Procjena bruto plaća za neaktivne i nezaposlene osobe u Republici Hrvatskoj odabranim ekonometrijskim modelima

professional thesis

• Author: Slavko Bezeredi
• Mentor: Nataša Erjavec (mentor)
• Committee member: Vlasta Bahovec (predsjednik povjerenstva)
• Committee member: Nataša Erjavec (član povjerenstva)
• Committee member: Katarina Ott (član povjerenstva); MBZ: 140891
• Granter: University of Zagreb; Faculty of Economics and Business; Zagreb
• Defense date and country: 2015, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Economics; Business Mathematics and Statistics

Abstract

U radu se procjenjuje vjerojatnost zaposlenosti i bruto-2 plaće po satu (koja je jednaka ukupnom trošku rada po satu) za neaktivne i nezaposlene osobe. Analiza se provodi odvojeno za muškarce i žene. Analiziraju se razlike u karakteristikama (dob, obrazovanje, bračni status, mjesto stanovanja, broj djece, ekonomske djelatnosti) zaposlenih osoba u odnosu na nezaposlene ili neaktivne osobe. Modeli za procjenu bruto-2 plaća po satu utvrđuju kako pojedine osobne karakteristike utječu na bruto-2 plaću po satu i na vjerojatnost zaposlenosti.
Koriste se podaci iz Ankete o dohotku stanovništva za 2011. godinu, koju provodi Državni zavod za statistiku. U izabranom uzorku uspješno su anketirana 6.403 kućanstva, što daje uzorak od 16.948 osoba. Svakoj osobi iz uzorka dodijeljen je odgovarajući ponder koji je procijenjen od strane DZS-a. Navedena ponderacija uzorka omogućava projekciju uzorka na cijelu populaciju. U ovom radu su sve procjene dobivene na temelju ponderiranog uzorka.
U uzorcima poput ADS-a podaci o plaćama su prikupljeni samo za osobe koje rade, dok za nezaposlene i neaktivne osobe ne postoje podaci o njihovim plaćama. Stoga, ako su potrebni podaci o plaćama za osobe koje ne rade, potrebo ih je procijeniti. U ovom radu se njihove procjene vrše na sljedeći način. Bruto-2 plaće po satu su najprije procijenjene primjenom modela višestruke linearne regresije. Međutim, ako postoji problem odabira uzorka, takve procjene mogu biti pristrane pa se preporuča korištenje tobit II modela. U Hrvatskoj je dobiveno da je problem odabira uzorka prisutan kod žena, pa se kod njih bruto-2 plaće po satu trebaju procjenjivati tobit II modelom. Kod muškaraca je dobiveno da ne postoji selekcijski problem. Procijenjeni parametri tobit II i linearnog regresijskog modela su gotovo identični i bruto-2 plaće po satu se mogu procijeniti koristeći model višestruke linearne regresije.

Abstract (english)

The thesis estimates the probabilities of employment and gross-2 hourly wages (which is equal to total labour cost per hour) for inactive and unemployed persons in Croatia. The analysis was conducted separately for men and women. The differences in characteristics (age, education, marital status, place of residence, number of children, economic activities) of employed persons in comparison to the unemployed or inactive persons are analysed. Models for estimating gross-2 hourly wage determine how personal characteristics affect gross-2 hourly wage and probability to being employed.
The microdata used in the research come from the Survey on Income and Living Conditions (Anketa o dohotku stanovništva, ADS). The survey has been conducted by Croatian Bureau of Statistics (Državni zavod za statistiku, DZS). The selected sample contains data for 6,403 households with 16,948 persons. Every person has its own sampling weight, which is calculated by DZS. These sampling weights enable the aggregation of sample data to the whole population level. All estimations and calculation in this thesis are performed using personal sampling weights.
In samples like ADS, data on wages are recorded only for people who are actually working, whereas for unemployed and inactive persons no wage data are present. Therefore, if wage data on non-working population are required, they have to be somehow estimated. In this thesis, estimation is performed in the following way. Gross-2 hourly wages are estimated using multiple linear regression model. However, if the sample selection problem exists, such estimates may be biased and the use of tobit II model is recommended. In Croatian case it is obtained that the sample selection problem is present for women and the gross-2 hourly wages have to be estimated using tobit II model. For men sample selection problem does not occur. The estimated coefficients in both models are almost identical and the gross-2 hourly wages can be estimated using multiple linear regression model.

• Keywords: nezaposlene osobe; neaktivne osobe; vjerojatnost zaposlenosti; bruto-2 plaća po satu; satnica; probit model; model višestruke linearne regresije; tobit II model.
• Keywords (english): unemployed persons; inactive persons; the likelihood of employment; gross-2 hourly wage; hourly wage; probit model; multiple linear regression model; tobit II model
• Language: croatian
• URN:NBN: urn:nbn:hr:148:898871
• Study programme: Title: Statistical Methods for Economic Analysis and Forecasting; Study programme type: university; Study level: postgraduate specialist; Academic / professional title: sveučilišni/a specijalist/specijalistica statističkih metoda za ekonomske analize i prognoziranje (sveučilišni/a specijalist/specijalistica statističkih metoda za ekonomske analize i prognoziranje)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to students and staff of home institution
• Created on: 2016-11-11 08:12:54