ESTABLISHING A SET of mAcroEcoNomIc fAcTorS EXPLAINING vArIATIoN ovEr TImE of PErformANcE IN BuSINESS SEcTorS

With increasing competitiveness of companies and business sectors in the domestic markets of Lithuania, economic units are frequently confronted with the lack of methods for more detailed analysis of external factors explaining the variation over time of corporate financial indicators. The analysis or forecasting of financial indicators is usually linked with the development of a stock market or undertaken to estimate the probability of bankruptcy. However, there is a lack of studies aimed at identifying links between macroeconomic factors and financial performance indicators and explaining their variation over time. To serve that purpose, the factors of the macroeconomic environment that are most significant for certain economic activities have been identified and analysed to enable explaining the variation over time patterns of corporate financial indicators. The analysis covers economic performance, i.e. financial performance indicators and their links with macroeconomic factors, in 89 business sectors of Lithuania at a three-digit level of NACE 2 ed. The findings of the research indicate that the unemployment level in the country, the volume of export and import and the GDP are the most important macroeconomic factors that can be used to forecast different profitability, financial leverage, liquidity and other financial performance indicators of individual business sectors or companies. The research has not unfolded any significant differences between business sectors therefore the above factors are considered generic macroeconomic factors enabling to explain financial performance indicators of the 89 business sectors. Hence, special attention has to be paid to identifying and analysing specific factors and assessing the causal link. When established, the set of such factors provides a framework for building of a model to forecast business sector financial indicators.


Introduction
In Lithuania, the financial indicators approach is often used to forecast probability of bankruptcy of Lithuanian companies. As a rule, models of discriminant analysis, which are more suitable than regression analysis, are applied. In addition to the above forecasting models intended for assessment of companies' situation, it is recommended to apply additional approaches based on the assessment of absolute and relative financial indicators. The analysis of companies' competitiveness also often lacks more detailed factors of external environment, explaining variation over (companies or business sectors) were lacking. Therefore, it is appropriate to identify and examine an exhaustive set of individual external environment factors that are most signi ficant to specific economic activities, as a research object. The purpose of this study is, hence, to identify and analyse individual external environment factors most important for specific economic activities that would allow explaining the variation over time of corporate financial indicators. The analysis performed for the purpose of the pursued objective is based on official public statistics. Correlationregression analysis methods are also applied.

Overview of the theory concerning appraisal of an economic unit's performance
The modern business environment is defined by competiti veness. Companies find it increasingly important to analyse their financial positions and appraise their performance with a view to assessing their market shares and future de velopment prospects. (Martišius, A. S., Martišius, M. 2008).
The analysis of academic literature shows that financial statements by companies reflect their current situation with a 70−80% reliability and can be used to analyse their perfor mance (Janovič 2012). To make proper use of the informa tion disclosed in the financial statements, financial perfor mance indicators of the companies should be analysed and the factors that affect their variation over time should be identified. In Lithuania, these issues have been discussed by Bagdžiūnienė (2005), Juozaitienė (2000), Lazauskas (2005) and Mackevičius (2005Mackevičius ( , 2010. Gökçehan Demirhan and Anwar (2014) emphasise that in the framework of as sessment of the factors affecting business performance the analysis of both internal and external factors is relevant.
I. Arbidane and J. Volkova (2012) concluded that rese archers tend to focus on the analysis of internal and exter nal factors when examining management processes in the companies. To assess a company's performance indicators (including financial performance indicators) specific factors of macroeconomic environment that influence the company must be identified (Franceschini et al. 2014). Given the in creasing influence of external factors on companies' perfor mance, the approaches commonly used are PEST or SWOT analyses which reveal external factorsrelated opportunities and threats (Auškalnytė, Ginevičius 2001). R. Beker (2012) states that in the recent years, in Lithuania much attention has been paid to the analysis of business profitability of the companies, while comprehensive studies covering external factors and their impact on the companies' performance (e.g. profitability) are often lacking.
