Financing decisions during different stages of the ...

Financing decisions during different stages of the business cycle

Ludwig F. M. Reinhard and Abu T. Mollik School of Commerce, University of South Australia

By focusing on financing decisions of firms under ’normal’ circumstances, the existing finance structure literature does not address the impact of changes in economic and financial-market conditions on a company’s financing decisions. This article overcomes this shortcoming by focusing on the financing decisions of companies that ‘survived’ different boom and crisis periods. Results show that changes in the economic and financial-market conditions exert a significant influence on a company’s financing decisions. In addition, it is found that successful companies align their financial structures in a way that allows them to switch their financial sources quickly if market conditions change.

The authors wish to thank Michael Burrow, Monica Behrend and Karlin Reinhard for their comments and support.

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I

Introduction

Fluctuations in the economic activity of a country are described by the business cycle. The different stages of the business cycle (peak, contraction, recovery, prosperity) can influence a company’s cash flows and consequently its ability to fulfil its financial obligations. Companies might therefore favour different sources of corporate finance during different stages of the business cycle (Petty et al., 2006).

The modern theoretical capital-structure literature, which started with Modigliani and Miller’s (1958) seminal paper, does not address the influence that different stages of the business cycle have on a company’s financing decisions. It can therefore not answer the question how financial managers should determine their firm’s capital-structure during different phases of the business cycle e.g. during boom and crisis periods1.

Empirical evidence on corporate financing decisions during different stages of the business cycle is sparse. The study of Drobetz and Wanzenried (2006) which found that the speed at which companies adjust their capital-structures towards their capital-structure target ratios differs over the business cycle is one exception. Another exception is the study of Allayannis et al. (2003) that focused on the effects that different forms of debt finance had on the performance of a sample of East Asian companies during the Asian crisis. Both studies do however not provide any guidance for financial managers on what to do during different stages of the business cycle, especially during boom and crisis periods.

The study reported in this paper aims to close this gap in the literature and to provide financial managers with some guidance on their financing decisions by focusing on the financing

1

The terms peak and boom respectively contraction and crisis are used synonymously in the following.

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behaviour of a sample of companies from three different countries that ‘survived’ different boom and crisis periods over the years from 1997 to 2005.

Results show that changes in the economic and financial-market conditions experienced by a company significantly influence its financing decisions as reflected by its capital-structure and debt-maturity-structure decisions. Successful companies that survived the different boom and crisis periods aligned their financial structures in a way that allowed them to switch their financial sources quickly when the capital-market conditions changed (‘market timing’).

The next section briefly describes the different business cycle stages in the three sample countries: Germany, Indonesia and Malaysia. Thereafter, the empirical model is introduced followed by an analysis of the regression results.

II

Sample

Different stages of the business cycle are usually separated by referring to changes in a country’s GDP. Those changes are however not always clear-cut and it is often difficult to determine when the change from one business cycle stage to the next took place. For that reason, the following separation of the different business cycle stages for the sample countries does not solely refer to changes in a country’s GDP alone but takes additional factors, such as stock market developments, into account.

II.1

Germany

II.1.1

Peak: 1997–1999

The economic and financial boom in Germany, which lasted from 1997 to 1999, was caused by the emergence of the so-called ‘new economy’, i.e. bio-tech, high-tech and internet 3

companies. One of the triggers of this boom was the privatisation of the former state monopolist ‘Deutsche Telekom’ in November 1996. Accompanied by a large advertising campaign, the first share issue of the ‘Deutsche Telekom’ company attracted a large number of retail investors that invested in the stock market for the first time (Nowak, 2001). The establishment of the ‘Neuer Markt’ in 1997—a stock market segment especially designed for small, young, bio-, high-tech and internet companies—that provided those companies with a venue to raise funds on a large scale was another important factor that contributed to the emergence of this boom. Many of the previously mentioned first-time share investors started to increasingly invest in stocks—especially in stocks of ‘new economy’ companies—due to the good experience that they made with the Deutsche Telekom share2 (Burghof and Hunger, 2003). This increased share investment flooded companies with new equity capital that could be used e.g. for investment purposes. Based on those considerations, it can be expected that the German sample companies used in this study financed a significant part of their investments by external equity funds over the years from 1997 to 1999—Hypothesis 1.

II.1.2

Contraction: 2000–2002

The initial good development of the stock prices on the ‘Neuer Markt’ fuelled the stock market boom further and contributed to the development of a stock market ‘bubble’3. This bubble finally burst in early 2000 when a combination of misleading disclosure practices, rumours about imminent bankruptcies, alleged fraud and insider trading destroyed the reputation of the ‘Neuer Markt’ and of the German stock markets in general (Burghof and Hunger, 2003, Nowak, 2001, Vitols, 2005). The reputational damage caused a crisis of 2

In the first six months after the IPO (Initial Public Offering), the share price of Deutsche Telekom increased by

more than 20%. 3

During the second year of the “Neuer Markt”, investors could have gained more than 80% on average by

selling shares on the first trading day, see Burghof and Hunger (2003).

4

confidence in stock market investments and induced many investors to liquidate their shareholdings, which lead to a steep and long-lasting fall in share prices4. Due to those unfavourable stock market conditions, it was de facto impossible for companies to raise new equity funds from local stock markets5 (Vitols, 2005). The concurrent recession of the German economy also made it more difficult to raise new external debt funds since financial institutions became more cautious in granting bank loans. Consequently, it is hypothesized that during the years from 2000 to 2002, the German sample companies had to rely mainly on internally generated financial funds—Hypothesis 2.

II.1.3

Recovery: 2003–20056

Despite the negative GDP growth rate of -0.2% (see Table 1) , the year 2003 is chosen as the first year of the recovery period since the German benchmark stock index ‘CDAX’ surpassed its all time low level in early March 2003. Thenceforward, the stock market capitalisation and thus the general financing possibilities of the German sample companies improved again. Together with the improving economic conditions, it can be expected that—after overcoming the crisis years—the German sample companies returned to more traditional forms of bankrelated finance (Siebert, 2004, Vitols, 2005) —Hypothesis 3.

4

From March 2000 until March 2003, the German benchmark stock index ‘CDAX’ lost more than 70% of its

index value. 5

In 2002 no single IPO took place in Germany.

6

The year 2005 does not only determine the end of the sample years covered in this study, it also determines the

last year of the recovery period, since the German GDP considerably increased again by more than 2.5% in 2006.

