The influence of capital structure on Baltic corporate performance/Kapitalo struktura baltijos imonese.
Bistrova, Julia ; Lace, Natalja ; Peleckiene, Valentina 等
1. Introduction
The decision of target capital structure is one of the most
difficult in enterprise management as there is always a dilemma between
corporate profitability, which is offered by fiscal benefit, and the
risk, which is faced when the share of debt in total assets starts to
prevail over equity. This becomes especially sensitive in the uncertain
market conditions, e.g. during downcycles of the economy. Contractions
or expansions in bank lending may affect firms' balance sheet
liquidity (or solidity) position. Banks are likely to be more reluctant
to lend to firms in difficulty. This is reinforced when the banks are in
lack of liquidity themselves. Thus, the companies in need for external
financing face increased risk.
Though there have been multiple studies on how the role model of
capital structure should look like, still there is no consensus
regarding that yet. One observes different capital structures from
country to country, sector to sector, company to company. Researchers
generally point to the differences in capital structure between
developed and emerging markets as well as across developed markets. For
instance, companies in France, Italy, Japan are more highly levered than
the companies in the United States and United Kingdom. At the moment
average equity ratio of US companies (S&P 500) is 41%, while Western
European companies (Stoxx 600) have it over 37%. Not only are certain
patterns seen in capital structure but also in debt maturity. It is
interesting that companies in the developed markets typically have more
long-term debt and tend to have higher long-term debt to total debt
ratios compared to the peers located in emerging the markets (Booth et
al. 2001). Companies in higher inflation environment usually exhibit
lower levels of financial leverage, rely more on equity financing, and
have shorter debt maturity structure compared to their peers in lower
inflation countries --as high inflation has a negative impact on both
the level of debt financing and desired debt maturity.
Public companies domiciled in the emerging markets (China, India,
Russia, Brazil, Eastern Europe) are under scrutinized attention
regarding the quality of their balance sheets as in the conditions of
tight liquidity equity markets of developing countries are the first to
suffer. This was clearly seen during the recent liquidity crunch on the
financial markets--there was a major money outflow seen in the emerging
countries. Management of the companies needed to make significant
efforts to persuade investors to stay loyal, to demonstrate that
companies are able to generate enough cash flows to self-finance and
that balance sheet is strong enough to overcome the downturn in the
global economy. This is also closely connected with the corporate
sustainability question, which has been extensively researched within
the Baltic market (Adekola et al. 2008; Balkyte, Tvaronaviciene 2010;
Tvaronaviciene et al. 2009).
Thorough investigation of corporate financing structure becomes
more topical as institutional investors make their investment decisions
more sophisticated and understand that the abnormal growth, which was
experienced on the emerging markets in early years of 21st century, has
expired and now one needs to make well thought through decisions. More
careful approach to balance sheets assessments is also encouraged by the
recent bankrupts: Lehman Brothers, General Motors, MGM, Cello Energy
etc.
As a consequence of these corporate actions and recent liquidity
crisis, one sees major deleveraging going on nowadays, but where the
limits are. According to the FT journalist John Plender (2011)
deleveraging is going on not only in the private but also in the public
sector. However, as he points out the deleveraging has slowed down too
soon and the current debt reduction definitely is not sufficient.
The authors of the present research conducted a study on the
influence of capital structure and quality of balance sheet of the
Baltic and Central and Eastern European (CEE) companies on the share
return in 2007-2009, which proved that the investors praise high quality
of the balance sheet in the condition of market crisis.
The authors of the study are expanding the previous research to
check the hypothesis also in the expansion phase, which was seen on
stock markets in 2009 and 2010. Moreover, the research is also expanded
to check how the capital structure influences the profitability of the
Baltic companies. Thus, two hypotheses were advanced:
H1: Companies with sufficient level of capital and, thus, high
quality of balance sheet, are more valued by the investors.
H2: Companies with high quality of balance sheet are able to show
better profitability in the long-term.
The aim of the present research is to understand the dual influence
of the capital structure: on the corporate profitability as well as on
stock returns of the Baltic listed companies.
The methods chosen for conducting a research are mainly
quantitative, which include benchmarking, running correlation and
regression, assessing statistical significance.