According to K. N. Gourdin (2006), the external envi ronment of a company can be analysed in two aspects: in terms of business sector wherein the company is com peting, or in terms of macroeconomic environment. The external environment of the business sector where in the company is operating usually combines such elements as competitors, clients and suppliers. While the macroecono mic environment embraces more elements, i.e. economic, social, demographic, political, legal and technological fac tors. For a company to be able to successfully implement the envisaged strategy and to compete on the market, it is import that it examines the macroeconomic environment specifically focusing on the economic aspect. According to J. Mackevičius (2010), such economic factors are among the most important elements exerting much impact on a business sector or a specific company. However, business performance appraisal methods, including methods for assessing of the probability of bankruptcy, are limited to the sole analysis of a company's financial position, often neglecting influence of the environment (Stundžienė, Bliekienė 2012).
Financial performance indicators are among the most important measures of a company's business success (Katja 2009). They constitute a very important analytic financial tool enabling managers to derive critical insights with re gard to the cost structure, the opportunities to increase the capital and the available reserves, as well as the efficiency of the assets. Comparison of the financial performance indica tors among companies operating in the same business sector or with the sector's median ratios allows justifying strengths and weaknesses of a company as part of a SWOT analysis and different aspects of the company's performance (Joy 2008). The analysis of financial indicators also helps to assess liquidity, business profitability and solvency contributing to a company's managementrelated decisions (Periasamy 2005).
In Lithuania, the analysis of financial performance indicators is usually undertaken with a view to assessing probability of bankruptcy, however, the increasing intensity of developments in the business sector and its environment also raise quite many challenges (Ginevičius, Čirba 2009). To this end, examining of the links between the financial performance indicators and the external factors is relevant. The examining of the links between the financial perfor mance indicators and the external factors provide insights on the elements likely to influence certain business sector. For instance, there was much debate on what mistakes had been made and what led to the adverse situation on the real estate sector in 2008-2009, therefore analysing of the development of macroeconomic and financial indications has gained importance (Misiūnas 2011). Hence, it is ultima tely important to identify the external factors determining competitiveness of a company or an industry and to filter a set of the available data and indicators to be appraised (Liučvaitienė, Paleckis 2011).
Once established, the relationship between the financial performance indicators of a business sector and the external factors influencing them allow to draw prospects for the development of business sectors and forecast the expected level of the future financial indicators. Bruner et al. (2012) states that a valid forecast of financial indicators has to be based on the assessment of the external environment of a business sector. Since business development correlates with the economic indicators of a country's level, information about the external factors (including economic ones) has to be taken into account to determine business development prospects. In addition to that, any changes of the external factors have either positive or negative implications on more than one, if not tens of companies operating in the same business sector (Wei, Zhang 2008).
The above leads to the need to identify those macroe conomic factors that are linked with financial performance indicators. Hence, it is appropriate to examine an exhaustive set of individual factors of the external environment that are most important to a specific economic activity by applying correlationregression analysis methods.

Methodology to analyse the relationship between the macroeconomic factors and the financial indicators of business sectors
In the framework of the researches, to ensure precision of economic and financial results special attention must be paid to the quality of the input data and information (Dzikevičius et al. 2011). To this end, only publically avai lable and validated statistical data has been compiled, grou ped and analysed.
In the first phase of the research, the set of the business sectors to be analysed has been established. Public statistics reflecting economic efficiency, i.e. financial performance indicators of business sectors, is available for a total of 223 business sectors (3digit level of NACE 2 ed.). The research deals only with the business sectors wherein financial in dicators were consistently disclosed and are available for at least five years over the 2004-2014 period, inclusively. The analysis of publically available data has produced a set of 89 business sectors to be studied.
The second phase of the research concerns building of a set of the macroeconomic factors to be analysed. These factors influence activities of an economic unit and deter mine its financial outputs (Chiaroni et al. 2010), therefore it is important to know these factors in advance, estima te their development and adapt to the resulting evolution (Arnold, Staffelbach 2012). The selection of the macroeco nomic factors has been based on the review of publically available data. Statistics Lithuania (2015) publishes lists of the macroeconomic factors that are likely to influence indi vidual business sectors. The selection includes such factors as the GDP, the gross value added, the inflation, the import, the export, the unemployment level in the country and the average wage (net of taxes).
These factors have been selected on the basis of macro economic reviews published by different banks (SEB, Swedbank, etc.) in the recent years.
The third phase of the research deals with drawing of a list of the financial indictors. The financial performance in dicators have been chosen through an extensive analysis of the academic literature. It is recommended that the analysis should be structured around the main groups of financial indicators, i.e. the profitability, the efficiency of the activi ties, the financial stability, the liquidity and other indica tors (Bivainis, Garškaitė 2010). It is appropriate to compare these indicators with the values of other companies or a business sector as a whole as published in statistic releases (Mackevičius, Poškaitė 1998;Bernstein 2000;Buškevičiūtė, Mačerinskienė 2004;Mackevičius 2007).