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II.2

Indonesia

II.2.1


The economic and financial slump in Indonesia over the years from 1997 to 1998 was caused by the Asian crisis7, which started in mid 1997 with the devaluation of the Thai Bath (Pangestu and Habir, 2002). From Thailand, the crisis quickly spread to other East Asian countries, among others, Indonesia and damaged its economy badly. The damage, which has been done in Indonesia, was caused by an interaction of several factors. The factors, which are most often cited (Ananta and Riyanto, 2006, Asian Development Bank, 1999b, Australian Department of Foreign Affairs and Trade, 1999, 2002, McLeod, 2004, Pangestu and Habir, 2002) are: First, large capital inflows into Indonesia’s economy, which exceeded profitable investment opportunities. Second, the liberalization of the financial sector that was not accompanied by the establishment of adequate supervisory capacities. Third, the breach of lending controls and other preventive measures by banks. Fourth, excessive short-term and unhedged foreign corporate borrowings. Fifth, confusing government policies that caused a lack of confidence in the government’s ability to deal with the effects of the Asian crisis and which finally triggered bank runs. The combination of these and several other factors8 resulted in a dramatic decline in the Indonesian GDP, stock market capitalisation and in several bank and business failures. Estimates of the total ‘damage’ (decline in GPD) caused by the Asian crisis range from 40% of Indonesia’s 1998-GDP to around 80% of Indonesia’s 1998-GDP (Australian Department of Foreign Affairs and Trade, 1999, McLeod, 2004). The failures of several banks and the stock market slump would be expected to significantly reduce the external financing possibilities of companies in Indonesia. Internal funding 7

It is not possible to describe all factors and events that lead to the emergence of the Asian crisis

comprehensively here. Therefore, reference is made to other sources in the literature. 8

See e.g. Asian Development Bank, 1999b.

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possibilities would have also possibly been scarce due to the economic downturn and the consequent decline in corporate profits. For that reason, it is hypothesized that the Indonesian sample companies used in this study would be forced to significantly reduce their investment activities and that they had to rely almost completely on internally generated funds due to the unavailability of external financing possibilities—Hypothesis 4.

II.2.2


The years that followed the 1997-1998 Asian crisis were characterized by reforms and programs that aimed to overcome the negative effects of the Asian crisis (Pangestu and Habir, 2002). With the support of the International Monetary Fund (IMF) the Indonesian government either closed or nationalised several banks as a start to restructure its banking system. However, the initial inconsistent and slow implementation of these reforms and programs caused a general loss of confidence in the Indonesian economy and induced international investors to withdraw their capital from Indonesia (Asian Development Bank, 1999b). Foreign direct investment inflows became subsequently negative and thus reduced the availability of financial funds further. Due to this reduction together with the steep fall in the foreign exchange rate relative to the US-$ and the slow improvement in economic conditions (see Table 1) it is hypothesized that the Indonesian sample companies had to rely almost completely on domestic financial sources over the years from 1999 to 2003—Hypothesis 5.

II.2.3

Prosperity: 2004–2005

The years from 2004 to 2005 were chosen as the first years of the ‘prosperity’ business cycle stage for the following reasons. First, foreign direct investment inflows significantly increased indicating an increased confidence in the future prosperity of the Indonesian economy.

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Second, the closure of IBRA9 in February 2004, which designates the end of the restructuring of the Indonesian banking-sector. Finally, the change in the composition of the growth in the Indonesian GDP10. Under these conditions, it is expected that the investment activities and financing possibilities of the Indonesian sample companies would significantly increase over the years from 2004 to 2005 compared to the crisis and post-crises years—Hypothesis 6.

II.3

Malaysia

II.3.1


Despite its comparatively good corporate governance and control system (Asian Development Bank, 1999a), Malaysia’s economy was severely affected by the Asian crisis. The effects of the Asian crisis on Malaysia’s economy were however less severe than in the other Asian crises affected countries due to—among others—deliberate regulations that were passed several years before the Asian crisis to strengthen the Malaysian banking sector11. Consequently, mainly the poorly regulated Malaysian non-bank financial institutions, were most affected. Liquidity concerns in these non-bank financial institutions and in some of the smaller Malaysian banks induced many depositors to transfer their savings from these institutions to the major local and foreign banks—which were assumed to be of higher quality—and thereby triggered a flight of capital (Australian Department of Foreign Affairs and Trade, 1999). The concurrent plunge in the foreign exchange rate of the Malaysian Ringgit relative to the US-$ (see Table 1), the collapse of the Malaysian stock market and a 9

IBRA (Indonesian Bank Restructuring Agency), established in 1998, was the government agency created to

restructure and recapitalise distressed banks following the Asian crisis. 10

For the first time after the Asian crisis and starting from 2004 onwards, investments and exports contributed

more to the Indonesian GDP growth than private consumption (see Ananta and Riyanto, 2006). 11

For example, commercial banks were prohibited to sell short-term monetary instruments to non-residents and

faced ceilings on their net external liability positions (Asian Development Bank, 1999a).

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rapid rise in interest rates subsequently cut the supply of external financing funds. Consequently it is hypothesized that the Malaysian sample companies were forced to rely almost exclusively on internally generated financial funds—Hypothesis 7.

II.3.2


Even though Malaysia was not officially under the control of the IMF, it initially followed the IMF programs that were imposed on other Asian crisis affected countries by tightening its monetary and fiscal policy in order to sustain the confidence—especially of international investors—in its financial markets (Asian Development Bank, 1999a). Those early measures caused an increase in domestic interest rates and reduced the availability of bank loan finance for companies. As the measures did not improve but deepen the negative effects of the Asian crisis on the Malaysian economy, the Malaysian government completely changed its policy in mid 1998 and introduced a monetary and fiscal expansion recovery plan (Asian Development Bank, 2001a, Hasan, 2000). This plan was supported by the introduction of capital controls and the pegging of the Malaysian Ringgit to the US-$12 in order to eliminate currency speculation and to stabilize short-term capital flows (Asian Development Bank, 1999a). The combination of these measures finally succeeded as the change in Malaysia’s GDP growth rate in Table 1 shows. At the microeconomic level, the internal financing possibilities of companies quickly improved. However, external equity finance remained difficult to obtain for companies due to the slow recovery of the stock market and the tightening of the listing rules on Bursa Malaysia (Asian Development Bank, 2000, Australian Department of Foreign Affairs and Trade, 1999). On the other hand, the recapitalisation of the Malaysian bankingsector continuously improved external debt financing possibilities. Due to those factors it is

12

Before the onset of the Asian crisis until the flotation of the Malaysian Ringgit on 17 July 1997 the Malaysian

Ringgit was informally linked (pegged) to the US-$ (Hasan, 2000).

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hypothesized that the usage of internally generated equity funds and external debt funds by Malaysian companies would increase over the years from 1999 to 2002—Hypothesis 8.

