Impact Of Macroeconomic Indicators Research Articles

A Study on the Impact of MacroEconomic Indicators in Vietnam on Real Estate Investment

A Study on the Impact of MacroEconomic Indicators in Vietnam on Real Estate Investment

The Impact of Macroeconomic Indicators on Medical Tourism: A Global Perspective

Medical tourism is an expanding global phenomenon stimulating economic development driven by a combination of multiple macro and socioeconomic factors. The study aims to investigate whether the development of medical tourism globally is associated with specific macroeconomic indicators. The association of Medical Tourism Index (MTI) is explored with Gross Domestic Product (GDP), healthcare spending and international tourism receipts. A countries’ grouping method and an ordinary least squares (OLS) regression model were used. MTI was used as the outcome variable, while macroeconomic indicators as potential predictors. The grouping of countries showed that European and Asian countries as well as Canada excel high ranking in all indicators. However, the Gulf Cooperation Council countries (GCC) that exhibit high performance in GDP, rank below the MTI average. Caribbean and Latin American countries are ranking high in the MTI but fall below the average in all the indicators. The OLS analysis showed a positive correlation between the score of the MTI and health expenditure and no correlation among MTI, GDP and international tourism receipts, a finding also supported by the grouping analysis. Taking into consideration the similarities and disparities found among countries regarding the macroeconomic indicators mostly impacting medical tourism, it seems that there is a consensus on their relationship but not clearly identified rather due to a variety of social, cultural and ethical factors that dominate in each country. Further research is needed in order to obtain more robust and comparative evidence.

Performance of Chinas Macroeconomic Indicators in a Regression Model-Based Sales Forecasting

The impact of macroeconomic indicators on sales forecasts is a topic worthy of corporate consideration in China. However, previous research on this topic is rarely based on the Chinese context and lacks discussion of specific industry scenarios. In this study, 5 macroeconomic indicators that the Chinese government and people are concerned about are selected and put into the regression model and the AIC model selection criterion to study their performance in sales forecasts of 4 industries in China. It is concluded that under Chinas national conditions, Disposable Income per Capita and National Fixed Asset Investment are two macroeconomic indicators that deserve attention and perform better than other indicators in sales forecasts, and they have hardly been mentioned in previous studies. At the same time, the most appropriate model for sales forecasting in each industry contains different combinations of macroeconomic indicators. It is believed that this result is valuable for companies in various industries, and will be inspiring for subsequent research in the field of sales forecasts.

Impact of macroeconomic indicators on Indian stock market

Impact of macroeconomic indicators on Indian stock market

The Impact of Macroeconomic Indicators on the Balance of Payments: Empirical Evidence from Afghanistan

This study aims to empirically investigate the impact of a set of macroeconomic variables including balance of trade, FDI, exchange rate, and inflation on the balance of payments (BOP) of Afghanistan using quarterly data from the second quarter of 2004 to the fourth quarter of 2020 (2004Q2 to 2020Q4). The paper uses the Vector Error Correction Model (VECM), and Johansen co-integration test for analysis to explore the BOP of Afghanistan and provides comparable literature to other least-developed and low-income developing countries. The findings reveal that balance of trade (BOT), foreign direct investment (FDI), and exchange rate are significant determinants of Afghanistan’s BOP in the long run. More specifically, BOT and FDI positively impact the BOP, whereas the effect of the exchange rate on the BOP is found negative. Yet, inflation has an insignificant impact on the BOP. Though all variables have an insignificant impact on the BOP in the short run, the relevant policy measures ought to consider improvement in BOT, promoting FDI, and exchange rate stability to ensure synchronized improved BOP and economic growth.

