The Atlanta Fed's macroblog provides commentary and analysis on economic topics including monetary policy, macroeconomic developments, inflation, labor economics, and financial issues.
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February 13, 2018
GDPNow's Forecast: Why Did It Spike Recently?
If you felt whipsawed by GDPNow recently, it's understandable. On February 1, the Atlanta Fed's GDPNow model estimate of first-quarter real gross domestic product (GDP) growth surged from 4.2 percent to 5.4 percent (annualized rates) after a manufacturing report from the Institute for Supply Management. GDPNow's estimate then fell to 4.0 percent on February 2 after the employment report from the U.S. Bureau of Labor Statistics. GDPNow displayed a similar undulating pattern early in the forecast cycle for fourth-quarter GDP growth.
What accounted for these sawtooth patterns? The answer lies in the treatment of the ISM manufacturing release. To forecast the yet-to-be released monthly GDP source data apart from inventories, GDPNow uses an indicator of growth in economic activity from a statistical model called a dynamic factor model. The factor is estimated from 127 monthly macroeconomic indicators, many of which are used to estimate the Chicago Fed National Activity Index (CFNAI). Indices like these can be helpful for forecasting macroeconomic data, as demonstrated here and here.
Perhaps not surprisingly, the CFNAI and the GDPNow factor are highly correlated, as the red and blue lines in the chart below indicate. Both indices, which are normalized to have an average of 0 and a standard deviation of 1, are usually lower in recessions than expansions.
A major difference in the indices is how yet-to-be-released values are handled for months in the recent past that have reported values for some, but not all, of the source data. For example, on February 2, January 2018 values had been released for data from the ISM manufacturing and employment reports but not from the industrial production or retail sales reports. The CFNAI is released around the end of each month when about two-thirds of the 85 indicators used to construct it have reported values for the previous month. For the remaining indicators, the Chicago Fed fills in statistical model forecasts for unreported values. In contrast, the GDPNow factor is updated continuously and extended a month after each ISM manufacturing release. On the dates of the ISM releases, around 17 of the 127 indicators GDPNow uses have reported values for the previous month, with six coming from the ISM manufacturing report.
[ Enlarge ]
For months with partially missing data, GDPNow updates its factor with an approach similar to the one used in a 2008 paper by economists Domenico Giannone, Lucrezia Reichlin and David Small. That paper describes a dynamic factor model used to nowcast GDP growth similar to the one that generates the New York Fed's staff nowcast of GDP growth. In the Atlanta Fed's GDPNow factor model, the last month of ISM manufacturing data have large weights when calculating the terminal factor value right after the ISM report. These ISM weights decrease significantly after the employment report, when about 50 of the indicators have reported values for the last month of data.
In the above figure, we see that the January 2018 GDPNow factor reading was 1.37 after the February 1 ISM release, the strongest reading since 1994 and well above either its forecasted value of 0.42 prior to the ISM release or its estimated value of 0.43 after the February 2 employment release. The aforementioned rise and decline in the GDPNow forecast of first-quarter growth is largely a function of the rise and decline in the January 2018 estimates of the dynamic factor.
Although the January 2018 reading of 59.2 for the composite ISM purchasing managers index (PMI) was higher than any reading from 2005 to 2016, it was little different than either a consensus forecast from professional economists (58.8) or the forecast from a simple model (58.9) that uses the strong reading in December 2017 (59.3). Moreover, it was well above the reading the GDPNow dynamic factor model was expecting (54.5).
A possible shortcoming of the GDPNow factor model is that it does not account for the previous month's forecast errors when forecasting the 127 indicators. For example, the predicted composite ISM PMI reading of 54.4 in December 2017 was nearly 5 points lower than the actual value. For this discussion, let's adjust GDPNow's factor model to account for these forecast errors and consider a forecast evaluation period with revised current vintage data after 1999. Then, the average absolute error of the 85–90 day-ahead adjusted model forecasts of GDP growth after ISM manufacturing releases (1.40 percentage points) is lower than the average absolute forecast error on those same dates for the standard version of GDPNow (1.49 percentage points). Moreover, the forecasts using the adjusted factor model are significantly more accurate than the GDPNow forecasts, according to a standard statistical test . If we decide to incorporate adjustments to GDPNow's factor model, we will do so at an initial forecast of quarterly GDP growth and note the change here .
