7-Score Function for Assessing the Strength of Association Rules Applied for Construction Risk Quantifying

There are several factors influencing the time of construction project execution. The properties of the planned structure, the details of an order, and macroeconomic factors affect the project completion time. Every construction project is unique, but the data collected from previously completed projects help to plan the new one. The association analysis is a suitable tool for uncovering the rules—showing the influence of some factors appearing simultaneously. The input data to the association analysis must be preprocessed—every feature influencing the duration of the project must be divided into ranges. The number of features and the number of ranges (for each feature) create a very complicated combinatorial problem. The authors applied a metaheuristic tabu search algorithm to find the acceptable thresholds in the association analysis, increasing the strength of the rules found. The increase in the strength of the rules can help clients to avoid unfavorable sets of features, which in the past—with high confidence—significantly delayed projects. The new 7-score method can be used in various industries. This article shows its application to reduce the risk of a road construction contract delay. Importantly, the method is not based on expert opinions, but on historical data.

Non-Performing Loans and Macroeconomics Factors: The Italian Case

The purpose of this work is to investigate the influence of macroeconomics determinants on non-performing loans (NPLs) in the Italian banking system over the period 2008Q3–2020Q4. We mainly contribute to the literature by being the first empirical article to study this relationship in the Italian context in the recent period, thus providing fresh evidence on the macroeconomic impact on NPLs, i.e., on the credit risk of Italian banks. By employing the Autoregressive Distributed Lag (ARDL) cointegration model, we are able to investigate the short and long-run effects of macroeconomic factors on NPLs. The empirical findings show that gross domestic product and public debt have a negative impact on NPLs. On the other hand, we find that the unemployment rate and domestic credit positively influence impaired loans. Finally, we find evidence of the “gamble for resurrection” approach, i.e., Italian banks tend to support “zombie firms”.

Determining the Impact of Economic Factors to the Gross Domestic Product in Bangladesh

Gross Domestic Product (GDP) is believed to be an indicator of a country’s economic condition. Bangladesh’s GDP increased at a pace of 8.15% in fiscal 2018-19 as per the base year 2005-06. By the year 2019, Bangladesh has become the seventh fastest-growing economy in the world. This paper used multiple regression analysis model for the macroeconomic factors. The aim of this study is to measure the effects of macroeconomic factors considering GDP as the dependent variables and inflation rate, import, and export are considered as independent. This paper represents that import and export are positively associated factors with GDP whereas inflation rate is a negatively associated factor. This study concluded with revealing the importance of conducting further study by considering more economic variables to measure the economic growth as a whole.

Explaining Aggregated Recovery Rates

This study on explaining aggregated recovery rates (ARR) is based on the largest existing loss and recovery database for commercial loans provided by Global Credit Data, which includes defaults from 5 continents and over 120 countries. The dependence of monthly ARR from bank loans on various macroeconomic factors is examined and sources of their variability are stated. For the first time, an influence of stochastically estimated monthly growth of GDP USA and Europe is quantified. To extract monthly signals of GDP USA and Europe, dynamic factor models for panel data of different frequency information are employed. Then, the behavior of the ARR is investigated using several regression models with unshifted and shifted explanatory variables in time to improve their forecasting power by taking into account the economic situation after the default. An application of a Markov switching model shows that the distribution of the ARR differs between crisis and prosperity times. The best fit among the compared models is reached by the Markov switching model. Moreover, a significant influence of the estimated monthly growth of GDP in Europe is observed for both crises and prosperity times.

Determinants of Foreign Direct Investment in Indonesia

We examine what determines the flow of foreign direct investment (FDI) in Indonesia, focusing on the role of institutional measures. A knowledge-and-physical-capital (KPC) model is applied to a panel dataset that covers 42 of Indonesia’s FDI partners from 2004 to 2012. Evidence shows that both horizontal and vertical FDIs coexist in the bilateral aggregate data of Indonesia’s FDI flows, but horizontal FDI appears to be dominant. This can be explained by the market size (proxied by the total GDP of both countries and similarity in incomes per capita) and the relative factor endowments (proxied by skilled labor and physical capital). The vertical FDI, on the other hand, could be only explained by the significant effect of unskilled labor. Institutional factors, particularly corruption, are apparently important in affecting Indonesia’s bilateral FDI flows. The results also show that a higher FDI level in Indonesia positively correlates with macroeconomic factors, open policy factors, and utility infrastructure factors.

