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As the COVID-19 pandemic came unexpectedly, many real estate experts claimed that the property values would fall like the 2007 crash. However, this study raises the question of what attributes of an apartment are most likely to influence a price revision during the pandemic. The findings in prior studies have lacked consensus, especially regarding the time-on-the-market variable, which exhibits an omnidirectional effect. However, with the rise of Big Data, this study used a web-scraping algorithm and collected a total of 18,992 property listings in the city of Vilnius during the first wave of the COVID-19 pandemic. Afterwards, 15 different machine learning models were applied to forecast apartment revisions, and the SHAP values for interpretability were used. The findings in this study coincide with the previous literature results, affirming that real estate is quite resilient to pandemics, as the price drops were not as dramatic as first believed. Out of the 15 different models tested, extreme gradient boosting was the most accurate, although the difference was negligible. The retrieved SHAP values conclude that the time-on-the-market variable was by far the most dominant and consistent variable for price revision forecasting. Additionally, the time-on-the-market variable exhibited an inverse U-shaped behaviour.
Andrius Grybauskas; Vaida Pilinkienė; Alina Stundžienė. Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic. Journal of Big Data 2021, 8, 1 .
AMA StyleAndrius Grybauskas, Vaida Pilinkienė, Alina Stundžienė. Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic. Journal of Big Data. 2021; 8 (1):1.
Chicago/Turabian StyleAndrius Grybauskas; Vaida Pilinkienė; Alina Stundžienė. 2021. "Predictive analytics using Big Data for the real estate market during the COVID-19 pandemic." Journal of Big Data 8, no. 1: 1.
Investments in pharmaceutical companies remain challenging due to the inherent uncertainties of risk assessment. Our paper aims to assess the impact of the drug development setbacks (DDS) on the stock price of pharmaceutical companies while taking into account the company’s financial situation, pipeline size and trend of the stock price before the DDS. The model-based clustering based on finite Gaussian mixture modeling was employed to identify the clusters of pharmaceutical companies with homogenous parameters. An artificial neural network was constructed to aid the prediction of the positive mean rate of return 120 days after the DDS. Our results reveal that a higher pipeline size and a lower rate of return before the DDS, as well as a lower ratio of the market value of the equity and the book value of the total liabilities, are associated with a positive mean rate of return 120 days after the DDS. In general, the DDS have a negative impact on the company’s stock price, but this risk can be minimized by investors choosing the companies that satisfy certain criteria. The higher pipeline size(spip) and lower rate of return before (srr) the drug development setback (DDS) and the Market Value of Equity/Book Value of Total Liabilities ratio (sx4) are associated with a positive mean rate of return 120 days after the DDS.
Silvijus Abramavičius; Alina Stundžienė; Laura Korsakova; Mantas Venslauskas; Edgaras Stankevičius. Stock price reaction to the drug development setbacks in the pharmaceutical industry. DARU Journal of Pharmaceutical Sciences 2021, 29, 1 -11.
AMA StyleSilvijus Abramavičius, Alina Stundžienė, Laura Korsakova, Mantas Venslauskas, Edgaras Stankevičius. Stock price reaction to the drug development setbacks in the pharmaceutical industry. DARU Journal of Pharmaceutical Sciences. 2021; 29 (1):1-11.
Chicago/Turabian StyleSilvijus Abramavičius; Alina Stundžienė; Laura Korsakova; Mantas Venslauskas; Edgaras Stankevičius. 2021. "Stock price reaction to the drug development setbacks in the pharmaceutical industry." DARU Journal of Pharmaceutical Sciences 29, no. 1: 1-11.
Nuestra investigación pretende revelar si existen diferencias entre los países de la zona euro y los de fuera de ella en cuanto al cumplimiento de algunas variables relevantes establecidas en los criterios de Maastricht (inflación, déficit y deuda pública). También examinamos las consecuencias del incumplimiento de uno o varios de estos criterios, incluyéndose el desempleo, relacionándolo con el rendimiento de los bonos a largo plazo de los países que se incorporaron a la moneda común con los que no lo hicieron. Los resultados muestran que, en términos generales, el incumplimiento ha sido más perjudicial en los países de la Eurozona, especialmente en términos de déficit y desempleo.
