The Analysis of the Effect of Covid 19 on Macroeconomic Indicators via MDS and Clustering Methods

Abstract

BackgroundCovid 19, which emerged in China in December 2019 and affected the whole world in a short period, caused serious contractions in the world economy. Analyzing these effects is important in terms of reducing economic losses and measuring the effectiveness of the measures taken.MethodsThe aim of this study, covering the period 2019: q1- 2020q3 is to is to analyze the volatility in macroeconomic indicators caused by the pandemic process, taking into account the % changes in macroeconomic indicators and whether OECD countries show similar tendencies in terms of volatilities during the pandemic process. The period 2019: q1-2019: q3 represents the pre-pandemic period, while the period 2019: q4-2020: q3 represents the pandemic process. By using cluster analysis and multidimensional scaling analysis, countries that have similar characteristics in terms of the change in macroeconomic indicators for each period were grouped, and it was investigated whether this grouping changed during the pandemic process. Clustering and multidimensional scaling analysis are the most appropriate methods for the purpose of the study. Exports, imports, inflation, unemployment, private consumption and economic growth are macroeconomic indicators used in the model. ResultsAccording to the results of the analysis, although most OECD countries showed similar characteristics in terms of economic impact before the pandemic, countries such as Turkey, Iceland, Ireland, New Zealand and Mexico differ significantly from other countries in terms of economic impact during the pandemic process. The separation in question continues throughout the period discussed for Turkey. In addition, it was concluded that Spain, Britain, Mexico and Colombia suffered the most economic losses due to COVID-19 in the second quarter of 2020, when the pandemic was felt the most. ConclusionThe economic variable that has seen the most contraction is the volume of foreign trade. Unemployment rates have increased more slowly in countries where employment is sought to protect with employment packages, while unemployment rates have increased more in other countries. The contraction in the volume of production and consumption also negatively affected economic growth. Differences in economic impact have diversified the cluster between countries.

The application of multidimensional scaling of data to determining changes in retailer customers’ preferences

“…When dealing with the problem of how to analyse its impact on the economy, many different methods and approaches can be used. Among those, multidimensional scaling stands out as very popular (see, for example, its applications presented by Braithwaite et al, 2021;Coco et al, 2021;Güre et al, 2021;Kutlar et al, 2021). The authors decided to use symbolic data analysis and combine individual, monthly information from Polish health and beauty retailers to obtain symbolic interval-valued variables that would make it possible to capture variability in the data (see for example Billard & Diday, 2006).…”