Long time readers already know what I’m going to say, but since Tyler Cowen asked the following:

Let’s say more migrants arrive in a country.  One view, held by Bryan Caplan, is that (ceteris paribus) the monetary base is fixed, so now the monetary base per capita has decline.  Thus immigration is deflationary.  There are more people and not more money, alternatively you could say that the demand to hold money has gone up.  (I am, by the way, blogging this with Bryan’s permission.)

Another view, mine, is that the new immigrants shift out both the aggregate demand and aggregate supply curves, and the net effect can be either inflationary or deflationary.  Even given a fixed monetary base, M2 likely will go up, as for instance banks will find they have more desirable loans to make, for instance to the new arrivals.  Optimal reserve requirements and money multiplier variables are likely to change, so the fixed monetary base need not choke off a demand increase.

Who is right and under which conditions?

My first response is that immigration probably won’t impact inflation, as the Fed targets inflation at 2%. Thus the monetary base (and IOR) will be adjusted as needed to keep long run inflation at 2%. But what if we assume a fixed monetary base? Who’s right in that case?

I’d say that Bryan is probably correct in the long run. (And long run effects are presumably what we care about with immigration.)

But Tyler’s reasoning is correct; immigration would likely provide a one-time boost to base velocity. Thus at cyclical frequencies you might well get higher inflation. Think of it this way:

1. Suppose an extra 3 million immigrants per year permanently boosts trend RGDP growth by 1%. As a result, US real interest rates rise by 75 basis points.

2. Suppose that a 75 basis point increase in interest rates permanently boosts base velocity from 10 to 11.

In that case, with a fixed monetary base you get a roughly 10% one-time boost in NGDP (and inflationary boom) followed by a permanent reduction in trend inflation of 1% (due to faster RGDP growth.)

In my view, we should not assume that the monetary base would actually be fixed, and the baseline assumption should be no effect on inflation due to monetary offset. But if the economy is currently out of equilibrium (as it is today), then more immigration might affect inflation in the short run. Surprisingly, I suspect it might actually reduce inflation by boosting the economy’s supply side so much that the Fed can bring inflation down more easily without creating a recession. By that’s highly speculative, and you could also argue that it would trigger a Fed expansionary policy mistake by boosting the natural interest rate by more than the Fed estimates. If the Fed doesn’t raise rates, inflation would rise.

When thinking about the merits of more immigration, I’d put inflation near the bottom of the list of factors we should consider.

PS. FWIW, high immigration Australia has generally had relative high base velocity, which fits the model.

1. The Economist reports that British Columbia is decriminalizing possession of small amounts of all hard drugs:

On January 31st British Columbia became the first province in Canada to decriminalise certain illegal drugs. Anyone aged 18 and older can now legally possess a combined 2.5 grams of illicit substances, including cocaine, opioids such as heroin, methamphetamine and ecstasy (or mdma). Owners will no longer be arrested, charged or have their drugs seized. Police will hand out leaflets with treatment suggestions instead.

2. Also from Canada:

It helps that few Canadians are opposed to migrants. Some 85% of those surveyed believe immigration is good for the economy and 69% support current or increased immigration levels. Fully 76% would like to see the country accept more refugees. By contrast, 30 years ago, when half as many immigrants came each year, 70% felt there was too much immigration.

Some of this generosity is pragmatic. Around 1m posts are unfilled across the country, about 6% of the total. With an ageing population, things are likely only to get worse. Fifty years ago there were seven workers for every pensioner; by 2035 the ratio is forecast to be 2:1. Already more than 40% of Canadians are 55 or older.

Pro-migration sentiment also stems from the fact that a quarter of Canadians today are themselves immigrants. 

3. And still more good news from Canada. A year ago, Canada had a land border with only one country (the US). Today, Canada has a land border with two countries, the US and Denmark:

The resolution also had the side effect of giving Canada and Denmark a land border with each other, which means that both countries no longer border only one other country (the United States and Germany, respectively).

4. Attitudes in the UK are also turning more pro-immigration:

If it is a race, one of the unexpected winners so far is the UK. Plenty of Brits who voted against Brexit — myself included — thought that outside the EU, the country would become more insular. But net migration reached a record high of about half a million people last year. The UK shot into the top 10 of the OECD’s rankings of countries that are most attractive to highly skilled workers. Most strikingly, the public seems fine with it. In 2022, for the first time in polling history, more people favoured maintaining, or even increasing, levels of migration than favoured cuts.