Would the adjustment have made a big difference in the initial first-quarter GDP forecast? The February 1 GDP growth forecast of GDPNow with the adjusted factor model was "only" 4.7 percent. Its current (February 9) forecast of first-quarter GDP growth was the same as the standard version of GDPNow: 4.0 percent. These estimates are still much higher than both the recent trend in GDP growth and the median forecast of 3.0 percent from the Philadelphia Fed's Survey of Professional Forecasters (SPF).
Most of the difference between the GDPNow and SPF forecasts of GDP growth is the result of inventories. GDPNow anticipates inventories will contribute 1.2 percentage points to first-quarter growth, and the median SPF projection implies an inventory contribution of only 0.4 percentage points. It's not unusual to see some disagreement between these inventory forecasts and it wouldn't be surprising if one—or both—of them turn out to be off the mark.
August 09, 2007
Just in case it isn't completely obvious, macroblog is on a temporary hiatus as I make the transition to my new position at the Federal Reserve Bank of Atlanta. For those of you who have asked -- and really, thanks so much for asking -- this blog will indeed live on. Hope you hang tight, and don't delete me from your feeds -- I'll be back in action before you know it,
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June 21, 2007
Dark Matter By Any Other Name
... The United States miracle of the 1990s was that our productivity began growing faster than that of other countries, even though we were the richest to start with...
To explain the experience in the United States, one would have to believe that Americans have some better way of translating the new technology into productivity than other countries. And that is precisely what [London School of Economics] Professor [John] Van Reenen’s research suggests.
His paper “Americans Do I.T. Better: U.S. Multinationals and the Productivity Miracle,” (with Nick Bloom of Stanford University and Raffaella Sadun of the London School of Economics) looked at the experience of companies in Britain that were taken over by multinational companies with headquarters in other countries. They wanted to know if there was any evidence that the American genius with information technology transfers to locations outside the United States. If American companies turn computers into productivity better than anyone else, can businesses in Britain do the same when they are taken over by Americans?
And in the huge service sectors — financial services, retail trade, wholesale trade — they found compelling evidence of exactly that. American takeovers caused a tremendous productivity advantage over a non-American alternative.
When Americans take over a business in Britain, the business becomes significantly better at translating technology spending into productivity than a comparable business taken over by someone else. It is as if the invisible hand of the American marketplace were somehow passing along a secret handshake to these firms.
Sound familiar? If you can't quite put your finger on it, here's a refresher from Ricardo Hausmann and Federico Sturzenegger:
There is a large difference between our view of the US as a net creditor with assets of about 600 billion US dollars and BEA’s view of the US as a net debtor with total net debt of 2.5 trillion. We call the difference between these two equally arbitrary estimates dark matter, because it corresponds to assets that we know exist, since they generate revenue but cannot be seen (or, better said, cannot be properly measured)...
At least three factors account for the accumulation of dark matter. The first refers to foreign direct investment (FDI). Consider a simple example. Imagine the construction of EuroDisney at the cost of 100 million (the numbers are imaginary). Imagine also, for the sake of the argument that these resources were borrowed abroad at, say, a 5% rate of return. Once EuroDisney is in operation it yields 20 cents on the dollar. The investment generates a net income flow of 15 cents on the dollar but the BEA would say that the net foreign assets position would be equal to zero. We would say that EuroDisney in reality is not worth 100 million (what BEA would value it) but four times that (the capitalized value at our 5% rate of the 20 million per year that it earns). BEA is missing this and therefore grossly understates net assets. Why can EuroDisney earn such a return? Because the investment comes with a substantial amount of know-how, brand recognition, expertise, research and development and also with our good friends Mickey and Donald. This know-how is a source of dark matter. It explains why the US can earn more on its assets than it pays on its liabilities and why foreigners cannot do the same. We would say that the US exported 300 million in dark matter and is making a 5 percent return on it. The point is that in the accounting of FDI, the know-how than makes investments particularly productive is poorly accounted for.
That story might only go so far, as the Federal Reserve Bank of New York's Matthew Higgins, Thomas Klitgaard, and Cedric Tille claim...