II.3.3

Prosperity: 2003–2005

The considerable increase in the growth rate of both, the Malaysian real GDP and stock market capitalisation from 2003 onwards were the determining factors for choosing the years from 2003 to 2005 as the ‘prosperity’ business cycle stage (see Table 1). An additional reason for selecting these years is the closure of Danamodal, the government agency established in 1998 to recapitalise distressed banks. Its closure in 2003 together with the closure of Danaharta in 2005—the national asset management company, which was established in 1998, to purchase non-performing bank loans—symbolizes the completion of reforms and programs to overcome the negative effects of the Asian crisis (Bank for International Settlement, 2006). Reflecting these closures and the improving stock market conditions (see Table 1) it is hypothesized that the availability of external debt and equity capital significantly improved, enabling Malaysian companies to increase the proportion of external finance in their capital structures—Hypothesis 9.

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Table 1 Selected economic and financial indicators 1997–2005

Year

1997

1998

1999

2000

2001

2002

2003

2004

2005

Germany

39.09

51.01

68.09

66.85

56.67

34.18

44.16

43.59

43.90

Indonesia

13.49

23.16

45.78

16.26

14.02

14.99

23.02

28.81

28.35

Malaysia

93.45

136.55

183.76

129.47

136.37

130.03

161.98

160.59

139.26

Germany

0.88

0.89

0.94

1.09

1.12

1.06

0.89

0.81

0.80

Indonesia

2909.38

10013.60

7855.15

8421.78

10260.90

9311.19

8577.13

8938.85

9704.74

Malaysia

2.81

3.92

3.80

3.80

3.80

3.80

3.80

3.80

3.79

Germany

12244

24593

56077

198276

26414

53520

29202

-15113

32663

Indonesia

4678

-241

-1865

-4550

-2978

145

-597

1896

5260

Malaysia

6323

2714

3895

3788

554

3203

2473

4624

3967

Germany

1.70

2.00

1.90

3.10

1.20

0.00

-0.20

1.20

0.90

Indonesia

4.70

-13.10

0.80

5.40

3.60

4.50

4.80

5.00

5.70

Malaysia

7.30

-7.40

6.10

8.90

0.30

4.40

5.50

7.20

5.20

Stock market capitalization in % of GDP

Foreign exchange rate against the US-$

Foreign direct investment inflows in mio US-$

Real GDP growth in %

Sources: Euromonitor International and Worldbank World Development Indicator database.

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II.4

Sample companies

Although the sample period covered in this study (1997-2005) does not comprise a full business cycle in each of the sample countries, there are sufficiently different business cycle stages to test whether the financing decisions of the sample companies significantly changed over the different stages. The financing decisions of companies in three countries are examined in order to identify whether a consistent (‘best practice’) financial behaviour during different business cycle stages exists. This comparison is possible as the accounting standards applying to companies in the three different countries are all based on international accounting standards (IFRS13) for the whole sample period from 1997 to 2005 (Asian Development Bank, 2000, BDO et al., 2002, Delvaille et al., 2005, Kueting et al., 2002, Saudagaran and Diga, 1997, UNPAN, 2005). Consequently, financial ratios and measures are comparable across the three different sample countries. Initially all companies listed on the stock exchanges in Germany, Indonesia and Malaysia from 1997 to 2005 were selected for this study. However, financial companies (SIC14 6000–6999), utility companies (SIC 4900– 4999) and companies with incomplete data sets were excluded from the sample. Further, all companies with a market value to total asset ratio of greater than the 99% percentile of all sample companies in a country and all sample companies with a debt to total asset ratio of greater than one were excluded in order to avoid the influence of outliers on the results. After those exclusions were made, the final sample consisted of 344 companies (3440 firm-year observations). Corporate financial data were obtained from Thomson Financial; all other data were obtained from Euromonitor International and the Worldbanks’ World Development Indicator database. The following table shows the number of sample companies separated by country and industry. 13

International Financial Reporting Standards.

14

Standard Industry Code (SIC).

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Table 2 Number of sample companies by country and industry Germany

Indonesia

Malaysia

Agriculture, Forestry, Mining

1

0

11

Mining

1

3

4

Construction

6

1

9

97

33

89

7

4

10

13

7

14

Retail Trade

6

2

4

Services

4

2

16

Others

0

0

0

135

52

157

Manufacturing Transport.& Communication Wholesale Trade

Total number of companies

III

Method

To identify the influences that the different business cycle stages had on the financing decisions of the sample companies and to analyse how they responded to those changes the following two regression models were used.

Regression model 1 D/V adj.it = α + β1 * DEPR it + β 2 * VAR(CF)it + β 3 * CF/INTEXPit + β 4 * INTEXP/(FXR * FFR) it + β 5 * INCTAX it + β 6 * DIV/NINCit

(1)

+ β 7GER NEWECD it + β 7IDO/MAL FDIINFit + ε it An adjusted capital-structure ratio (D/V adj.) was used as the dependent variable in order to separate changes in a company’s capital-structure that resulted from decisions to raise new debt and equity finance from automatic changes in a company’s capital-structure caused by its current profit and dividend payments. The first independent variable, a company’s depreciation expense (DEPR) was used to identify whether the sample companies changed the way in which they financed their long-term investments—as proxied by a company’s

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depreciation expenses—over the different business cycle stages. The next independent variable, the variability of a company’s cash flows (VAR(CF))—as measured by the variance of a company’s earnings before interest and tax and depreciation expenses—was included in the regression model to identify whether and to what extent the sample companies’ financing decisions were influenced by changes in their cash flows (Graham and Harvey, 2001). The rationale for including a company’s cash flow over its interest expense (CF/INTEXP) in the first regression model is based on the consideration that a company’s financing decisions might be influenced by bankruptcy risk considerations, especially during crisis periods (Baxter, 1967, Kraus and Litzenberger, 1973, Scott, 1976).

As mentioned previously, unhedged foreign corporate borrowings are often mentioned as one of the major causes of the Asian crisis (Asian Development Bank, 2000, 2001b, Pangestu and Habir, 2002). The underlying reason for those unhedged foreign corporate borrowings were comparatively lower foreign interest rates and the fact that many of the Asian crisis affected countries (informally) pegged their currencies to the US-$ (Australian Department of Foreign Affairs and Trade, 1999). Due to the informal peg to the US-$, companies faced de facto no exchange rate risk and saw thus no necessity to hedge their—mainly US-$ denominated— foreign borrowings (Asian Development Bank, 2000). To analyse the influence that foreign currency denominated borrowings had on the financing decisions of the sample companies used in this study requires information on a company’s domestic and foreign currency denominated borrowings, which is however not available. To overcome this problem, a variable that proxies for a company’s foreign (US-$) currency denominated borrowings (INTEXP/(FXR*FFR) is constructed based on the following considerations.

