Search

The purpose of this paper is to evaluate poverty reduction possibilities determining the effect of average wage and unemployment on poverty, identifying the factor that is a more important predictor of poverty in Lithuania. Based on scientific literature analysis, we identify the factors that determine the phenomenon under study. We perform a statistical analysis of the collected data in the period of 2008–2021 to identify trends and patterns in the factors under consideration. The ordinary least squares method allows to estimate the impact of the selected factors on poverty. The results show that unemployment has a statistically significant positive effect (based on the sign of the estimated parameter of the regression model) on poverty, while average wage has a statistically significant negative effect on poverty. Based on the obtained results, we present possible solutions to company managers on how they could contribute to reducing poverty in the country. We conclude that company managers could apply more sustainable development goals in their businesses, reduce gender inequality, increase wages, hire unskilled workers, and help them to improve. In this way, company managers could contribute to reducing poverty in the country.

Research background: Unemployment is a huge topic for policymakers, scholars, and, in general, society. Historically, there have always been a lot of discussions about this phenomenon. It is already acknowledged that unemployment is closely related to economic activity: when the economy is growing, more people are employed, and when economic activity is low, employment decreases, and unemployment rises. This relation is well-researched in the framework of Okun's law. However, it is far less known how this relationship holds if international economic relations are introduced. Thus, the motivation for the research was to examine the role of international trade and foreign direct investment (FDI) on the growthunemployment nexus. Purpose of the article: To assess how trade and FDI affect growth and gender-, age-, and educational attainment level-specific unemployment relationship and on what scale this effect varies over different business cycle phases. Methods: Scientific literature review, comparative analysis, and panel regression. Findings & value added: Given the lack of research examining what effect FDI and trade have on the growth-unemployment nexus, this paper estimates modified Okun's equation on the European Union (EU) countries (EU-28, by the composition of the EU until 31/01/2020) for the period from 2000 to 2019 while incorporating international aspects that can have an impact on this nexus. Also, this study develops a specification that can be useful to monitor the potentially different effects of FDI and trade on the growth-unemployment nexus during different business cycle phases. The estimations of the panel regression for unemployment disaggregated by age, gender and education level has showed that import, export, inward FDI, and outward FDI have a negative effect on the growth-unemployment nexus. It means that with an increase in the intensity of international economic relations, the influence of gross domestic product (GDP) growth on unemployment becomes less significant. Thus, the effectiveness of expansionary fiscal policy to reduce unemployment becomes less effective in more open economies, which in the case of the EU are the smallest member states with relatively small domestic markets. [ABSTRACT FROM AUTHOR]

This paper analyses the effect of inflation, gross domestic product (GDP) growth, and average salary on unemployment in Lithuania for the period from 2001 to 2021. First, the theoretical analysis is performed to review the links between inflation, GDP growth, average salary, and unemployment. Considering that the theoretical analysis reveals the effect of three macroeconomic factors, i.e., inflation, GDP growth, and average salary, on unemployment, the methodology of the research is described. It relies on the multiple regression model and its estimation using ordinary least squares (OLS). Econometric analysis reveals that only one out of three macroeconomic factors, i.e., GDP growth, has a statistically significant effect on unemployment and this effect is negative (based on the sign of the regression coefficient). In addition, to address the autocorrelation problem in the regression model, a lagged unemployment variable is included to the model, and it shows a statistically significant positive (based on the sign of the regression coefficient) effect on unemployment. The future study could only cover the agricultural sector since this sector is important for Lithuania and the macroeconomic indicators of this sector are unique compared to other economic activities or general indicators of Lithuania. [ABSTRACT FROM AUTHOR]