5. China’s going electric:

Chinese sales of petrol and diesel cars fell 20pc in absolute volume terms in February from a year earlier. Sales of plug-in electric vehicles kept rising explosively and reached a record 32pc of the market for standard passenger cars.

At the current pace, EV sales in China will hit eight million this year, helped by the proliferation of battery-swapping stations. Rather than charging your own car, you do an instant swap. No need to wait. No need for charge-points everywhere.

And bad news for Saudi Arabia—this is happening faster than expected:

The consensus forecast until recently was that EV penetration would reach 40pc of Chinese sales by 2030. That threshold could be crossed as soon as this year if manufacturers can produce fast enough to meet the demand. “We think EVs will reach 80pc of sales in China by 2030,” said Kingsmill Bond from energy strategists RMI.

6. Faux News network has to pay $787 million in a libel suit. (Unfortunately, the out of court settlement means that people like Tucker Carlson won’t be put under oath, having to explain the way they deceive their viewers.) And more lawsuits are coming.

7. And this:

Fox News and Tucker Carlson have parted ways. The rest of the network seems thrilled.

“Pure joy,” one Fox reporter told Rolling Stone of their reaction to the split. “No one is untouchable. It’s a great day for America, and for the real journalists who work hard every day to deliver the news at Fox.”

“Good riddance,” said a network correspondent. “For a while there it seemed like he was running the network. This clearly is a message that he’s not. In the interim, it’s a morale boost, that’s for sure.”

8. This may not be a big deal. But with so much bad news out of Xi Jinping’s China, this counts as at least a sliver of hope:

Update: Here’s the link to the resolution.

When did conservatives become such snowflakes? I frequently see conservatives complain that San Francisco has become a hellhole due to feces and needles on the sidewalk. While I didn’t notice that problem when I visited last year, no doubt there’s at least some truth to it. But so what?

When I grew up in Madison (in the 1960s), there was dog poop everywhere. No one picked up after their dogs. Maybe that was just Madison, but I doubt it. I suspect other American cities were the same. If you had told a Madisonian that their city was a hell hole due to dog poop on the sidewalks, they would have looked at you like you were a mentally ill germaphobe. What’s wrong with this guy? Is he one of those obsessive compulsives who wash their hands each day? (Just kidding, I mean 20 times a day.)

Seriously, dog poop on the sidewalk was not a major problem; we didn’t go through our lives obsessing about the issue. (Ditto for the ubiquitous cigarette smoke—no one cared.)

Needles? I don’t know about you, but I generally don’t make a practice of walking through the Tenderloin district barefoot. Get a grip!

San Francisco is actually a wonderful city, with two big problems. One is housing. They need to get rid of residential zoning in order to lower prices. And yet conservatives are turning against free markets in housing!

The other is petty crime. In this case the conservatives are correct. They need to arrest and imprison shoplifters and those crazy people on the sidewalk who repeatedly harass respectable people. Is it still political correct to say that? If not, feel free to cancel me.

PS. Not only was Madison not a hellhole, according to Life magazine it was the best place to live in America (in 1948). And America was the best country. And I lived in the best area of Madison (the westside). Ah, the good life.

But there’s a snake in the grass. See that dog in the picture? That mom is letting her little girls play near dog poop:

My new book focuses on the question of how best to think about the stance of monetary policy. This is closely related to the “identification problem”, which is the problem of identifying monetary policy shocks.

Some of the earliest attempts to estimate the impact of monetary shocks resulted in what’s called a “price puzzle”. It seemed like easy money led to lower inflation, and vice versa. That makes no sense. (A similar problem occurs with fiscal policy, where deficit spending is often correlated with slower economic growth.) The trick is to find the exogenous part of monetary policy, not the response to economic conditions. Are interest rates rising because of tight money, or because of higher NGDP growth expectations?

Some of the best work in this area has been done by Eric Swanson. In a new paper, Michael Bauer and Eric Swanson estimate structural VAR models in two ways. In the set of graphs below, the results on the right show a naive model, that doesn’t fully account for feedback effects. The response functions show the impact of a 25 basis point rise in the 2-year Treasury yield.

You can see the price puzzle in the left column (second row), where the CPI seems to rise in response to an increase in interest rates (assumed to be a tighter monetary policy.)

In the right column, the monetary policy shock (mps) is orthogonalized. This involves regressing the shock on previous macro data, and then using the residual (the unexplained portion) as the exogenous monetary policy shock. Now industrial production, the CPI, credit spreads (EBP) and interest rates all move as expected.

