The an­i­mal is ag­ing. Not sur­pris­ing; I knew it would hap­pen even­tu­ally, but I did­n’t make any pro­vi­sions to deal with that even­tu­al­ity.  Somehow the re­al­ity crept up on me. And now it must be dealt with, day af­ter day.

It is rest­less in the night, moan­ing about aches, un­able to find a com­fort­able po­si­tion for sleep.  It awakes me too early, mus­cles stiff and re­luc­tant to move but un­able to re­turn to sleep. And if I let it sit still, it dozes off in the mid­dle of the day.  Finding foods it can eat with­out up­set­ting its di­ges­tion has be­come a task as it re­jects more and more foods but balks at the mo­not­o­nous diet it can man­age.  And de­spite re­strict­ing its food, it is putting on pounds, its mid­dle thick­en­ing as the crea­ture loses strength, loses flex­i­bil­ity.

When it was young, I drove it hard.  I fed it what­ever was to hand, or did­n’t feed it at all.  It slept only when I no longer needed its la­bor at the end of a long day. Day af­ter day of steady work, night sleep sac­ri­ficed for more work; It did­n’t seem to mind.  It could run, it could climb, it could carry heavy loads.  It was never the loveli­est of its kind, but it had en­durance and strength be­yond what some oth­ers  pos­sessed.  It still does, but it pays more dearly when what I de­mand ex­ceeds what I should ex­pect of it.  It never had fast re­flexes, and now it’s even slower to re­act.

The an­i­mal re­mem­bers every harsh thing I’ve done to it. I kept it too long in the cold, frost­bit­ing its feet, and now every cold floor re­minds it of what I did.   I have de­gen­er­ated its joints to keep to a sched­ule.  Now its grip is fad­ing.  I risked its eye­sight by star­ing end­lessly at a screen, and now the col­ors are fad­ing out of its day.

As our time to­gether is wind­ing slowy to a close, I wish I’d taken bet­ter care of it.  Better food, more ex­er­cise, more re­lax­ation . . . but I also won­der if it would have made any dif­fer­ence.  I tell my­self it still has use­ful years ahead of it, even if it can’t do some of the things it once ac­com­plished with ease.  I re­flect, sheep­ishly, that it is the only an­i­mal I have ever treated this way.  Would I have fed a beloved dog stim­u­lants to keep it work­ing when it needed sleep? Never.  Would I have dosed a cat with a mild poi­son­ing of al­co­hol to re­lax it among strangers?  Of course not.

But this one an­i­mal re­ceived no mercy from me. And I re­gret that now.

And so we en­ter our 70th year to­gether.  Me, and the an­i­mal I live in­side.

Be kind to an­i­mals. It’s never too late to start.

Are you tired of your URLs be­ing just too darn short? Worry no fur­ther, as aaa.aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa.com has got your back. No need to be anx­ious about peo­ple think­ing the size of your URL is too small, as it will guar­an­teed be the largest one around. So what are you wait­ing for? Give it a go!

Your date will be im­pressed with the sheer size of your URLs, and for­get hav­ing to take time spelling them out to your cowork­ers; just yell at the top of your lungs. Want to au­to­mate it? Check out the docs for more info.

Like and com­ment on the Replit App.

Data col­lec­tion:

I use Plausible to col­lect in­sights on web­site us­age. You’re prob­a­bly won­der­ing, “Why would such a small, jok­ing web­site need to col­lect such an­a­lyt­ics?” Well, the an­swer to that is since the site it­self is sta­tic, this was the eas­i­est way I could sim­ply see how many peo­ple were us­ing my site. Since I want to be as trans­par­ent as pos­si­ble, I’ve ac­tu­ally made my plau­si­ble dash­board pub­lic so you can see the num­bers for your­self and also how lit­tle data I am col­lect­ing. The dash­board is avail­able here.

Use a path in­stead of a pa­ra­me­ter¹:

Override URL check²:

In the Cloud Connect Community, dis­cuss the lat­est fea­tures with Googlers and other Google Workspace ad­mins like you. Learn tips and tricks that will make your work and life eas­ier. Be the first to know what’s hap­pen­ing with Google Workspace.

On the “What’s new in Google Workspace?” Help Center page, learn about new prod­ucts and fea­tures launch­ing in Google Workspace, in­clud­ing smaller changes that haven’t been an­nounced on the Google Workspace Updates blog.

Google Workspace Beta Programs give par­tic­i­pat­ing cus­tomers an op­por­tu­nity to help us im­prove and de­velop new prod­ucts and fea­tures as well as pro­vide feed­back on them, be­fore they’re made gen­er­ally avail­able.

JavaScript has come a long way since I knew it as the “D” in DHTML. For any­one like me, who’s been re­luc­tant to use the lat­est syn­tax that could re­quire poly­fills or a tran­spiler, I’ve writ­ten this cheat­sheet to get you caught up on all the good­ness that’s widely sup­ported in mod­ern browsers.

I’ve made this page con­cise, with runnable ex­am­ples and links to fur­ther doc­u­men­ta­tion. If you have any ques­tions or spot any er­rata, please con­tact me.

Check out all these new built-in ar­ray func­tions! No more need for un­der­score or lo­dash!

These new key­words de­clare vari­ables in block scope (as op­posed to global or func­tion scope). Using const im­plies that the value will not change as the ref­er­ence is im­mutable. Use let if the value will change.

The ?? op­er­a­tor checks if the value is null or un­de­fined. No more need to use the !! check.

The ?. op­er­a­tor checks if the value is truthy be­fore call­ing the next prop­erty or func­tion. Extremely use­ful when deal­ing with op­tional props.

The async/​await key­words are here to save you from call­back hell. Use await to make an asyn­chro­nous call re­sem­ble a syn­chro­nous call, i.e. run­ning await fetchUser­Name() will not pro­ceed to the next line un­til fetchUser­Name() is com­plete. Note, in or­der to use await, you have to be ex­e­cut­ing a func­tion de­clared as async, i.e.

async func­tion fn(){ await fetchUser­Name() }.

These are func­tions that are bound to the cur­rent con­text. There are three main forms you’ll see in the wild:

sin­gle ar­gu­ment, sin­gle line, multi-line.

The sin­gle ar­gu­ment form does not re­quire paren­the­sis, and the sin­gle line form does not re­quire a re­turn state­ment; the re­turn is im­plicit.

The multi-line form re­quires a re­turn state­ment if the func­tion in­tends to re­turns some­thing. Multiple ar­gu­ments re­quire paren­the­sis.

Used for loop­ing over an it­er­a­tor. Similar to for…in ex­cept you don’t have to check for ha­sOwn­Prop­erty. You can­not use this loop­ing syn­tax on an Object di­rectly be­cause the Object does­n’t have an it­er­a­tor. Instead use Object.entries({}) to re­trieve an it­er­able.

Asynchronous it­er­a­tion was in­tro­duced In 2018. Much like Promise.all, it can be used to syn­chro­nize many asyn­chro­nous tasks. The ex­am­ple be­low shows 3 tasks hap­pen­ing asyn­chro­nously. The loop processes one re­sult at a time, in or­der; in this case, the quick­est tasks to com­plete are only ev­i­dent at the end of the it­er­a­tion.

for await…of docs

In 2015, ES6 brought classes to Javascript 🎉. Javascript classes are sim­i­lar to the classes you know and love from other lan­guages. Inheritance, class meth­ods, get­ters and set­ters, prop­er­ties, etc.

Get and set are func­tions that are called like prop­er­ties, i.e. per­son.age = 16; per­son.age > 18. These are very con­ve­nient when you need a dy­namic or com­puted prop­erty. And they can be used with both classes and reg­u­lar ob­jects.

Yay! You can now spec­ify de­fault pa­ra­me­ters in your func­tion de­f­i­n­i­tion. Works as you would ex­pect.

With a bit of ob­ject de­struc­tu­ing magic, func­tions can now have named pa­ra­me­ters.