Some researchers often recommend assessing only the key financial indicators as part of financial performance analysis (Karalevičienė, Bužinskienė 2012;Buškevičiūtė, Mačerinskienė 2004Mackevičius, Valkauskas 2010). However, the most important financial indicators differ depending on a sector. Therefore with a view to identifying the macroeconomic factors that can spe cify the variation over time of a set of financial indicators, 20 indicators have been analysed, their statistical values being provided by Statistics Lithuania (Table 1). For reasons of expediency, these were grouped into four categories: profi tability, financial leverage, liquidity and other, following the OMX Nasdaq (NASDAQ OMX 2010) classification. Given that not all the business sectors have their fi nancial indicators and macroeconomic factors consistent ly disclosed for the 2004-2014 period, the data covering 2008-2012 has been studied for the research purposes.
To establish the relationship between the macroecono mic factors and the financial indicators correlationregres sion analysis has been applied. Correlation is defined as a parameter of certain stochastic processes applied in model ling as a measure of movement of two variables (Alexander 2001). Correlation coefficient is calculated in accordance with formula 1: (1) where: x -j th macroeconomic factor; y -i th financial indi cators of the business sector. The analysis of the set of external environment factors specifying variation over time of financial indicators follows the assumption that a correlation coefficient falling within the interval: − |0.00-0.24| defines correlation of a very weak form; − |0.25-0.49| defines correlation of a weak form; − |0.50-0.74| defines moderate correlation; − |0.75-0.90| defines correlation of a strong form; − |0.90-1.00| defines strong correlation.
To eliminate the links which define weak or moderate correlation between the macroeconomic factors and the fi nancial performance indicators of different business sectors, the r values below |0.75| are filtered out and further analysis focuses on the r values defining strong correlation between the macroeconomic factors and the financial performance indicators of business sectors. Quite often, the relationship between the financial indicators of the same business sector and the macroeconomic factors might be based on a few links. Therefore two pairs of values with the strongest cor relation have been filtered.
To establish whether there exists a linear dependence between the selected values, a hypothesis has been formu lated and a Tstatistics test has been performed, where the significance level a = 0.05. To verify this hypothesis, we have applied a statistic hypothesis of a zero correlation co efficient: where: = 0 : 0 H r -zero hypothesis; ≠ 1 : 0 H r -alternative to a zero hypothesis.
Tstatistics of the criterion is calculated by applying formula 7: A hypothesis is accepted, when t a/2 (n-2) (Student's dis tribution with (n-2) degrees of freedom critical value at a/2 level) is larger than |T |. Then it is concluded that there exists a linear dependence between certain macroeconomic factor and certain a financial indicator of a business sector's performance.

Description of the findings from the research
The calculated correlation between the profitability indi cators of business sectors and the selected macroeconomic factors has led to a conclusion that the specified indicators most often correlate with the unemployment level, the vo lume of export and import and the GDP ( Table 2).
The majority of the profitability indicators have stron gest correlation with the volume of import, when the gross profitability indicator, reflecting the ability of an economic unit to generate profit from the core activity of the company, to control sales income and sales costs, correlate with the unemployment level in the country.
The analysis of the correlation between the financial le verage indicators and the macroeconomic factors has led to a conclusion that the unemployment level is probably the most important factors affecting debt ratio (longterm and shortterm) and gross solvency ratios, as well as debt to equity ratio (Table 3).
The inflation rates in the country, in turn, in many cases correlate with the financial dependency ratio of business sectors, enabling assessment of an economic unit's depen dency upon external sources of funding, and with the ma noeuvrability coefficient, defined as a shortterm asset to equity ratio.
The correlation analysis of the current liquidity and macroeconomic factors has revealed that the unemployment Net profitability, % Import (28.46%), export (20.77%) and GDP (15.38%).
Costefficiency of the activity, % Import (22.76%), export (22.07%) and inflation (15.17%). level, export and import in 55.86% of cases correlate with the given financial indicator (Fig. 1). Correlation of the above macroeconomic factors is strongest with the ratio reflecting the extent to which short term assets cover shortterm liabilities of an economic unit. In other words, the unemployment level of the country, the volume of export and the rate of inflation define the capacity of a business sector to discharge shortterm liabilities by using available shortterm assets within one year.