2. Optimal capital structure and its influence
The topical issue about balance sheet leverage and optimal
financing structure is being discussed by the leading economists and
financiers for several decades already. The choice of financing reflects
the trade-off between the tax benefits of debt and associated bankruptcy
and agency costs. Company's capital structure largely depends on
company-specific factors such as the probability of bankruptcy,
profitability, quality and structure of assets. Beyond these factors,
company's industry affiliation and characteristics of country the
company operates also influence financing structure. Thus, choice of the
capital structure is an individual decision of each company.
Leverage increases the potential volatility of company's
earnings and cash flows and increases the risk of lending to or owning a
company. Choice of the capital structure has a strong influence on the
company's market value, and it becomes crucial during the period of
monetary tightening, which occurred during the liquidity crisis. Highly
leveraged companies usually have a discount in valuations as they pose a
greater chance of incurring significant losses during downturns.
There have been a number of studies and academic researches to find
out what is the best policy of capital management corporate executives
should stick to in order to win investors' respect, praise and
loyalty.
Modigliani and Miller (1958, 1963) state that in the tax-free world
there should not be any dependence of market value of the company on its
capital structure, but when the taxes are deducted there is a positive
relation between value of the company and level of debt.
Masulis (1983) argues further that when firms which issue debt are
moving toward the industry average from below, the market will react
more positively than when the firm is moving away from the industry
average.
Hatfield et al. (1994) examined the capital structure dependence on
the industry the firm operates in. They also tested the relationship
between firm's debt level and its shareholder returns and were not
able to find any significant relationship.
Professor of Columbia Business School, Gur Huberman (1984),
explains the empirical evidence showing negative relation between
firm's external financing and its market value. Income from
operations is an important source of liquidity and, therefore, low
earnings lead to low liquidity. The company anticipating decreasing
earnings favours external financing. Thus, high level of external
financing is associated with the low earnings that tend to decrease the
value of a company.
The study on 70 Brazilian companies covering the period of 7 years
(1995-2001) shows positive relations between corporate profitability and
short-term debt and with equity, while an inverse relationship with
company's long-term debt (Mesquita, Lara 2003). It is worth
mentioning also Chou and Lee (2010) research, which considered 37
Taiwanese companies during the period of 20 years (1987-2007) and
discovered that the relationship between level of debt and corporate
performance is consistent with the trade-off theory: as the debt level
increases the profitability increases until it reached the maximum and
then it starts to decrease.
Static trade-off theory suggested by Modigliani and Miller proves
that the higher company's leverage the higher is also the
profitability. Other academics added the basics of M&M theorem with
personal taxes (Miller 1977) showing that optimal debt level can be
obtained just on macro level not on company's level. Stiglitz
(1972) added bankruptcy costs, while Jensen and Meckling (1976) and Kim
(1978) added agency costs, gains from leverage-induced tax shields were
added by DeAngelo and Masulis (1980). Empirical works by Bradley et al.
(1984) and Long and Malitz (1985) strongly support that the agency and
bankruptcy costs are partial determinants of the capital structure.
There were further researches and empirical evidences, which showed
that more profitable firms employ lower leverage and, thus, the results
contradicted with static trade-off theory. The possible explanation is
found in the pecking order theory (Donaldson 1961; Myers, Majluf 1984;
Myers 1984; Fama, French 2002): to avoid the costs associated with the
attraction of new funds, the companies are likely to use more internal
funding, which can only be provided if the company is able to generate
sufficient cash flows and is profitable. However, if the firm sees huge
growth opportunities and the debt is available at reasonable cost, then
the firm increases its leverage to capture future return and shows good
performance, but there is the risk of overinvestment, which might lead
to an inverse relationship.
There have been several studies, which proved that to explain
company's capital structure with the pecking order theory is not
enough (Fama, French 2004; Leary, Roberts 2005).
Baker and Wurgler (2002) proposed another theory--market timing
theory. It states that the capital structure depends on the equity value
of the company as the companies exploit equity issuance when the stock
prices are high. This lowers the cost of equity of the company and
benefits new shareholders at the expense of the old. The companies issue
new equity while not making any effort to understand the market
mispricing (Schultz 2003; Dittmar, Thakor 2007).
