Financial Factors Explaining Value Migration: Evidence from Central Europe

Value creation is widely recognised as the main purpose of a company's actions. The growth of the company's value can be realized through several different strategies, but all of them involve the need to compete with other market players. As a result, winners capture value from other companies. Hence, it is important to recognize financial factors that may determine the value inflow or outflow in the market. Such value drivers are defined as economic variables that are crucial to company performance. Previous studies, mostly from the management area, mention a variety of financial value drivers. However, their impact on value migration has not been widely explored in empirical studies, especially from the financial perspective. There is also a need to examine whether and in what direction value migration has occurred.

This research focuses on the largest industries in Central Europe before and during the pandemic period. These sectors are supposed to have a comparative advantage during market turbulence. Many companies suffered from the crisis, however, including the most prominent examples of market participants. The number of companies in the largest sectors allows for a more detailed analysis. Based on a literature review, the research provides what had been a missing link in the empirical studies and answers the following questions:

What has been the extent of value migration in the largest industries in Central Europe before and during the pandemic crisis?

These questions allow for the development of research hypotheses, which are detailed in the existing literature provided in the next section. The main objective of this research is to identify the relationship between financial factors and value migration on a yearly basis. The sample includes nonfinancial companies listed on Central European stock markets, as Europe has been severely affected by the COVID-19 pandemic. The main contribution comes from the fact that we explore the migration of company value between industries. This is important because it allows us to assess the inflow and outflow of value during a pandemic. A comparison of value migration processes can be relevant from the perspective of managers, investors, and public authorities, giving the decision-making process new perspectives. The conclusions can possibly also help to mitigate the effects of macroeconomic crises.

The remainder of the paper is structured as follows. The next section provides a literature overview and develops hypotheses. Then, the research methodology, research sample, methods, and data are described. Next, empirical results are detailed and discussed. The final section presents the conclusions.

Value creation depends on how efficiently a firm manages its resources compared to its competitors. More efficient entities capture value from less efficient units. The same occurs between business industries. Some sectors may grow faster than others, attracting investor interest and capturing value. These changes may also be the result of external factors, such as a global crisis. As Slywotzky (1996) noted, companies and the industries in which they operate are continually going through different phases of development, which is also related to the change in their value. Value migration is the process by which value flows away from economically obsolete business models towards new ones that more efficiently manage shareholder value. Phillips (2012) defined value migration as shareholder assets return on profits, which moves between business units of low attractiveness for investors (value outflow) to companies with the highest growth potential (value inflow) and the highest possible return. Value creation by firms plays a central role in the evolution of populations by enabling adaptive efficiency (Di Gregorio, 2013). This process will be influenced by economic, technological, political, and social factors. Rappaport (1995), however, clearly indicates that the process of value migration is influenced by the financial performance of individual firms.

A value migration analysis can be carried out in an aggregate way at the level of individual industries (Siudak, 2014). Sectors experiencing an inflow of value also include companies characterised by an outflow of value. On the other hand, firms with a very good financial standing may belong to an industry in the process of value outflow (Rappaport, 1995). It is therefore worth exploring whether and to what extent there has been value migration in the largest industries of the Central European countries. It will be interesting to investigate whether the process of value migration intensified during the first year of the COVID-19, and, if so, in what direction. Observation of changes in market values during previous major crises, such as the recent global financial crisis (2008–2009), indicates there were large changes in value flows (Bartram and Bodnar, 2009; Fratzscher, 2012). Choi (2021) investigated market efficiency during a crisis in the US stock market in individual sectors of the economy. Each sector showed a different multifractal feature in the periods of the recent global finance crisis and the COVID-19 pandemic, but regardless of the crises, some sectors consistently demonstrate the highest and lowest efficiency. Thus, we hypothesized:

H1: The migration of value in Central Europe's largest industries intensified during the pandemic crisis.

In his concept of shareholder value networks Rappaport (1995) identified areas of management decisions that determine the value drivers: operational, investment, and financing decisions. Thus, we investigated whether factors relating to these areas were linked to value migration in Central Europe's largest industries. The measures we adopted to determine the effects of operational decisions were as follows: return on sales, sales dynamics, and cash liquidity. In order to analyse the relationship between investment decisions and value creation, we used the following indices: capital expenditure in relation to assets and productivity of fixed assets. Decisions on the method of financing are taken into account in our study by means of the debt-to-assets ratio.

