Analiza utjecaja onečišćenja okoliša na gospodarski rast u zemljama OECD-a primjenom panel analize

master's thesis

• Title (english): Analysis of environmental pollution on economic growth in OECD countries using panel model
• Author: Doris Trefilj
• Mentor: Lucija Rogić Dumančić (mentor)
• Committee member: Vladimir Arčabić (predsjednik povjerenstva)
• Committee member: Tomislav Gelo (član povjerenstva)
• Granter: University of Zagreb; Faculty of Economics and Business; Zagreb
• Defense date and country: 2023-09-28, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Economics; General Economy

Abstract

Svrha ovog rada je istražiti utjecaj raznih onečišćivača okoliša i emisija plinova na gospodarski rast u zemljama OECD-a. Istraživanje je rađeno na 38 zemlja u rasponu od 22 godine, odnosno podaci su prikazani za godine 1997.-2018. Godine nakon 2018. nisu korištene u radu zbog nedostatka podataka određenih zemalja i varijabli te nisu uključene u analizu. Nakon deskriptivne analize, u radu je primijenjena panel analiza kroz tri modela: model združene regresije, model sa fiksnim efektima i model sa slučajnim efektima. Zavisna varijabla u svim modelima je ista, gospodarski rast, odnosno BDP koji je pokazatelj gospodarskog rasta zemalja, dok u modelu brojimo 8 nezavisnih varijabli. Pa se tako gleda utjecaj emisije metana u poljoprivredi, poljoprivredne emisije dušikovog oksida , emisije CO2, emisije metana, emisije metana u energetskom sektoru, emisije dušikovog oksida, emisije dušikovog oksida u energetskom sektoru i ukupne emisije stakleničkih plinova na BDP zemalja. Za odabir najboljeg modela od tri navedena koriste se tri testa, F-test, Hausmanov test i Breusch-Paganov LM test. Nakon provođena testova odabran je model sa slučajnim efektima. Na modelu su provedeni testovi Breusch-Godfrey/Wooldridge da vidimo da li je prisutan problem autokorelacije i Breusch-Paganovog test za testiranje problema heteroskedastičosti. U modelu je prisutan problem autokorelacije do zaključno drugog reda.

Abstract (english)

The purpose of this paper is to investigate the impact of various environmental pollutants and gas emissions on economic growth in OECD countries. The research was conducted in 38 countries over a period of 22 years, the data are presented for the years 1997-2018. Years after 2018. were not used in the work due to the lack of data for certain countries and variables and were not included in the analysis. After descriptive analysis, in the ppaper was applied panel analyisthrough three models, a pooled model, a model with fixed effects and a model with random effects. The dependent variable in all models is the same, economic growth, or GDP, which is an indicator of the economic growth of countries, while we count 8 independent variables in the model. So the impact of GDP on methane emissions in agriculture, agricultural carbon nitrogen emissions, CO2 emissions, methane emissions, methane emissions in the energy sector, nitrogen oxide emissions, nitrogen oxide emissions in the energy sector and total greenhouse gas emissions is looked at. To select the best model from the three listed, three tests are used, the F-test, the Hausman test and the Breusch-Pagan LM test. After the tests, a model with random effects was selected. Breusch-Godfrey/Wooldridge tests were performed on the model to see if there is an autocorrelation problem and Breusch-Pagano test to test for heteroscedasticity problems. The model has an autocorrelation problem up to the second order.

• Keywords: bruto domaći proizvod; OECD; onečišćenje okoliša; panel analiza
• Keywords (english): Gross domestic product; OECD; environmental pollution; panel analysis
• Language: croatian
• URN:NBN: urn:nbn:hr:148:331972
• Study programme: Title: Economics; Study programme type: university; Study level: integrated undergraduate and graduate; Academic / professional title: sveučilišni magistar ekonomije/sveučilišna magistra ekonomije (sveučilišni magistar ekonomije/sveučilišna magistra ekonomije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2023-10-02 13:23:22