Several researchers tried to explain capital structure choice with
the stock returns for US companies (Welch 2004) and European companies
(Drobetz, Pensa 2007). However, the authors suppose that this assumption
is not relevant for emerging market companies yet as so common share
buybacks on the developed markets, which are major determinants of
capital structures, are not popular with emerging entities, perhaps due
to heavy investing in development there.
3. Research methodology
The cornerstone of the present research is testing the influence of
company's capital structure on its profitability and stock returns.
The relationship between the profitability and capital structure was
tested by employing the following function:
ROE = f(DE, NDE, SE), (1)
where: ROE is equity capital profitability, which is measured as
net profit divided by equity; DE is total debt divided by equity; NDE is
net debt, which is total debt minus cash, divided by equity; SE is
sufficiency of equity capital index which is measured as equity divided
by sufficient equity and multiplied by 100.
In the present research the authors are also testing asset
profitability with the following function:
ROA = f(DA, NDA, SE), (2)
where: ROA is asset profitability, which is measured as net profit
divided by total assets; DA is total debt divided by total assets; NDA
is net debt, which total debt minus cash, divided by total assets; SE is
sufficiency of equity capital index.
Though ROE appears to be one of the most important ratios investors
take into account, the authors believe that ROA also needs to be tested
as it measures the profitability of total assets regardless of whether
they are pure equity or a mixture of debt and internal capital. It is
important to find out which capital structure helps to achieve highest
asset profitability.
Sufficiency of equity needs to be explained more thoroughly as is
relatively new concept of the financial theory. Capital sufficiency
helps to understand if the business entity is financed in the way that
ensures its sustainable development. The methodology of sufficient
equity calculation was developed by Riga Technical University professors
Natalja Lace and Zoja Sundukova (2008), taking into account asset
financing rules: long-term capital should take responsibility for less
liquid assets. Sufficient equity for the present research purposes was
calculated according to the following formula (Lace, Sundukova 2010):
Sufficient equity = Long-term assets + Inventories
Provisions--Long-term liabilities. (3)
Having calculated sufficient equity, one needs to consider relative
ratio: equity ratio divided by necessary level of sufficiency equity:
sufficient capital index. If it is significantly above 100 points, it
should be considered that the company has too low debt, which needs to
be increased to raise shareholder's value. In opposite, if the
index tends to be below 100, then the balance sheet is highly levered,
and the management should think about decreasing its total debt in the
capital structure. However, it should be taken in the account, that one
never gets 100. So, certain deviations from 100 points are acceptable
(20 points within the present research).
The relationship between the stock returns and capital structures
was tested with the help of the following function:
[A.sub.t] - [A.sub.ave] = f(DA, NDE, SE), (4)
where: [A.sub.t] - [A.sub.ave] is the performance of the company
per annum compared to the equally weighted market performance; DA is
total debt divided by total assets; NDE is net debt, which total debt
minus cash, divided by equity; SE is sufficiency of equity capital
index. The above discussed functions are tested with the help of
regression, t-tests and F-tests to understand how significant the
regressions and the independent variables to explain the relationship
are.
The research primarily covered the companies listed in the Baltic
States (Lithuania, Latvia and Estonia), which are included in the Baltic
blue-chip index, OMXBBGI, consisting of 36 components.
It should be noted, however, that the representatives of financial
industry (Siauliu Bankas, Ukio Bankas, Snoras) were systematically
excluded from the research corpus, when analyzing equity capital
sufficiency, due to the balance sheet structure that significantly
deviates from the classical balance sheet structure.
The period selected for the present research was January 2007
through January 2011, which covered the financial crisis on the
world's stock exchange and as well as pre and post crisis period.
Thus, total observation number totalled 144.
Fundamental data necessary to carry out a study (for ROE, ROA etc.
calculation) were extracted from the annual reports of the companies
published on the corporate web-sites. The price development for each
company was provided by NASDAQ OMX Riga
(http://www.nasdaqomxbaltic.com/). The authors used the following set of
data for the research needs: monthly stock prices, total assets,
shareholder's equity, long-term assets, inventories, provisions,
long-term liabilities, total liabilities, cash and equivalents.