The impact of profitability on the ability to create value is widely reported. It is considered a fundamental factor in value creation. Increasing a company's profitability can be seen as a positive signal to investors regarding the value of the company. The positive impact of profitability on a firm's value is evidenced by, i.a., Laitinen, (2008), Rizqia and Sumiati (2013) Fajaria and Isnalita (2018), Djashan and Agustinus (2020). Thus, we assume that:

H2a: The higher the profitability of sales, the higher the market value added.

Change in sales is a measure of a company's growth. It is perceived to be one of the most important factors of value creation. Khanna and Palepu (1999) warn that managers need to change their strategic orientation from “growth now, profitability later” to “profitable growth now.” This orientation is in line with empirical results obtained by Ramezani, Soenen and Jung (2002), who indicate that maximizing growth does not maximize corporate profitability or shareholder value. On the contrary, companies with moderate growth in sales or earnings show the highest rates of return and value creation. Bearing these conditions in mind, one might expect that the growth of a firm's operations is positively correlated with value creation. This is also confirmed by the research of Laitinen (2008), Fajaria and Isnalita (2018), and Djashan and Agustinus (2020). Hence, we hypothesize:

H2b: The greater the increase in sales, the higher the market value added.

In terms of operating activities, liquidity is also an important area. How liquidity affects value creation is ambiguous. Maintaining high liquidity is associated with high costs (i.e., opportunity costs). The negative impact of liquidity on the value of a company was observed by Zuhroh (2019). There is, however, an increasing number of studies showing that a high level of liquid assets serves to maintain financial flexibility, which has a positive effect on value creation. Using a sample of firms from 33 emerging countries, Yung at el. (2015) show that financial flexibility adds to firm value, particularly during the financial crisis. Bilyay-Erdogan (2020) investigates the effect of financial flexibility on firm value, on a comparative basis between developed and emerging countries in Europe between 2000 and 2016. His results demonstrate that firms’ flexibility positively contributes to firm value. Similar conclusions were reached by Yousefi and Yung (2022). Hence, we hypothesize:

H2c: The higher the value of the cash ratio, the higher the market value added.

Investment in fixed assets and effective management of current assets should contribute to value growth. Investment opportunity has a positive effect on firm value, and investing firms increase value (Del Brio, De Miguel, & Pindado, 2003; Rizqia & Sumiati, 2013). Lew (2015) found a positive association between investment expenditures and firm value across both industries and markets. Likewise, however, he found that the associations between them are different across industries and markets. According to Santoso and Willim (2022), investment decisions in fixed assets positively affect value creation. Thus, we proposed two hypotheses:

H2d: The greater the relative value of capital expenditures, the higher the market value added.

H2e: The greater the productivity of fixed assets, the higher the market value added.

Previous studies do not provide consistent results regarding the effect of leverage on firm value. Some studies indicate a positive effect (Rizqia & Sumiati, 2013; Kartikasari, Hermantno, & Mahmudah, 2019; Al-Ahdal et al., 2020), and some a negative effect (Kouki & Said, 2011; Fosu et al., 2016; Fajaria & Isnalita, 2018) of debt on firm value. This is likely due to the benefits and costs of debt, which are widely described in capital structure theory. Factors positively affecting the firm value include, for example, a tax shield on interest and increased control of managers. Negative consequences are associated with increased costs of financial distress and agency costs of debt. The level of these benefits and costs depends on many factors (e.g., financial performance, levels of managerial ownership, information asymmetry, debt capacity) and is not uniform for all firms. Thus, it is difficult to suggest the expected direction of the relationship between leverage and changes in market value added (MVA). Given that most of the period we studied was characterized by a bull market, we hypothesized that:

H2f: The higher leverage, the higher the market value added.

He et al. (2020) observed a wide variation in the valuation of stocks in different sectors of the economy during the pandemic in China. Lee, Chen, and Ning (2017) and Gruber (2021) pointed out that the value drivers and the determinants of company performance vary across noncrisis and crisis periods. Thus, we hypothesised:

H3: Value drivers changed during the pandemic crisis.

We gathered the financial data of firms listed on exchanges in Central European countries from 2016 to 2020. The source of our data is S&P Capital IQ. We excluded firms from the financial sector. We also discard observations with incomplete data. Our final dataset comprises 3980 firm-year observations (Table 1). We collected data on the five most numerous industries: communication services (CS), consumer discretionary (CD), health care (HC), industrials (In), and information technology (IT).