The re­set pa­ra­me­ter al­lows a func­tion to ac­cept an ar­bi­trary num­ber of ar­gu­mentsas an ar­ray. It’s rec­om­mended to use this over ar­gu­ments.

Object.assign(target, source) merges two or more ob­jects into one. It mod­i­fies the tar­get ob­ject in-place, so if you’d pre­fer a new ob­ject be cre­ated, pass an empty ob­ject lit­eral as the first ar­gu­ment.

Alternatively, you can use the spread op­er­a­tor … to merge mul­ti­ple ob­jects to­gether: {…obj1, …obj2}, though bear in mind, spread will not call set­ters on the ob­ject, so to be the most portable, con­sider Object.assign. The spread op­er­a­tor can also be used on ar­rays as shown in the last code sam­ple.

Destructuring al­lows you to ex­tract val­ues from ob­jects and ar­rays through pat­terns. It is a com­plex topic with many ap­pli­ca­tions…far too many for me to enu­mer­ate, but I’ve shown some of the most com­mon uses I can think of.

Destructuring docs and MDN docs­func­tion f() {

re­turn [1, 2];

let [a, b] = f()

print(“a=“+a + ” b=” + b)

const obj = {state: {id: 1, is_ver­i­fied: false}}

const {id, is_ver­i­fied: ver­i­fied} = obj.state

print(“id = ” + id)

print(“ver­i­fied = ” + ver­i­fied)

for (const [key, value] of Object.entries({a: 1, b: 2, c: 3})) {

print(key + ” is ” + value);

Functions de­clared on ob­jects can use a new short­hand style that omits the func­tion key­word.

The two func­tions (fn1, fn2) are equiv­a­lent in the sam­ple be­low.

I’ve mostly skipped over promises be­cause async/​await is pre­ferred, but some­times you need to syn­chro­nize mul­ti­ple asyn­chro­nous calls, and Promise.all is the eas­i­est way to do it.

Also known as tem­plate strings, this new syn­tax pro­vides easy string in­ter­po­la­tion and multi-line strings.

A Proxy al­lows you to in­ter­cept get/​set calls on an­other ob­ject. This could be use­ful for watch­ing a prop­erty for changes, then up­dat­ing the DOM, or mak­ing in­no­v­a­tive APIs like the www proxy be­low.

Proxy doc­slet _nums = [1,2,3]

let nums = new Proxy(_nums, {

set(tar­get, key, value) {

tar­get[key] = value

print(“set called with ” + key + “=” + value)

print(“up­date DOM”)

re­turn true

nums.push(4)

print(“nums: ” + nums)

print(“_nums: ” + _nums)

Modules al­low you to name­space your code and break down func­tion­al­ity into smaller files. In the ex­am­ple be­low, we have a mod­ule named greet.js that gets in­cluded in in­dex.html. Note, mod­ule load­ing is al­ways de­ferred, so it won’t block the HTML from ren­der­ing. There are many ways to im­port/​ex­port func­tion­al­ity from js files, read more in the ex­port docs.

Okay, so I did­n’t cover every­thing that’s changed over the last decade, just the items I find most use­ful. Check out these other top­ics.

Permafrost Engine is an OpenGL 3.3 Real Time Strategy game en­gine writ­ten in C. It is made in the im­age of old clas­sics, but in­cor­po­rat­ing some mod­ern ideas.

EVERGLORY is the flag­ship game de­vel­oped us­ing Permafrost Engine.

Download the free (or do­nate what-you-want) demo on itch.io or on Steam. With the demo you also get ac­cess to all the scripts and as­sets pow­er­ing the game­play to learn from and mod­ify as you wish.

* OpenGL 3.3 pro­gram­ma­ble pipeline (more mod­ern ex­ten­sions used where avail­able)

* Dynamic col­li­sion avoid­ance of mul­ti­ple en­ti­ties us­ing Hybrid Reciprocal Velocity Obstacles and the ClearPath al­go­rithm

* Pathfinding of dif­fer­ent kinds/​sizes of units (using “navigation lay­ers”)

* Support for dif­fer­ent res­o­lu­tions and as­pect ra­tios

* Serialization and de­se­ri­al­iza­tion of the en­tire Python in­ter­preter state

* Saving and restor­ing of any en­gine ses­sion, in­clud­ing all Python-defined state

* Fiber sys­tem for putting work in light­weight tasks that are sched­uled in user­space

* Windows launcher to au­to­mat­i­cally cap­ture a minidump and std­out, stderr logs on ap­pli­ca­tion er­ror

All de­pen­den­cies can be built from source and dis­trib­uted along with the game bi­nary if de­sired. Python is built with a sub­set of the de­fault mod­ules and pack­aged with a trimmed-down stdlib.

make deps (to build the shared li­brary de­pen­den­cies to ./lib)

Now you can in­voke make run to launch the demo or make run_ed­i­tor to launch the map ed­i­tor. Optionally, in­voke make launch­ers to cre­ate the ./demo and ./editor bi­na­ries which don’t re­quire any ar­gu­ments.

The source code can be built us­ing the mingw-w64 cross-com­pi­la­tion tool­chain (http://​mingw-w64.org/​doku.php) us­ing largely the same steps as for Linux. Passing PLAT=WINDOWS

to the make en­vi­ron­ment is the only re­quired change.

The com­pli­a­tion can ei­ther be done on a Linux host, or na­tively on Windows us­ing MSYS2 (https://​www.msys2.org/).

Permafrost Engine is li­censed un­der the GPLv3, with a spe­cial link­ing ex­cep­tion.

Follow the de­vel­op­ment of Permafrost Engine and EVERGLORY on YouTube.

Comments or ques­tions re­gard­ing the pro­ject or the source code? E-mail: ed­ward.permyakov@gmail.com. Discuss EVERGLORY and its’ de­vel­op­ment on Discord. If you have a use­ful fix for a

non-triv­ial en­gine is­sue, feel free to make a PR. Be warned that I will scru­ti­nize every patch to make sure it meets my per­sonal qual­ity stan­dards for the en­gine code. It you wish to evel­ove the en­gine in some way and want the changes to be up­streamed, then do get in touch to dis­cuss it.

The DarkSide ran­somware af­fil­i­ate pro­gram re­spon­si­ble for the six-day out­age at Colonial Pipeline this week that led to fuel short­ages and price spikes across the coun­try is run­ning for the hills. The crime gang an­nounced it was clos­ing up shop af­ter its servers were seized and some­one drained the cryp­tocur­rency from an ac­count the group uses to pay af­fil­i­ates.

“Servers were seized (country not named), money of ad­ver­tis­ers and founders was trans­ferred to an un­known ac­count,” reads a mes­sage from a cy­ber­crime fo­rum re­posted to the Russian OSINT Telegram chan­nel.

“A few hours ago, we lost ac­cess to the pub­lic part of our in­fra­struc­ture,” the mes­sage con­tin­ues, ex­plain­ing the out­age af­fected its vic­tim sham­ing blog where stolen data is pub­lished from vic­tims who refuse to pay a ran­som.

“Hosting sup­port, apart from in­for­ma­tion ‘at the re­quest of law en­force­ment agen­cies,’ does not pro­vide any other in­for­ma­tion,” the DarkSide ad­min says. “Also, a few hours af­ter the with­drawal, funds from the pay­ment server (ours and clients’) were with­drawn to an un­known ad­dress.”

DarkSide or­ga­niz­ers also said they were re­leas­ing de­cryp­tion tools for all of the com­pa­nies that have been ran­somed but which haven’t yet paid.

“After that, you will be free to com­mu­ni­cate with them wher­ever you want in any way you want,” the in­struc­tions read.

The DarkSide mes­sage in­cludes pas­sages ap­par­ently penned by a leader of the REvil ran­somware-as-a-ser­vice plat­form. This is in­ter­est­ing be­cause se­cu­rity ex­perts have posited that many of DarkSide’s core mem­bers are closely tied to the REvil gang.

