Using data mining techniques to improve inflation rate management

Document Type : RESEARCH PAPER

Authors

1 Master of Computer Science, Department of Computer Engineering Golestan University, Gorgan, Iran

2 Associate Professor, Department of Computer Engineering, Golestan University, Gorgan, Iran

Abstract

Inflation means the continuous increase in the price of commodities and services in a society and for a certain period of time. Inflation decreases the purchasing power of households, although this decrease in purchasing power will not be the same in all commodities, and this makes it difficult to predict economic and analytical conditions and investment opportunities.
Investigating the consequences of inflation in countries, such as the reduction of purchasing power, using different techniques such as data mining techniques, seems necessary. On the other hand, by predicting inflation and analyzing the data, it is possible to manage it correctly and on time. Data mining techniques are a useful tool in solving various problems in the economic field by identifying correlations and discovering patterns that helps the analysts to make the best predictions of economic indicators. In the economic field, the use of some data mining techniques brings a set of advantages such as optimization of basic activities. The present study deals with the identification of bottleneck commodities in the chain of basic commodities in the country. In order to obtain different variables and the impact of different product groups on inflation, 12 basic groups, which are the main products that make up the Consumer Price Index (CPI), were analyzed and evaluated during the years 2017 to 2021.
the present study identifies bottleneck commodities which pricing them are more important in the control of inflation rate. In order to achieve this goal, 12 groups of basic commodities of the country, which are the main commodities that make up the Consumer Price Index (CPI), were collected and presented in a complete graph. For each node that represents a group of basic commodities, five fratures were considered, the annual inflation related to each group, the degree of influence in increasing the total index, the number of subgroups of each main group, the degree of dependency, and the priority (level of demand). Then, by running the traveling salesman algorithm on the graph, we found a path where the group of foods and beverages is the bottleneck of the research subject. The results of the present study show that the management of pricing this group can have an effective impact on the inflation control of other groups over time.

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References

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