Another innovation in the Bauer-Swanson paper was to look beyond FOMC announcements, and also include market responses to speeches by the Fed chair. The combined effect of all of these innovations was to produce much more reliable estimates of the impact of monetary policy. Policy was shown to have a four times larger impact than observed in previous studies.

The following graph also shows the response of commodity prices and unemployment. Notice that the (sticky price) CPI barely moves at first, while (flexible) commodity prices immediately plunge by about 100 basis points. But after 50 months, both are down roughly 20 basis points, which is consistent with long run money neutrality:

Bauer and Swanson do a nice job explaining why the private sector has a difficult time predicting (and identifying) changes in the stance of monetary policy:

There are a number of plausible reasons to think that private-sector learning about the Fed’s monetary policy rule would be quite slow in practice, with the result that changes in αt would cause a persistently large discrepancy αt − at . First, learning about a persistent component (αt) from a noisy time series (it) is difficult and happens only gradually, with longlasting biases in beliefs; see Farmer, Nakamura and Steinsson (2021) for a recent discussion. Second, the private sector in reality faces a multidimensional learning problem: Realistic policy rules are of course multivariate, requiring the public to learn about several parameters at once, which greatly slows down the learning process (Johannes et al., 2016). Third, the private sector must form beliefs about which macroeconomic and financial variables enter the Fed’s monetary policy rule, i.e., about its functional form. Fourth, the Fed’s monetary policy rule could contain nonlinearities—which we have also abstracted from here—so that, in practice, the Fed responds most aggressively to the economy when the economic data is most extreme. These extreme events occur only very rarely, so it is extraordinarily difficult for the private sector to learn the Fed’s true responsiveness to the economy during these rare episodes.

Interestingly, Bauer and Swanson found that Fed speeches had a surprisingly small impact on the stock market:

The last two columns of Table 3 report the estimated effects of Fed Chair speeches on financial markets. Two-year and five-year Treasury yields respond almost identically to Fed Chair speeches as they do to FOMC announcements, while ten- and 30-year Treasury yields respond even more strongly. The R2 for Fed Chair speech effects are also even higher than those for FOMC announcements. Together, these observations confirm the general point in Swanson and Jayawickrema (2021) that speeches by the Fed Chair are even more important for the Treasury market than FOMC announcements themselves. By contrast, the response of the stock market is substantially weaker, with an R2 around 3 percent. The modest stock market response to Chair speeches is somewhat puzzling in light of the fact that monetary policy typically has pronounced effects on the stock market (Bernanke and Kuttner, 2005; G¨urkaynak et al., 2005). One possible explanation is based on information effects: Speeches by the Fed Chair could potentially have larger information effects than FOMC announcements, given the extensive conversations the Chair is having with the public or Congress about the Fed’s outlook for monetary policy and the U.S. economy. . . . Another explanation is that other news besides the Chair’s speech could have moved interest rates and stock prices during the event window.

I wonder if this difference might also reflect the fact that FOMC announcements primarily move rates via the “liquidity effect”, that is, where higher interest rates represent tighter money. Perhaps Fed speeches also impact rates via the Fisher effect. Thus the speech might convey information about the chair’s longer run views on the appropriate monetary regime. In that case, higher rates can be associated with easier money.

Here it might be useful to review a couple graphs from my new book, which show two possible expected exchange rate paths after a monetary shock:

These two money announcements have an identical impact on interest rates. Due to the interest parity condition, both reduce the nominal interest rate for a period of time. But in the first case the shock produces long run currency depreciation, and hence is expansionary. This is Dornbusch overshooting. In the second case, there is long run currency appreciation, and hence the shock is contractionary.

If you think of monetary policy as moving the actual interest rate relative to the natural rate, in the first case the market rate has been reduced, without any necessary change in the natural rate. In the Swiss case from 2015, the sharp currency appreciation caused the natural interest rate to fall even more sharply than the actual interest rate, hence policy became tighter.

The ECB recently published a very interesting paper by Marek Jarociński, which looks at these issues using a slightly different approach. I’m pretty weak at econometrics so I’m not qualified to provide an overall evaluation of the paper (or Bauer-Swanson), but I like the way Jarociński thinks about these issues. Here’s the abstract:

Fed monetary policy announcements convey a mix of news about different conventional and unconventional policies, and about the economy. Financial market responses to these announcements are usually very small, but sometimes very large. I estimate the underlying structural shocks exploiting this feature of the data, both assuming that the structural shocks are independent and relaxing this assumption. Either approach yields the same tightly estimated shocks that can be naturally labeled as standard monetary policy, Odyssean forward guidance, large scale asset purchases and Delphic forward guidance.