Alina Stundžiené; Antonio Mihi Ramirez; Margarita Navarro Pabsdorf. Flaws in the European Monetary Union. Does the EMU Need a Solution? Revista de Economía Mundial 2020, 1 .
AMA StyleAlina Stundžiené, Antonio Mihi Ramirez, Margarita Navarro Pabsdorf. Flaws in the European Monetary Union. Does the EMU Need a Solution? Revista de Economía Mundial. 2020; (55):1.
Chicago/Turabian StyleAlina Stundžiené; Antonio Mihi Ramirez; Margarita Navarro Pabsdorf. 2020. "Flaws in the European Monetary Union. Does the EMU Need a Solution?" Revista de Economía Mundial , no. 55: 1.
Labour productivity is one of the key drivers for higher earnings and welfare standards in every economy. The problem of how to ensure the growth of labour productivity is especially relevant to less developed economies and forces justification of the factors affecting sustainable productivity growth. The purpose of this research is to test if the investment in tangible assets improves labour productivity in the European manufacturing industry and to reveal the countries with inefficient investment. The results show that with consideration of all European countries, a 1% increase in gross investment in tangible goods (G.I.T.G.) per person employed (P.E.) has a 0.0373% long-run effect on apparent labour productivity (A.L.P.). Considering various types of investments in tangibles, only an increase in gross investment in existing buildings and structures (G.I.E.B.S.) per P.E. and gross investment in machinery and equipment (G.I.M.E.) per P.E. caused growth of A.L.P. However, the impact of investment in assets on A.L.P. significantly differs among the countries and it is revealed that many European countries, which are characterised by low productivity, use investment inefficiently.
Alina Stundziene; Asta Saboniene. Tangible investment and labour productivity: Evidence from European manufacturing. Economic Research-Ekonomska Istraživanja 2019, 32, 3519 -3537.
AMA StyleAlina Stundziene, Asta Saboniene. Tangible investment and labour productivity: Evidence from European manufacturing. Economic Research-Ekonomska Istraživanja. 2019; 32 (1):3519-3537.
Chicago/Turabian StyleAlina Stundziene; Asta Saboniene. 2019. "Tangible investment and labour productivity: Evidence from European manufacturing." Economic Research-Ekonomska Istraživanja 32, no. 1: 3519-3537.
Gražina Startienė; Daiva Dumčiuvienė; Alina Stundžienė; Andrius Januškevičius. An Impact of the Euro Adoption on the International Trade of New EMU Members: the Lithuanian Case. Entrepreneurial Business and Economics Review 2019, 7, 201 -215.
AMA StyleGražina Startienė, Daiva Dumčiuvienė, Alina Stundžienė, Andrius Januškevičius. An Impact of the Euro Adoption on the International Trade of New EMU Members: the Lithuanian Case. Entrepreneurial Business and Economics Review. 2019; 7 (1):201-215.
Chicago/Turabian StyleGražina Startienė; Daiva Dumčiuvienė; Alina Stundžienė; Andrius Januškevičius. 2019. "An Impact of the Euro Adoption on the International Trade of New EMU Members: the Lithuanian Case." Entrepreneurial Business and Economics Review 7, no. 1: 201-215.
Alina Stundziene. Ekonominės statistikos praktikumas su MS EXCEL. Ekonominės statistikos praktikumas su MS EXCEL 2018, 1 .
AMA StyleAlina Stundziene. Ekonominės statistikos praktikumas su MS EXCEL. Ekonominės statistikos praktikumas su MS EXCEL. 2018; ():1.
Chicago/Turabian StyleAlina Stundziene. 2018. "Ekonominės statistikos praktikumas su MS EXCEL." Ekonominės statistikos praktikumas su MS EXCEL , no. : 1.