The REvil rep­re­sen­ta­tive said its pro­gram was in­tro­duc­ing new re­stric­tions on the kinds of or­ga­ni­za­tions that af­fil­i­ates could hold for ran­som, and that hence­forth it would be for­bid­den to at­tack those in the “social sec­tor” (defined as health­care and ed­u­ca­tional in­sti­tu­tions) and or­ga­ni­za­tions in the “gov-sector” (state) of any coun­try. Affiliates also will be re­quired to get ap­proval be­fore in­fect­ing vic­tims.

The new re­stric­tions came as some Russian cy­ber­crime fo­rums be­gan dis­tanc­ing them­selves from ran­somware op­er­a­tions al­to­gether. On Thursday, the ad­min­is­tra­tor of the pop­u­lar Russian fo­rum XSS an­nounced the com­mu­nity would no longer al­low dis­cus­sion threads about ran­somware mon­ey­mak­ing pro­grams.

“There’s too much pub­lic­ity,” the XSS ad­min­is­tra­tor ex­plained. “Ransomware has gath­ered a crit­i­cal mass of non­sense, bull­shit, hype, and fuss around it. The word ‘ransomware’ has been put on a par with a num­ber of un­pleas­ant phe­nom­ena, such as geopo­lit­i­cal ten­sions, ex­tor­tion, and gov­ern­ment-backed hacks. This word has be­come dan­ger­ous and toxic.”

In a blog post on the DarkSide clo­sure, cy­ber in­tel­li­gence firm Intel 471 said it be­lieves all of these ac­tions can be tied di­rectly to the re­ac­tion re­lated to the high-pro­file ran­somware at­tacks cov­ered by the me­dia this week.

“However, a strong caveat should be ap­plied to these de­vel­op­ments: it’s likely that these ran­somware op­er­a­tors are try­ing to re­treat from the spot­light more than sud­denly dis­cov­er­ing the er­ror of their ways,” Intel 471 wrote. “A num­ber of the op­er­a­tors will most likely op­er­ate in their own closed-knit groups, resur­fac­ing un­der new names and up­dated ran­somware vari­ants. Additionally, the op­er­a­tors will have to find a new way to ‘wash’ the cryp­tocur­rency they earn from ran­soms. Intel 471 has ob­served that BitMix, a pop­u­lar cryp­tocur­rency mix­ing ser­vice used by Avaddon, DarkSide and REvil has al­legedly ceased op­er­a­tions. Several ap­par­ent cus­tomers of the ser­vice re­ported they were un­able to ac­cess BitMix in the last week.”

The Pentagon is car­ry­ing out war­rant­less sur­veil­lance of Americans, ac­cord­ing to a new let­ter writ­ten by Senator Ron Wyden and ob­tained by Motherboard.

Senator Wyden’s of­fice asked the Department of Defense (DoD), which in­cludes var­i­ous mil­i­tary and in­tel­li­gence agen­cies such as the National Security Agency (NSA) and the Defense Intelligence Agency (DIA), for de­tailed in­for­ma­tion about its data pur­chas­ing prac­tices af­ter Motherboard re­vealed spe­cial forces were buy­ing lo­ca­tion data. The re­sponses also touched on mil­i­tary or in­tel­li­gence use of in­ter­net brows­ing and other types of data, and prompted Wyden to de­mand more an­swers specif­i­cally about war­rant­less spy­ing on American cit­i­zens.

Some of the an­swers the DoD pro­vided were given in a form that means Wyden’s of­fice can­not legally pub­lish specifics on the sur­veil­lance; one an­swer in par­tic­u­lar was clas­si­fied. In the let­ter Wyden is push­ing the DoD to re­lease the in­for­ma­tion to the pub­lic. A Wyden aide told Motherboard that the Senator is un­able to make the in­for­ma­tion pub­lic at this time, but be­lieves it would mean­ing­fully in­form the de­bate around how the DoD is in­ter­pret­ing the law and its pur­chases of data.

“I write to urge you to re­lease to the pub­lic in­for­ma­tion about the Department of Defense’s (DoD) war­rant­less sur­veil­lance of Americans,” the let­ter, ad­dressed to Secretary of Defense Lloyd J. Austin III, reads.

Do you work for any of the agen­cies named in this piece? We’d love to hear from you. Using a non-work phone or com­puter, you can con­tact Joseph Cox se­curely on Signal on +44 20 8133 5190, Wickr on joseph­cox, OTR chat on jf­cox@jab­ber.ccc.de, or email joseph.cox@vice.com.

Wyden and his staff with ap­pro­pri­ate se­cu­rity clear­ances are able to re­view clas­si­fied re­sponses, a Wyden aide told Motherboard. Wyden’s of­fice de­clined to pro­vide Motherboard with specifics about the clas­si­fied an­swer. But a Wyden aide said that the ques­tion re­lated to the DoD buy­ing in­ter­net meta­data.

“Are any DoD com­po­nents buy­ing and us­ing with­out a court or­der in­ter­net meta­data, in­clud­ing ‘netflow’ and Domain Name System (DNS) records,” the ques­tion read, and asked whether those records were about “domestic in­ter­net com­mu­ni­ca­tions (where the sender and re­cip­i­ent are both U. S. IP ad­dresses)” and “internet com­mu­ni­ca­tions where one side of the com­mu­ni­ca­tion is a U.S. IP ad­dress and the other side is lo­cated abroad.”

Netflow data cre­ates a pic­ture of traf­fic flow and vol­ume across a net­work. DNS records re­late to when a user looks up a par­tic­u­lar do­main, and a sys­tem then con­verts that text into the spe­cific IP ad­dress for a com­puter to un­der­stand; es­sen­tially a form of in­ter­net brows­ing his­tory.

Wyden’s new let­ter to Austin urg­ing the DoD to re­lease that an­swer and oth­ers says “Information should only be clas­si­fied if its unau­tho­rized dis­clo­sure would cause dam­age to na­tional se­cu­rity. The in­for­ma­tion pro­vided by DoD in re­sponse to my ques­tions does not meet that bar.”

The ques­tions were specif­i­cally sent to the Under Secretary of Defense for Intelligence and Security in February 2021, Wyden’s let­ter adds. Beyond the NSA and DIA, the Under Secretary of Defense for Intelligence and Security pro­vides over­sight to a range of agen­cies in­clud­ing the National Geospatial-Intelligence Agency (NGA) and the National Reconnaissance Office (NRO). A Wyden aide said it is not clear if the an­swers go be­yond the agen­cies that act un­der the Under Secretary of Defense for Intelligence and Security.

The DoD did not re­spond to a re­quest for com­ment.

Wyden’s ques­tions came in re­sponse to Motherboard’s re­port­ing on spe­cial forces pur­chas­ing lo­ca­tion data, a Wyden aide said. Specifically, Motherboard pre­vi­ously re­vealed that U. S. Special Operations Command (SOCOM) bought ac­cess to a tool called Locate X that uses lo­ca­tion data har­vested from or­di­nary phone apps in­stalled on peo­ples’ phones. Motherboard also found that a National Guard unit tasked with car­ry­ing out drone strikes bought the same tool.

A Wyden aide said the of­fice sent its orig­i­nal query to SOCOM’s leg­isla­tive af­fairs sec­tion. That de­part­ment then said that the Under Secretary of Defense for Intelligence and Security would re­spond, the aide added.

As part of Wyden’s of­fice’s own par­al­lel in­ves­ti­ga­tion into the lo­ca­tion data sell­ing space, the DIA said in a memo its an­a­lysts have searched com­mer­cial data­bases of smart­phone lo­ca­tion data with­out a war­rant in five in­ves­ti­ga­tions over the past two and a half years, The New York Times re­ported in January.

“Other than DIA, are any DoD com­po­nents buy­ing and us­ing with­out a court or­der lo­ca­tion data col­lected from phones lo­cated in the United States?” one of Wyden’s ques­tions reads. The an­swer to that is one that Wyden is urg­ing the DoD to re­lease.

The DIA memo said the agency be­lieves it does not re­quire a war­rant to ob­tain such in­for­ma­tion. Following this, Wyden also asked the DoD which other DoD com­po­nents have adopted a sim­i­lar in­ter­pre­ta­tion of the law. One re­sponse said that each com­po­nent is it­self re­spon­si­ble to make sure they fol­low the law.