The Impact of Macroeconomic Indicators on the Share Prices of Dividend Companies – A Comparative Analysis of Polish and US Issuers for the Period 2016–2020

Abstract Research background: The aim of the article is to compare Polish and US dividend companies with potential growth with dividend companies with potential value, including in the period of economic turbulence caused by the pandemic, and to identify macroeconomic determinants that affect changes in the level of share prices of dividend companies with potential value listed on the stock exchange in Poland and the US. An analysis of the literature and international studies conducted allows us to identify inflation, gross domestic product (GDP), interest rate levels, exchange rate changes, and market P/E and P/BV ratios, as well as the PMI index, as the most important macroeconomic factors. Purpose: The aim of the article was to present research on the impact of macroeconomic indicators on the prices of Polish and US shares of dividend companies, divided into shares with potential value and potential growth for the period 2016–2020. The research was enriched by analyzing the return rate on shares and the risk of the share prices of companies with potential value during the turbulence of the economy caused by the COVID-19 pandemic. Research methodology: The study was conducted using the Spearman rank correlation coefficient and significance test for the Spearman rank correlation coefficient. A non-parametric t-test was carried out to check whether the estimated correlation is statistically significant. Results: The research indicates that Polish and US dividend companies with potential value have lower average annual return rates than dividend companies with potential growth. Referring to the determinants of the share prices of US dividend companies with potential value, it was found that they are significantly determined by inflation and moderately determined by industrial production and GDP, as well as the P/BV ratio. Novelty: The added and application value are the recommendations regarding the attractiveness of investing in Polish dividend companies with potential value as compared to companies from the US market.

ECONOMIC GROWTH AND TOTAL FACTOR PRODUCTIVITY IN CENTRAL AND EASTERN EUROPEAN COUNTRIES BETWEEN TWO GLOBAL CRISES AND BEYOND

The aim of the article is to assess the factors of economic growth of the CEE countries over the 30-year history, the productivity of capital and human resources, the resilience of these countries to the negative impact of the global financial crisis. Methodology. The Solow growth model was used to estimate the growth rates of capital, labor and total factor productivity (TFP). The impact of macroeconomic indicators on GDP and TFP growth is assessed. The group of Central and Eastern European countries that joined the European Union was chosen for the analysis: Bulgaria, Romania, Poland, Hungary, Czech Republic, Slovakia, Slovenia, Estonia, Lithuania, Latvia, as well as post-Soviet European countries: Ukraine, Belarus, Russia and Moldova and Albania in the period from 1991 to 2019. Results. TFP makes a significant contribution to the economic growth of CEE countries. During the period of market reforms, TFP significantly decreased, and during the boom of 2000-2008 it fully ensured the growth of the CEE economies, after the crisis of 2008, the contribution of TFP decreased by 2 times. In the conditions of recovery, TFP growth is positively influenced by inflation, negative CA balance, and unemployment reduction. In the post-crisis period, a decrease in inflation, a positive CA balance, and an increase in unemployment had a positive impact on TFP growth. During a depression, the influence of capital becomes dominant. Restrictive monetary policy contributes to the efficiency of CEE economies. In the short run, unemployment increases, but in the long run it decreases significantly due to the growth of investment and exports. Practical implications. The analysis makes it possible to identify effective macroeconomic policies to stimulate the productivity of the economies of Central and Eastern Europe during the period of economic recovery and depression. Value/originality. A long-term study of the economic performance of CEE countries using the Solow methodology has revealed the behavior of total factor productivity in different periods of modern economic history and its contribution to economic growth.

The Impact of Macroeconomic Indicators on Indonesia’s Foreign Exchange Reserve Position

A country’s foreign exchange reserves are its foreign currency savings that can be utilized to finance international transactions. The purpose of this study is to determine how macroeconomic indicators (exports, imports, exchange rates, inflation rates, and foreign debt) influence Indonesia’s foreign currency reserves. The researchers used secondary data in the form of monthly time series, as well as quantitative analysis using multiple linear regression. The model that was used was the Vector Error Correction Model (VECM). According to the research, future exports and external debt have a positive impact on Indonesia’s foreign exchange reserves. Indonesia’s foreign exchange reserves are negatively impacted by imports and predicted inflation rates, whereas the rupiah exchange rate has no effect. In the model, there is a short-run to long-run equilibrium relationship. The IRF results show that shocks from other independent variables have little effect on foreign exchange reserves and that the foreign exchange reserves variable contributes the most to the shocks that occur