Lithuania is one of the EU Member States, where the rate of energy consumption is comparatively low but consumption of electricity has been gradually increasing over the last few years. Despite this trend, households in only three EU Member States consume less electricity than Lithuanian households. The purpose of this research is to analyse the impact of socio-economic factors on the domestic electricity consumption in Lithuania, i.e., to establish whether electricity consumption is determined by socio-economic conditions or population’s awareness to save energy. Cointegration analysis, causality test and error-correction model were used for the analysis. The results reveal that there is a long run equilibrium relationship between residential electricity consumption per capita and GDP at current prices as well as the ratio of the registered unemployed to the working-age population. In consequence, the results of the research propose that improvement of living standards for Lithuanian community calls for the necessity to pay particular attention to the promotion of sustainable electricity consumption by providing consumers with appropriate information and feedback in order to seek new energy-related consumption practices.
Sergej Vojtovic; Alina Stundziene; Rima Kontautiene. The Impact of Socio-Economic Indicators on Sustainable Consumption of Domestic Electricity in Lithuania. Sustainability 2018, 10, 162 .
AMA StyleSergej Vojtovic, Alina Stundziene, Rima Kontautiene. The Impact of Socio-Economic Indicators on Sustainable Consumption of Domestic Electricity in Lithuania. Sustainability. 2018; 10 (2):162.
Chicago/Turabian StyleSergej Vojtovic; Alina Stundziene; Rima Kontautiene. 2018. "The Impact of Socio-Economic Indicators on Sustainable Consumption of Domestic Electricity in Lithuania." Sustainability 10, no. 2: 162.
Scientific literature is rich in the discussions about social and economic welfare. A number of studies on the relationship between subjective well-being and various economic and social indicators have been carried out over the last decade. Reliability and validity of survey-generated data are very important factors in this type of research as they determine credibility of the conclusions. The purpose of this research is to verify whether the data of surveys on population’s life satisfaction is valid. The object of this research is the index of Overall life satisfaction in the European Union announced by the Eurostat. As the index of Overall life satisfaction is available only for 2013, verification of data validity was complemented with the analysis of the index of population’s Satisfaction with financial situation, which strongly correlates with the index of Overall life satisfaction. This approach provided more opportunities to collate and compare the data of different surveys. Collation of the data generated by several interrelated surveys on population’s life satisfaction has disclosed some significant differences in final results. The results of the research lead to the conclusion that the sample data does not represent the real situation of population’s life satisfaction, and this trend is particularly evident in less developed European countries. As a consequence, the index of Overall life satisfaction cannot be considered a good measure for the research in human welfare, and the conclusions concerning the relationship between the indicator of life satisfaction and other relevant indicators cannot be treated as credible.
Alina Stundžienė. Human Welfare: Can We Trust What They Say? Journal of Happiness Studies 2018, 20, 579 -604.
AMA StyleAlina Stundžienė. Human Welfare: Can We Trust What They Say? Journal of Happiness Studies. 2018; 20 (2):579-604.
Chicago/Turabian StyleAlina Stundžienė. 2018. "Human Welfare: Can We Trust What They Say?" Journal of Happiness Studies 20, no. 2: 579-604.
Identification of leading indicators that precede economic events and predict the next phase of business cycle is undoubtedly important issue seeking to protect the country against the recession or other negative economic events. The paper analyses potential leading indicators and identifies the best predictors of the business cycles in Lithuania. Various economic, industrial, financial, real estate market indicators as well as consumer and business expectations are analysed in order to find which of them cause the changes in growth rate of GDP. The analysis is based on Granger causality test and autoregressive distributed lag model. The research shows that considered economic indicators are weak predictors of the growth rate of GDP. Volume index of intermediate goods production is the best predictor in the group of industry data as it holds predictive attributes even three years before the changes in economics. That can be also said about two financial indicators, i.e. short-term interest rate and the value of stock market index. Real estate market data such as residential buildings permits and growth rate in house price index can also warn about the changes in the growth rate of GDP two years before. Nevertheless, consumer and business expectations are the most important for prediction of the changes in the growth rate of GDP.DOI: http://dx.doi.org/10.5755/j01.ee.28.3.16705
Alina Stundziene; Vytautas Barkauskas; Vilda Gižienė. The Leading Indicators of the Economic Cycles in Lithuania. Engineering Economics 2017, 28, 280 - 289 .