4. Results of the research
4.1. General overview
Before checking the hypotheses stated in the introduction, it is
worth having a general look at the quality of balance sheet of Baltic
stock exchange listed companies.
The results confirm previous research that emerging markets
companies tend to have more conservative balance sheets than their peers
in developed countries. Median equity ratio of Baltic companies is 54%,
which is obviously significantly higher than the ratio of European and
US companies.
Average net debt to equity is rather low as well. When splitting
the data into the regions, one sees great difference of Latvian
companies' balance sheet compared to their peers in the
neighbouring countries: equity ratio is 70% and net debt is just 8%
compared to 46% and 45%, respectively, in Lithuania. It may seem that
the balance sheets of Latvia based companies are rather overcapitalized
and they lack investment opportunities.
[FIGURE 1 OMITTED]
The Table 1 offers the insight into main characteristics of the
variables used in the regression to explain the relationship of the
capital structure and corporate performance (measured as profitability)
as well as stock returns.
Average debt level of the Baltic companies is rather on a low
level: debt to assets is 48%, while net debt to assets is 19%. Average
debt to equity is 158% and net debt to equity is 79% pointing to the
substantial cash reserves on the balance sheets. It should be noted that
here the median is obviously much lower than the average levels: 100%
and 47% respectively. Also the standard deviation of these data is
rather on a high level compared to debt to assets ratios.
The mean ratio of sufficiency of capital is 58, which means
insufficient equity capital. However, the median ratio (94), which is
less subjective than mean, shows that Baltic companies have sufficient
equity capital.
Profitability of the Baltic companies is on a low level which is
demonstrated by both return on assets and return on equity, which can be
explained by the time period covered in the research as it also included
financial crisis. The latter definitely had a negative impact on the
majority of Baltic companies.
It should be also noted that the values of average ROE and ROA are
very close to each other, which can be explained by the high equity
share in total asset structure and by the low level of the numerator,
i.e. net income.
Annual stock return picture is rather ambiguous: over the period
covered Baltic companies in average could beat the market by 5%
according to the mean ratio, while the median ratio shows an
underperformance of 4% a year.
4.2. Capital structure and profitability interaction
First, the equity capital profitability dependence on capital was
tested. According to the regression run, there is a strong negative
relation of net debt to equity and debt to equity ratios with return on
equity as suggested by the regression output:
ROE = 14.76 - 4.96DE - 3.85NDE - 0.02SE. (5)
Sufficiency of equity capital as it seems does not have a major
impact on the result.
Table 2 shows the statistical significance of the model. According
to the F-test, the regression overall is good as F-test value is high.
Coefficient of determination (R square) is rather on the high level,
showing that 32% of the variations of the return rate (ROE) were
explained in conjunct by the independent variables.
Two of three independent variables, which are net debt to equity
and debt to equity, are statistically significant at 95% confidence
level. As it was also stated before, sufficiency of equity does not have
major influence on the final output as well as it is not significant at
95% level, it is significant only at 90% level.
The result indicates that the return rates are inversely
proportional to the debt, in other words: the larger the debt, the lower
is the profitability. Obtained results confirm the findings of Booth et
al. (2001), Fama & French (2002), Graham (2000), and Miller (1977),
but no arguments are found to support Modigliani and Miller theorem
(1958).
The chart on Fig. 2 provides an overview of the Baltic
companies' financing structure for the financial year 2010. The
chart shows that there is a sharp difference in the debt levels for the
companies of various profitability levels: higher levered companies have
negative ROE, while companies with positive ROE have a debt level which
approximately is equal to the equity capital.
[FIGURE 2 OMITTED]
Second, financing structure influence on asset profitability was
tested. This was done in order to test profitability of the whole asset
base, not just equity part. The regression output was the following:
ROA = 0.05 - 0.153NDA + 0.014DA - 0.00SE. (6)
As the regression data shows there is a negative relation of asset
profitability and net debt to assets, while positive with the amount of
debt to assets.
However, when checking the statistical significance (see Table 3),
one finds out that only net debt to assets as independent variable
contributes to the regression result being significant at 95% level.