METHODICAL TOOLS FOR INTEGRATED ASSESSMENT OF THE ECONOMIC SECURITY OF UKRAINE’S BANKS

Abstract. The article offers methodical tools for integrated assessment of the economic security of banks. It is based on 59 indicators and takes into account such components of security as resource, asset-forming (transformational), risk-forming, stabilization and functional, productive. The resource component of banks’ economic security reflects the sufficiency of their own, involved and borrowed financial resources for stable and efficient operation to make a profit and protect the interests of shareholders, depositors, and creditors. The asset-forming (transformational) component of economic security is one of the most important, as it represents not only the degree of use of the banking system’s potential in economic development but also the credit and investment direction of assets, their quality, the degree of problematicity, and the impact on the economic security of the banking sector. Assessing the impact of risk on economic security involves the use of the indicators of prudential banking supervision, namely basic economic standards and several coefficients that reflect the risk of active banking transactions. The stabilization and functional component of economic security shows the impact of macroeconomic indicators on the state of the monetary and credit market and inflation rate. Profit (loss) as a result of the functioning of the banking system is one of the key indicators of security and a necessary prerequisite for the implementation of development strategies. This approach allowed determining the level of the economic security of Ukrainian banks based on the calculated value of the integral indicator. The differentiation of the quantitative value of the indicator within the proposed values allows assessing the level of banks’ security as high, satisfactory, low, critical. The practical significance of this approach is that it allowed identifying risks, threats, and dangers to banks and defining the most significant of them. Keywords: banks, economic security of banks, integrated assessment, risks, threats, dangers. JEL Classification G 21, D 81 Formulas: 5; fig.: 1; tabl.: 0; bibl.: 11.

Impact of macroeconomic indicators on bankruptcy prediction models: Case of the Portuguese construction sector

<abstract> <p>The importance of macroeconomic indicators on the performance of bankruptcy prediction models has been a contentious issue, due in part to a lack of empirical evidence. Most indicators are primarily centered around a company's internal environment, overlooking the impact of the economic cycle on the status of the company. This research brings awareness about the combination of microeconomic and macroeconomic factors. To do this, a new model based on logistic regression was combined with principal component analysis to determine the indicators that best explained the variations in the dataset studied. The sample used comprised data from 1,832 Portuguese construction companies from 2009 to 2019. The empirical results demonstrated an average accuracy rate of 90% up until three years before the bankruptcy. The microeconomic indicators with statistical significance fell within the category of liquidity ratios, solvency and financial autonomy ratios. Regarding the macroeconomic indicators, the gross domestic product and birth rate of enterprises proved to increase the accuracy of bankruptcy prediction more than using only microeconomic factors. A practical implication of the results obtained is that construction companies, as well as investors, government agencies and banks, can use the suggested model as a decision-support system. Furthermore, consistent use can lead to an effective method of preventing bankruptcy by spotting early warning indicators.</p> </abstract>

Impact of Macroeconomic Indicators on the Yuan-SDR Exchange Rate

The paper endeavours to explore the macroeconomic impact on the Yuan SDR exchange rate of China during 2017m1-2021m6 to justify the internationalization of RMB which had entered into the SDR basket of IMF in October 2016.To evaluate the impact ,the paper used the methodology of Johansen (1988) cointegration and vector error correction model considering monthly Yuan per SDR as dependent variable and monthly GDP, inflation rate, foreign exchange reserves, export and import as the independent macro-economic variables. The pattern of trendline of Yuan per SDR is found nonlinear having cyclical fluctuations and seasonal variations according to Hamilton (2018). The paper also found that Yuan per SDR has significant long run causalities with export, import, inflation rate, GDP and foreign exchange rate of China during the specified period. Even, Yuan per SDR has significant short run causality with export only. The cointegrating equation converged towards the equilibrium with the speed of adjustment 11.83% per month significantly. The impulse response function of import to Yuan per SDR showed significantly convergent. The VECM contains autocorrelation problem and unit root for which it is non-stationary.