AMA StyleAlina Stundziene, Vytautas Barkauskas, Vilda Gižienė. The Leading Indicators of the Economic Cycles in Lithuania. Engineering Economics. 2017; 28 (3):280 - 289.
Chicago/Turabian StyleAlina Stundziene; Vytautas Barkauskas; Vilda Gižienė. 2017. "The Leading Indicators of the Economic Cycles in Lithuania." Engineering Economics 28, no. 3: 280 - 289.
Alina Stundziene. Key Indicators for Improving the Resource Productivity in the Baltic States. BE-ci 2016 International Conference on Business and Economics 2016, 339 -354.
AMA StyleAlina Stundziene. Key Indicators for Improving the Resource Productivity in the Baltic States. BE-ci 2016 International Conference on Business and Economics. 2016; ():339-354.
Chicago/Turabian StyleAlina Stundziene. 2016. "Key Indicators for Improving the Resource Productivity in the Baltic States." BE-ci 2016 International Conference on Business and Economics , no. : 339-354.
Purpose of the article: The paper seeks to analyse the problematics of estimation of the social discount rate (SDR). The SDR is the critical parameter of cost-benefit analysis, which allows calculating the present value of cost and the benefit of public sector investment projects. Incorrect choice of the SDR can lead to the realisation of ineffective public project or conversely, cost-effective project will be rejected. The relevance of this problem analysis is determined by discussions and different viewpoints of scientists on the choice of the most appropriate approach to determine the SDR and absence of methodically based the SDR on the national level of Lithuania. Methodology/methods: The research is performed by the scientific and methodical literature analysis, systematization, time series and regression analysis. Scientific aim: The aim of the article is to calculate the SDR based on the statistical data of Lithuania. Findings: The analysis of methods of SDR determination, as well as the researches performed by foreign researchers, allows stating that the social rate of time preference (SRTP) approach is the most appropriate. The SDR, calculated by the SRTP approach, reflects the main purpose of public investment projects, i.e. to enhance social benefit for society, the best. The analyses of SDR determination practice of the foreign countries shows that the SDR level should not be universal for all states. Each country should calculate the SDR based on its own data and apply it for the assessment of public projects. Conclusions: The calculated SDR for Lithuania using the SRTP approach varies between 3.5 % and 4.3 %. Although it is lower than 5 % that is offered by European Commission, this rate is based on the statistical data of Lithuania and should be used for the assessment of the national public projects. Application of the reasonable SDR let get the more accurate and reliable cost-benefit analysis of the public projects.
Vilma Kazlauskiene; Alina Stundziene. Estimation of social discount rate for Lithuania. Trends Economics and Management 2016, 10, 39 .
AMA StyleVilma Kazlauskiene, Alina Stundziene. Estimation of social discount rate for Lithuania. Trends Economics and Management. 2016; 10 (26):39.
Chicago/Turabian StyleVilma Kazlauskiene; Alina Stundziene. 2016. "Estimation of social discount rate for Lithuania." Trends Economics and Management 10, no. 26: 39.