Neither debt to assets nor sufficiency of equity capital significantly
influence return on assets of the Baltic companies.
The F-test of the ROA regression is not as high as in ROE
regression but still is high enough for the regression to be
significant. According to R square, only 9.74% of the profitability can
be explained by the selected independent variables, which is quite low
level. Overall the profitability explaining power of this regression is
lower than that of ROE regression. But it also shows that the lower is
net debt of the company the higher is the asset profitability.
[FIGURE 3 OMITTED]
Net debt to asset ratio due to being significant in the ROA
regression was selected to reflect the current situation with the Baltic
companies (see Fig. 3).
The companies with ROA being deep in the negative zone have highest
net debt to asset ratio. These companies have net debt to assets ratio 3
times higher than the debt level of the companies being in asset
profitability top quartile.
4.3. Capital structure and stock returns interaction
Third, the authors tested also the relationship of capital
structure and corporate performance on the equity markets. For the
reasons explained below it was decided to run two regressions, which
would explain the annual performance relative to the benchmark of the
Baltic stock exchange quoted companies.
[A.sub.t] - [A.sub.ave] = 0.15 - 0.05NDE - 0.19DA + 0.0005SE; (7)
[A.sub.t] - [A.sub.ave] = 0.14 + 0.00055SE. (8)
The regression (7) shows that there is a negative relationship
between the level of debt and stock outperformance, while positive
relationship of sufficiency of capital and stock returns, which is also
seen in the regression (8).
The data in the panel A (see Table 4) provides statistical data on
the regression (7).
The results of the t-test of net debt to equity and debt to equity
ratios show that these independent variables are not statistically
significant in the regression. This corresponds to the study made
previously by the authors (Lace, Bistrova 2009), when it was found out
that the companies with the highest equity ratios (over 80%) are not the
best performers even during the shortage of liquidity on the markets.
This fact can be explained by their inability to expand the business due
to saturation on the market, thus, this type of companies (e.g.
telecoms) has limited growth potential, which is being negatively
evaluated by the market players.
It is also interesting that the t-test of the net debt to equity
ratio exceeds the value of debt to equity ratio, which confirms previous
results: the best performers were the companies with negative net
debt--companies of the first quartile, thus, the cash on the accounts is
favoured by the investment professionals in the conditions of tight
liquidity. Reasoning on the regression results, one can conclude that
the amount of debt is not the best proxy for the company performance on
the Baltic equity market. Debt ratios turned to be significant in the
relation to the profitability while they are not in relation with the
stock returns. The findings of the previous study (Bistrova, Lace 2010)
carried out within the Baltic equity market showed that for the investor
in Baltic equities the future perspective of the business model is the
key criterion to consider.
Continuing on the stock returns regression (7), one should mention
that sufficiency of equity capital has the highest t-test value, which
makes this independent variable important at 90% confidence level. That
is why the authors decided to run another regression, which would
include solely sufficiency of capital to explain stock outperformance.
Panel B of table shows the results of the regression (8). F-test value
of 3.87 makes the regression statistically significant in contrast to
the regression, where F-test was 2.05 (7). T-test value of equity
sufficiency has also increased and much better contributes to the
regression result. However, the explanation power of the regression (8),
according to R square (3.76%) is still low.
The relevance of equity capital sufficiency is also shown on chart
(Fig. 4). The whole analysed universe of the Baltic listed companies was
divided into three parts according to the level of equity capital. For
each part share price index was calculated for the period from January
1, 2007 to January 31, 2011. As seen on the chart, in the long run the
companies with insufficient equity capital (less than 80 points) are
lagging behind those, which have enough equity financing and those who
have too high equity financing.
Previous research on the Baltic listed companies (Lace, Grigorjeva
2008) showed that during the FY 2007, when the liquidity on the market
was not such an obvious problem, the best investment strategy was to
favour the companies, which have equity financing in range of 80-120,
while the significant setback in performances was seen in the group of
the business entities, which either had too conservative (sufficient
equity capital exceeding 120) or too aggressive (sufficient equity
capital being below 80) capital management policy. However, obviously
the situation changed during the crisis and in the recovery phase as the
companies with very high equity capital outperformed their peers with
adequate and with insufficient equity capital.