... we review the argument that the United States holds large amounts of intangible assets not captured in the data—assets that would bring the true U.S. net investment position close to balance. We argue that intangible capital, while a relevant dimension of economic analysis, is unlikely to be substantial enough to alter the U.S. net liability position.
... but it's apparently more than a fairy tale.
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Tracked on Jun 22, 2007 12:46:50 AM
June 20, 2007
Apples To Apples
Today at Angry Bear, my friend pgl is doing some back-of-the-envelope econometrics:
From 1980QIV to 1992QIV, average annual real GDP growth = 3.0%.
From 1992QIV to 2000QIV, average annual real GDP growth = 3.6%.
From 2000QIV to 2006QIV, average annual real GDP growth = 2.6%.
Notice something? During the low tax eras (Reagan-Bush41 and Bush43), we witnessed lower growth rates. During the Clinton Administration – which began with its fiscally responsible policies with a tax rate increase – we saw strong growth. Maybe part of the explanation has to do with the impact on national savings from fiscal irresponsibility justified by phony free lunch promises.
I have a bit of a problem with the evidence here. To get the gist of my objection, take the following quiz:
Which one of these time periods did not include a recession?
a. 1980QIV to 1992QIV
b. 1992QIV to 2000QIV
c. 2000QIV to 2006QIV
If you answered b, you win the gold star. And if you knew that, are you really surprised that the period from 1992 through 2000 had higher average growth than the other two periods, which did include recessions? Suppose we instead make the comparisons including only the expansion years of the Reagan-Bush41 and Bush43 administrations? Here's what you get:
From 1983 to 1989, average annual real GDP growth = 4.3%.
From 1992 to 2000, average annual real GDP growth = 3.7%.
From 2002 to 2006, average annual real GDP growth = 2.9%.
You could just as well look at those numbers and conclude that potential GDP growth -- measured cycle to cycle -- is declining through time. And if you accept pgl's characterization of irresponsible policy, followed by responsible policy, followed by irresponsble policy, you might then conclude that policy has very little to do with that trend.
Perhaps you would want to argue that I shouldn't exclude recessions because the absence of a downturn in the 1992-2000 period is itself evidence of the superior growth effects of the fiscally responsible policies of the Clinton administration? Let me try to talk you out of that with a few more questions:
1. Do you really want to blame the Reagan fiscal policies for the 1980-82 recessions -- which are almost universally attributed to the Volcker Fed's fight against double digit inflation inherited from the policies of the 1970s?
2. Do you really want to characterize Bush41 as a tax cutter? And would you maintain that position knowing that Clinton's major piece of fiscal policy -- the Omnibus Reconciliation Act of 1993 --was pretty much of copy of the Omnibus Reconciliation Act of 1990, the legislation in which President Bush the Elder famously broke his "no new taxes" pledge?
3. Do you really want to finger the Bush43 tax cuts for the 2001 recession which began a scant two months into the administration and was over even before the tax cuts took effect?
Look -- It might very well be that "fiscal responsibility," as pgl defines it, is a central ingredient of pro-growth policy. But those GDP comparisons don't make the point.
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June 03, 2007
Taking It Slow
The recent spate of relatively good economic news has some people thinking rosier scenarios. From the Wall Street Journal (page A3 in yesterday's print edition):
The latest data show employment and manufacturing growing at a vigorous rate, suggesting the U.S. economy is regaining momentum after a slow start to 2007...
Nonfarm employers added 157,000 jobs to their payrolls in May, nearly double the 80,000 new jobs recorded in April, the Labor Department said Friday. Led by the service sector, the rebound brought the three-month average job gain to about 137,000, a pace strong enough to keep unemployment low and wages rising. The unemployment rate held steady at 4.5%.
Meanwhile, the Institute for Supply Management, a purchasing managers' trade group, reported that its index of manufacturing activity came in at 55 in May, up from 54.7 in April, indicative of expanded factory production. That is a stark contrast to earlier this year, when manufacturing activity was contracting.
Economists saw the reports as confirmation that the economy is regaining momentum despite the pain that high gasoline prices and the housing slump are inflicting on the consumer...