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 LC  US - $ loan * Interest rate (US FFR) * FXR   = Interest expense in LC  US - $ 

(2)

Equation (2) shows the relationship between a company’s local currency (LC) interest expense that is reported in its income statement and its foreign currency (US-$) denominated borrowings (US-$ loan). Under the assumption that US-$ denominated loans depend on the US Fed fund rate (US FFR)—one of the benchmark interest rates in the US—and by rearranging equation (2), a company’s interest expense in local currency (INTEXP) divided by the product of the US FFR and the foreign exchange rate to the US-$ (FXR (LC/US-$)) is used a proxy for a company’s foreign (US-$) currency borrowings. The next two independent variables, a company’s income tax payments (INCTAX) and a company’s dividend payout ratio (DIV/NINC), are included in the regression model in order to control for the influence that corporate tax payments and agency cost considerations respectively growth opportunities had on the sample companies’ financing decisions (Graham, 2000, Miller, 1977, Myers, 2001). A dummy variable for new economy companies (NEWECD)15 is chosen as the last independent variable for the sample of German companies to identify whether the financing decisions of these companies differed from the financing decisions of other—‘old economy’—companies, especially during the stock market boom years from 1997 to 1999. Companies of the ‘new economy’ did not have a similar influence on the economic and financial development in Indonesia and Malaysia over the years from 1997 to 2005. For that reason, another final independent variable is used for the Indonesian and Malaysian sample companies that controls for the influence that foreign direct portfolio investment 15

New economy companies are defined as companies operating in the development of drugs and biological

products (SIC 2833-2836), companies in the telephone and communication business (SIC 3661-3674), companies in the computer software and software development area (SIC 7370-7374) and companies in the research related service area (SIC 8700-8734).

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inflows—which are often mentioned as one of the major reasons of the Asian crisis (Australian Department of Foreign Affairs and Trade, 1999, Suto, 2003)—had on the financing decision of those companies. Due to the unavailability of data on foreign portfolio investment inflows, foreign direct investment inflows (FDINF) are used as a proxy instead. Finally, to avoid that companies with large variable values bias the regression results, a company’s total assets scale all control variables.

Regression model 2 LT/ST Liab it = α + β1 * DEPR it + β 2 * VAR(CF)it + β 3 * CF/INTEXPit +

β 4 * INTEXP/(FXR * FFR)it + β 5 * INCTAX it + β 6 * DIV/NINCit

(3)

+ β 7GER NEWECD it + β 7IDO/MAL FDIINFit + ε it The second regression model aims to identify what influence the different business cycle stages had on the debt-maturity-structure—as proxied by a company’s long-term over its short-term liabilities (LT/ST Liab)16—decisions of the sample companies in the different countries. It uses the same independent variables as the first regression model and similarly scales all independent variables by a company’s total assets in order to avoid that companies with large variable values influence the results.

IV

Results

In the following the regression results of regression model 1 and 2, which are shown in Table 3 and Table 4 respectively, are analysed together on a variable-by-variable basis for each sample country separately.

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For the German sample companies, short-term debt is defined as debt that matures within four years or less

whereas for the Indonesian and Malaysian sample companies it is defined as debt that matures within one year or less. The results of the second regression model are thus not directly comparable across countries.

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Table 3 Fixed effect panel-data regression results for regression model 2 The table shows the regression estimators of the first regression model by using fixed effect-panel-data regressions. The F-tests and the Hausman-tests show that the fixedeffect panel-data regression model is preferable over OLS and random-effect panel-data regression models. T-statistics are shown in parenthesis.

Intercept DEPR VAR (CF) CF/INTEXP INTEXP/(FXR*FFR) INCTAX DIV/NINC GER:NEWECD; IDO/MAL: FDIINF

Germany Peak (1997-1999) 0.43*** (15.99) -0.51*** (-2.63) -0.00 (-0.69) -0.00 (-0.33) 0.11*** (3.95) -0.30** (-2.28) -0.58*** (-4.51) 223.92** (2.53)

Contraction (2000-2002) 0.36*** (12.24) 0.12 (0.63) -0.00 (-1.24) 0.01 (1.40) 0.02*** (3.32) -0.09 (-0.42) -0.01 (-0.82) -497.79* (-1.95)

Recovery (2003-2005) 0.38*** (12.02) 0.44 (1.44) 0.00 (1.04) 0.00 (0.19) 0.01 (1.50) 0.36* (1.80) 0.20** (2.12) -584.18* (-1.65)

Indonesia Contraction (1997-1998) 0.81*** (12.33) 0.26 (0.37) -0.00 (-0.09) 9.04 (0.38) 99.29 (0.56) -0.41 (-0.51) 4163.04 (0.68) 0.01 (0.07)

Recovery (1999-2003) 0.62*** (13.33) -0.75** (-2.14) -0.00* (-1.79) 0.40 (0.36) 316.19*** (5.30) -0.26 (-1.00) -5268.05 (-1.17) -0.50 (-0.95)

Prosperity (2004-2005) 0.55*** (9.03) -0.55 (-0.51) 0.00 (0.42) -12.10 (-0.68) -151.96 (-0.59) 1.11 (1.29) -7219.96 (-1.17) -1.03 (-1.07)

Malaysia Contraction (1997-1998) 1.01*** (11.04) -0.59 (-1.24) -0.01*** (-6.81) -0.00 (-0.38) 0.30*** (3.22) 0.69* (1.89) 0.90 (1.45) 0.00 (0.30)

Recovery (1999-2002) 0.90*** (10.64) -0.87* (-1.69) -0.01*** (-5.83) -0.00*** (-3.01) 0.16*** (6.11) -0.24 (-0.70) -0.30 (-0.99) 0.00 (0.85)

Prosperity (2003-2005) 0.89*** (25.46) -0.49 (-1.32) -0.01*** (-11.28) -0.00 (-0.11) 0.08*** (3.59) -0.05 (-0.13) -1.39 (-1.62) -0.00*** (-4.21)

R2

0.9503

0.9301

0.9268

0.931

0.8747

0.9571

0.9738

0.9093

0.9534

F test for no fixed effects

24.76

19.3

18.58

6.38

16.31

13.21

17.44

19.9

26.07

Hausman test (m value)

25.73

22.66

27.36

18.27

14.43

32.14

326.53

56.47

279.64

***

significant at the 1% level, ** significant at the 5% level, * significant at the 10% level.

