Economics and Business Review

Examining the performance of Shari’ah‑compliant versus conventional stock indexes: A comparative analysis pre-, during, and post-COVID-19

Ahmad Abu-Alkheil — 2024-06-07

This study aims to conduct an empirical comparative analysis of the performance of Shari’ah and conventional stock indexes during the period 2017–2023, which includes the COVID-19 pandemic. Additionally, it aims to investigate investors’ preferences and analyse the long-term relationship of these indexes, as well as exploring the potential diversification benefits. The research methodology incorporates stochastic dominance analysis, the VARMAX procedure, and Johansen’s co-integration approach. The data utilized consists of 31 conventional and 31 Islamic stock indexes, specifically from the FTSE, DJ, MSCI, and S&P series.
The results show that there are no long-term co-integration links between 30 out of 31 pairs of Islamic and conventional indexes. While conventional indexes tend to outperform Islamic indexes, they also come with a higher risk. On the other hand, Islamic indexes are considered to be less risky, offering potential diversification opportunities that may be attractive for global portfolios, particularly during periods of financial distress.

Determinants of labor productivity regional diversity in Italy

Oleksij Kelebaj — 2024-06-04

The aim of the paper is to assess the causes of spatial variations in labour productivity of Italian regions using the gravity model of economic growth. The model is an extension of Robert Solow’s economic growth model. The authors calibrate the model parameters using historical data and carry out numerical simulations of the long-run equilibrium states of the model. The scenarios considered in the paper vary in forecast investment rates, employment growth rates and urbanization rates. To achieve the full convergence in labour productivity, it is necessary to maintain higher investment rates in the south of the country than in Lombardy (by about 4-11%), and to keep investment rates in central and northern Italy at a similar level as in Lombardy. The fall in investment has affected the poorest regions, southern Italy, the most, followed by central Italy and the richest regions of the north of the country the least

Growth prospects for the silver economy in the market segment of residential care services provided to dependent elderly people

Rafał Iwański — 2024-06-07

The aim of this study is to characterise the determinants of the development of the silver economy in the field of care services provided in a residential form for dependent elderly persons in Poland. The analysis was carried out on the basis of statistical and financial background data, including those from the Ministry of Family and Social Affairs, the Ministry of Health, OECD, etc. Although the demand for care services will continue to grow in the coming years, the following barriers to the development of this segment of the silver economy can be identified: lack of employees, unattractiveness of monetary gratification, inefficient financing mechanisms, lack of public investment in the development of care facilities, and increasing costs of providing services in all forms.

Personal bankruptcy prediction using machine learning techniques

Magdalena Brygała — 2024-06-12

It has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to that, this study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the study is to examine the usefulness of machine learning models such as random forest, XGBoost, LightGBM, AdaBoost, CatBoost, and support vector machines in forecasting personal bankruptcy. The research relies on two samples of households (learning and testing) from the Survey of Consumer Finances, which was conducted in the United States. Among the estimated models, CatBoost and XGBoost showed the highest effectiveness. Among the most important variables used in the models are income, refusal to grant credit, delays in the repayment of liabilities, the revolving debt ratio, and the housing debt ratio.