Looking back, it’s utterly bizarre how the world of science could have gone so silent even as the world locked down and lives were shattered by the billions by governments the world over. The silence was deafening. We went from a March 2, 2020, letter signed by 800 public health experts associated with Yale University—which warned against quarantines and closures—to a strange disappearance of nearly all clear voices a few weeks later. And so things stood for the better part of two years.
Governments were allowed to create vast carnage based on a novel experiment with absolutely no precedent in history and no scientific literature that backed it. Even the World Health Organization’s pandemic plan included nothing like lockdowns as a solution to a widespread pathogen. At the time, it was obvious to me and others that the silence was due not to broad agreement with the policies but to something else.
That something, sad to say, was money.
We are more and more discovering the heightened role that the crypto exchange FTX played in funneling money to major public health outposts and academics at Johns Hopkins and Stanford University, as well as its family connections to the Columbia University department of public health. And before that funding spigot opened up, there was the Gates Foundation which had clearly pivoted from seemingly nonpartisan research to full support for the lockdowns.
To be sure, there is no one explanation for the disaster. The whole profession had already been infected by the intellectual virus of mechanistic rationalism and modeling. The idea was that if you slap some math and equations together and let the computer take over, you can gain a picture of disease outcomes under various scenarios. Such models are easily manipulated with small changes in variables.
Deborah Birx relied on these entirely in her push to get the Trump administration to greenlight the lockdowns. And there can be no doubt about that history now that Trump’s Twitter account is alive again. The end of the censorship allows us to see how he was pressured to throw out his best instincts and instead adopt a lockdown policy, not just for two weeks but for months after, even to the point of criticizing Governor Brian Kemp of Georgia for opening up that Trump considered to be “too soon.”
(As an aside, the restoration of Trump’s account also allows us to see that his last two tweets urged all Jan. 6, 2021, protesters on Capitol to stay peaceful and respect the blue. It’s no wonder the ancien régime at Twitter wanted his account blocked and blasted away.)
Having studied this trajectory closely, it seems impossible to overlook the political motives here. No question that many elites in many places had whipped themselves up into a frenzy to the point that they were willing to crush the whole of society and even give up two years of education for kids in order to drive Trump from office. The plot was to get him to make the initial call himself based on telling him lies about virus severity and the effectiveness of lockdowns. No question that he was hornswoggled.
However, in addition to these factors, one cannot neglect financial factors. Quite plainly, the grant money at the time and for two years later was clearly on the side of lockdowns and the Democrat Party, plus the elite media and their narrative line that openness equals death and lockdowns/masking/mandates were public-spirited.
Vast numbers of scientists who could have and should have spoken out remained silent, or, worse, lent their voices in support of the outrage. Much of the reason has to do with how science is funded at the university level. It’s all about getting the next grant. It’s tragic but there is a strong motivation here to curate one’s opinions in a way that paves the way for future funding sources.
This is why it is not necessary that every sellout scientist be in receipt of direct funds from Gates, FTX, or the pharmaceutical industry. All that needs to happen to control a whole sector of opinion is for the word to get out on the streets that a funding source is there with countless millions and is ready to fork over.
As a result, even the smartest and most credentialled people can be easily made to fall in line. And no question that FTX quickly picked up the reputation of somehow being concerned about “pandemic planning” and so the whole of the industry lined up with their palms out. After all, FTX promised $100 million in grants!
This is why, the Washington Post reports, “The shock waves from FTX’s free fall have rippled across the public health world, where numerous leaders in pandemic-preparedness had received funds from FTX funders or were seeking donations.”
The seeking part is key here. But so is the money trail. FTX funded the later stages of the single biggest trials for repurposed therapeutics for COVID. Countless lives hung in the balance on these trials. Many physicians the world over had experienced great outcomes in dire circumstances from generic drugs such as HCQ, Ivermectin, fluvoxamine, and others, especially when used with other vitamins and zinc. Testing them was crucial.
The results were backed by a predictable media blitz: such therapeutics don’t work. Meanwhile, the study has been severely criticized not only for poor study construction but also for the conflicts of interests of top researchers who also consulted with pharmaceutical companies.
This is all very significant because there is a strong sense that the reason for the neglect of therapeutics—by the National Institutes of Health, Gates Foundation, and also major media, which smeared anyone who suggested there might be a better way—might all trace to the economic motive of shutting down cheap alternatives to vaccines.
Independent journalist Alexandros Marinos has mapped out the timeline of the study:
The Gates Foundation was first in, followed by Rainwater and FastGrants. FastGrants is a program established by the Charles G. Koch Foundation that also ended up giving money to Imperial College modeler Neil Ferguson, who first drove lockdown propaganda in the UK and United States. FTX modeled its own grant-giving program on FastGrants and then picked up the funding burden later in the process. (There is supreme irony here: the lie all over the internet was that the Great Barrington Declaration was funded by Koch, whereas in fact that money stream was going to the opposition!)
In addition, the Post notes, FTX “awarded $1.5 million to Stanford University’s Center for Innovation in Global Health in July for seed grants intended ‘to catalyze research and innovations that prepare for and help prevent the next pandemic.’”
Also: “The Future Fund’s commitments included $10 million to HelixNano, a biotech start-up seeking to develop a next-generation coronavirus vaccine; $250,000 to a University of Ottawa scientist researching how to eradicate viruses from plastic surfaces; and $175,000 to support a recent law school graduate’s job at the Johns Hopkins Center for Health Security.”