The primary measure of the value of listed companies is MVA (Ehrbar, 2000). It is the difference between the capital that owners invest in a company and what they can get by selling its shares at today's market price. (1) MVAi=Vi−Ki {MVA_i} = {V_i} - {K_i} where: MVA_i - market value added; V_i - gross market value; K_i - book value of equity capital.

To measure industry migration, we used Siudak's (2014) share of industry migration balance (SMB_ind) was calculated. (2) SMBind=∑i=1n indΔMVAi∑i=1n ind|ΔMVA|i {SMB_{ind}} = {{\Sigma _{i = 1}^{n\;ind}\Delta {MVA_i}} \over {\Sigma _{i = 1}^{n\;ind}{{\left| {\Delta MVA} \right|}_i}}} where: n ind number of companies in the industry.

The change in MVA between periods is calculated as: (3) ΔMVAi=MVAi,t−MVAi,ti−1 \Delta {MVA_i} = {MVA_{i,t}} - {MVA_{i,ti - 1}}

The change in MVA to invested capital is calculated as: (4) ΔMVAiKi=(MVAiKi)t−(MVAiKi)t−1 \Delta {{{MVA_i}} \over {{K_i}}} = {\left( {{{{MVA_i}} \over {{K_i}}}} \right)_t} - {\left( {{{{MVA_i}} \over {{K_i}}}} \right)_{t - 1}} We categorised value drivers into three groups relating to managerial decisions, as in Figure 1. (5) ROS=net profitsales ROS = {{net\;profit} \over {sales}} where: ROS - return on sales. (6) ΔS=salest−salest−1salest−1 \Delta S = {{sale{s_t} - sale{s_{t - 1}}} \over {sale{s_{t - 1}}}} where: ΔS -change of sales. (7) CLiq=cash and its equivalentscurrent liabilities CLiq = {{cash\;and\;its\;equivalents} \over {current\;liabilities}} where: CLiq -cash liquidity ratio. (8) CAP=CAPEXtotal assets CAP = {{CAPEX} \over {total\;assets}} where: CAP-capital expenditures (CAPEX) to assets. (9) FAP=fixed assetssales FAP = {{fixed\;assets} \over {sales}} where: FAP -fixed asset productivity. (10) Lev=total debttotal assets Lev = {{total\;debt} \over {total\;assets}} where: Lev -total debt to assets.

Figure 1.

To determine the importance of the value factors, we calculated their averages in terciles within each industry. The terciles were determined on the basis of the value of the change in MVA to invested capital. In order to check the significance of differences between amounts of variables for the first and third terciles, we applied the t-test and the Mann-Whitney U test of two independent samples.

This paper discusses the importance of financial factors affecting value migration among nonfinancial public companies in Central Europe. The following final conclusions can be drawn with regard to the hypotheses:

The results of the share in the industry migration balance supports the hypothesis that the value migration in the largest industries in Central Europe intensified during the pandemic crisis. The industries analysed, due to their characteristics, were not negatively affected by the pandemic. Moreover, IT and health industries responded strongly to the pandemic in a positive way. These results are consistent with those observed for other regions. The good performance of companies in these industries was also observed in China during the pandemic (He et al., 2020).

This study contributes to the existing empirical literature on value migration in several ways. First, it refers to the Central European region. Next, the period of analysis covers the period of market turbulence caused by the pandemic. Exploring the relationship between financial factors and value migration processes may be useful for investors in the decision-making process. This is also important for proper development of business strategies. A comparison of value migration processes in periods of different macroeconomic conditions is crucial for stakeholders, especially investors. This research extends the discussion on value migration by a comparison of industries. Our conclusions are in line with Fama and French (2007), who emphasised the need for further analysis of value fluctuations in the capital market between companies, as well as sectors. In summary, this research contributes to increasing the efficiency of decision-making in capital allocation.

This study has several limitations, which could provide a starting point for future research. The study was limited to the largest sectors of Central Europe. This ensured the homogeneity of the sample and allowed for a detailed analysis. However, including other regions or industries could also be beneficial. This would probably show other dimensions of company value creation. This research focuses on three dimensions of financial factors. However, nonfinancial factors could also be analysed by experts from other fields, like marketing, business maintenance, logistics, etc. We also see some opportunities in expanding the study to other, smaller sectors, using different methods more appropriate for small samples. Another direction of our future studies could involve the development of value migration proxies. So far, we implemented a two-dimensional indicator approach combining market and book value. For further research, we point to the above opportunities. We also see the need for further research, using different statistical tools. It would allow to shed new light on the relationship between value drivers and value migration.