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This study investigates the impact of economic growth, inflation, money supply, and real interest rates on non-performing loans (NPLs) in the Vietnamese banking system. To achieve the research objective, we employ Ordinary Least Squares and Quantile regression methods to estimate models with data collected from the World Bank on the Vietnamese banking system for the period 2000-2020. The Ordinary Least Squares estimation results do not find a significant impact of economic growth on NPLs, but Quantile regression estimation results reveal that economic growth has a negative effect on NPLs for the lower quantile groups, with this effect being insignificant for the quantile groups above 0.3. Furthermore, the study's findings indicate that inflation and real interest rates have a negative impact on NPLs across most quantile groups, while the money supply has a negative impact on NPLs only in the medium quantiles (0.4 and 0.5) and high quantile groups (above 0.7). Additionally, we found a stable equilibrium between NPLs and economic growth, inflation, money supply, and real interest rates, with a positive long-term impact of economic growth, inflation, money supply, and real interest rates on NPLs. The research findings propose several policy implications for controlling NPLs in the Vietnamese banking system.

Sick absence affects companies both operationally and economically and the matter has become increasingly prominent following the COVID-19 pandemic. MedHelp Care is an e-health company working towards increasing workplace wellness by offering insights into absence and rehabilitation matters. Forecasting future absence levels could help with matters such as staffing and garner more insight into which factors that impact absenteeism. Moreover, gauging how external factors affect the absence could help deepen the knowledge further. With absence data now being digital, it is able to be modeled using statistical tools. The dataset was aggregated to a daily basis and preprocessed to better represent the Swedish labour force. Then, by applying time series analysis and machine learning methods, predictions of sick absence were formed. Datasets of the Swedish stock market and the discourse around COVID-19 on Twitter, respectively, were processed to time series and their relation to the sick absence was explored using crosscorrelation. The sets were then individually incorporated into exogenous models using autoregression, and then their impact was evaluated. Results show that the SARIMA model is better for predicting short and medium length horizons while the machine learning methods used were more apt for long horizons. Results from the exogenous models were mixed; the OMX set improved short term prediction accuracy while other horizons were largely unaffected, and the Twitter set worsened performance for all horizon lengths. While the model results are promising, their current complexity hinder large-scale deployment and further research is needed to further verify the effect of exogenous datasets.

This study investigates the impact of economic growth, inflation, money supply, and real interest rates on non-performing loans (NPLs) in the Vietnamese banking system. To achieve the research objective, we employ Ordinary Least Squares and Quantile regression methods to estimate models with data collected from the World Bank on the Vietnamese banking system for the period 2000-2020. The Ordinary Least Squares estimation results do not find a significant impact of economic growth on NPLs, but Quantile regression estimation results reveal that economic growth has a negative effect on NPLs for the lower quantile groups, with this effect being insignificant for the quantile groups above 0.3. Furthermore, the study's findings indicate that inflation and real interest rates have a negative impact on NPLs across most quantile groups, while the money supply has a negative impact on NPLs only in the medium quantiles (0.4 and 0.5) and high quantile groups (above 0.7). Additionally, we found a stable equilibrium between NPLs and economic growth, inflation, money supply, and real interest rates, with a positive long-term impact of economic growth, inflation, money supply, and real interest rates on NPLs. The research findings propose several policy implications for controlling NPLs in the Vietnamese banking system.

Sick absence affects companies both operationally and economically and the matter has become increasingly prominent following the COVID-19 pandemic. MedHelp Care is an e-health company working towards increasing workplace wellness by offering insights into absence and rehabilitation matters. Forecasting future absence levels could help with matters such as staffing and garner more insight into which factors that impact absenteeism. Moreover, gauging how external factors affect the absence could help deepen the knowledge further. With absence data now being digital, it is able to be modeled using statistical tools. The dataset was aggregated to a daily basis and preprocessed to better represent the Swedish labour force. Then, by applying time series analysis and machine learning methods, predictions of sick absence were formed. Datasets of the Swedish stock market and the discourse around COVID-19 on Twitter, respectively, were processed to time series and their relation to the sick absence was explored using crosscorrelation. The sets were then individually incorporated into exogenous models using autoregression, and then their impact was evaluated. Results show that the SARIMA model is better for predicting short and medium length horizons while the machine learning methods used were more apt for long horizons. Results from the exogenous models were mixed; the OMX set improved short term prediction accuracy while other horizons were largely unaffected, and the Twitter set worsened performance for all horizon lengths. While the model results are promising, their current complexity hinder large-scale deployment and further research is needed to further verify the effect of exogenous datasets.