We don’t know how much money Gates/FTX gave to JHU’s Center for Health Security (which had sponsored Event 201) but it was enough to cause the Center’s head Tom Inglesby to completely reverse his earlier position against lockdowns to become a leading champion of them.
“Overall, the [FTX] Future Fund was a force for good,” Inglesby told the Post. “The work they were doing was really trying to get people to think long-term … to build pandemic preparedness, to diminish the risks of biological threats.”
Following the money trail from FTX to the public health establishment will undoubtedly reveal more in the way of information, especially considering that Sam Bankman-Fried’s brother Gabe ran a lobbying organization entirely devoted to “pandemic planning.”
No question that this whole machine became an industrial behemoth over two years. When I first started Brownstone Institute, my phone and email began to blow up with offers of money and funding, but always with a proviso. I had to connect our scientists with their network of scientists in an already established system.
There was no question in my mind what was going on: I was being told to play ball in exchange for large checks to make this fledgling nonprofit work. In some way, this astonished me: I was being offered a path to riches provided I would gut the whole mission! And this was happening even before we had published any of our research!
So, yes, I saw how this system works firsthand. Of course I completely rejected the idea simply because going along would defeat the whole point of founding an institute in the first place. And yet the presumption on the part of the contacts was that surely this was just another racket in a space full of them and I would be happy to give up all principles for generous funding. I never considered it even for one instant.
There is a grotesque tragedy to all of this. Great people gave up all their principles and integrity in exchange for grants and grease from big shots who used their money and power to wreck the world over two years, and they were able to do it with very little professional opposition. And yet here we are today. Who are the real stars in the world of science today? Not those on the Gates/FTX gravy train. It is the men and women who stuck their necks out to do the right thing.
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)…
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 Period
2023
2024
2025
2026
Date of Forecast
Sep23
Jun23
Sep24
Jun24
Sep25
Jun25
Sep26
Jun26
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.
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.
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/.
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).
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…
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.
New study unveils direct synthesis of FCMs via solid-state mechanochemical reaction between graphite and PTFE
A research team, led by Professor Jong-Beom Baek and his team in the School of Energy and Chemical Engineering at UNIST have achieved a significant breakthrough…
A research team, led by Professor Jong-Beom Baek and his team in the School of Energy and Chemical Engineering at UNIST have achieved a significant breakthrough in battery technology. They have developed an innovative method that enables the safe synthesis of fluorinated carbon materials (FCMs) using polytetrafluoroethylene (PTFE) and graphite.
Credit: UNIST
A research team, led by Professor Jong-Beom Baek and his team in the School of Energy and Chemical Engineering at UNIST have achieved a significant breakthrough in battery technology. They have developed an innovative method that enables the safe synthesis of fluorinated carbon materials (FCMs) using polytetrafluoroethylene (PTFE) and graphite.
Fluorinated carbon materials have garnered considerable attention due to their exceptional stability, attributed to the strong C-F bonding—the strongest among carbon single bonds. However, traditional methods of fluorination involve highly toxic reagents such as hydrofluoric acid (HF), making them unsuitable for practical applications.
In this study, the research team introduced a straightforward and relatively safe approach for scalable synthesis of FCMs through mechanochemical depolymerization of PTFE—a commonly used compound found in everyday items—and fragmentation of graphite. By utilizing ball-milling techniques that induce both mechanical and chemical reactions, they successfully produced FCMs with significantly improved performance compared to graphite.
The use of hazardous compounds like fluorine gas or HF in conventional carbon fluoride production raises safety concerns, increasing manufacturing costs associated with stringent safety measures. To address these challenges, Professor Baek’s team devised a solid-phase fluorination method using PTFE—an inert polymer known for its stability under atmospheric conditions and harmlessness when consumed orally.
Through experiments, it was observed that subjecting PTFE to higher energy than it can withstand leads to molecular chain breakage and radical formation—initiating a reaction resulting in the production of carbon fluoride complexes. These complexes then adhere to the surface and edges of graphite particles during subsequent processes.
The resulting FCMs demonstrated superior storage capacity and electrochemical stability compared to traditional graphite anodes. At a low charging rate of 50 mA/g, the FCMs exhibited storage capacities 2.5 times higher (951.6 mAh/g) than graphite, while at a high charging rate of 10,000 mA/g, their storage capacity was tenfold higher (329 mAh/g). Remarkably, even after more than 1,000 charge/discharge cycles at a rate of 2,000 mA/g, the FCMs retained 76.6% of their initial capacity compared to only 43.8% for graphite.
“This study highlights not just safe fluorination methods but also the broader potential of solid-phase reactions,” stated Boo-Jae Jang, a researcher in the School of Energy and Chemical Engineering at UNIST.
“This research prompts us to reconsider materials that are commonly found in our surroundings,” added Professor Baek. He further emphasized the significance of understanding solid-phase reactions as it opens doors to developing novel materials that were previously unexplored.
The study findings have been published ahead of their official publication in the online version of Advanced Functional Materials on July 27, 2023. This work has been supported through the U-K Brand and Carbon Neutrality projects of UNIST, and the Creative Research Initiative program through the National Research Foundation (NRF) of Korea.
Journal Reference
Boo-Jae Jang, Qiannan Zhao, Jae-Hoon Baek, et al., “Direct Synthesis of Fluorinated Carbon Materials via a Solid-State Mechanochemical Reaction Between Graphite and PTFE,” Adv. Funct. Mater., (2023).
Journal
Advanced Functional Materials
Article Title
Direct Synthesis of Fluorinated Carbon Materials via a Solid-State Mechanochemical Reaction Between Graphite and PTFE
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