Research Papers in Economics and Finance

Assessment of Poland’s fiscal position in the European Union in the face of crisis conditions

Sławomir Zwierzchlewski — Wed, 10 Apr 2024 00:00:00 +0200

Crisis conditions in the 21st century also reached the European Union countries, including Poland, and were reflected in the nominal and real economy. In particular, what suffered most was the fiscal condition of individual countries. To support the state of the economy, the economic authorities often took extraordinary, unconventional actions, which unfortunately resulted and still result in a deterioration of the state of public finances. It is therefore worth referring to this research and empirical problem from the perspective of the current and ongoing economic crisis.

How institutions are related to agriculture? Systematic literature review

Michał Barszczewski — Thu, 09 May 2024 00:00:00 +0200

In this paper, the author reviews the literature on institutions and their relations with agricultural economics. The aims of the article are to clarify the definition of an institution, indicate its relevance from the perspective of agricultural economics and propose a method of institution classification. Using the PRISMA method, 35 articles were selected out of 238 articles from the Web of Science database that met the established requirements (i.e. they were simultaneously related to institutions, economic performance and the agricultural sector). Based on the identified articles as well as the preliminary literature review it can be concluded that there is a lack of research that precisely defines institutions and examines the historical context at the same time. There are not many papers in which authors assess relations between institutions.

Financial frauds throughout the years – literature review

Marek Kot — Mon, 03 Jun 2024 00:00:00 +0200

Financial frauds have been a growing problem across the global financial markets. Losses generated by such illegal activities affect both the global economy and individual entities, especially those operating in the financial market. Perpetrators of such frauds seem to always be one step ahead of the law enforcement, regulators as well as private sector entities such as banks and scientists. This review examines publishing actions taken throughout the years. It also shows whether there has been any correlation spotted between the number of papers published in a particular year and the events on the financial markets. The study involved a systematic literature review to achieve the set goals. Following the final results of the article, it is clear that the issue of financial frauds has been a growing global concern. It is crucial to strengthen the collaboration between the regulators, law enforcement, academic environment and private sector. Cooperation across the sectors should include research on how to prevent and mitigate the consequences of this kind of frauds.

Financial performance and cash flow: Evidence from the US banking industry

Gerasimos G. Rompotis — Thu, 20 Jun 2024 00:00:00 +0200

This study examines the relationship between cash flow and financial performance with a sample of 122 American banks covering the period 2019-2022. Panel data analysis is applied. Financial performance is computed as the Return on Assets (ROA) and Return on Equity (ROE). The explanatory variables used are the net cash flow, free cash flow, cash flow from operating activities, cash flow from investing activities, cash flow from financing activities, size of banks, the leverage ratio, i.e., total liabilities to total assets, the liquidity ratio, i.e., current assets to current liabilities, and the efficiency ratio, i.e., total revenue to total assets. The results provide evidence of a negative relationship between financial performance and net cash flow. This is also the case for cash flow from investment and financing activities. On the contrary, the relationship of free cash flow with performance is positive. On the other explanatory variables, leverage and efficiency are positively related to financial performance.

Forecasting foreign exchange rate volatility using deep learning: Case of US dollar/Algerian dinar during the COVID-19 pandemic

Meryem-Nadjat Naas, Habib Zouaoui — Mon, 24 Jun 2024 00:00:00 +0200

This study explores the application of deep learning techniques in forecasting foreign exchange rate volatility, leveraging the capabilities of neural networks to capture complex patterns and nonlinear relationships within financial data.

We applied the auto regressive integrated moving average (ARIMA) and machine learning linear regression (LR) model, deep learning models ( recurrent neural networks (RNN), bidirectional LSTM (Bi-LSTM), long short-term memory (LSTM) and gated recurrent unit (GRU). In terms of forecasting errors, and Python routines were used for such purpose. Morever, In order to investigate the quality of the models used, we compared the performances of these algorithms in US dollar/algerian dinar exchange rate forecasting througt the application of significance satistical tests (R-squared, MSE, RMSE, MAE, MAPE)The results clearly depict that contemporary techniques have been shown to produce more accurate results than conventional regression-based modeling. The machine learning linear regression (LR) model provides the maximum accuracy rate of (99.83%) followed by the RNN models with GRU model (92.27%) , Bi-LSTM model (87.34%), LSTM model (74.68%) and ARIMA model (32.29%) .