Determinants of stock market liquidity – a macroeconomic perspective

ABSTRACT This study examines the impact of macroeconomic indicators on the liquidity of the Indian stock market by using the Granger Causality, Vector Auto-Regressive Model, and Impulse Response Functions. Numerous macroeconomic indicators were analysed at monthly and quarterly frequencies for their effect on the liquidity of NIFTY 500 stocks measured across four facets, i.e. depth, breadth, immediacy, and tightness. The study reveals that the tightness facet of liquidity is primarily affected by the indicators and further concludes that higher foreign investment inflows and gold prices impair the aggregate liquidity. In contrast, a surge in money supply strengthens the stock market liquidity.

Impact of Macroeconomic Indicators on Mortgage Loans in the V4

Impact of Macroeconomic Indicators on Mortgage Loans in the V4

Quantitative parameters of anti-money laundering regulation

Subject. As financial institutions carry out a huge number of transactions, the financial sector definitely needs to automate some control procedures, including anti-money laundering ones. The effectiveness of automated control measures directly depends on how adequately tasks for the software are written. The article examines the impact of macroeconomic indicators, such as GDP per capita, average wage, and the scale of the shadow economy in the G20 countries and in two of the CIS countries (Belarus and Tajikistan) on thresholds of the fixed limit of transaction (FLT), which is regulated with the anti-money laundering legislation, including the fixed limit of cash transaction (FLCT). Objectives. I investigate approaches to setting FLT (FLCT) in different countries and formulate my opinion on this issue. Methods. The methodological basis of the study was made up of empirical and logical constructions, statistical analysis, synthesis, systems approach. Results. I identified why FLT (FLCT) are denied. This happens due to lawmakers’ confidence in the effectively controlled financial sector, or the corruption pressure. The countries with FLT (FLCT) introduce and use them formally. The article presents the risk-based approach to measuring the FLCT based on the macroeconomic indicators (average annual wages, savings per capita). Conclusions and Relevance. The case of Russia shows that the inflation undermines the barrier function of FLT (FLCT), while the analytical division of financial intelligence has to handle more issues. The proposed approach will help reduce costs the financial system incurs to process financial information in order to counter money laundering.

A study on the impact of macroeconomic indicators on the stock price by relaxing the assumptions of stationarity in time series data in a general linear model

A study on the impact of macroeconomic indicators on the stock price by relaxing the assumptions of stationarity in time series data in a general linear model

A study on the impact of macroeconomic indicators on the stock price by relaxing the assumptions of stationarity in time series data in a general linear model

A model has been evolved by keeping the stock index as dependable variable and gross domestic product, consumption and consumer price index as independent variables. The assumptions to arrive the model are tested. The behaviour of the model is studied by including and relaxing the important assumption of stationarity in the economic data. It was finally found that the model becomes significant if we violate the stationary assumption for both dependent variable stock price and independent variable consumer price index, consumption and gross domestic product. This is evidenced by demonstrating the model by using the data related to the macroeconomic variables of developed countries (USA, UK), emerging countries (India, Brazil), and frontier countries (Latvia, Estonia).

A Data Analysis Framework to Predict the Behavior of Macroeconomic Indicators of Countries

The impact of macroeconomic indicators on the economy of countries is difficult to establish correctly as the effects of these indicators are nonlinear and time variant. In this study, we have evol...