How quickly the economy rebounds will depend to a large extent on how U.S. consumers, whose purchases make up more than two-thirds of all economic activity, respond to the conflicting influences of high gasoline prices, falling house prices, a robust stock market and rising incomes. Friday, the latest reading on the University of Michigan's consumer sentiment index suggested they were still in relatively good spirits: The index rose to 88.3 in May from 87.1 in April.
It does feel like we've gained a little breathing room, but this picture sticks in my mind:
That second quarter of 2000 should remind us that it sometimes looks pretty sunny before the storm.
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May 21, 2007
Why Do We Have Money?
UPDATE: The broken link is fixed.
Think about a dollar bill.
If you’re hungry, you can’t eat it; in a rainstorm, it won’t keep you dry. But you can trade it for an apple or an umbrella. If you lived in a world without money, how would you get the things you want and need?
Play Escape from the Barter Islands to find out!
If you are a young student, a teacher presenting economic concepts to young students, or simply someone who feels like a young student, give it a shot.
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May 17, 2007
Soft, Not Too Soft
This morning's email from the Goldman Sachs Global Markets Research Group contains this assessment:
The recent industrial news, including April US industrial figures yesterday, have been positive, especially as it reduces the probability of one of the tail risks in the market, i.e. too soft growth. Nevertheless, we think the market remains too optimistic about US growth trends going forward. This is highlighted in the current Blue Chip Consensus, which shows US GDP growth rebounding from 1.3% in Q1 (which as the US Daily discusses overnight is likely to be revised down) to 3% as soon as second half of this year.
If our US growth views prove correct, the market may yet need to revise down its growth expectations. In that regard, it is striking how growth expectations in the equity markets (as captured by our Wavefront US growth basket) have continued to grind higher.
So, while we are comfortable with our view of a US soft landing, markets may need to adjust to a less optimistic macro reality than is priced in. This potential downward adjustment could prove to be one of the several road bumps for risky assets in coming quarters.
Not everyone will have to revise down those expectations. The economists queried for last week's Wall Street Journal forecasting survey seem to (at least broadly) share the Goldman view:
On the whole, the 60 economists predict gross domestic product, the broadest measure of economic output, will grow at a 2.2% annual rate this quarter. Over the second half, they expect growth of about 2.6%, which is a slight reduction from what they had forecast in a survey conducted last month. They don't expect growth to reach 3% until the second quarter of 2008.
Certainly the voices of Fed chairs past and present, while not endorsing a particular forecast, are aligned with the no-tailspin crowd. From Bloomberg:
The Fed chairman maintained his forecast that the slump in housing won't have a broader impact on the economy. "We do not expect significant spillovers from the subprime market to the rest of the economy or financial system,'' Bernanke said.
Fed officials this year have cited the housing recession as a main risk to growth, which was the weakest in four years last quarter. Bernanke's comments today reflect the consensus of policy makers that the downturn in housing is unlikely to cause consumers to cut spending. Former Fed chief Alan Greenspan also said that subprime problems aren't spreading to lower-risk loans.
"The prime market is doing reasonably well,'' Greenspan, who retired in January 2006, said today at a meeting hosted by the Atlanta Journal-Constitution in Atlanta. "Some people are holding off on purchasing homes. Even so, we are getting a gradual rise in the prime market.''
Meanwhile, the rest of the world seems to be doing pretty well, thank you. Back to the Goldman boys:
We do not expect the prolonged period of sub-trend US growth that we foresee to cause major problems for the rest of the world. Recent data has shown further evidence of global decoupling with softer US economic news on the one hand (soft retail sales), and robust growth dynamics in the rest of the world, particularly in Europe and China (Q1 GDP growth in Euroland was above consensus and the April activity data for China have been strong).
However, this begs the question of how bad it would have to get for the global decoupling theme to unravel?
In our latest Global Economics Weekly, we extended the spill-over analysis we conducted last year to study the growth experience of other major economies (Japan, Germany, UK and France) conditional on whether US economy is contracting (i.e. real growth on qoq terms is negative) or expanding (i.e. real growth on qoq terms is positive)...
... Overall, our analysis supports our thinking that as long as US growth remains in expansion mode (which we forecast), other major economies should be able to decouple.