Economic and social cohesion is one of the economic objectives of the European Union’s (EU). Therefore it is important to analyse the impact of the European Union's policies on the cohesion. The establishment of the common market itself did not offer a solution for the economic problems faced by the member states. The EU structural funds should seek to promote equality between the levels of development and employment. Economic and social cohesion is very important to strengthen political and economic development of EU Member States. The cohesion policy provides the possibility to finance the various activities in order to promote economic growth in the EU Member States and their regions. The convergence, the regional competitiveness and the employment and the European territorial cooperation are three main objectives of the current EU cohesion. The cohesion policy can be an effective tool to achieve the economic convergence. The EU investments are intended to create the sustainable high-quality jobs in order to combat the unemployment and boost the growth by supporting innovation, the low-carbon economy as well as the education and training in both cities and rural areas. In summary, the funds should lead to economic growth. This article includes the analysis of impact of structural support on the economic growth of the EU and optimization of distribution. The research methods used in the article include literature and statistical data analysis, correlation analysis. The analysis showed that correlation between main economic indicators and the funds is not significant and it can show the insufficient use of the support.DOI: http://dx.doi.org/10.5755/j01.ee.26.5.8831
Grazina Startiene; Daiva Dumčiuvienė; Alina Stundžienė. Relationship between Structural Funds and Economic Indicators of the European Union. Engineering Economics 2015, 26, 507-516 .
AMA StyleGrazina Startiene, Daiva Dumčiuvienė, Alina Stundžienė. Relationship between Structural Funds and Economic Indicators of the European Union. Engineering Economics. 2015; 26 (5):507-516.
Chicago/Turabian StyleGrazina Startiene; Daiva Dumčiuvienė; Alina Stundžienė. 2015. "Relationship between Structural Funds and Economic Indicators of the European Union." Engineering Economics 26, no. 5: 507-516.
The data of business and consumer surveys are often used for the prediction of the future changes of economics. But doubts that survey data are suitable for such prediction also exist. The objective of this research is to test how the survey data on new orders corresponds to the real data of industrial new orders. An incentive to make such the research arises after the decision of European Commission to stop the collection of data on industrial new orders. The research showed that the survey data on new orders weakly represents the real data of new orders. Moreover, the survey data on new orders is not an appropriate measure for prediction of the future industrial production. It means that lots of managers participate in the survey irresponsible and don’t show the real situation or the questions that they must answer are not very clear for them.
Alina Stundžienė; Grazina Startiene; Rita Remeikienė; Mindaugas Dapkus. Does the Survey Data on New Orders Lie? Procedia - Social and Behavioral Sciences 2015, 213, 5 -11.
AMA StyleAlina Stundžienė, Grazina Startiene, Rita Remeikienė, Mindaugas Dapkus. Does the Survey Data on New Orders Lie? Procedia - Social and Behavioral Sciences. 2015; 213 ():5-11.
Chicago/Turabian StyleAlina Stundžienė; Grazina Startiene; Rita Remeikienė; Mindaugas Dapkus. 2015. "Does the Survey Data on New Orders Lie?" Procedia - Social and Behavioral Sciences 213, no. : 5-11.
Daiva Dumčiuvienė; Alina Stundziene. The efciency of structural support and impact on economic and social indicators. Technological and Economic Development of Economy 2015, 21, 660 -675.
AMA StyleDaiva Dumčiuvienė, Alina Stundziene. The efciency of structural support and impact on economic and social indicators. Technological and Economic Development of Economy. 2015; 21 (4):660-675.
Chicago/Turabian StyleDaiva Dumčiuvienė; Alina Stundziene. 2015. "The efciency of structural support and impact on economic and social indicators." Technological and Economic Development of Economy 21, no. 4: 660-675.
There are several institutions that constantly announce their predictions of general domestic product (GDP) and lots of institutions that use this information. Frequently the forecasts of different institutions vary because they use different methods, but all the institutions for which this indicator is relevant cannot make the predictions themselves because the models are too sophisticated. The main purpose of this research is to create simple enough but also accurate model for prediction of Lithuanian GDP that can be used by all the institutions that need this indicator. The research is based on the economic data that are measured and published quarterly or monthly by Statistics Lithuania. 154 economic indicators were analysed as possible independent variables for regression model creation. The analysis showed that the regression model with twelve lag independent variables can be quite accurate for a short-term prediction of Lithuanian GDP. It can be forecasted by such indexes as the number of immigrants, the turnover of wholesale and retail trade and repair of motor vehicles and motorcycles, the number of overnight stays in the accommodation establishments, an average hourly earnings, the rate of change in the producer prices of all the industry (except construction) of Lithuanian market, the imports and seasonally adjusted imports, the seasonally adjusted exports, the projected number of employees in the trade enterprises for the next 2–3 months, the industrial production (of all the industry except construction).DOI: http://dx.doi.org/10.5755/j01.ee.26.2.7003
Alina Stundziene. PREDICTION OF GDP BASED ON THE LAG ECONOMIC INDICATORS. Engineering Economics 2015, 26, 188-195 .