The Random Forest Method in Research of Impact of Macroeconomic Indicators of Regional Development on Informal Employment Rate

The topic of quantitative research on informal employment has a consistently high relevance both in the Russian Federation and in other countries due to its high dependence on cyclicality and crisis stages in economic dynamics of countries with any level of economic development. Developing effective government policy measures to overcome the negative impact of informal employment requires special attention in theoretical and applied research to assessing the factors and conditions of informal employment in the Russian Federation including at the regional level. Such effects of informal employment as a shortfall in taxes, potential losses in production efficiency, and negative social consequences are a concern for the authorities of the federal and regional levels. Development of quantitative indicators to determine the level of informal employment in the regions, taking into account their specifics in the general spatial and economic system of Russia are necessary to overcome these negative effects. The article proposes and tests methods for solving the problem of assessing the impact of hierarchical relationships on macroeconomic factors at the regional level of informal employment in constituent entities of the Russian Federation. Majority of the works on the study of informal employment are based on basic statistical methods of spatial-dynamic analysis, as well as on the now «traditional» methods of cluster and correlation-regression analysis. Without diminishing the merits of these methods, it should be noted that they are somewhat limited in identifying hidden structural connections and interdependencies in such a complex multidimensional phenomenon as informal employment. In order to substantiate the possibility of overcoming these limitations, the article proposes indicators of regional statistics that directly and indirectly characterize informal employment and also presents the possibilities of using the «random forest» method to identify groups of constituent entities of the Russian Federation that have similar macroeconomic factors of informal employment. The novelty of this method in terms of research objectives is that it allows one to assess the impact of macroeconomic indicators of regional development on the level of informal employment, taking into account the implicit, not predetermined by the initial hypotheses, hierarchical relationships of factor indicators. Based on the generalization of the studies presented in the literature, as well as the authors’ statistical calculations using Rosstat data, the authors came to the conclusion about the high importance of macroeconomic parameters of regional development and systemic relationships of macroeconomic indicators in substantiating the differentiation of the informal level across the constituent entities of the Russian Federation.

Trends and Development Factors of the Non-banking Financial Sector in Ukraine

The article describes the trends and factors of development of non-banking financial institutions in the Ukrainian economy. The authors analyze the current state and dynamics of the market development of the non-banking financial sectors on the basis of data on the number of financial institutions in the market, the volume of their assets, and the volume of services provided by them during 2013–2019. The article determines that the trend of decreasing or increasing the market participants is not generally traced, but it can be determined by individual types of institutions. In particular, financial institutions such as insurance companies, credit unions, pawnshops, and non-state pension funds had a declining trend in terms of the number, but the number of financial companies, on the contrary, increased. The article determines that most of the assets of the non-banking financial sector belong to financial companies, the second largest part of the sector is the insurance market, and institutions such as non-state pension funds, pawnshops and credit unions had small shares of the market assets during this period. With regard to services provided by non-banking financial institutions, it is determined that the main activity is attributable to financial companies and their services of “non-bank loans (micro loans)”, which occupies 51 % of the total market of services. The authors also describe the impact of macroeconomic indicators in Ukraine (GDP – gross domestic product, population income, public expenditure, inflation and unemployment) on trends and changes in the structure of non-bank financial intermediaries in the period of 2013–2019. JEL classіfіcatіon: G20-23, G29 Manuscript received 21.04.2020

Pakistan Stock Exchange and Macroeconomic Indicators A Case Study of KSE 100 Index

This study has found a relatively strong and consistent response of stock market returns to Pakistan’s macroeconomic indicators. It was observed that the variables that have been set were seen to be in a stationary motion. The economic model used, provided that there has been a strong relation that was occurring in between the variables that had been studied. As the movements in the KSE-100 index are a significant indicator of the Pakistan economy, this study particularly examine the impact of macroeconomic indicators on Karachi Stock Exchange-100 index. For analysis, yearly data from December 1991 to December 2017 was used in this specific study. The result reflects that there was a negative impact of internal and external debt, inflation, GDP, foreign direct investment on KSE-100 index, while, exchange rate and interest rate had a significant positive effect on the KSE-100 index. Moreover, money supply found out to be a variable which has no influence on KSE-100 index. The results of vector auto regression revealed that out of eight macroeconomic variables only money supply could be excluded in future research as it has no impact on KSE-100 index.