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Table 4 Fixed effect panel-data regression results for regression model 2 The table shows the regression estimators of the first regression model by using fixed effect-panel-data regressions. The F-tests and the Hausman-tests show that the fixedeffect panel-data regression model is preferable over OLS and random-effect panel-data regression models. T-statistics are shown in parenthesis.

Intercept DEPR VAR (CF) CF/INTEXP INTEXP/(FXR*FFR) INCTAX DIV/NINC GER:NEWECD; IDO/MAL: FDIINF

Germany Peak (1997-1999) 0.23*** (5.95) 0.00 (0.00) 0.00 (0.73) 0.00 (1.00) 0.00 (0.09) -0.15 (-0.77) 0.25 (1.38) 381.82*** (3.02)

Contraction (2000-2002) 0.20*** (5.68) 0.50** (2.30) -0.00 (-0.15) -0.01* (-1.80) 0.02** (2.06) 0.22 (0.83) -0.01 (-0.43) -156.57 (-0.51)

Recovery (2003-2005) 0.13*** (3.20) 1.27*** (3.32) 0.00 (0.03) -0.00 (-0.05) -0.00 (-0.29) -0.14 (-0.54) -0.37*** (-3.05) -421.06 (-0.94)

Indonesia Contraction (1997-1998) -0.04 (-0.35) 0.90 (0.74) -0.00 (-0.28) -8.10 (-0.20) 54.65 (0.18) 0.21 (0.15) -3846.51 (-0.36) -0.46 (-1.65)

Recovery (1999-2003) 0.03 (0.48) 0.26 (0.57) -0.00 (-0.52) 0.59 (0.40) 179.35*** (2.29) -0.62* (-1.81) -45.15 (-0.01) 0.89 (1.31)

Prosperity (2004-2005) 0.28*** (4.12) -0.23 (-0.19) 0.00 (0.26) 3.21 (0.16) 369.80 (1.27) 0.22 (0.23) -379.21 (-0.06) -0.79 (-0.74)

Malaysia Contraction (1997-1998) 0.44*** (4.41) -0.37 (-0.72) -0.00* (-1.93) -0.00 (-0.43) 0.16 (1.56) -0.01 (-0.03) 0.45 (0.67) 0.00 (1.45)

Recovery (1999-2002) 0.62*** (7.43) -1.27** (-2.49) -0.01*** (-3.87) -0.00*** (-3.40) 0.10*** (3.73) -0.00 (-0.01) -0.11 (-0.37) -0.00 (-1.39)

Prosperity (2003-2005) 0.77*** (23.77) -0.66** (-1.90) -0.01*** (-13.06) -0.00 (-0.12) 0.02 (0.87) -0.49 (-1.52) 0.18 (0.22) 0.00 (0.66)

R2

0.8671

0.8779

0.8644

0.8295

0.7751

0.9328

0.9338

0.7455

0.9105

F test for no fixed effects

10.44

11.43

9.30

3.10

8.90

8.78

10.79

6.43

16.83

Hausman test (m value)

24.00

8.53

25.81

5.42

9.44

3.74

13.53

63.14

123.67

***


18

IV.1

Financing of long-term assets

IV.1.1

Germany

The regression results in Table 3 indicate that the German sample companies financed a significantly part of their long-term investments by external equity funds over the years from 1997 to 1999, which is in line with the predictions of Hypothesis 1. This higher reliance on external equity funds for investment purposes during a time when the German stock markets were booming indicates a form of market timing behaviour in the sense that these companies used more external equity funds when the external equity market conditions were favourable. Over the next 3-year period, from 2000 until 2002, the relationship between the capitalstructure ratios and the long-term investment proxy variable of the German sample companies becomes statistically insignificant positive (see Table 3). Based on the aforementioned adjustment of a company’s capital-structure ratio for a company’s dividend payments and retained earnings, this insignificant positive regression estimator indicates that the long-term investment projects of the German sample companies were—in accordance with Hypothesis 2—mainly financed by internally generated funds. After the German sample companies overcame the crisis period, they returned to more traditional forms of bank-related finance (see Hypothesis 3), as the larger but marginally insignificant positive regression estimator in Table 3 indicates (Vitols, 2005). Table 4 shows further that the German sample companies financed their long-term assets according to the ‘matching principle’17 over the years from 2000 to 2005. However, during the boom years from 1997 to 1999, this principle was not strictly followed as the statistically insignificant regression estimator in Table 4 shows. A possible explanation for the deviation from this principle might be based on the favourable economic conditions and the comparatively small size of the German capital 17

The matching principle requires financing long-term assets by long-term liabilities and short-term assets by

short-term liabilities.

19

markets, which could not provide sufficient financial funds in the form required by companies.

IV.1.2

Indonesia

The statistically insignificant relationship between the capital-structure ratios of the Indonesian sample companies and their long-term investment proxy variable indicates—as proposed in Hypothesis 4—that these companies primarily financed their long-term investments by internally generated funds during the period of the Asian crisis. Over the next business cycle stage, from 1999 to 2003, this financing behaviour fundamentally changed and the Indonesian sample companies started to finance a large part of their long-term investments by external equity funds (see Table 3). This outcome indicates that the shareholders of the Indonesian sample companies had to ‘pump’ new equity capital into their companies possibly because no other—internal and external—financial sources were available for investment purposes during those years. Finally, as the economic conditions and the external financing possibilities of the Indonesian sample companies slightly improved over the next two-year period from 2004 to 2005, they returned to a more conservative way of corporate finance and mainly relied on internally generated funds for their long-term investments. Thus, despite the better economic conditions, the Indonesian sample companies did not significantly increase their investment activities (see Appendix 1 and Hypothesis 6), which indicates a more cautious and sustainable growth compared to the years before the Asian crisis (Asian Development Bank, 1999b). The regression results in Table 4 show further that the Indonesian sample companies did in general not strictly follow the aforementioned matching principle, which possibly caused the financial difficulties during the crisis years (see below).