[FIGURE 4 OMITTED]
5. Conclusions and recommendations
The main objective of the present research was to evaluate the
quality of the balance sheet and the capital structure of the Baltic
listed companies. Besides, the key task was to find out the effect of
their influence on the share performance and on the profitability. The
two hypotheses stated in the introduction were proved.
The results of the study demonstrate that the companies operating
in Baltic countries pursue conservative capital management policy and
the balance sheets possess low leverage characteristics, which is
typical for the emerging markets.
The first hypothesis that investors favour companies with stronger
balance sheets was proved. The choice of financing the entity evidently
influences equity performance as positive relationship between
sufficiency of equity capital and share performance was found. The
inverse interaction of the debt level and stock outperformance has been
also found but the results in this case were not statistically
significant.
The second hypothesis that companies having lower debt levels on
their accounts are able to demonstrate higher profitability was proved,
too. The results are supported by the two regressions, which explain the
influence of debt level on the return on equity and return on assets.
The lower the debt level (net debt to equity, net debt to assets, debt
to equity, debt to assets), the higher is the profitability of the
company. These results confirm the pecking order theory, which states
that companies prioritize their sources of financing according to the
Principle of least effort. Internal funds are the first to be used, then
debt is issued and the last way to raise financing is the public
offering (equity issue) (Myers, Majluf 1984). Thus, the more profitable
is the company, the more internal capital the company uses for
development.
As it was found out in the previous research (Bistrova, Lace 2010),
the profitability of the capital is not the best proxy for the Baltic
market investors, which is possibly explained by the market immaturity
and inefficiency. Though there is a strong relationship between capital
structure and entity's profitability, it cannot add a lot of value
in creating superior performance. However, as the sufficiency of equity
ratio was able to add value to generating above average returns, the
recommendations to the investors in Baltic equities would be to consider
the sufficiency of equity financing and put more emphasis on those
companies that ensure sufficient and even more than sufficient level of
capital. Undoubtedly, growth perspectives and the attractiveness of the
business model should also be checked as it is a prerequisite for the
company's high performance on the equity market.
The conducted research can be repeated covering larger equity
universe (e.g. Central and Eastern European countries) as well as longer
time period, including different market phases. The suggestions for
further research would be deeper analysis of equity capital sufficiency.
This ratio can be views from two dimensions: company's (internal)
and investor's (external) perspectives. Future study should be
focused on determining and harmonizing strategy of sufficient and
over-sufficient equity capital management for internal and external
purpose taking into account the return and risk trade-off.
doi: <DO>10.3846/16111699.2011.599414</DO>
References
Adekola, A.; Korsakiene, R.; Tvaronaviciene, M. 2008. Approach to
innovative activities by Lithuanian companies in the current conditions
of development, Technological and Economic Development of Economy 14(4):
595-612. doi:10.3846/1392-8619.2008.14.595-611
Baker, M.; Wurgler, J. 2002. Market timing and capital structure,
Journal of Finance 57: 1-32. doi:10.1111/1540-6261.00414
Balkyte, A.; Tvaronaviciene, M. 2010. Perception of competitiveness
in the context of sustainable development: facets of "Sustainable
competitiveness", Journal of Business Economics and Management
11(2): 341-365. doi:10.3846/jbem.2010.17
Bistrova, J.; Lace, N. 2010. Created Value of Fundamental Analysis
During Pre and Post Crisis Period on the Baltic Equity Market, The
Scientific Journal of Riga Technical University, Economics and
Management 3(20): 26-32.
Booth, L.; Aivazian, A.; Demirguc-Kunt, A.; Maksimovic, V.
2001.Capital Structures in Developing Countries, Journal of Finance 56:
87-130. doi:10.1111/0022-1082.00320
Bradley, M.; Jarrell, G.; Kim, E. H. 1984. On the Existence of an
Optimal Capital Structure: theory and Evidence, Journal of Finance 39:
857-878. doi:10.2307/2327950
Chou, S. R.; Lee, C. H. 2010. The Research on the Effects of
capital Structure on Firm Performance and Evidence from the
Non-financial Industry of Taiwan 50 and Taiwan Mid-cap 100 from 1987 to
2007, Journal of Statistics and Management Systems 13(5): 1069-1078.