AMA StyleAlina Stundziene. PREDICTION OF GDP BASED ON THE LAG ECONOMIC INDICATORS. Engineering Economics. 2015; 26 (2):188-195.
Chicago/Turabian StyleAlina Stundziene. 2015. "PREDICTION OF GDP BASED ON THE LAG ECONOMIC INDICATORS." Engineering Economics 26, no. 2: 188-195.
Mindaugas Dapkus; Alina Stundžienė. Identification of lying in the case of Germany industrial sector: improvement of the method. Applied Economics: Systematic Research 2015, 9, 129 -140.
AMA StyleMindaugas Dapkus, Alina Stundžienė. Identification of lying in the case of Germany industrial sector: improvement of the method. Applied Economics: Systematic Research. 2015; 9 (2):129-140.
Chicago/Turabian StyleMindaugas Dapkus; Alina Stundžienė. 2015. "Identification of lying in the case of Germany industrial sector: improvement of the method." Applied Economics: Systematic Research 9, no. 2: 129-140.
Rita Remeikienė; Grazina Startiene; Alina Stundžienė. The Identification of the Impact of Bidirectional Self-employment Factors on Self-employment Start-up and Duration: Latvian Case. Procedia - Social and Behavioral Sciences 2014, 156, 268 -273.
AMA StyleRita Remeikienė, Grazina Startiene, Alina Stundžienė. The Identification of the Impact of Bidirectional Self-employment Factors on Self-employment Start-up and Duration: Latvian Case. Procedia - Social and Behavioral Sciences. 2014; 156 ():268-273.
Chicago/Turabian StyleRita Remeikienė; Grazina Startiene; Alina Stundžienė. 2014. "The Identification of the Impact of Bidirectional Self-employment Factors on Self-employment Start-up and Duration: Latvian Case." Procedia - Social and Behavioral Sciences 156, no. : 268-273.
The problem of Lithuanian GDP prediction is relevant. There are several institutions, such as Statistics Lithuania, state’s central bank, other banks that constantly announce their predictions of GDP. Frequently the forecasts of different institutions vary because they use different methods. The main purpose of the paper is to investigate whether regression models made of the monthly published economic indicators or time series models are better for Lithuanian GDP prediction.The changes of Lithuanian GDP as well as many other economic indicators that have impact on GDP are published quarterly. Prediction of quarterly economic indicators as it was done by the most researchers can be related to greater errors comparing with the prediction models that are made according to the monthly data. Monthly data can ensure that the newest information is used for prediction of GDP and show how the state’s economy is changing in the current quarter, that’s why it can reduce the error of prediction.The research is based on the economic data that is measured and published monthly by Statistics Lithuania (154 ratios at all). Various linear and non-linear regression models are made in order to find the best model for Lithuanian GDP prediction. The results of regression models are also compared with the results got by ARIMA (time series) models. The analysis showed that the regression models made of monthly published economic indicators may be better than time series models for prediction or Lithuanian GDP.DOI: http://dx.doi.org/10.5755/j01.em.18.4.5041
Alina Stundziene. PREDICTION OF LITHUANIAN GDP: ARE REGRESSION MODELS OR TIME SERIES MODELS BETTER? ECONOMICS AND MANAGEMENT 2014, 18, 721-734 .
AMA StyleAlina Stundziene. PREDICTION OF LITHUANIAN GDP: ARE REGRESSION MODELS OR TIME SERIES MODELS BETTER? ECONOMICS AND MANAGEMENT. 2014; 18 (4):721-734.
