Year: 2024
Type: article
Abstract: This study aims to demonstrate how different economic variables that have been chosen have an impact on the industrial production index. The study looked at the relationship between a few key economic indicators and the industrial output index data, which is significant information for the Turkish economy and has been corrected for calendar and seasonal influences. The data was analyzed from 1990 to 2021. The study's analysis method was the multiple linear regression model. The series' stationarity status was investigated in the first section of the regression analysis. After doing unit root tests, it was found that all of the other variables—with the exception of the two variables representing total unemployment and the CPI—had unit roots and were not stationary.These variables were found to be stationary when the first degree differences were calculated. Following this phase, multiple methods were employed to assess the validity and reliability of the regression analysis model.Here, tests for multiple linear connections, correlation, heteroskedasticity, and normal distribution were run, and the outcomes were assessed. The study's dependent variables included data from the industrial output index, while the independent variables included net national savings, energy consumption, overall unemployment, exports of goods and services, and CPI value. The findings of the regression analysis showed that there was a substantial correlation between the industrial output index, net national savings, and exports of goods and services as well as energy consumption. Once more, the findings of the regression analysis showed that there was no meaningful correlation between the industrial output index, the CPI, and the overall unemployment rate.Furthermore, based on the findings, the paper offers suggestions for raising the industrial output index.
Source: DergiPark (Istanbul University)
Author: Bolat, İsmet
Institution: Kahramanmaraş Sütçü İmam University
Language: English
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6987743783
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