DeAngelo, H.; Masulis, R. W. 1980. Optimal Capital Structure under
Corporate and Personal Taxation, Journal of Financial Economics 8: 3-29.
doi:10.1016/0304-405X(80)90019-7
Dittmar, A.; Thakor, A. 2007. Why Do Firms Issue Equity?, Journal
of Finance, American Finance Association 62(1): 1-54.
Donaldson, G. 1961. Corporate Debt Capacity. Harvard University,
Boston, Mass.
Drobetz, W.; Pensa, P. 2007. Capital Structure and Stock Returns:
the European Evidence [online]. Available from Internet: <
http://ssrn.com/abstract=957302>.
Fama, E. F.; French, K. R. 2002. Testing tradeoff and pecking order
predictions about dividends and debt, Review of Financial Studies 15:
1-33. doi:10.1093/rfs/15.1.1
Fama, E. F.; French, K. R. 2004. New lists: fundamentals and
survival rates, Journal of Financial Economics, Elsevier 73(2): 229-269.
doi:10.1016/j.jfineco.2003.04.001
Graham, J. 2000. How big are the Tax Benefits of Debt, The Journal
of Finance 55(5): 1904-1941. doi:10.1111/0022-1082.00277
Jensen, M. C.; Meckling, W. H. 1976. Theory of the firm: managerial
behavior, agency costs, and ownership structure, Journal of Financial
Economics 3: 305-360. doi:10.1016/0304-405X(76)90026-X
Hatfield, G. B.; Cheng, L. T. W.; Davidson, W. N. 1994. The
Determination of Optimal Capital Structure: the Effect of Firm and
Industry Debt Ratios on Market Value, Journal of Financial and Strategic
Decisions 7(3).
Huberman, G. 1984. External Financing and Liquidity, Journal of
Finance 3: 895-908. doi:10.2307/2327954
Kim, E. H. 1978. A Mean-Variance Theory of Optimal Capital
Structure and Corporate Debt Capacity, Journal of Finance 33: 45-63.
doi:10.2307/2326349
Lace, N.; Grigorjeva, J. 2008. The Liquidity Crunch Impact on Stock
Selection: Case from Baltic Equity Market, in The 12th World
Multi-Conference on Systemics, Cybernetics and Informatics, Orlando,
Vol. 4: 50-54.
Lace, N.; Bistrova, J. 2009. Capital management during liquidity
crunch: Baltic States in the context of CEE equity markets, in
"Challenges of Europe: Financial Crisis and Climate Change"
Eighth International Conference Challenges of Europe Proceedings, Split,
145-156.
Lace, N.; Sundukova, Z. 2008. Financial stability of enterprises:
case from Latvia, in VI International Scientific Conference
'Management and Engineering'08', Proceedings, The
Scientific-Technical Union of Mechanical Engineering, Sofia, 212-216.
Lace, N.; Sundukova, Z. 2010. Company's standards for
financial soundness indicators, in The 6th International Scientific
Conference "Business and Management 2010", Vilnius, 112-117.
Leary, M. T.; Roberts, M. R. 2005. Do Firms Rebalance Their Capital
Structures?, Journal of Finance, American Finance Association 60(6):
2575-2619.
Long, M. S.; Malitz, E. B. 1985. Investment Patterns and Financial
Leverage, in Friedman, B. (Ed.). Corporate Capital Structures in the
United States.
Masulis, R. W. 1983. The Impact of Capital Structure Change on Firm
Value: Some Estimates, Journal of Finance 38: 107-126.
doi:10.2307/2327641
Mesquita, J. M. C.; Lara, J. E. 2003. Capital structure and
profitability: the Brazilian case, in Academy of Business and
Administration Sciences Conference, Vancouver, Canada.
Miller, M. H. 1977. Debt and Taxes, Journal of Finance 32(2):
261-275. doi:10.2307/2326758
Modigliani, F.; Miller, M. H. 1958.The Cost of Capital, Corporate
Finance and the Theory of Investment, American Economic Review 48:
261-296.
