Speaker
Description
Gross domestic product (GDP) is an important variable used to compare regions and countries as a welfare indicator. But is GDP everything? Post-growth and de-growth approaches criticize the idea that solely focus on GDP growth. These alternative approaches, based on the unsustainability of unlimited growth, seek ways to ensure welfare, and sustainability and to conserve resources beyond growth.
This critical approach emphasizes the need to focus on development rather than economic growth. Indeed, while economic growth is measured through basic economic data such as GDP, development includes variables such as education, health, quality of life and innovation. In the literature, there are studies examining the impact of GDP on concepts such as human development index, welfare, and sustainability that post-growth and de-growth approaches focus on. However, such studies are quite limited in Türkiye
In relation to this, the main question identified in the study is whether the change in GDP at the provincial level in Türkiye is effective on the change in the level of development. The dependent variable is the change in level of development and the independent variable is the change in GDP.
Development data at the provincial level is taken from the socio-economic development index prepared on different dates. In this respect, the 2003 socio-economic development index prepared by the State Planning Organization and the index data prepared by the Ministry of Industry and Technology, General Directorate of Development Agencies in 2017, which is the current data, were used. The change in the development rank of the provinces among 81 provinces between 2003 and 2017 is taken as the change in the level of development, which is the dependent variable of the study. In terms of GDP change (dollar), the proportional change between 2004 data, which is the oldest data at the provincial level, and 2017 data is taken as the independent variable.
A two-stage method was applied in the study. First, the change in the level of development and the change in GDP were analyzed by mapping through geographic information systems. Secondly, linear regression analysis was applied to determine the effect of GDP change on the change in the level of development. Regression analysis is a statistical method used to examine the effect of the dependent variable on the independent variable. For the application of this method, the data must fit the normal distribution. In the normality analysis performed through the Statistical Package for the Social Sciences, it was seen that the data fit the normal distribution, and regression analysis was applied.
According to the results of the analysis, the effect of GDP on the change in development level is not statistically significant. The average GDP increase of the 6 provinces with the highest decrease in development level ranking (11 and below) is 74%, while the average GDP increase of the other provinces that have a decrease in development level ranking (30 provinces) is 69%. On the other hand, the average GDP increase of the 8 provinces with the highest increase in development level ranking (8 ranks and above) is 77%, while the average GDP increase of the 30 provinces that have an increase in development level ranking (7 ranks and below) is 77%.
These findings show that GDP has no statistically significant effect on the level of development. Therefore, as a policy recommendation, it is important to focus on the welfare level, development, and sustainability along with GDP as emphasized in the literature.
| Keywords | De-growth; Post-growth; Development; Gross domestic product; Türkiye |
|---|---|
| Best Congress Paper Award | No |