I like this. It’s not just a question of how much the interest rate changes, there are qualitative differences between various types of monetary shocks. Again, if we use the market rate/natural rate language, monetary shocks can move both the market interest rate and the natural interest rate.

In my research on the Great Depression, I concluded that extremely large shocks provided an unusually important source of information about the structure of the economy. Here’s Jarociński:

To identify the structural shocks I exploit a striking, yet hitherto neglected feature of the data. Namely, financial market reactions to FOMC announcements are usually very small, but sometimes very large, i.e. they have very fat tails, or excess kurtosis. This feature implies that the data may contain information about the nature of the underlying structural shocks. Given the importance of the Fed policies, it is vital to exploit this available information as well as possible. Previous literature has ignored it, treating the shocks explicitly or implicitly as Gaussian. This paper is, to my knowledge, the first attempt to tap this valuable source of information.

And here’s how he identifies the four types of shocks:

More in detail, the baseline model expresses the surprises (i.e., the high-frequency reactions to FOMC announcements) in the near-term fed funds futures, 2- and 10-year Treasury yield and the S&P500 stock index as linear combinations of four Student-t distributed shocks. It turns out that these four shocks are very precisely estimated and ex post have natural economic interpretations. The first shock raises the near-term fed funds futures, with a diminishing effect on longer maturities, and depresses the stock prices. It can be naturally labeled as the standard monetary policy shock. The remaining shocks do not meaningfully affect the near-term fed funds futures. The second shock increases the 2-year Treasury yield the most and depresses the stock prices. It can be naturally labeled as the (Odyssean) forward guidance shock. The third shock increases the 10-year Treasury yield the most and plays a large role in some of the most important asset purchase announcements. It can be naturally labeled as the asset purchase shock. The fourth shock has a similar impact on the yield curve as the Odyssean forward guidance shock, but triggers an increase, rather than a decrease, in the stock prices. Therefore, this shock matches the concept of Delphic forward guidance introduced by Campbell et al. (2012).

I welcome all of these studies, partly because they support my intuition that monetary policy (including forward guidance and QE) are much more powerful than many people seem to believe. We have a monetary regime that when combined with the dominant theoretical framework (roughly IS-LM) is almost ideally suited to making monetary policy appear less effective than it actually is.

On the other hand, I don’t think we’ll ever be able to resolve the key macro policy problems using this approach. Policy is too complex—it’s about both Fed errors of commission and omission, what are often extremely hard to identify.

Instead, I favor moving toward a regime where we collapse the monetary policy indicator, instrument and goal into one variable—NGDP futures prices. Ideally, NGDP futures prices would be the policy instrument (the thing we target), the policy indicator (the thing we look at to determine the current stance of policy) and the policy goal (with the goal being say 4%/year growth in NGDP futures prices, level targeting.)

Then we can stop doing all these SVAR models.

HT: Ben Southwood.

PS. I also comment on the Bauer/Swanson paper over at Econlog.

Bloomberg has an article on the growing unpopularity of the US:

Former Treasury Secretary Lawrence Summers warned of “troubling” signs that the US is losing global influence as other powers align together and win favor among nations not yet aligned. . . .

“Somebody from a developing country said to me, ‘what we get from China is an airport. What we get from the United States is a lecture,’” said Summers, a Harvard University professor and paid contributor to Bloomberg TV.

Obviously, lecturing other countries is not the best way to win friends and influence people. Better to lead by example. But it’s actually far worse than Summers suggests.

Over the past 4 decades, many if not most of our “lectures” have been US officials arrogantly telling less developed nations (and even developed places) that they needed to follow the “Washington Consensus”. You remember the Washington Consensus, the idea that countries should refrain from protectionism and industrial policies.

Now the US has abandoned the Washington Consensus and decided to go all in with protectionism and industrial policy. And that’s because we supposedly need to do this to keep from falling behind. But weren’t we told that these policies slow economic development?

It’s annoying when you get lectured to by more successful countries. It’s especially annoying then the lecture comes from self righteous societies that don’t follow their own advice. Is it any wonder that developing countries have lost respect for the US government.

I have too.