20

IV.1.3

Malaysia

In accordance with Hypothesis 7, the regression results in Table 3 show that the Malaysian sample companies primarily financed their long-term investments by internally generated funds during the years of the Asian crisis. As Malaysia’s economy moved from the contraction to the recovery business cycle stage, the long-term investment activities of the Malaysian sample companies significantly increased (see Appendix 1). Table 3 shows that this increase in the investment activity of the Malaysian sample companies was accompanied by an increase in the external equity fund usage of these companies, which is in contrast to Hypothesis 8. In other words, the long-term investments of the Malaysian sample companies during the years from 1999 to 2002 were largely financed by new external equity funds, which were possibly provided by the owners of these companies since new stock market finance was de facto inaccessible after the stock market crash. As the investment activities of the Malaysian sample companies unexpectedly slowed down slightly over the next 3-year period from 2003 to 2005 (see Appendix 1), so did their external equity fund usage (see Hypothesis 9), which allows concluding that the long-term investments of the Malaysian sample companies were to a large extent financed by external equity funds. In addition to the external equity funds, the regression results in Table 4 indicate that the Malaysian sample companies used short-term external debt funds to finance their long-term investment. This financial mismatch—possibly caused by the lower interest rates on short-term borrowings (Bank Negara Malaysia, 2007)—was already identified before the Asian crisis (Asian Development Bank, 1999a) and has apparently not changed. For that reason, it can be expected that changes that influence the availability of short-term borrowings significantly affect the ability of the Malaysian sample companies to roll over their short-term borrowings and thus increase their bankruptcy risk (see below).

21

IV.2

Variability of cash flows and bankruptcy risk

IV.2.1

Germany

The cash flows of the German sample companies significantly decreased after the end of the economic and financial boom period in 2000 as the t-test for the mean difference in their cash flows in Appendix 1 shows. Everything else being equal, a decrease in a company’s cash (in)-flows reduces its ability to fulfil its financial obligations and thus increases its bankruptcy risk. It can therefore be expected that companies with high fixed financial obligations, such as interest expenses, that face huge declines in their cash flows have to change their capital and debt-maturity-structures to reduce their bankruptcy risk. The regression results in Table 3 and Table 4 show however that the variability in the cash flows of the German sample companies and their bankruptcy risk proxy variable had in general no significant influence on their capital-structure and debt-maturity-structure decisions indicating ‘conservative’, i.e. riskneutral, financial structures. Only during the contraction years from 2000 to 2002, an increase in the long-term external borrowings of the German sample companies significantly increased their bankruptcy risk (see Table 4). The German sample companies did however quickly lower this risk by reducing their long-term investments (see Appendix 1), which helped them overcome the crisis years.

IV.2.2

Indonesia

As for the German sample companies, the variability in the cash flows of the Indonesian sample companies and considerations about their bankruptcy risk did in general not significantly influence their capital-structure and debt-maturity-structure decisions (see Table 3 and Table 4). Only during the years after the Asian crisis from 1999 to 2003, increases in the cash flow variability of the Indonesian sample companies induced them to

22

change their capital-structures primarily—as mentioned before—by capital injections of their shareholders.

IV.2.3

Malaysia

Table 3 and Table 4 show that increases in the variability of the Malaysian sample companies’ cash flows induced them to reduce their debt usage, especially their long-term debt usage. Those reductions appear to have succeeded in lowering the bankruptcy risk of the Malaysian sample companies most of the time. However, during the recovery years from 1999 to 2002, the capital-structure and debt-maturity-structure decisions of the Malaysian sample companies have significantly been influenced by bankruptcy risk considerations (see Table 3 and Table 4). The reason for the increased importance of bankruptcy risk considerations in the capital-structure and debt-maturity-structure decisions of the Malaysian sample companies appears to be caused by the tightening of the loan application procedures and the consequent reduction in the availability of external borrowings (Asian Development Bank, 1999a, Detragiache and Gupta, 2004, Kochhar et al., 1999). This fact together with the aforementioned structural mismatch in the financing of the long-term assets significantly influenced the ability of the Malaysian sample companies to roll over their short-term liabilities and consequently increased their bankruptcy risk. Overall, from the mismatch in the financing of the Malaysian sample companies’ long-term investments and the change in the external debt market conditions it can be concluded that the advantage of lower interest rates on short-term borrowings that are used for long-term financing purposes comes at a cost, namely a higher bankruptcy risk if external market conditions change.

23

IV.3

Foreign debt usage

IV.3.1

Germany

Table 3 shows that the German sample companies successively reduced the usage of foreign currency (US-$) denominated external debt relative to the use of domestic external debt over the years from 1997 to 2005. This successive decline is possibly caused by the introduction of the Euro currency in 1999, the consecutive elimination of the foreign exchange risk in the Euro area and the integration of the capital markets in Europe (European Central Bank, 2004, Vitols, 2005). The regression results in Table 4 show further that the German sample companies primarily raised long-term US-$ denominated borrowings over the years from 2000 until 2002. This preference was possibly influenced by the decline in US interest rates18, which more than offset the depreciation in the foreign exchange rate of the Euro against the US-$ (Mussa, 2005), and thus made US-$ denominated borrowings comparatively more attractive for companies in Germany and in the Euro currency area in general. As the Euro appreciated again against the US-$ over the next 3-year period, this preference disappeared (see Table 4 and Table 1).

IV.3.2

Indonesia

Appendix 1 shows that the mean external foreign debt usage of the Indonesian sample companies did not significantly change from the crisis to the recovery period. This finding and the significant higher external foreign debt usage of the Indonesian sample companies during the recovery years from 1999 to 2003 (see Table 3) indicates that a significant change in the composition of their foreign borrowings took place. In other words, a large part of the existing external foreign borrowings of the Indonesian sample companies were withdrawn and replaced by new external foreign debt funds during the recovery period from 1999 to 2003. 18

The US Fed Fund rate declined from 5.5% at the beginning of 2000 to 1.25% at the end of 2002.

24

This replacement, which is in contrast to the predictions of Hypothesis 5, was possible due to the considerable reduction in US interest rates, which more than offset the depreciation in the Indonesian Rupiah against the US-$. Everything else being equal, this increase in the US-$ borrowings of the Indonesian sample companies made them relatively more vulnerable against changes in the exchange rate to the US-$ and against changes in US interest rates and provided thus the ground for a ‘second Asian crisis’. This ‘second Asian crisis’ did however not emerge since the Indonesian sample companies significantly reduced their foreign currency denominated borrowings over the years from 2004 to 2005 when interest rates in the US increased again (see Table 3 and Appendix 1). It can therefore be summarized that the Indonesian sample companies appear to have learned their ‘lesson’ from the Asian crisis and became more cautious in the usage of foreign currency denominated borrowings especially in regard to the influence of macro-economic changes on those borrowings.