According to a report in todays the Wall Street Journal, some rather astute folks think it may be the other way around:
Early last year, [chief investment officer at Pacific Investment Management Company William H.] Gross's outlook for the U.S. bond market hinged on housing. "We did our homework," he says. "We sent out scouts into middle America, down to Florida." They did make some correct calls, such as predicting a drop in long-term interest rates last summer.
What Pimco didn't foresee was the impact on the U.S. of the strength in the global economy, led by China and the rest of the Asia. Mr. Gross says they recognized there was inherent strength abroad. But they counted on issues such as the U.S. trade deficit and increasing leverage around the world to have "snapback potential like a rubber band" that would restrain growth and allow the Fed to lower rates. That didn't happen.
Either way, the soft-landers appear to be feeling their oats.
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May 16, 2007
The Wisdom Of Forecasting Crowds (Such As It Is)
Ever wonder who you should turn to for expert economic prognostications? My colleagues Mike Bryan and Linsey Molloy (future Chicago MBA!) remind us that the answer is everybody and nobody:
... we examine economists' year-ahead growth and inflation predictions since 1983 to see whether any have distinguished themselves as particularly good (or bad) forecasters over time.
We find little evidence that any forecaster consistently predicts better than the consensus (median) forecast and, further, we find that forecasters who gave better-than-average predictions in one year were unable to sustain their superior forecasting performance—at least no more than random chance would suggest.
Not that consensus forecasts are all that great:
... we summarize the track record of the median economist’s year-ahead predictions for real GDP growth and CPI inflation since 1983. (Forecasts were compiled by the Livingston Survey.) If we arbitrarily define an accurate prediction as being within 1/2 percentage point of the realized outcome, we would say that since 1983 the median forecast was accurate in only seven years, or about 30 percent of the time... The accuracy of the median forecaster’s prediction of inflation was a bit better over the 23-year period. Inflation predictions were accurate—that is, within 1/2 percentage point of actual inflation—39 percent of the time...
... So suppose the median forecaster expects the economy to grow 3.4 percent next year (its average since 1983). You could conclude—with 90 percent confidence—that the economy will grow between a robust 5.8 percent and a sluggish 1 percent. Similarly, the RMSE of the median economist’s inflation prediction over this period was 1 percent, which means that given an average inflation rate of 3.1 percent, you could be about 90 percent confident that prices will rise between a stable 1.4 percent and an uncomfortably rapid 4.8 percent over the coming year.
Fair warning, I think.
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» Forecast Accuracy and Consensus Forecasts from Businomics Blog
A recent report from the Cleveland Fed by Michael F. Bryan and Lindsey Molloy confirm older results that consensus forecasts do better than any one forecaster. (Hat tip to Macroblog.) That's one reason I pay close attention to consensus forecasts, [Read More]
Tracked on May 19, 2007 1:19:48 PM
May 07, 2007
Long-Term Capital Management And The Fed
My colleague Joe Haubrich writes about "Some Lessons on the Rescue of Long-Term Capital Management":
... the LTCM episode raises many key issues about the resolution of financial crises: How far should the involvement of the central bank extend, what is the scope of action each of the various players should be responsible for, and what are the costs and benefits of the differing options? ...
Joe starts with two distinct views of the event and the Federal Reserve's involvement. First, from Myron Scholes:
Although the Federal Reserve Bank (FRB) facilitated the takeover, it did not bail out LTCM. Many debtor entities found it in their self-interest not to post the collateral that was owed to LTCM, and other creditor entities claimed to be ahead of others to secure earlier payoffs. Without the FRB acting quickly to mitigate these holdup activities, LTCM would have had to file for bankruptcy—for some, a more efficient outcome, but a far more costly outcome for society. If there was a bailout, it failed: LTCM has been effectively liquidated.
The Fed’s intervention was misguided and unnecessary because LTCM would not have failed anyway, and the Fed’s concerns about the effects of LTCM’s failure on financial markets were exaggerated. In the short run the intervention helped the shareholders and managers of LTCM to get a better deal for themselves than they would otherwise have obtained.
After more discussion of arguments pro and con, Dr. Haubrich concludes with his own take on the lessons learned:
Lesson 1: Context matters. Large losses at a financial firm do not by themselves create a need for Federal Reserve action: there must be a systemic component...