The world trends of the development of seaports in recent years are investigated in the article. During the last twenty years, the volume of world seaborne trade has doubled, especially in the sectors of dry cargo and container traffic. This is due to the increase in trade in the southern hemisphere and the continued strong demand for iron ore in China. In terms of regional influence, Asia continues to dominate as the primary transshipment site, then follow North and South America, Europe, Oceania and Africa. The fall in oil prices has affected the volume of supply and sea trade, in particular the tanker trade, its share fell to 28.7 percent in 2014. Meanwhile, lower fuel costs make it possible to reduce the costs of ship operators and the rates paid by the shipper. This in turn could stimulate demand for maritime transportation services and the increase in marine cargo flow. The research allowed to identify macro factors that have a significant effect on the activity of the enterprises of the maritime industry (economic, political, technological) and to recommend the development directions for each group. Most of Ukrainian sea ports problems are systemic and interrelated and require settlement at the national level through the creation of an appropriate regulatory framework and the formation of the conceptual foundations on combination of government regulation and market self-regulation of sea ports development. Capacity building and improving the quality of works and port services is the main direction of investment and innovation activity. All this will lead to an increase in the competitiveness of Ukrainian ports in the world market due to increased volumes of cargo handling, attraction of new cargo flows and expansion of the range of work and services.

Den 18 februari i år fick Sverige en negativ reporänta. Ett historiskt ögonblick i Sveriges ekonomiska historia. I detta arbete har vi valt att fokusera på hur den kommersiella fastighetsmarknaden kommer att påverkas av denna händelse. Den kommersiella fastighetsmarknadens rörelse är inte beroende av enbart en variabel utan av flera. Som i sin tur är mer eller mindre beroende av varandra. BNP och reporäntan är två av dessa variabler som påverkar den studerade marknaden. I arbetet valdes fyra scenarion ut där BNP och reporäntan befann sig i olika lägen under 2000-talet. Dessa fyra scenarion leder fram till en diskussion angående ett eventuellt samband mellan de olika faktorerna och makrofaktorernas rörelse. Vi studerar även om vi på grund av detta eventuella samband kan förutsäga framtiden. Den framtid som förväntas kantas av en sjunkande negativ reporänta och en växande ekonomisk tillväxt. Efter att ha genomfört studien kan vi utläsa ett samband mellan våra utvalda makrofaktorer och den kommersiella fastighetsmarknaden. Ett tydligt mönster, vid en sammanställning av resultaten från våra scenarion, har inte hittats och kan därför inte användas i en argumentation kring följden av reporäntans nu negativa värde. Resonemanget förs dock kring att den negativa reporäntan och dagens ekonomiska tillväxt kommer påverka den kommersiella fastighetsmarknaden positivt snarare än negativt., On 18th of February this year, the Swedish central bank set a negative repo rate. This was a historic moment in Sweden's economic history. In this paper, we have chosen to focus on how the commercial property market will be affected by this event. The commercial property market movements is not dependent on only one variable, but a set of dependent and independent variables. GDP and the repo rate are two variables that affect the studied market. In this essay, four different scenarios were chosen where GDP and the repo rate were in different positions during the 2000s. These four scenarios lead to a discussion about a possible relationship between the commercial property market- and the macro factors movement. The paper also discusses if the future can be predicted, because of a possible relationship. The future that is expected to consist of a sinking negative repo rate and an economic growth. After conducting the study, the paper concludes that there is a strong connection between our selected macro factors and the commercial property market. Although, a clear pattern, after a summary of the results of our scenarios, has not been found and therefore cannot be used in an argument about the result of the negative repo rate. The conclusion is, however, that the negative repo rate and today's economic growth will affect the commercial property market positively rather than negatively

