Analysis of corruption impact on the poverty level in Kazakhstan

2023

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.46914/1562-2959-2023-1-3-354-367
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

The authors of the article investigated the impact of corruption on the level of poverty in Kazakhstan. The aim of the study is to assess the impact of corruption on poverty in Kazakhstan, and compare with estimates from other countries, including Argentina, Germany and Denmark, to identify similarities and differences. In conducting the study, the authors use the Corruption Perceptions Index and other variables such as the unemployment rate and inflation. Corruption not only breeds poverty, but also undermines state power and threatens social stability. The results of the study show that corruption has a statistically significant impact on the level of poverty in all four countries, but with different intensity. As a result, it was revealed that the focus is on the context of Kazakhstan and the lack of quantitative research on the impact of corruption on poverty in this country. In particular, in Kazakhstan, the effect of corruption on the level of poverty was less pronounced after adding additional variables. The authors suggest that less obvious mechanisms of the relationship between corruption and poverty may operate for Kazakhstan, and suggest further research directions, such as the use of nonlinear models and a more accurate choice of variables. This study provides a better understanding of the impact of corruption on poverty and emphasizes the need for further research in this area.