Determinants of bank profitability during oil price decline

This study examines the influence of macroeconomic factors, namely Inflation, Gross Domestic Production (G.D.P.) and changes in oil price and Bank-Specific Factors such as capital, asset size, liquidity risk, loan and deposit on bank profitability as measured by return on equity (R.O.E.) and net profit ratio (NPR) during the period of oil price decline, 2013-2017. The top 7 commercial banks were chosen as a sample of the study based on the availability of the data and the possible influence it can contribute to representing Oman's banking industry. The quantitative approach utilized appropriate statistical tools to analyze and interpret the secondary data gathered, including descriptive statistics, panel regression, Pearson correlation, and correlation matrix. Key findings of the study revealed no significant relationship between macroeconomic factors and the return on equity. There is also no significant relationship between macroeconomic factors and the net profit ratio. On the other hand, bank-specific factors significantly correlate return on equity and the net profit ratio. The study's findings contribute to the bank's management, economic policymakers, a research body, and academia in distinguishing the best indicator for a bank's profitability influenced by macroeconomic and bank-specific factors.

Role of macroeconomic factors predicting financial performance of commercial banks in Nepal

Purpose: This study analyzes the effect of macroeconomic indicators such as domestic products, interest rate, inflation rate, and unemployment rate on the financial performance of commercial banks in Nepal. Design/Methodology: Five top commercial banks based on the financial performance were selected with stratified sampling, with secondary data of ten years. Hausman test was used to examine the endogeneity issue in the predictor variables and the effect of predicators on financial performance were estimated using OLS estimation (random effect model). Findings: The study result revealed significant influence of macroeconomic factors except the unemployment rate for estimating ROE of commercial banks in Nepal while no significant impact was revealed for ROA. Among the significant variables, GDP contributes more in predicting the financial performance of commercial banks in Nepal. Implication: As the study found significant role of macroeconomic variables to estimate ROE, bank administrators, government officials, and investors can focus in such variables, especially in GDP for competitive financial performance. They need to develop products based on macroeconomic variables. Besides, this study finds and tries to mitigate the gap in findings of previous empirical studies. Originality/value: This study contributes to the literature on macroeconomic determinants predicting financial performance of banks, more specifically in finding the gap in determining ROA and ROE within the country specific issue.

BANK SPECIFIC AND MACROECONOMIC FACTORS INFLUENCING ISLAMIC BANKS DEPOSITS

Deposits are like the bloodline for banks as they determine banks' lending capacity and a country's economic savings. However, the existence of a dual banking system poses a challenge to Malaysian Islamic banks competing for deposits. Despite this problem, few investigations were done to comprehensively identify the factors that could help banks attract deposits, particularly for Islamic banks. The purpose of this paper is to fill this gap on deposits of 16 Islamic banks in Malaysia. Secondary data from the bank's annual reports and the Department of Statistics of Malaysia from 2015 to 2019 were analyzed, comprising Islamic Bank Deposits and seven predictors in an empirical model using STATA. The result shows a strong model fit with 92% R squared value that Return on Assets, bank concentration, and Business Enterprise Depositor affect Islamic Bank Deposits positively and significantly while Capital Adequacy Ratio showed negative and significant influence on the deposits. These factors are strongly effective to deposits, significant at 1% level. In contrast, Financing Deposit Ratio and Gross Domestic Product do not significantly influence Islamic deposits. Contrary to economic theory, this study found that an increase in inflation encourages customers to increase their saving deposits in Malaysian Islamic banks. The findings from this study are unique to Malaysian Islamic banks. They indicate important policy implications for Islamic banks practitioners, namely, to increase their focus on business enterprise customers, improve bank's market share and profitability in order to increase deposits while taking advantage of high inflationary period to attract more depositors.

Impact of Macroeconomic Factors on Underpricing: Case of Indonesia Stock Exchange

The stock market is one of the alternatives chosen by companies to meet their funding needs. The first offering of a company's shares through the stock market to investors is called an Initial Public Offering. At the time of initial public offering, underpricing often occurs when the initial stock price on the primary market is lower than the stock price on the secondary market which will disadvantage the company because the collected funds are not maximum. This research aims to analyze the effect of macroeconomic factors on underpricing in companies conducting IPOs listed on the Indonesia Stock Exchange from 2010 to 2020. Using Regression Linear Analyze we found that macroeconomic variables as Inflation, IDX Composite Index, and GDP significantly affect underpricing on IPO in Indonesia Stock Exchange for 2010 to 2020

Investigating the Link Between Macroeconomic Factors and Income Inequality of Asian Countries

The main purpose of the study was to analyze the impact of macroeconomic factors on income inequality. The panel data analysis is conducted on the sample data of 36 Asian countries. The data of 19 years from the period 2001 to 2019 is collected to analyze the impact of interest rate, economic growth, FDI and exports. The findings revealed the positive relationship between income inequality and economic growth whereas FDI and exports have negative relationship with income inequality. Result of the study implies that authorities should pay special attention to design policies that encourage inward FDI and increase exports.