean forecasts, and the numbers in parentheses are the 68 percent bands.

Forecasts of Output Growth

Source: Authors’ calculations.
Notes: These two panels depict output growth. In the top panel, the black line indicates actual data and the red line shows the model forecasts. The shaded areas mark the uncertainty associated with our forecasts at 50, 60, 70, 80, and 90 percent probability intervals. In the bottom panel, the blue line shows the current forecast (quarter-to-quarter, annualized), and the gray line shows the June 2023 forecast.

Forecasts of Inflation

Source: Authors’ calculations.
Notes: These two panels depict core personal consumption expenditures (PCE) inflation. In the top panel, the black line indicates actual data and the red line shows the model forecasts. The shaded areas mark the uncertainty associated with our forecasts at 50, 60, 70, 80, and 90 percent probability intervals. In the bottom panel, the blue line shows the current forecast (quarter-to-quarter, annualized), and the gray line shows the June 2023 forecast.

Real Natural Rate of Interest

Source: Authors’ calculations.
Notes: The black line shows the model’s mean estimate of the real natural rate of interest; the red line shows the model forecast of the real natural rate. The shaded area marks the uncertainty associated with the forecasts at 50, 60, 70, 80, and 90 percent probability intervals.

Marco Del Negro is an economic research advisor in Macroeconomic and Monetary Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.

photo of Gundam Pranay

Pranay Gundam is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

Donggyu Lee is a research economist in Macroeconomic and Monetary Studies in the Federal Reserve Bank of New York’s Research and Statistics Group.

Ramya Nallamotu is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

photo of Brian Pacula

Brian Pacula is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.

How to cite this post:
Marco Del Negro, Pranay Gundam, Donggyu Lee, Ramya Nallamotu, and Brian Pacula, “The New York Fed DSGE Model Forecast— September 2023,” Federal Reserve Bank of New York Liberty Street Economics, September 22, 2023, https://libertystreeteconomics.newyorkfed.org/2023/09/the-new-york-fed-dsge-model-forecast-september-2023/.

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The New York Fed DSGE Model Forecast— June 2023

Disclaimer
The views expressed in this post are those of the author(s) and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the author(s).

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The Big Picture of the housing market, and its almost complete bifurcation, in 3 easy graphs

  – by New Deal democratI want to spend some time commenting on the broader issue of why the public perceives that inflation is still rampant, even though…

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41 mins ago

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September 22, 2023

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 - by New Deal democrat


I want to spend some time commenting on the broader issue of why the public perceives that inflation is still rampant, even though almost all official measures show it rapidly decelerating, and even completely absent on a YoY basis currently by a few measures. A big part of that has to do with housing, and since I’ve discussed several facets of that issue in discussing the data releases this week, I wanted to pull that together into a “Big Picture” summary. I do that in 3 simple graphs below.

Graph #1: Active listing counts of existing homes (red, left scale) vs. new housing under construction (blue, right scale):



The average mortgage on an existing home is something like 3.5%. Huge numbers of people either bought or refinanced when mortgage rates were 3%, and now those people are locked in. For example, a $1000 monthly interest payment at 3% is a $2333 monthly interest payment at 7%. Those people are locked into their existing home for the foreseeable future.

As a result, the existing home market has collapsed. As I showed yesterday, sales are near 25 year lows. The active listing count above, which averaged 1.3 million in the years prior to the pandemic, even with a modest recovery in the past year is still only about 700,000, a -600,000 decline.

Meanwhile the number of new homes under construction has risen from about 1.125 million annualized in the years before the pandemic to about 1.725 annualized, a mirror image +600,000 increase.

In other words, the seizing up of the existing home market has diverted people to the new home market.

Graph #2: median price of existing (red) vs. new (blue) homes:



The NAR only lets FRED publish the last year of their price data, which is not seasonally adjusted, but that is fine for today’s purposes, so the above graph compares it with the not seasonally adjusted price data for new homes.

The lack of inventory of existing homes means that prices got bid up, and remain bid up. Builders responded by building lots of new units, and unlike existing homeowners, they can respond to market conditions by varying their price point, which the above graph shows they have done. The median price for a new home went down -$100,000, or 20%, a few months ago, and is still down about -15% from its peak last year.

Graph #3: Single vs. multi-family units under construction:



The Millennial generation and the first part of Gen Z are well into their home-buying years. But because they have been priced out of large parts of the market, due to both the aforesaid big rise in mortgage rates, but also the post-pandemic increase in prices, they have had to downsize their target from single family homes to the less expensive condos or apartments.

As part of their adjustment described above, apartments and condos are being built hand over fist, and builders are offering price or financing concessions. Single family houses under construction have declined by about 20% from summer 2022, while multi-family units soared to a new all-time record, about 20% higher than their level in summer 2022.

It’s the housing version of shrinkflation, since - although the data isn’t easily available - I think we can take notice of the fact that apartment and condo units are considerably less expensive on average than single family detached houses.

[As an aside, note that a very similar thing happened in the 1970s when the Baby Boom generation was well and truly into their first home-buying years. While the Millennial generation is slightly bigger numerically than the Boomers, since the total US population was only 50% of its current size back in the 1960s, proportionately the Boomers had an even bigger impact on the market.]

That’s the Big Picture of the almost complete bifurcation of the current housing market. The “shrinkflation” I’ve described above is very much a part of why the public continues to believe that inflation remains a big problem. 

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