10 interesting stories served every morning and every evening.




1 1,182 shares, 48 trendiness, words and minutes reading time

ROBIN HOBB

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.

...

Read the original on www.robinhobb.com »

2 1,096 shares, 38 trendiness, words and minutes reading time

URL Lengthener

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:

...

Read the original on aaa.aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa.com »

3 1,079 shares, 43 trendiness, words and minutes reading time

Google Docs will now use canvas based rendering

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.

...

Read the original on workspaceupdates.googleblog.com »

4 1,045 shares, 45 trendiness, words and minutes reading time

Everything you missed over the last 10 years

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.

...

Read the original on turriate.com »

5 1,025 shares, 41 trendiness, words and minutes reading time

eduard-permyakov/permafrost-engine

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.

...

Read the original on github.com »

6 739 shares, 24 trendiness, words and minutes reading time

DarkSide Ransomware Gang Quits After Servers, Bitcoin Stash Seized

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.”

...

Read the original on krebsonsecurity.com »

7 670 shares, 28 trendiness, words and minutes reading time

Pentagon Surveilling Americans Without a Warrant, Senator Reveals

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 SOCOMs 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.

...

Read the original on www.vice.com »

8 662 shares, 24 trendiness, words and minutes reading time

Release 3.0.0 · lampepfl/dotty

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!

...

Read the original on github.com »

9 644 shares, 25 trendiness, words and minutes reading time

Germany bans Facebook from handling WhatsApp data

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 DPAs 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.

...

Read the original on www.euronews.com »

10 641 shares, 23 trendiness, words and minutes reading time

The Ultimate Guide to Inflation

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.

...

Read the original on www.lynalden.com »

To add this web app to your iOS home screen tap the share button and select "Add to the Home Screen".

10HN is also available as an iOS App

If you visit 10HN only rarely, check out the the best articles from the past week.

If you like 10HN please leave feedback and share

Visit pancik.com for more.