EconPapers    
Economics at your fingertips  
 

Spatial analysis of determinants affecting+ the total number of Covid-19 cases of provinces in Turkey

Serkan Cahit Dinç () and Necati Alp Erilli ()
Additional contact information
Serkan Cahit Dinç: Sivas Cumhuriyet University, Sivas, Turkey
Necati Alp Erilli: Sivas Cumhuriyet University, Sivas, Turkey

Applied Econometrics, 2022, vol. 65, 102-116

Abstract: The Covid-19 which is accepted as a pandemic by the World Health Organisation, has created a global panic effect all over the world. To stop this epidemic, in which more than 4 million people died as of July 2021, researches are being carried out on all kinds of issues related to the disease. In this study, a spatial econometric analysis of the determinants of the total number of Covid-19 cases in the provinces in Turkey between February 8, 2021, and May 7, 2021, was conducted. The existence of spatial autocorrelation was investigated through the Moran I test, and as a result, the Spatial Lagged Model (SAR) was found to be the most appropriate model. According to the results of the spatial analysis, it has been determined that the change in the total number of cases in a province will be in the same direction in the neighboring provinces of that province. A spatial interaction finding was obtained between the provinces and a significant and positive relationship was found between the total number of Covid-19 cases and the population density and the number of people over the age of sixty. Similarly, a significant and negative relationship was found with the average temperature and the total number of healthcare workers, and no significant relationship was found with the literacy rate

Keywords: spatial analysis; Covid-19; spatial lag model; Moran I test; LM test (search for similar items in EconPapers)
JEL-codes: C31 C54 I18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://pe.cemi.rssi.ru/pe_2022_65_102-116.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:apltrx:0441

Access Statistics for this article

Applied Econometrics is currently edited by Anatoly Peresetsky

More articles in Applied Econometrics from Russian Presidential Academy of National Economy and Public Administration (RANEPA)
Bibliographic data for series maintained by Anatoly Peresetsky ().

 
Page updated 2025-03-19
Handle: RePEc:ris:apltrx:0441