IV.3.3

Malaysia

A significant part of the Malaysian sample companies’ external debt finance was raised in US-$ over the whole sample period from 1997 to 2005 as the regression results in Table 3 show. The reasons behind this relative high reliance on US-$ loans is possibly based on the ability of the Malaysian government to successfully peg the Malaysian Ringgit again to the US-$ after its depreciation and short-term flotation from July 1997 until September 1998 (Hasan, 2000, Kochhar et al., 1999). The reliance on foreign (US-$) borrowings did possibly not significantly influence the bankruptcy risk of the Malaysian sample companies, since—in addition to the de facto absence of foreign exchange risk due to the US-$ peg—borrowers were required to demonstrate that they had sufficient foreign currency income to repay their foreign borrowings (Hasan, 2000). The successively decreasing foreign-debt-usage regression estimator in Table 3 indicates further that the relative importance of foreign currency borrowings decreased over time, which can possibly be explained by the aforementioned 25

recapitalisation of the Malaysian banking-sector and the improved external debt financing possibilities. An additional factor, which contributed to the reduced importance of foreign currency borrowings, is possibly the growth in the Malaysian corporate bond market, which was supported by the simplification of the issuance procedures and the increasing demand for so-called Islamic bonds (Bank for International Settlement, 2006, Bursa Malaysia, 2005, Singhand and Yusof, 2002).

IV.4

Corporate taxes

Whether taxes influence a company’s financing decisions is debatable (Barclay et al., 1995, Graham, 2003, Graham et al., 1998, Miller, 1977). To shed some new light on this issue, especially from a non-US perspective, tax variables that that control for a company’s tax payments are included in the first and second regression model. Since tax regulations are often complex and change over time, brief descriptions of the tax-systems in the three sample countries and changes thereof are provided in Appendix 2, 3 and 4. Based on these descriptions, the following interpretations can be made19.

IV.4.1

Germany

Table 3 shows that an increase in the capital-structure ratios of the German sample companies significantly reduced their corporate tax payments. Appendix 2 shows further that this negative relationship is possibly caused by the German tax system and its preference of debt over equity finance. Despite the fact that the German tax reform did not change the preference of debt over equity finance, the relationship between capital-structure ratios and the tax payments of the German sample companies changes and becomes statistically significant

19

It has to be emphasized that the effective tax-rate measures used in this study show the relationship between a

company’s financial ratios and its corporate tax rates after a company made its financing and investment decisions. For details, see Graham et al., 1998.

26

positive during the recovery period. This change does however not appear to be caused by the German tax reform, which came already into effect in 2001. The reason for the change in the sign of the tax regression estimator appears to be caused by tax loss carry-forwards that accumulated during the contraction period, the significant reduction in the capital-structure ratios of the German sample companies (see Appendix 1) and a slight reduction in their dividend payments, as unreported t-tests show.

IV.4.2

Indonesia

Despite the fact, that Indonesia’s classical tax system allows a company to shelter a part of its profits from taxation by the increased use of external borrowings (Baxter, 1967), the regression results in Table 3 and Table 4 show that the Indonesian sample companies did predominantly not make use of this option. A possible explanation for this outcome might be based on the relatively weak enforcement of the tax laws in Indonesia and the conception that taxes are negotiable rather than fixed (Ang et al., 1997, Asian Development Bank, 1999b).

IV.4.3

Malaysia

The regression results in Table 3 and Table 4 indicate that tax aspects did in general not influence the financing decisions of the Malaysian sample companies. This outcome can be explained by the fact that changes in a company’s tax payments do not affect the after tax income of its shareholders (see Appendix 4). Only during the years of the Asian crisis, corporate tax payments appear to have influenced the capital-structure decisions of the Malaysian sample companies (see Table 3). This result can however be explained by the concurrent reduction in the capital-structure ratios, which was caused by the aforementioned injection of new capital by the owners of these companies, and the tax payments of the Malaysian sample companies during the years of the Asian crisis.

27

IV.5

Agency conflicts/ Growth opportunities

(Myers, 2001) claimed that agency conflicts that exist between a company’s debt and equityholders might induce the latter to transfer ‘wealth’ from their debtholders, e.g. by using borrowed funds for increases in dividend payments. The existence of such an agency conflict implies a statistically significant positive relationship between a company’s capital-structure ratio and its dividend payout ratio, which can be observed for the German sample companies over the years from 2003 to 2005 (see Table 3). Based on a similar argumentation, the debtmaturity-structure contracting-cost hypothesis claims that companies with more growth opportunities use more short-term debt (Barclay and Smith, 1995, Yi, 2005). Under the assumption that a company that retains more of its profit has higher growth opportunities, the contracting-cost hypothesis implies a statistically significant positive relationship between the debt-maturity structure variable and the dividend-payout variable. The regression results in Table 4 do however not support this notion and provide thus some evidence against the debtmaturity-structure contracting-cost hypothesis.

IV.6

New economy/Foreign direct investment inflows

IV.6.1

Germany

The regression results in Table 3 show that the capital-structure ratios of the ‘new economy’ companies in Germany differed significantly from those of the ‘old economy’. Unreported t-tests show in addition that the ‘new economy’ companies used significantly less foreign borrowings and significantly more long-term borrowings possibly because they were not ‘established’ enough to borrow in foreign currencies and in large volumes at the lower end of the debt-maturity-structure20. 20

Under the assumption of an upward-sloping yield-curve, short-term borrowings are cheaper than long-term

borrowings.

28

IV.6.2

Indonesia/Malaysia

Different as generally expected (Australian Department of Foreign Affairs and Trade, 1999), changes in the foreign direct investment inflows did in general not significantly affect the financing decisions of the Indonesian and Malaysian sample companies (see Table 3 and Table 4). It is possibly this fact that ensured the survival of these companies especially during the time of the Asian crisis when significant amounts of mainly short-term capital were withdrawn from the South East Asian region (Australian Department of Foreign Affairs and Trade, 1999). Yet, the regression results in Table 3 show that the capital-structure decisions of the Malaysian sample companies have significantly been affected by foreign direct investment inflows over the years from 2003 to 2005, which were possibly attracted by the comparatively high growth rate and the de facto absence of foreign exchange risks (see Table 1).

V

Summary

The analysis of the financing decisions of the sample companies from the three different countries showed that companies have to rely mainly on internally generated fund for their investments during crisis periods. The unavailability of external financial funds during those periods might additionally require that companies reduce their investment activities and/or obtain new capital from the owners. A second major finding of this study is that long-term assets should be financed by long-term financial funds (matching principle). Temporary deviations from this principle are possible but can easily endanger the survival of a company. A third major outcome is the finding that the advantage of comparatively cheaper foreign debt can quickly turn into a disadvantage. Companies have thus to prepare for changes in foreign exchange and/or interest rates and can in general not rely on informal pegs of their local currency, which can often not be maintained when needed most.