Wyden is cur­rently propos­ing a new piece of leg­is­la­tion called The Fourth Amendment Is Not For Sale Act which would force some agen­cies to ob­tain a war­rant for lo­ca­tion and other data. Current spon­sors in­clude Sen. Rand Paul, R-Ky., Majority Leader Chuck Schumer, D-N. Y. Sen. Mike Lee, R-Utah, Sen. Steve Daines, R-Mont., Sen. Edward Markey, D-Mass., Sen. Tammy Baldwin, D-Wisc., Sen. Elizabeth Warren, D-Mass., Sen. Sherrod Brown, D-Ohio, Sen. Brian Schatz, D-Hawaii, Sen. Cory Booker, D-N.J., Sen. Bernie Sanders, D-Vt., Sen. Jeff Merkley, D-Ore., Sen. Jon Tester, D-Mont., Sen. Martin Heinrich, D-N.M., Sen. Mazie Hirono, D-Hawaii, Sen. Patty Murray, D-Wash., Sen. Maria Cantwell, D-Wash., Sen. Patrick Leahy, D-VT., and Sen. Richard Blumenthal, D-Conn, Wyden’s of­fice pre­vi­ously told Motherboard.

Thank you to all the con­trib­u­tors who made this re­lease pos­si­ble

All-time con­trib­u­tors who made Scala 3 a re­al­ity, ac­cord­ing to git short­log -sn –no-merges 2308509d2651ee78e1122b5d61b798c984c96c4d..3.0.0, are:

If you en­counter a bug, please open an is­sue!

Germany’s lead­ing data pro­tec­tion reg­u­la­tor for Facebook has banned the so­cial net­work from us­ing data from WhatsApp users.

It fol­lows con­tro­versy of the mes­sag­ing ap­p’s lat­est pri­vacy terms which the au­thor­ity be­lieves are il­le­gal.

The move fol­lows emer­gency dis­cus­sions in Hamburg af­ter WhatsApp asked users to con­sent to the new terms or stop us­ing it.

WhatsApp is used by al­most 60 mil­lion users in Germany.

Johannes Caspar, head of the Data Protection Authority in Hamburg said: “This or­der seeks to se­cure the rights and free­doms of the many mil­lions of users who give their con­sent to the terms of use through­out Germany.

“My ob­jec­tive is to pre­vent dis­ad­van­tages and dam­ages as­so­ci­ated with such a black-box pro­ce­dure”.

The reg­u­la­tor sug­gested that the de­ci­sion was­n’t just about pro­tect­ing users’ pri­vacy but also to avoid the use of data “to in­flu­ence vot­ers’ de­ci­sions to ma­nip­u­late de­mo­c­ra­tic choices,” cit­ing the up­com­ing September 26 par­lia­men­tary elec­tions in Germany.

The reg­u­la­tor will now sub­mit the case to the European Data Protection Committee, the body re­spon­si­ble for en­forc­ing the rules across the EU.

WhatsApp, which is owned by Facebook, ac­cused the Hamburg data pro­tec­tion au­thor­ity of mis­un­der­stand­ing the pur­pose of the up­date and said there was no le­git­i­mate ba­sis for the ban.

The mes­sag­ing app de­fended the lat­est pri­vacy terms, say­ing they won’t af­fect the con­fi­den­tial­ity of mes­sages ex­changed with friends and fam­ily, but was pri­mar­ily in­tended to help com­pa­nies com­mu­ni­cate bet­ter with their cus­tomers via the plat­form, no­tably to al­low them to sell their prod­ucts di­rectly on it.

A spokesper­son for WhatsApp said: “As the Hamburg DPA’s claims are wrong, the or­der will not im­pact the con­tin­ued roll-out of the up­date. We re­main fully com­mit­ted to de­liv­er­ing se­cure and pri­vate com­mu­ni­ca­tions for every­one”.

The reg­u­la­tory ac­tion has opened a new front in Germany over Facebook’s pri­vacy poli­cies, with its na­tional an­titrust reg­u­la­tor wag­ing a le­gal bat­tle over data prac­tices it says amount to an abuse of mar­ket dom­i­nance.

Since 2018, on­line pri­vacy in Europe has been sub­ject to the General Data Protection Regulation (GDPR). Under these rules, Ireland over­sees Facebook be­cause the com­pa­ny’s European head­quar­ters is there.

Inflation is a con­tro­ver­sial and com­plex topic. This ar­ti­cle looks at 150 years of data across mul­ti­ple coun­tries to pro­vide a gen­eral idea of what in­fla­tion is, what to look for, and how to in­vest with in­fla­tion­ary and de­fla­tion­ary risks in mind.

Read from the be­gin­ning, or jump to the sec­tion you want.

Merriam-Webster de­fines in­fla­tion as “a con­tin­u­ing rise in the gen­eral price level usu­ally at­trib­uted to an in­crease in the vol­ume of money and credit rel­a­tive to avail­able goods and ser­vices”.

In other words, if the num­ber of cur­rency units in the sys­tem goes up way more than the avail­abil­ity of goods and ser­vices in the econ­omy, then we can get sup­ply short­ages and price in­creases.

That dic­tio­nary de­f­i­n­i­tion is a good place to start, but opens up some ob­vi­ous ques­tions. Which goods and ser­vices are we mea­sur­ing the price level of when we quan­tify over­all price in­fla­tion lev­els, and with what weight­ing? Can there be in­stances where the vol­ume of money and credit goes up a lot and yet prices still re­main low, and if so, why would that hap­pen and what would we call that?

This leads to a de­bate of de­f­i­n­i­tions. Economists of dif­fer­ent schools of thought of­ten speak past each other about what in­fla­tion is. So, rather than de­bate which de­f­i­n­i­tion is best, we can de­fine three types of in­fla­tion, and go from there.

Monetary in­fla­tion gen­er­ally refers to an in­crease in the broad money sup­ply, such as M2. In other words, it’s not about prices go­ing up; it’s about the amount of money in the fi­nan­cial sys­tem go­ing up.

Broad money sup­ply, M2, refers to all of the var­i­ous bank de­posits for peo­ple and busi­nesses that ex­ist in the sys­tem, like check­ing ac­counts and sav­ings ac­counts, as well as phys­i­cal cur­rency in cir­cu­la­tion. There are al­ter­na­tive mea­sures of broad money that can in­clude ad­di­tional types of cash-equiv­a­lents as well.

This chart shows the US broad money sup­ply over time in blue on the left axis, and the year-over-year per­cent change in that broad money sup­ply in red on the right axis:

There are two main forces that drive up the broad money sup­ply over time: ei­ther banks make more pri­vate loans and thus cre­ate new de­posits (which in­creases the money mul­ti­ple, the ra­tio of broad money to base money), or the gov­ern­ment runs large fis­cal deficits while the cen­tral bank cre­ates new bank re­serves to buy large por­tions of the bond is­suance as­so­ci­ated with those deficits (which in­creases both broad money and base money). For a full break­down of how money cre­ation works, see my ar­ti­cle about money print­ing.

This chart shows the growth in pri­vate sec­tor loans, gov­ern­ment deficits, and broad money growth, as a per­cent­age of that year’s GDP for the United States since 1881:

We can see on that chart that the 1880s, 1890s, and 1900s decades, as well as the 1950s and 1960s decades, were char­ac­ter­ized by strong loan growth and low gov­ern­ment deficits. The pri­vate sec­tor drove the cre­ation of money. We also see ma­jor bank­ing crises, such as the Panic of 1893, the Great Depression (early 1930s), the Savings and Loans Crisis (early 1990s) and Great Financial Crisis (2008/2009), where loans col­lapsed.

On the other hand, dur­ing in­stances like the 1940s and the 2020s so far, it was gov­ern­ment deficits that drove broad money growth, rather than pri­vate sec­tor loan growth.