While the critical liquidity ratio which is deemed to be slightly more stringent than the current liquidity ratio because it does not involve estimation of reserves, correlates Fig. 1 with the import, the unemployment level and the export (Fig. 2).
As part of assessment of the set of macroeconomic fac tors correlating with the critical liquidity ratio, it should be remembered that in some business sectors, the settlement of accounts between the buyers and the economic units is typically short or creditworthiness is typically high. It is therefore necessary to identify additional variables that can potentially influence the critical liquidity ratio of an economic unit or a business sector as a whole.
The research has concluded that the net working capital ratio indicating the proportion of the assets falling on the funds earmarked for circulation correlates with the unem ployment level (20.48%), the volume of import (15.66%) and the rate of inflation in the country (15.66%) (Fig. 3).
Once it has been established which macroeconomic factors correlate with the profitability, financial leverage, liquidity and other indicators, it has been assessed whether there exists linear dependency between these, i.e. a regres sion analysis has been performed. The Tstatistics test has led to a finding that although the variables are correlated, the links between the macroeconomic factors and the financial performance indicators of business sectors are not always these of linear dependency.
Hence, based on the findings of the correlationregres sion analysis, the final list of the macroeconomic indicators was drawn, as provided in Table 4. Comparison of the results from the correlation and correlationregression analysis shows that with correlation analysis only, the inflation rates have bigger weight in the research as to what macroeconomic factors influence varia tion over time of the financial indicators. While the results of regression analysis indicate that this macroeconomic factor often can not be used to measure variation over time of business sectors' financial indicators. The unemployment level in the country, the volumes of export and import and the GDP are probably the most important macroeconomic factors that can be applied with a view to forecasting diffe rent financial performance indicators of individual business sectors or companies in terms of profitability, financial le verage and other aspects.
Since the research has not revealed any significant diffe rences between business sectors, the below listed factors can be defined as generic macroeconomic factors enabling to define financial performance indicators of 89 business sectors: − import; − export; − unemployment level in the country; − GDP. Therefore it is necessary to focus on the identification and analysis of the specific factors and the establishment of the causal links. When established, the set of such factors provides a framework for building of a model to forecast financial indicators of business sectors.

Conclusions and recommendations
Financial performance indicators are among the most im portant indicators defining business success of an economic unit (a company or a business sector). Since financial state ments reflect the current situation, they can be applied to analyse economic activities with a view to estimating future financial prospects of an economic unit. The analysis of the financial performance is considered an important analytic tool providing significant insights into the cost structure, possibilities to increase capital and the available reserves and the effectiveness of the assets.
In Lithuania, financial performance indicators are usu ally analysed to assess probability of bankruptcy of an eco nomic unit, however emerging of one or another crisis and efforts to identify what errors had been made and what led to an adverse situation, cause significant amount of debates, therefore analysis into the development of macroeconomic and financial indicators is becoming particularly relevant.
A research of macroeconomic factors explaining va riation over time of corporate financial indicators taking into consideration the specific characteristics of a particular business sector has to be performed in stages. First of all, the macroeconomic factors that correlate with the financial performance indicators of an economic unit are identified. Once the factors with the strongest correlation links are es tablished, a research has to be performed to confirm depen dency of the variables (for instance, to determine the exis tence of a linear dependency Tstatistics test is applied), i.e. a regression analysis is performed. Where it is established that there is no dependency between certain macroecono mic factors, these have to eliminated from further research to ensure higher precision of the results. In addition to the correlation analysis, a regression analysis is hence needed. As indicated by the present research, the unemployment level in the country, the export and import and the GDP are the most important macroeconomic factors that can be used to forecast the financial performance indicators of different business sectors or individual companies in terms of profi tability, financial leverage, liquidity and other aspects. The above factors can be considered generic macroeconomic factors, as the researches have not pointed to any significant differences between different business sectors.
The results achieved by the present research provide all the grounds for a new study to identify the external envi ronment factors typical to each business sector. Once cor relating and statistically significant indicators are selected (for this purpose, ANOVA model is to be built) these can be integrated into a generic model enabling to define variation over time of financial performance indicators of a specific business sector.