... Federal Reserve Board Chairman Alan Greenspan explained:
The scale and scope of LTCM's operations, which encompassed many markets, maturities, and currencies and often relied on instruments that were thinly traded and had prices that were not continuously quoted, made it exceptionally difficult to predict the broader ramifications of attempting to close out its positions precipitately.
In that passage, Mr. Greenspan continued:
It was the judgment of officials at the Federal Reserve Bank of New York, who were monitoring the situation on an ongoing basis, that the act of unwinding LTCM's portfolio in a forced liqudiation would not only have a significant distorting impact on market prices but also in the process could produce large losses, or worse, for a number of creditors and counterparties, and for other market participants who were not directly involved with LTCM. In that environment, it was the FRBNY's judgment that it was to the advantage of all parties--including the creditors and other market participants--to engender if at all possible an orderly resolution rather than let the firm go into disorderly fire-sale liquidation following a set of cascading cross defaults.
Joe goes on:
Lesson 2: Details matter.
That the problem was resolved successfully depended, in a large part, on “the orderly continuation in the risk arbitrage business of the newly recapitalized LTCM” (Bank for International Settlements, 1999, p. 9) which in turn depended on getting the details of the recapitalization right. In the LTCM case it meant retaining the management, giving enough stake in the firm to provide an incentive for efficient liquidation, and bringing in outside oversight.
Even after taking the intermediate step of “providing good offices,” the amount and type of moral suasion had to be decided on. Each choice in turn faced trade-offs...
Which brings us to:
Lesson 3: Look for the minimum effective intervention; or work with the market not against it.
... there is some evidence that even more reliance could have been placed on the market in the LTCM case. Stock prices and federal funds rates incorporated substantially correct information about exposures to LTCM. Fed intervention, despite its limited character, may have indeed increased moral hazard by increasing the perception of too-big-to-fail.
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April 29, 2007
What Are You Going To Believe -- Theory Or Your Own Lying Eyes?
The blogger epicenter of the free-trade debate is rumbling at Harvard, with Greg Mankiw and Dani Rodrik engaged in a terrific -- and important -- conversation about winners, losers, and how (or whether) economic theory divides the two. You can check-in on the state of the debate at Angry Bear, where pgl provides the appropriate links. It is highly recommended reading, but I think it ought to come with a few warning labels. For example, Professor Rodrik responds to Professor Mankiw with this claim:
... there is no theorem that guarantees that the partial-equilibrium losses to import-competing producers “are more than offset by gains to consumers from lower prices.”
In a related vein, pgl opens his post with:
Let's be perfectly clear: There are no theorems in economics that guarantee anything about the real world. Economic models are not descriptions of physical realities but formalizations of stories about how social interactions deliver particular outcomes. Different, equally coherent, stories deliver different predictions about the world. The claim that "free trade benefits everyone" is not a fallacy, but a particular outcome based on a particular model. Different models deliver different answers, so theory alone does nothing beyond eliminating stories that are internally inconsistent.
Or, perhaps, unconvincing. The missing ingredient in this most recent installment of the free-trade discussion is evidence in favor of one story or another, a task that is a good deal messier than writing down models. What makes matters worse is that adjudicating the issue is not a mere matter of counting up winners and losers. In the court of determining what is "good" or "bad", economists have standing to address one question, and one question only: Can someone be made better off without making anyone worse off? That too depends on the model at hand, and in fact it's even worse than that. The Rodrik-Mankiw debate revolves in part around a result known as the Stolper-Samuelson theorem. Greg Mankiw does a good job explaining Stolper-Samuleson and its relevance to the subject at hand, but I'll note one item from the Wikipedia description of the theorem:
If considering the change in real returns under increased international trade a robust finding of the theorem is that returns to the scarce factor will go down, ceteris paribus. A further robust corollary of the theorem is that a compensation to the scarce-factor exists which will overcome this effect and make increased trade Pareto optimal.
In simple terms, there are losers, but the winners can win enough to more than match those losses. All would be well with the world if the winners and losers could be easily identified, and an appropriate compensation scheme implemented. But what if that is not feasible? What is the right move then? To protect the losers at the expense of significant opportunity cost to potential winners? The other way around? I've yet to encounter an economist trained to answer those questions, and you should be very suspicious of any who speak as if they are.
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