Monetary in­fla­tion is gen­er­ally a start­ing point for the next two forms of in­fla­tion: con­sumer price in­fla­tion and as­set price in­fla­tion, which we feel more di­rectly.

Consumer price in­fla­tion is when the nom­i­nal price of a broad set of goods and ser­vices goes up. In other words, if you paid $4 for a Big Mac five years ago, and $5 for a Big Mac this year, then it in­flated 25% in price at an av­er­age an­nual price in­fla­tion rate of 4.56% dur­ing that pe­riod.

Some goods or ser­vices can have unique sup­ply/​de­mand bal­ances that af­fect their price, so we can’t fo­cus on sin­gle goods or ser­vices when mea­sur­ing in­fla­tion. When the ma­jor­ity of goods and ser­vices start go­ing up in price, that’s con­sumer price in­fla­tion. The value of the cur­rency it­self is what is los­ing pur­chas­ing power in that case, rather than a spe­cific prod­uct or ser­vice go­ing up in price.

The dif­fi­culty with this mea­sure­ment is com­ing to an agree­ment on a bas­ket of goods and ser­vices to mea­sure the price of. If we cherry-pick cer­tain types of goods or ser­vices, we can make con­sumer price in­fla­tion seem higher or lower than it re­ally is. And if cer­tain goods or ser­vices im­prove in qual­ity, how do we fac­tor that into year-over-year price changes?

For ex­am­ple, if the new Toyota Camry car has gone up a lot in price com­pared to then-new Toyota Camry cars from a decade ago, but comes with a ton of ex­tra fea­tures thanks to new tech­nol­ogy com­pared to back then, how do we mea­sure its price in­fla­tion? We can eas­ily mea­sure the price in­fla­tion of a sim­ple com­mod­ity like cop­per or alu­minum that does­n’t change at all over time, but how do we main­tain an ap­ples-to-ap­ples price com­par­i­son for com­plex items like Toyota Camry cars? Governments use a he­do­nic ad­just­ment to ad­just for this, but nat­u­rally it is prone to de­bate. So, we al­ready have an area of in­evitable con­tro­versy.

And then how do we weight prices? If “Household A” spends 40% of their ex­pen­di­tures on hous­ing, 20% on trans­porta­tion, 10% on ed­u­ca­tion, 10% on health­care, and 20% on all other cat­e­gories com­bined, while “Household B” is much richer and spends only 20% of their ex­pen­di­tures on hous­ing, 10% on trans­porta­tion, 5% on ed­u­ca­tion, 5% on health­care, and 60% on all other cat­e­gories com­bined, then how do we weight var­i­ous prod­ucts and ser­vices into a for­mula to de­ter­mine the ac­tual rise in prices as it re­lates to most peo­ple?

If, thanks to im­prov­ing tech­nol­ogy and chang­ing lifestyles and work habits, the typ­i­cal mix of ex­pen­di­tures for the me­dian house­hold changes over time, should we change the bas­ket of goods and ser­vices that we are mea­sur­ing the price of to re­flect that? Or should we keep the bas­ket of goods and ser­vices fixed for the sake of con­sis­tency, even if it be­comes less rel­e­vant for the typ­i­cal house­hold over time?

Quite of­ten, con­sumer price in­fla­tion is tied to com­mod­ity price in­fla­tion. If oil, cop­per, lum­ber, and other key com­modi­ties are abun­dant and cheap, it puts down­ward pres­sure on most types of prices. On the other hand, if there are sup­ply con­straints of ma­jor com­modi­ties rel­a­tive to de­mand, then com­mod­ity prices go up a lot, and that trick­les into other prices be­cause the cost to make them and trans­port them goes up.

This chart shows the con­sumer price in­dex and the com­mod­ity pro­ducer price in­dex since 1913, which was when the Federal Reserve was founded. We can then di­vide the pe­riod since then into two halves due to a sig­nif­i­cant change in mon­e­tary struc­ture that oc­curred in 1971:

What that con­sumer price in­dex chart shows, is that a bas­ket of goods that would cost $100 in 1982, would cost $265 to­day, and would cost about $10 in 1913. The price of a bas­ket of goods, in other words, has risen over 26x from 1913 to to­day in dol­lar terms. Breaking that down fur­ther, it rose by about 4x from 1913-1971 (58 years) when Nixon took the US off the gold stan­dard, and about 6.5x from 1971 to 2020 (49 years).

As I de­scribed in my ar­ti­cle on the petrodol­lar sys­tem, the 1971 dol­lar-gold break­down re­al­is­ti­cally failed in the late 1960s, and was in­evitable by 1971 when it was made of­fi­cial.

To give a bit more gran­u­lar­ity, this chart shows the year-over-year per­cent change in the con­sumer price in­dex, which is what we gen­er­ally re­fer to as price in­fla­tion:

Prior to 1971, there were both pe­ri­ods of in­fla­tion and de­fla­tion. Since 1971, there have been pe­ri­ods of in­fla­tion, but barely any pe­ri­ods of de­fla­tion, due to dif­fer­ent mech­a­nisms and goals that pol­i­cy­mak­ers have as it re­lates to mon­e­tary pol­icy.

Asset price in­fla­tion refers to the prices and val­u­a­tions of fi­nan­cial as­sets, like stocks, bonds, real es­tate, gold, fine art, and col­lectibles in­creas­ing over time. These are things that can be held for a while and tend to ap­pre­ci­ate in price over the long term.

There are mul­ti­ple ways to mea­sure as­set val­u­a­tion, and I use sev­eral of them through­out my newslet­ters and ar­ti­cles. None of them are per­fect, which is why I use sev­eral to see if they agree or don’t agree.

Here is US house­hold net worth as a per­cent­age of GDP in blue (currently 600%, left axis) and short-term in­ter­est rates in red (near zero, right axis):

Household net worth in­cludes stocks, bonds, cash, real es­tate, and other as­sets, mi­nus li­a­bil­i­ties like mort­gages and other debts.

Asset price in­fla­tion of­ten hap­pens dur­ing pe­ri­ods of high wealth con­cen­tra­tion and low in­ter­est rates. If a lot of new money is cre­ated, but that money gets con­cen­trated in the up­per ech­e­lons of so­ci­ety for one rea­son or an­other, then that money can’t re­ally af­fect con­sumer prices too much but in­stead can lead to spec­u­la­tion and over­priced buy­ing of fi­nan­cial as­sets.

Think of it like this. If the gov­ern­ment and cen­tral bank were to cre­ate a tril­lion new dol­lars and give the 100 rich­est peo­ple in the coun­try an ex­tra $10 bil­lion each with that money, what would they spend it on? All of their phys­i­cal needs and de­sires are met many times over al­ready. They’re not go­ing to eat bet­ter, travel more, or re­ally do any­thing dif­fer­ently in terms of per­sonal con­sump­tion than they’re al­ready do­ing. Instead, they’ll buy more fi­nan­cial as­sets, like more stocks or real es­tate, and push those prices up with this ex­tra de­mand. This money won’t get out and push the prices of things like cop­per or beef up.

On the other hand, if the gov­ern­ment and cen­tral bank were to dis­trib­ute $5,000 to every American adult who makes less than a mil­lion dol­lars (which would be in the ball­park of 200 mil­lion peo­ple, and thus also to­tal up to $1 tril­lion in brand new money), then a sig­nif­i­cant por­tion of them would spend that money on every­day goods, and push up many con­sumer prices as de­mand out­paces sup­ply for a pe­riod of time. This is money that would ac­tu­ally lead to more con­sump­tion and cir­cu­late more.

Due to tax poli­cies, au­toma­tion, off­shoring, and other fac­tors, wealth has con­cen­trated to­wards the top in the US in re­cent decades. People in the bot­tom 90% of the in­come spec­trum used to have about 40% of US house­hold net worth in 1990, but more re­cently it’s down to 30%. The top 10% folks saw their share of wealth climb from 60% to 70% dur­ing that time. When broad money goes up a lot but gets rather con­cen­trated, then the link be­tween broad money growth and CPI growth can weaken, while the link be­tween broad money growth and as­set price growth in­ten­si­fies.

