Using the Econometric Models for Identification of Risk Factors for Albanian SMEs (Case study: SMEs of Gjirokastra region)

TL;DR

This study employs econometric models, specifically binary logistic regression, to analyze how Albanian SMEs in Gjirokastra identify risks, revealing their ability to perceive risk factors through statistical analysis of survey data.

Contribution

The paper applies logistic regression to assess risk identification capabilities of Albanian SMEs, providing quantitative insights into their risk perception using survey data.

Findings

Albanian SMEs can identify risk factors affecting them.

Logistic regression effectively models risk perception.

Quantitative analysis supports risk management strategies.

Abstract

Using the econometric models, this paper addresses the ability of Albanian Small and Medium-sized Enterprises (SMEs) to identify the risks they face. To write this paper, we studied SMEs operating in the Gjirokastra region. First, qualitative data gathered through a questionnaire was used. Next, the 5-level Likert scale was used to measure it. Finally, the data was processed through statistical software SPSS version 21, using the binary logistic regression model, which reveals the probability of occurrence of an event when all independent variables are included. Logistic regression is an integral part of a category of statistical models, which are called General Linear Models. Logistic regression is used to analyze problems in which one or more independent variables interfere, which influences the dichotomous dependent variable. In such cases, the latter is seen as the random variable and is dependent on them. To evaluate whether Albanian SMEs can identify risks, we analyzed the factors that SMEs perceive as directly affecting the risks they face. At the end of the paper, we conclude that Albanian SMEs can identify risk