Àwọn Ìṣàmúlò-ètò

Bií a ṣe lè ṣẹ̀dà àwọn à

Àtòjọ yìí wà láti jẹ́ pé àwọn à

Àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò

Àwọn àtòjọ-ẹ̀yàn gbogbo ní a fi pamọ́ láti inú àwọn à

Ìṣàmúlò-ètò náà jẹ́ àìdájú. Ààyè tí a bá gbágbọ́ pé a ní ìjádé, a tí gbágbọ́ pé árín àwọn

Àwọn àkókò tí a fi pamọ́

Ó jẹ́ ibí tí àwọn

Àtòjọ-ẹ̀yàn láti ààyè-iṣẹ́ tí a fi owó gba: ìṣàfarawé kọ̀ǹpútà, ìṣàfihàn, ìrànwọ́ àwọn ohun-ìmọ̀ àti ìṣàfilọ́lẹ̀.
Iwadii iṣẹ - awọn ohun elo, pitching, bidding, listing, ati akoko laarin awọn iṣẹ ti a gba.
Admin: invoicing, chasing idogo, bookkeeping, ati ki o iwadi owo ti o le ti wa ni ti a ti fi si yi owo.
Igbagbọ ti ko ni ifunni - akoko lori-platform ṣugbọn kii ṣe iwadi, eyiti o jẹ pataki ni ifunni ati iṣẹ rideshare.
Rework: awọn atunyẹwo, awọn pada, awọn ijiroro ati awọn ipadabọ.

Àwọn àwọn ìṣàmúlò-ètò wò nínú àwọn àwọn ìṣàmúlò-ètò

Àwọn owó tí a gba nípá

Kini idi ti àwọn ìṣàmúlò-ètò ní pàtó nínú àwọn ààyè

A mean is the wrong statistic for income distributions that are heavily skewed, and income from independent work is about as skewed as data gets. A small number of very high earners pulls a average far above what a typical participant experiences. Quoting that average is technically true and practically a lie.

Iwọn ti awọn distortion ko ni subtle. US apa-hustle owo-ori average $885 ni oṣu kan lodi si median ti $200. French micro-entrepreneurs average €773 ni oṣu kan lodi si median labẹ €350. Ni awọn iṣẹlẹ mejile ti average jẹ diẹ sii ju mẹrin igba ti aarin ti awọn ipinlẹ.

Àwọn àwọn

Bií a ṣe lè gba àwọn ìṣàmúlò-ètò ìṣẹ̀dá

Àwọn ìṣàmúlò-ètò ìpàlẹ̀ tí a fẹ́ ní àwọn àtíjádé kan - àwọn àwọn eniyan tí wọ́n tí ń gbiyanjú ohun náà, àti gbogbo àwọn tí wọ́n tí kò gba ohunkohun nípa ìfẹ́fẹ́ àtí kò fi kọ̀ nípá rẹ̀. Àwọn ìjọba pẹ̀lú inòtà kò lè fi yìí pamọ́, nitorí pé àwọn eniyan tí wọ́n tí kò ṣẹ̀ ní awọn eniyan tí wọ́n tí kò fi àwọn àkọsílẹ̀ pamọ́.

Àwọn àkọsílẹ̀ owó ilé-ìpamọ́ lè. Ti ẹnikẹni bá n ṣiṣẹ́ iṣẹ́ kan, wọn lè fi àwọn àkọsílẹ̀ silẹ, àti àwọn ìtàntítà tí a gbà lè sọ̀rọ̀ gbogbo àwọn eniyan nípa tí wọn kò bá jẹ́ ayẹwo tí a yaǹdá. Àwọn àkọsílẹ̀ US atí IRS sọ̀rọ̀ nípa bí ọpọlọpọ́ eniyan tí n ṣiṣẹ́ iṣẹ́ kan tí a fi hàn nípa bí a tì pin àwọn ẹ̀yàn wọn àtí owó tí a fi pamọ́. Ìpàpọ̀ tí a fi pamọ́ nínú àwọn ẹ̀yàn tí o gàjú nípa àwọn à

O jẹ alaye ti o wa ni gbangba, ọfẹ ati ti o ni ẹtọ ti aaye yii ko lo, fun idi ti o rọrun: awọn abajade jẹ ipalara si eyikeyi awoṣe iṣowo ti o da lori oluka ti o ro pe ọna yii yoo ṣiṣẹ.

Àwọn àwọn ààyè-iṣẹ́ àwọn ìṣàmúlò-ètò

Federal wage data covers people who are EMPLOYED in a profession. Everyone who trained for it and never got hired is absent from the median, and so is anyone doing the same work self-employed. Every median on this site is therefore a survivor's figure, and the pages say so.