Over the very long run, we should ex­pect tech­nol­ogy to con­tin­u­ally im­prove and push prices down. For ex­am­ple, peo­ple use to farm by hand. Then, the in­ven­tion of the trac­tor and sim­i­lar equip­ment em­pow­ered one per­son to do the work of many peo­ple. And then, we can imag­ine a fleet of self-dri­ving farm­ing equip­ment al­low­ing one per­son to do the work of a hun­dred peo­ple. As a re­sult, a smaller and smaller per­cent­age of the pop­u­la­tion needs to work in agri­cul­ture in or­der to feed the whole pop­u­la­tion.

However, money cre­ation processes and other pol­icy choices can cre­ate in­fla­tion­ary re­sults that off­set those tech­no­log­i­cal price re­duc­tions.

In gen­eral, per-capita money sup­ply growth is one of the most closely-cor­re­lated vari­ables to con­sumer price in­fla­tion, and this sec­tion takes a look at that re­la­tion­ship over 150 years.

For this set of charts for 1875-2020, I used the 1870-2017 aca­d­e­mic data­base from macro­his­tory.net and added 2018-2020 data from the St. Louis Federal Reserve. Here is the full ci­ta­tion for that macro­his­tory dataset:

Òscar Jordà, Moritz Schularick, and Alan M. Taylor. 2017. “Macrofinancial History and the New Business Cycle Facts.” in NBER Macroeconomics Annual 2016, vol­ume 31, edited by Martin Eichenbaum and Jonathan A. Parker. Chicago: University of Chicago Press.

This chart shows the rolling 5-year cu­mu­la­tive per­cent­age in­crease in the con­sumer price in­dex for the United States com­pared to the rolling 5-year cu­mu­la­tive per­cent­age in­crease in the broad money sup­ply per capita:

Individual years can be very noisy. By look­ing at 5-year rolling to­tal in­creases rather than 1-year fluc­tu­a­tions, we can fil­ter out the noise and look at pe­ri­ods of sig­nif­i­cant and per­sis­tent broad money growth and price in­fla­tion.

We see that the chart has a rather strong cor­re­la­tion; broad money sup­ply growth and the con­sumer price in­dex growth of­ten go up or down to­gether. Thanks to pro­duc­tiv­ity gains (real growth), broad money sup­ply usu­ally grows faster than CPI. There are some no­table pe­ri­ods where the dis­con­nect is larger than usual, and wor­thy of re­view.

The 1875-1910 pe­riod and the 1990s-present pe­riod are two no­table times on that chart where broad money grew rather quickly with­out caus­ing sig­nif­i­cant price in­fla­tion, and are worth ex­plor­ing. In other words, these are the “exceptions” where the cor­re­la­tion was­n’t as close as the rest of the time.

For the first ex­cep­tion pe­riod in the late 1800s, that chart ba­si­cally shows a tech­no­log­i­cal rev­o­lu­tion and the rise of a su­per­power, which kept prices low and al­lowed for tremen­dous growth. The United States had abun­dant land as the pop­u­la­tion spread out west across the con­ti­nent (displacing the na­tives, to put it lightly), which put down­ward pres­sure on prices. Cheap la­bor im­mi­grated from around the world to work in the United States. Huge amounts of oil was dis­cov­ered, and Standard Oil was founded in 1870 and made vast im­prove­ments in re­fin­ing and trans­port­ing tech­niques. The transcon­ti­nen­tal rail­road was com­pleted in 1869, Edison com­mer­cial­ized the light bulb, var­i­ous folks in­clud­ing Tesla and Edison led to broad elec­tri­fi­ca­tion, and the in­ter­nal com­bus­tion en­gine was in­vented. Modern san­i­tary tech­niques be­came wide­spread, to re­duce dis­ease and im­prove health­care and longevity. The bank­ing sys­tem grew as a share of GDP from tiny to sig­nif­i­cant. So, money sup­ply could grow a ton, and it was all real growth to­wards mas­sive gains in pro­duc­tiv­ity rather than in­fla­tion. The dol­lar was on a gold stan­dard as well.

For the sec­ond ex­cep­tion pe­riod from 1990s-present, we had an­other tech­nol­ogy rev­o­lu­tion with the cre­ation/​adop­tion of the in­ter­net and smart phone, with a pro­lif­er­a­tion in soft­ware. The ex­po­nen­tial in­crease in com­puter power and net­work­ing al­lowed us to dig­i­tize a lot of our equip­ment and processes. With the fall of the Soviet Union and the sub­se­quent ex­pan­sion of free trade agree­ments as im­pov­er­ished ar­eas opened up eco­nom­i­cally to in­ter­face with de­vel­oped coun­tries, glob­al­iza­tion ac­cel­er­ated around the world. Corporations out­sourced do­mes­tic la­bor to cheaper places like Mexico and China and east­ern Europe, which put down­ward pres­sure on do­mes­tic wages and prices in wealthy na­tions. The rise of au­toma­tion also dis­placed quite a bit of la­bor and put more down­ward pres­sure on wages and prices. Additionally, the CPI cal­cu­la­tion method changed dur­ing this pe­riod, and there is a dis­cus­sion on that later in this ar­ti­cle.

There is a com­mon idea that high mon­e­tary ve­loc­ity (GDP di­vided by broad money sup­ply) is needed for in­fla­tion. However, the data show that this is not the case.

Here is the rolling 5-year cu­mu­la­tive per­cent­age in­crease in the con­sumer price in­dex on the left axis, com­pared to broad money ve­loc­ity each year on the right axis:

Monetary ve­loc­ity was ex­tremely high and de­clin­ing in the late 1800s, while in­fla­tion was low and ris­ing. Velocity had pe­ri­ods of tem­po­rary cor­re­la­tion with in­fla­tion dur­ing World War I and the Great Depression, and not much cor­re­la­tion with in­fla­tion dur­ing World War II. In the 1970s, ve­loc­ity was­n’t any higher than the 1950s or 1960s, and yet in­fla­tion rose sub­stan­tially. In the 1990s, ve­loc­ity went up no­tice­ably, but in­fla­tion went down.

Brief pe­ri­ods of col­laps­ing ve­loc­ity are gen­er­ally de­fla­tion­ary shocks, which con­tributes to the idea that ve­loc­ity is the key vari­able for in­fla­tion, but in gen­eral, in­fla­tion is far more cor­re­lated to broad money sup­ply per capita than it is to mon­e­tary ve­loc­ity.

In the pre­vi­ous ex­am­ple of the United States, we saw the rise of a su­per­power with abun­dant new land and re­sources that took the man­tle of the global re­serve cur­rency.

With this ex­am­ple of the United Kingdom, we in­stead see the grad­ual de­cline of a su­per­power and loss of the global re­serve cur­rency. Here is 5-year rolling cu­mu­la­tive broad money sup­ply per capita growth vs 5-year rolling CPI growth:

This chart has even tighter cor­re­la­tion be­tween broad money sup­ply per capita and price in­fla­tion than the United States. There was no free and abun­dant land in the 1800s for the United Kingdom like the United States had, so broad money and in­fla­tion went more closely in hand.

The United States and United Kingdom never out­right lost a crit­i­cal war dur­ing this pe­riod. Japan, how­ever, was dev­as­tated dur­ing World War II and ex­pe­ri­enced hy­per­in­fla­tion upon their loss. So, that makes for an­other in­struc­tive ex­am­ple:

Japan spent the ear­lier half of this chart as an emerg­ing mar­ket, and then be­came an im­pe­r­ial power and de­vel­oped mar­ket later on.

Similar to what the United States ex­pe­ri­enced in the late 1800s af­ter the American Civil War, Japan ex­pe­ri­enced what was known as an “economic mir­a­cle” from the 1950s to 1990 af­ter World War II. We can see on the chart, there was a large gap be­tween broad money growth and price in­fla­tion, as Japan rapidly re-in­dus­tri­al­ized and be­came an ex­tremely ef­fi­cient ex­porter. Money sup­ply went up a ton, but so did goods and ser­vices, which kept prices in check.