Institutional differences and threats to international tourists from the perspective of new institutional economics

Wed, 26 Jun 2024 00:00:00 +0200

The main aim of this article is to demonstrate theoretical connections in the context of institutional differences for the international tourist, which may constitute a source of threats due to institutional differences between countries. The article highlights theoretical threats stemming from institutional differences for international tourists from the perspective of new institutional economics, the research methods of which provide the analytical framework for this analysis. The post-pandemic period could transform preferences among international tourists, who are increasingly drawn to countries with significant cultural diversity. This creates dangers arising from institutional differences that may affect their sense of security and, consequently, have implications for social costs significant to the industry, as demonstrated during the COVID-19 pandemic, underscoring its crucial role in global economic development.

Application of a single-equation SARIMA model for short-term conditional forecast (projection) of CPI price dynamics in Poland

Patryk Kołbyko — Fri, 28 Jun 2024 00:00:00 +0200

The aim of the article is to construct an optimal SARIMA model for short-term conditional forecasting (projection) of the dynamics of prices expressed by the Consumer Price Index (CPI), as understood within the extended Box-Jenkins procedure. The construction of such a forecast aims to influence, through the expectations channel, the institutional trust of society in monetary authorities and assess the effectiveness of achieving the monetary policy goal within the framework of the democratic responsibility of the decision-making body of the National Bank of Poland – the Monetary Policy Council. The selection of the optimal SARIMA model was carried out using an iterative method within the Box-Jenkins procedure, with the goal of reducing the systematic bias of estimators – coherence with empirical data. The analysis was conducted on compiled secondary data of the monthly Consumer Price Index for goods and services from the Central Statistical Office for the years 2010-2023 (on a monthly basis). Results show that the short-term forecast demonstrated accuracy within a specified confidence interval. The application of the SARIMA model serves as a useful methodological tool for constructing elaborate DSGE models (for example, the NECMOD model) using procedures such as SEM (System for Averaging Models) from Norges Bank.

Digitalisation and income inequality in Central and Eastern European countries

Sławomir Kuźmar, Dawid Piątek — Fri, 28 Jun 2024 00:00:00 +0200

The COVID-19 pandemic has highlighted the importance of digital technologies in business and daily life. The paper aims to explore the theoretical and empirical aspects of the relation between digitalisation and income inequality in Central and Eastern European (CEE) countries between the years 2000-2020. It contributes to existing research on determinants of income inequality, focussing on the potential negative role of digitalisation as an unnoticeable driver of income inequality in CEE countries. To investigate the potential impact of digitalisation on income inequality, empirical analysis was performed for the sample of 10 CEE countries, namely Bulgaria, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, the Slovak Republic and Slovenia. The results of canonical correlation analysis indicated that the sets of variables related to digitalisation and inequality as a group are significantly related to each other and a strong correlation exists between them. The relative contribution of each indicator to each standardised function showed that the highest values of significant standardised coefficients were observed for income inequality indicators such as the top 10% share, the Gini coefficient, and the top 1% share, while in digitalisation measures, the highest value was observed for Internet users and fixed and mobile broadband subscriptions.

Stock market return and merger and acquisition activity in Poland

Eliasz Czajkowski, Mateusz Mikutowski — Fri, 28 Jun 2024 00:00:00 +0200

This article explores mergers and acquisitions trends in the Polish market in a period between 2019 and 2022, focusing on transactions exceeding one million dollars and their correlation with sector-specific stock market returns. The research reveals that the real estate sector, encompassing both development and property management, dominated M&A activity, comprising 25% of transactions in 2022. Significant positive correlations were observed between transaction volumes and average stock market returns, notably in sectors like real estate (R-Pearson = 0.75) and TMT (R-Pearson = 0.87). These findings indicate that sectors with higher returns attracted more M&A activity, reflecting investor confidence and strategic growth opportunities. Despite fluctuations in company valuations post-pandemic, the overall volume of M&A transactions continued to rise, driven by firms with strong cash reserves leveraging lower valuations for strategic expansions. The study anticipates sustained momentum in technology and real estate sectors, alongside emerging opportunities in energy and biotechnology, influenced by global trends and technological advancements. This research contributes valuable insights into the evolving landscape of M&A in Poland, highlighting sectoral attractiveness and strategic implications for investors and businesses.

Praface

Piotr Lis — Fri, 28 Jun 2024 00:00:00 +0200