Modigliani, F.; Miller, M. H. 1963. Taxes and the Cost of Capital:
a Correction, American Economic Review 53: 433-443.
Myers, S. C. 1984. The Capital Structure Puzzle, Journal of Finance
34: 575-592. doi:10.2307/2327916
Myers, S.; Majluf, N. S. 1984. Corporate Financing and Investment
Decisions when Firms have Information that Investors Do Not Have,
Journal of Financial Economics 13(2): 187-221.
doi:10.1016/0304-405X(84)90023-0
Plender, J. 2011. Deleveraging efforts have stalled too soon,
Financial Times [online]. Available from Internet:
<http://www.ft.com/cms/s/0/b0b5aba8-338f-11e0-a388-00144feabdc0.
html#axzz1Fhlv2u50>.
Schultz, P. 2003. Pseudo Market Timing and the Long-Run
Underperformance of IPOs, Journal of Finance 58: 483-517.
doi:10.1111/1540-6261.00535
Stiglitz, J. E. 1972. A Re-Examination of the Modigliani-Miller
Theorem, American Economic Review 59: 784-793.
Tvaronaviciene, M.; Grybaite, V.; Tvaronaviciene, A. 2009. If
Institutional Performance Matters: Development Comparisons of Lithuania,
Latvia and Estonia, Journal of Business Economics and Management 10(3):
271-278. doi:10.3846/1611-1699.2009.10.271-278
Welch, I. 2004. Capital structure and stock returns, Journal of
Political Economy 112: 106-131. doi:10.1086/379933
Julia Bistrova (1), Natalja Lace (2), Valentina Peleckiene (3)
(1,2) Faculty of Engineering Economics and Management, Riga
Technical University, 1/7Meza Str., LV-1007 Riga, Latvia
(3) Faculty of Business Management, Vilnius Gediminas Technical
University, LT-10223 Vilnius, Lithuania
E-mails: (2)
[email protected] (corresponding author); (3)
[email protected]
Received 12 March 2011; accepted 15 May 2011
Julia BISTROVA. Mg.oec. Currently she is doctorate student at Riga
Technical University, works for CE Services SIA as a financial analyst,
being a team leader in research department. Her research interests cover
earnings management, corporate finance, equity markets.
Natalja LACE. Dr.oec. Professor of Riga Technical University. Her
research interests are focused on business financial management as well
as on critical success factors of small and medium-sized enterprises.
Valentina PELECKIENE. Doctor, Associate Professor of Vilnius
Gediminas Technical University, Social Economics and Management
Department. Author of more than 30 scientific articles. Research
interests: finance, insurance economics, management.
Table 1. Statistical Description of the Variables
Standard
Variable Mean Median Deviation
Net Debtto Assets NDA 19% 20% 25%
Debt to Assets DA 48% 52% 23%
Net Debtto Equity NDE 79% 47% 168%
Debt to Equity DE 158% 100% 234%
Sufficiency of Equity SE 58 94 267
Return on Assets ROA 3% 4% 12%
Return on Equity ROE 4% 8% 28%
Out/Underperformance [A.sub.t] - 5% -4% 77%
[A.sub.ave]
Table 2. Statistical Description of ROE Regression
Parameters t Stat
Intercept -14.755016 5.272405
NDE -4.9594519 -2.63427
DE -3.8499904 -2.81512
SE -0.0166654 -1.9266
F test 17.4049717
Correlation 0.56910798
R Square 0.3238839
Table 3. Statistical Description of ROA Regression
Parameters t Stat
Intercept 0.05300 1.751895
NDA -0.15284 -2.38677
DE 0.01357 0.187668
SE -0.00002 -0.50914
F test 3.61177
Correlation 0.30453
R Square 0.09274
Table 4. Statistical Description of Stock Return Regression
Panel A Parameters t Stat
Intercept 0.150581917 0.748601182
NDE -0.047283236 -0.887291395
DA -0.194350806 -0.462089903
SE 0.000509164 1.738908306
F test 2.050346044
Correlation 0.24419536
R Square 0.059631374
Panel B Parameters t Stat
Intercept 0.01442977 0.185745087
SE 0.000553368 1.967453382
F test 3.870872812
Correlation 0.193980573
R Square 0.037628463