More re­cently, peo­ple of­ten won­der why Japan did­n’t ex­pe­ri­ence high price in­fla­tion in the past two decades, due to how much it ex­panded its cen­tral bank bal­ance sheet. The an­swer is clear on the chart; Japan had very low broad money sup­ply growth over the past two decades, which I ex­plored in de­tail in my ar­ti­cle on Japan.

As our fi­nal ex­am­ple, here’s the chart for Australia, which had pretty strong cor­re­la­tion through­out the pe­riod:

The rise of China as a ma­jor trad­ing part­ner from the 1990s through the 2010s gave Australia an eco­nomic boost, where their money sup­ply could grow a lot faster than CPI. The coun­try went 28 years with­out a re­ces­sion from 1991 through 2019.

The CPI at­tempts to ac­cu­rately re­port the chang­ing cost of a rep­re­sen­ta­tive bas­ket of goods and ser­vices. Over time, some of those goods and ser­vices are in­flat­ing or de­flat­ing in price, be­ing sub­sti­tuted out, and be­ing weighted into the over­all cal­cu­la­tion in chang­ing ways.

And there have been changes to the CPI cal­cu­la­tions along the way, to use more qual­ity ad­just­ments.

There are many peo­ple who be­lieve that CPI, es­pe­cially due to changes in that cal­cu­la­tion over the past few decades, un­der­states the true in­fla­tion rate in the United States. House prices, food prices, health­care prices, and tu­ition prices are all ris­ing faster than CPI, and they rep­re­sent the bulk of mid­dle-class house­hold ex­pen­di­ture. Sometimes pro­po­nents of this idea are dis­missed as “inflation truthers”, since they push back on ex­pert num­bers and as­sert that CPI is ma­nip­u­lated in fa­vor of a nar­ra­tive.

On the other hand, there are folks like Brent Moulton who have worked in gov­ern­ment that think CPI over­states the real in­fla­tion rate. The gen­eral ar­gu­ment is that de­spite more wide­spread use of he­do­nic ad­just­ments in CPI, it still has­n’t been enough to cap­ture the true growth of tech­nol­ogy and dig­i­ti­za­tion that has pushed down the cost of liv­ing.

Back in 2011, there was a widely-re­ported in­ter­ac­tion where then-NY-Fed Chairman William Dudley was speak­ing with an au­di­ence in Queens NY, and re­ceived a lot of ques­tions about food in­fla­tion which was run­ning hot at the time. As Reuters re­ported, Dudley re­sponded by say­ing you have to look at all prices, and that for ex­am­ple an iPad 2 just came out for the same price as the iPad 1, but was far more pow­er­ful, and thus on a qual­ity-ad­justed ba­sis is way cheaper. Someone in the au­di­ence yelled back that you can’t eat iPads.

The power of tech­no­log­i­cal de­fla­tion is im­por­tant not to over­state, though. In every­day use, the rise of the smart phone dis­placed a lot of house phones, cam­eras, video recorders, film, CD play­ers, iPods, beep­ers, ra­dios, scan­ners, roadmaps, and many ATMs. They also dis­placed a big per­cent­age of phys­i­cal news­pa­pers, cal­en­dars, dic­tio­nar­ies, en­cy­clo­pe­dias, and books. In more niche ar­eas they dis­placed some mo­bile game de­vices, pocket trans­la­tors when trav­el­ing, com­passes, voice recorders, and photo scrap­books. We folded many of our de­vices and con­sum­ables into one pow­er­ful de­vice with dozens of soft­ware ap­pli­ca­tions.

In a 90s episode of the com­edy show Friends, a trav­el­ing en­cy­clo­pe­dia sales­men played by Penn Jillette tried to sell Joey a full phys­i­cal en­cy­clo­pe­dia for $1,200. Joey was broke, how­ever, so he only bought the book for top­ics start­ing with “V” for $50 and be­came a niche ex­pert in that let­ter.

That was less than 25 years ago. Today, we ac­cess count­less things like that for free any­where as part of a phone/​in­ter­net cost.

So we have a bit of a pop­ulist vs aca­d­e­mic feud here about whether of­fi­cial broad CPI ac­cu­rately cap­tures ris­ing prices due to money sup­ply growth. Who’s right? Folks pay­ing for things in the real world, or aca­d­e­mics with mod­els and the num­bers in front of them?

There are some num­ber-crunch­ers sup­port­ing the in­fla­tion­ary view too, though. John Williams’ Shadow Stats, for ex­am­ple, cal­cu­lates that an­nual price in­fla­tion has been around 5-10% for the past decade if it was cal­cu­lated as it used to be. Williams holds an MBA from Dartmouth. Interestingly, look­ing at the Way Back Machine, he has not raised his sub­scrip­tion price for his data at all since at least 2008.

As is of­ten the case, I find that the num­bers point some­where be­tween the ex­tremes in this case.

As I’ll show be­low, I think the ev­i­dence sug­gests that in a true ap­ples-to-ap­ples com­par­i­son, US in­fla­tion has been some­what higher than CPI re­ports, but not as high as some folks think. Official CPI says that broad prices rose by about 2.5% per year on av­er­age since 1990, while I think there’s a good case that it’s closer to 3% or more. In other words, prices went up more like 150% (2.5x) rather than 100% (2x) in to­tal dur­ing that three decade com­pounded an­nual pe­riod.

So, I don’t see good ev­i­dence that real in­fla­tion has been 2x-3x higher than CPI re­ports as some folks sug­gest, but I do think that CPI un­der­stated it enough in re­cent his­tory due to some cal­cu­la­tion changes, that over a three-decade pe­riod, it has­n’t fully cap­tured the rise in prices for an ap­pro­pri­ate bas­ket of goods. Even broad money sup­ply per capita only went up about 5% per year dur­ing the pe­riod, which rep­re­sents an ap­prox­i­mate ceil­ing for how high CPI in­fla­tion could have been, and as we’ve cov­ered, CPI in­fla­tion is usu­ally slower than broad money grow by a vary­ing gap.

More im­por­tantly, a lot of the dis­crep­ancy comes from the fact that, due to off­shoring and au­toma­tion, com­bined with rather high broad money sup­ply growth, we’ve been in an en­vi­ron­ment where some cat­e­gories have seen rapid price de­fla­tion, while other (often more es­sen­tial) cat­e­gories of goods and ser­vices that haven’t been au­to­mated or out­sourced, have risen in price faster than broad CPI.

Plus, wages have barely kept up with in­fla­tion, which is com­pounded by the fact that more ed­u­ca­tion (and thus more stu­dent debt) is re­quired on av­er­age to get those same in­fla­tion-ad­justed wages. In other words, on an in­fla­tion-ad­justed and ed­u­ca­tion-cost-ad­justed ba­sis, me­dian wages have de­creased.

The Economist has tracked the prices of McDonald’s Big Macs around the world since the late 1980s.

Apart from be­ing partly for hu­mor, the Big Mac is an in­ter­est­ing choice be­cause it’s iconic, fairly stan­dard­ized, and re­quires mul­ti­ple in­puts to pro­duce in­clud­ing var­i­ous agri­cul­tural com­modi­ties, do­mes­tic la­bor, and en­ergy. McDonald’s also needs to earn a profit and sup­port its real es­tate ex­penses through the sale of Big Macs and other menu items.

If we look at Big Mac prices in the US since 1990, they have trended no­tably higher than CPI, and have a smaller gap vs the growth of broad money sup­ply per capita, which is how prices have gen­er­ally moved in most his­tor­i­cal pe­ri­ods:

I also looked up McDonald’s gross mar­gins (revenue mi­nus cost of goods) since the 1990s us­ing data from YCharts, and McDonald’s made the same gross mar­gins in 1990 and 2020. So, it’s not like they had the same in­put costs but sim­ply charged more.