Den 18 februari i år fick Sverige en negativ reporänta. Ett historiskt ögonblick i Sveriges ekonomiska historia. I detta arbete har vi valt att fokusera på hur den kommersiella fastighetsmarknaden kommer att påverkas av denna händelse. Den kommersiella fastighetsmarknadens rörelse är inte beroende av enbart en variabel utan av flera. Som i sin tur är mer eller mindre beroende av varandra. BNP och reporäntan är två av dessa variabler som påverkar den studerade marknaden. I arbetet valdes fyra scenarion ut där BNP och reporäntan befann sig i olika lägen under 2000-talet. Dessa fyra scenarion leder fram till en diskussion angående ett eventuellt samband mellan de olika faktorerna och makrofaktorernas rörelse. Vi studerar även om vi på grund av detta eventuella samband kan förutsäga framtiden. Den framtid som förväntas kantas av en sjunkande negativ reporänta och en växande ekonomisk tillväxt. Efter att ha genomfört studien kan vi utläsa ett samband mellan våra utvalda makrofaktorer och den kommersiella fastighetsmarknaden. Ett tydligt mönster, vid en sammanställning av resultaten från våra scenarion, har inte hittats och kan därför inte användas i en argumentation kring följden av reporäntans nu negativa värde. Resonemanget förs dock kring att den negativa reporäntan och dagens ekonomiska tillväxt kommer påverka den kommersiella fastighetsmarknaden positivt snarare än negativt., On 18th of February this year, the Swedish central bank set a negative repo rate. This was a historic moment in Sweden's economic history. In this paper, we have chosen to focus on how the commercial property market will be affected by this event. The commercial property market movements is not dependent on only one variable, but a set of dependent and independent variables. GDP and the repo rate are two variables that affect the studied market. In this essay, four different scenarios were chosen where GDP and the repo rate were in different positions during the 2000s. These four scenarios lead to a discussion about a possible relationship between the commercial property market- and the macro factors movement. The paper also discusses if the future can be predicted, because of a possible relationship. The future that is expected to consist of a sinking negative repo rate and an economic growth. After conducting the study, the paper concludes that there is a strong connection between our selected macro factors and the commercial property market. Although, a clear pattern, after a summary of the results of our scenarios, has not been found and therefore cannot be used in an argument about the result of the negative repo rate. The conclusion is, however, that the negative repo rate and today's economic growth will affect the commercial property market positively rather than negatively

The article is devoted to the study of factors that affect foreign direct investment, namely the factors that influence the decision of foreign investor conserning investing

Firm capital structure is one of the most widely researched topics in corporate finance. However, the results are not always consistent and applicable from one market to another when explaining financing patterns. The majority of available research focuses on finding the role of firm-specific factors to leverage while ignoring macro and institutional factors. This paper examines how the capital structure of firms in the Baltic is influenced by both firm level and country level determinants. The study demonstrates that changes in leverage of firms in the Baltic is subject to both changes in firm specific characteristics, such as asset tangibility, growth opportunity, firm size and liquidity, as well as the changes in macro and institutional factors namely bank development, stock development and financial openness to different extent.

Firm capital structure is one of the most widely researched topics in corporate finance. However, the results are not always consistent and applicable from one market to another when explaining financing patterns. The majority of available research focuses on finding the role of firm-specific factors to leverage while ignoring macro and institutional factors. This paper examines how the capital structure of firms in the Baltic is influenced by both firm level and country level determinants. The study demonstrates that changes in leverage of firms in the Baltic is subject to both changes in firm specific characteristics, such as asset tangibility, growth opportunity, firm size and liquidity, as well as the changes in macro and institutional factors namely bank development, stock development and financial openness to different extent.

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in