Chicago/Turabian StyleAlina Stundziene. 2014. "PREDICTION OF LITHUANIAN GDP: ARE REGRESSION MODELS OR TIME SERIES MODELS BETTER?" ECONOMICS AND MANAGEMENT 18, no. 4: 721-734.
Ingrida Balaboniene; Rūta Bliekienė; Alina Stundžienė. Ekonometrija. Praktinis regresijos ir laiko eilučių modelių taikymas. Ekonometrija. Praktinis regresijos ir laiko eilučių modelių taikymas 2013, 1 .
AMA StyleIngrida Balaboniene, Rūta Bliekienė, Alina Stundžienė. Ekonometrija. Praktinis regresijos ir laiko eilučių modelių taikymas. Ekonometrija. Praktinis regresijos ir laiko eilučių modelių taikymas. 2013; ():1.
Chicago/Turabian StyleIngrida Balaboniene; Rūta Bliekienė; Alina Stundžienė. 2013. "Ekonometrija. Praktinis regresijos ir laiko eilučių modelių taikymas." Ekonometrija. Praktinis regresijos ir laiko eilučių modelių taikymas , no. : 1.
The influence of economic environment on companies and their activity results are investigated in this article. The analysis of Lithuanian and foreign literature showed that impact of the changes of economic situation on company results has been very poorly explored. The company bankruptcy valuation question is more popular among researchers, but we think, that the tasks to identify the circumstances that warn about the changes of company results in advance, to adapt the company to new business conditions and to block the way to bankruptcy are more important. The aim of this article is to define how the changes of economic situation in the state influence the results of Lithuanian companies and their bankruptcy risk. The general data that include all sectors and all companies in this country are used in this research. The correlation analysis and regression analysis are used in order to establish the relation between company results and the changes in economic situation that are reflected by the changes of general domestic product (GDP). The investigation of the relationship between companies’ results and the changes of GDP showed that the number of companies and the number of bankruptcies in the state are directly dependent on the changes of GDP in a year. The authors showed that there is strong linear dependence between the changes of GDP and the main financial ratios of the company: the changes in sales, changes in gross profit and various profitability ratios. The results showed that changes of GDP influence Z value of Altman model that reflect the bankruptcy risk of the companies. The influence of economic environment on companies and their activity results are investigated in this article. The analysis of Lithuanian and foreign literature showed that impact of the changes of economic situation on company results has been very poorly explored. The company bankruptcy valuation question is more popular among researchers, but we think, that the tasks to identify the circumstances that warn about the changes of company results in advance, to adapt the company to new business conditions and to block the way to bankruptcy are more important. The aim of this article is to define how the changes of economic situation in the state influence the results of Lithuanian companies and their bankruptcy risk. The general data that include all sectors and all companies in this country are used in this research. The correlation analysis and regression analysis are used in order to establish the relation between company results and the changes in economic situation that are reflected by the changes of general domestic product (GDP). The investigation of the relationship between companies’ results and the changes of GDP showed that the number of companies and the number of bankruptcies in the state are directly dependent on the changes of GDP in a year. The authors showed that there is strong linear dependence between the changes of GDP and the main financial ratios of the company: the changes in sales, changes in gross profit and various profitability ratios. The results showed that changes of GDP influence Z value of Altman model that reflect the bankruptcy risk of the companies.
Alina Stundžienė; Rūta Bliekienė. Ekonomikos svyravimų įtaka įmonių veiklos rezultatams. Business: Theory and Practice 2012, 13, 5 -17.
AMA StyleAlina Stundžienė, Rūta Bliekienė. Ekonomikos svyravimų įtaka įmonių veiklos rezultatams. Business: Theory and Practice. 2012; 13 (1):5-17.
Chicago/Turabian StyleAlina Stundžienė; Rūta Bliekienė. 2012. "Ekonomikos svyravimų įtaka įmonių veiklos rezultatams." Business: Theory and Practice 13, no. 1: 5-17.