Based on this funny but ac­tu­ally kind of rel­e­vant met­ric, CPI has fallen short over the past three decades, and par­tic­u­larly within the sec­ond half of that pe­riod. Back in the late 1990s and early 2000s, com­modi­ties were very cheap, and so the Big Mac rose in price more slowly than CPI. Starting in 2003, com­mod­ity prices had a big rise up, and Big Mac prices caught back up to CPI and even­tu­ally out­paced it by a no­tice­able mar­gin.

During the whole pe­riod from 1990 to 2020, the broad con­sumer price in­dex rose at about 2.5% per year, the Big Mac price rose about 3% per year, and broad money sup­ply per capita rose about 5% per year. I’ll leave it to read­ers to judge how the qual­ity of the Big Mac has changed or not over the pe­riod.

According to the of­fi­cial CPI for new ve­hi­cles in the United States, prices for new cars only rose by 22% for the en­tire span from 1990 to 2020.

I dug up an old Chicago Tribune ar­ti­cle that had some data to cross-ref­er­ence that. According to that ar­ti­cle, the av­er­age price of a new car in 1990 was $15,472. In 2020, the av­er­age price of a new car crossed over $40,000. That’s more than a 2.5x or 150%+ in­crease in price, dur­ing which the new ve­hi­cle CPI says that it ef­fec­tively rose only 22%.

Why the dis­crep­ancy? Well, new cars got big­ger and bet­ter. They have more fea­tures, and pref­er­ences shifted to­wards a higher mix of SUVs, so the CPI model dis­counted their in­fla­tion rate to com­pen­sate for that. Offshoring and au­toma­tion did help sup­press ve­hi­cle prices on a qual­ity-ad­justed ba­sis.

Let’s pick the Toyota Camry as a di­rect com­par­i­son to re­duce the size/​type changes. The start­ing MSRP for the au­to­matic was $12,258 in 1990. The start­ing MSRP in 2020 was $24,425. That’s a 100% price in­crease, al­most ex­actly. That’s about 2.5% per year.

Certainly we can al­low for a sub­stan­tial amount of qual­ity ad­just­ment in the new car CPI cal­cu­la­tion. The new Camry has power every­thing, a nav­i­ga­tion sys­tem, bet­ter safety fea­tures, and bet­ter gas mileage. But is the qual­ity/​size ad­just­ment enough to re­duce the ac­tual price ap­pre­ci­a­tion from 100% down to just 22% on a qual­ity-ad­justed ba­sis dur­ing this three-decade pe­riod, as of­fi­cial new car CPI says was the case?

Plus, ac­cord­ing to of­fi­cial CPI re­ports, the cost of car main­te­nance has gone up faster than broad CPI dur­ing the past thirty years, with a roughly 140% in­crease from 1990 to 2020. Gasoline prices went up around 130%, which were also faster than broad CPI.

According to the US Bureau of Labor Statistics, the av­er­age American house­hold spends 33% of its ex­pen­di­tures on hous­ing, 17% on trans­porta­tion, 13% on food, 11% on the com­bi­na­tion of in­sur­ance and so­cial se­cu­rity and pen­sions, 8% on health­care, 5% on en­ter­tain­ment, 3% on char­i­ta­ble con­tri­bu­tions, 3% on ap­parel, 2% on ed­u­ca­tion, 1% on per­sonal care prod­ucts, and the re­main­der on other cat­e­gories.

Housing, trans­porta­tion, food, health­care, and ed­u­ca­tion col­lec­tively are 60% of the ex­pen­di­tures. The com­bi­na­tion of pen­sions/​in­sur­ance/​so­cial se­cu­rity and char­ity is 15%. Everything else com­bined is 25%.

The me­dian house, health­care CPI, and ed­u­ca­tion/​child­care CPI all went up faster than broad CPI ac­cord­ing to the of­fi­cial met­ric. Food CPI was in-line with broad CPI ac­cord­ing to the of­fi­cial met­ric, but po­ten­tially higher ac­cord­ing to things like the Big Mac Index.

New car prices, as we saw, went up at the same rate as CPI (about a 100% in­crease from 1990-2020, or 2.5% per year) even though their CPI model said they went up ex­tremely slowly on a qual­ity-ad­justed ba­sis. Car main­te­nance CPI and gaso­line prices of­fi­cially went up faster than CPI as well. Overall, trans­porta­tion spend­ing grew at least as fast as broad CPI.

So, if the ma­jor­ity of things that Americans spend money on went up faster than broad CPI, it brings into ques­tion the ac­cu­racy of broad CPI. That bas­ket of hous­ing, ed­u­ca­tion, food, health­care, and trans­porta­tion rep­re­sents 60% of to­tal av­er­age house­hold spend­ing ac­cord­ing to the BLS, or about 70% of to­tal ex-pen­sion and ex-char­ity spend­ing.

If 70% of their goods/​ser­vices ex­pen­di­ture bas­ket is go­ing up equal-or-higher (in some cases no­tably higher) than the broad in­fla­tion rate, do cheaper goods in the smaller cat­e­gory out­weigh that?

That dis­crep­ancy is how we get to a sit­u­a­tion of NY Fed Chair Dudley talk­ing about the iPad 2 vs the iPad 1, and an au­di­ence mem­ber shout­ing back that you can’t eat an iPad.

Here’s a chart that shows var­i­ous prices, in­clud­ing the me­dian house, health­care CPI, tu­ition/​child­care CPI, the Big Mac, and ma­jor com­modi­ties, rel­a­tive to broad money sup­ply per capita and broad CPI:

During the three-decade length of the chart, most ma­jor ex­penses and com­modi­ties rose faster than CPI.

There are many de­fla­tion­ary or low-in­fla­tion cat­e­gories as well. Unlike the chart above, elec­tron­ics, ap­parel, dig­i­tal goods, toys, and many other con­sumer prod­ucts have in­deed ei­ther de­flated in price or in­flated less slowly than CPI, thanks to im­prov­ing tech­nol­ogy and off­shoring la­bor to cheaper mar­kets. Collectively, how­ever, these types of items and ser­vices only rep­re­sent 25% of house­hold spend­ing ac­cord­ing to the BLS, or 30% of ex-pen­sion and ex-char­ity spend­ing.

One of the dis­crep­an­cies in var­i­ous mea­sures of con­sumer price in­fla­tion is the way hous­ing costs are cal­cu­lated. The biggest ex­pense for most peo­ple is their house or apart­ment, so dif­fer­ences here play a huge role in how ac­cu­rate an in­fla­tion bas­ket is.

The me­dian house price has out­paced broad CPI over the past three decades. The CPI went up about 2x (100%) over that pe­riod while the me­dian house price went up around 2.8x (180%). The me­dian home size grew about 15% dur­ing that time, but even do­ing an ad­just­ment for that, the me­dian house price per square foot has risen faster than CPI.

The CPI, how­ever, does not in­clude house prices, since that is a cap­i­tal as­set rather than a con­sump­tion as­set. Instead, they use “owner’s equiv­a­lent rent”, where they do sur­veys to ask peo­ple what they think the price to rent the dwelling they have would be. In some ways this makes sense but in other ways it opens up sur­vey er­rors and in­tro­duces fi­nanc­ing costs.

The big dis­crep­ancy in this part of the cal­cu­la­tion is whether or not we should in­clude fi­nanc­ing into the price of a home when cal­cu­lat­ing the cost of the home. Since own­er’s equiv­a­lent rent looks at monthly cost, it in­di­rectly takes into ac­count fi­nanc­ing rates.

Using the Bankrate mort­gage cal­cu­la­tor and his­tor­i­cal mort­gage rates from the St. Louis Fed, as­sum­ing 20% down with a 30-year fixed mort­gage, here is a back-of-the-en­ve­lope check. If you bought a me­dian home in 1990, it would cost around $125,000 and you’d have a 10% mort­gage rate. Your es­ti­mated monthly pay­ment would be $1,025. If you bought a me­dian home in 2020, it would cost nearly $350,000 and you’d have a 3% mort­gage rate. Your es­ti­mated monthly pay­ment would be $1,476.