Skip to content
Research Article Open access CC BY 4.0

The Prediction of Growth of the GDP of North Macedonia for 2024 using Logistic and Linear Regression Model

Leotrim Ramadani, Neritan Turkeshi, Shpetim Rexhepi

Asian Journal of Economics, Business and Accounting · pp. 221–228 · Published 16 Feb 2024

10.9734/ajeba/2024/v24i31255

Abstract

The purpose of this research is to get to know the statistical calculations that are used even in other fields except Mathematics, like economics, Finance, Informatics, Architecture, etc. In this research, we have used statistical calculations like those of Linear Regression and Logistic Regression to calculate and predict the GDP of a specific country, in our case, North Macedonia. Here we have used the chance to use these two statistical models to present and visualize the already made predictions. The data are derived from the World Organization which deals with statistical data of all the countries of the world. While using these two statistical models we even explained which are the pros and cons of each other, when we should use the first one and when the second one, in what use-cases we can use these two and what are the differences between them.

Logistic linear regressions GDP North Macedonia

References (3)

  1. 1 What does the yield curve tell us about GDP growth? [DOI]
  2. 2 Macroeconomics: A European Text. [DOI]
  3. 3 Taking the Pulse of the Economy: Measuring GDP [DOI]

Cited by 2

Weighted least squares estimation by multivariate-dependent weights for linear regression models

Lei Huang, Cheng-Tsung Liu, Li Wang · 2026

Exploring RAG Solutions for a Specific Language: Albanian

Leotrim Ramadani, Fisnik Doko · European Journal of Information Technologies and Computer Science · 2025

Related research

Article metrics

Real usage data collected on this platform.

23

Page views

0

PDF downloads

2

Outbound clicks

2

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.