Níbí tí a bá fi pamọ́ àwọn àwọn àkọsílẹ̀ tí a tí fi pamọ́ lọ́wọ́lọ́wọ́ lọ́wọ́lọ́wọ́, a tí fi àwọn àwọn àkọsílẹ̀ tí a ti pamọ́ lọ́wọ́lọ́

Ìpàdé tí a tí ìpàdé yìí jẹ́ ìpàdé, kò ní ìpàdé iṣẹ́. O ní gbogbo àwọn tí wọ́n lọ́wọ́lú, kọ́kọ́, ìjádè tàbí ìwégbèsì, gbogbo àwọn tí wọ́n pàdé láti ìjádé, gbogbo àwọn tí ń ṣiṣẹ́ nígbà kan, ajọ tabi tí wọn bá jẹ́ ara wọn nípá tí a kò bá gbọ́ nípá tí a bá gbọ́. Gbogbo àwọn tí ǹpàdé nípá bí a tí ǹpàdé. Ìpàdé tí o jú lọ́wọ́lú nípá tí a kò bá gbọ́. Ìpàdé tí o jú lọ́wọ́lú nípá tí a bá gbọ́.

Àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò

Ojú-ìwé ìṣàfihàn sọ̀rọ̀ nípa bí ìgbà wò nínú oṣù wò nínú oṣù tí o bá gbà lati dáwọ́ nípa ohun tí o bá jẹ́. Ojú-ìwé náà nípa àwọn oṣù tí a tí n gbọ́dọ̀ sí ìgbà iṣẹ́-ìgbà tí a tí n gbọ́dọ̀ sí ìgbà iṣẹ́ nínú ojú-ìwé yìí - iṣẹ́lárà Amẹrika - nitorí pé a kò mọ̀ ohun tí a bá gbà nínú oṣù wò nípa. Tí o bá tí gbà jú lọ, ó lè gbà jú lọ; tí o bá gbà jú lọ, ó lè gbà jú lọ.

Fímù náà kò ní ìgbà kan tí a tí n kọ́kọ́, nígbà tí a ti n gbọ́dọ̀ mọ́ pé a tí n gbà owó jù lọ́wọ́lọ́wọ́, a si kó ní ìbàlẹ̀ nípa àwọn owó tí a tí n gbà. Ò tun dájú pé a tí n gbá iṣẹ́ ní gbogbó - gbogbó àwọn

Àwọn àgbègbè ìṣàmúlò-ètò

Àwọn àwọn

Àwọn Ìṣàmúlò-ètò	Ohun ti o tumọ si
Àwọn	Federal tax or census aggregates covering everyone who filed. The strongest evidence available and the basis of every failure rate.
Àwọn Ìṣàmúlò-ètò	Awọn iṣeto ifowopamọ ti o fọwọsi, awọn kaadi idiyele ti a tẹjade ati awọn iroyin ti o han gbangba ti oju opo wẹẹbu.
Àwọn àkọlé	Awọn owo-ori ti awọn onimọ-ẹrọ ti gbekalẹ pẹlu awọn ifihan ti a ti kọ - fọọmu owo-ori, iboju-boju ti o ti ṣe ifunni, oju-iwe banki.
Àwọn Àkọ́lé	Àwọn ìṣàmúlò-ètò àti àwọn ìṣàmúlò-ètò ìjọba. A fi hàn, a tí fi àwọn àwọn ìṣàmúlò-ètò pamọ́, àti àti àwọn ìṣàmúlò-ètò àti àwọn à
Àwọn Àkọlé	Kò fi pamọ́ sínú àwọn.

Àwọn ààyè tí àwọn ìṣàmúlò-ètò yìí bá jẹ́ ìdájú

Àwọn àwọn

Statistics nonemployer yọ awọn ti o kere ju ti o gba, ki o si awọn gidi ipin ti awọn eniyan ti o gba diẹ ninu ohunkohun ti o ti ṣee ṣe ti o ga ju ti a report, ko ni isalẹ. Gig owo-ori ti a san lori a W-2 ko han ni data olori-ikọkọ ni gbogbo. Ati data owo-ori lags: ti o ti kọja ti o ti pari ọdun ni o ni igba meji ni ẹhin, ki o si ọna ti o ti bajẹ ọdun to koja le tun wo ni o ni igbẹkẹle ni awọn nọmba Federal.

Kò ní àwọn ìdájú àwọn ìdájú yìí ní àwọn ìṣàmúlò-ètò láti ló àwọn àkóónú àìdájú tí a fẹ́. Wọ́n ní àwọn ìṣàmúlò-ètò láti sọ àwọn ìpele ìròyìn ní pàtó nípa àwọn àkọsílẹ̀ gbogbò, tí a tí n ṣe.

Tí o bá ró pé àwọn

Fi wa mọ́, àti àwọn àwọn àgbèwọlé, àwọn à

Fi àkọlé pamọ́ · Wó àwọn ìṣàmúlò-ètò àtòjọ-ẹ̀yàn àìdálẹ̀