29

Apart from these practical implications, this study showed that changes in the economic conditions and financial market conditions exert a much larger influence on a company’s financing decisions than previously identified. Finally, this study found that companies appear to time their capital-markets. This market-timing does however not take place in the form as described by Baker and Wurgler (2002), by issuing stocks when a company’s stock price is high. On the contrary, the results indicate that companies try to time their capital markets by establishing their financial structures in a way that allows them to switch quickly from one financing source to another one if the capital-market conditions change.

30

Appendix 1 This table shows the mean difference in the capital-structure ratios, cash flows, long-term investments and US-$ denominated borrowings of the sample companies over the different business cycle stages. T-statistics are shown in parenthesis. Germany

Variable D/V adj.

Cash flow

Long-term investments

US-$ denominated borrowings

***

Indonesia

Malaysia

Peak vs. Contraction

Contraction vs. Recovery


Recovery vs. Prosperity


Recovery vs. Prosperity

-0.00

-0.02**

-0.06**

-0.03

-0.04**

0.01

(-0.25)

(-2.17)

(-2.56)

(-1.36)

(-2.47)

(0.77)

**

**

***

-0.01

-0.02

0.04

-0.02

-0.02

0.01*

(-2.21)

(-2.45)

(2.86)

(-1.52)

(-2.39)

(1.86)

*

***

**

*

-0.01

-0.01

0.00

0.00

(-1.86)

(-4.66)

(1.01)

(1.41)

***

***

***

0.00

-0.00

(1.72)

(-0.12)

***

0.53

0.19

-0.00

-0.00

0.06

-0.01

(12.64)

(2.87)

(-0.15)

(-7.49)

(5.87)

(-1.11)


31

Appendix 2 Companies in Germany are subject to three different taxes: a trade-tax, a corporation tax and a solidarity surcharge. The trade-tax, which is imposed on a company’s profit, allows only a 50% deduction of a company’s interest expenses on its long-term borrowings (> 1 year) (Bundesrepublik Deutschland, 2003). The corporation tax, which is based on an imputation system (see e.g. Twite (2001) and Appendix 4), is connected to the trade-tax in the way that the trade-tax is a tax-deductible item in the calculation of a company’s corporation tax. Finally, the solidarity surcharge is de facto a tax that is imposed on other taxes—the corporation tax and the personal income tax. In 2001, the German government introduced the following corporation tax changes (the trade tax and the solidarity surcharge have not been changed). First, it lowered the previous split rate of 40% on retained profits and 30% on distributed profits to a uniform corporation tax-rate of 25% and second, it replaced the dividend imputation system by a half-income taxation system according to which only 50% of the dividends that a company’s shareholders receive are taxed. The downside of the change to the half-income taxation system is that shareholders do not receive tax credits anymore for dividends, which are made out of profits that have already been taxed at the corporate level. The next table shows the tax treatment of a profit distribution in Germany before and after 2001 under the assumption that a company distributes its complete profit. Based on a total amount of debt and equity finance of 2000 currency units, the four columns below give a simplified comparison of the total net distributions to shareholders and the total amount of taxes paid (at the corporate and investor level) for different financial structures. The trade-taxrate is set at 20%, the corporate tax-rate is 30% before 2001 and 25% after 2001 and the average personal income tax-rate is set at 25%.

32

Equity finance Long-term debt finance (>1 year) Interest rate on debt finance Corporate level EBIT Interest expense Earnings before tax 50% interest expense on long-term debt Taxable income trade-tax law Trade tax Earnings before tax Less trade tax Taxable income corporate-tax law Corporate tax Solidarity surcharge on corporate tax Profit after tax Investor level Dividend income taxable Dividend income tax-free Imputation tax credit Taxable income Personal income tax Solidarity surcharge on pers. income tax Less credit for corporate tax and corporate solidarity surcharge Personal income tax payable

Total taxes paid Net distribution to shareholders Net distributions to shareholders and debtholders

21

before 2001 1000.00 500.00 1000.00 1500.00 10% 10%

20%

30% 5.5%

200.00 100.00 100.00 50.00 150.00 30.00

200.00 150.00 50.00 75.00 125.00 25.00

100.00 30.00 70.00 21.00 1.16 47.85

50.00 25.00 25.00 7.50 0.41 17.09

47.85 0.00 22.16 70.00 17.50 0.96

17.09 0.00 7.91 25.00 6.25 0.34

22.16 -3.69

after 2001 1000.00 500.00 1000.00 1500.00 10% 10% 200.00 100.00 100.00 50.00 150.00 30.00

200.00 150.00 50.00 75.00 125.00 25.00

100.00 30.00 70.00 17.50 0.96 51.54

50.00 25.00 25.00 6.25 0.34 18.41

25.77 25.77 0.00 25.77 6.44 0.35

9.20 9.20 0.00 9.20 2.30 0.13

7.91 -1.32

0.00 6.80

0.00 2.43

74.8421 51.5423

71.16 18.41

81.6322 44.7424

73.58 15.98

125.1625

128.84

118.3726

126.42

25% 5.5%

20%

25% 5.5%

25% 5.5%

74.84 = 30.00 trade tax + 17.50 personal income tax shareholder + 0.96 solidarity surcharge on personal

income tax shareholder + 26.38 (100.00*25%*(1+5.5%) personal income tax debtholder. 22

81.63 = 30.00 trade tax + 17.50 corporate tax + 0.96 solidarity surcharge corporate tax + 6.80 personal income

tax shareholder + 26.38 personal tax debtholder (100.00*25%*(1+5.5%)).(0.01 rounding error). 23

51.54 = 70.00 taxable income shareholder – 17.50 personal income tax shareholder – 0.96 solidarity surcharge

on personal income tax shareholder. 24

44.74 = 25.77 tax free income shareholder + 25.77 taxable income shareholder – 6.80 personal income tax

shareholder. 25

125.16 = 51.54 Net distribution to shareholder + 73.62 (100-25%*100.00*(1+5.5%)) after tax interest income

debtholder 26

118.37 = 44.74 net distribution shareholder + 73.62 net distribution debtholder (100.00 interest income

debtholder-26.38 personal income tax debtholder). (0.01 rounding error).

33

Appendix 3 Over the years from 1997 to 2005 Indonesia employed—as the US—a ‘classical tax-system’ (see e.g. Petty et al., 2006) according to which dividend payments are taxed twice, at the corporate and at the investor level. At the corporate level, profits above 100,000,000 Rupiah27 are taxed at a tax-rate of 30%28 (PricewaterhouseCoopers, 2005). Profit distributions made thereof, are taxed again at the investor level at the personal income taxrate of the investor. To alleviate the tax collection, Indonesian companies have to withhold 15% of the dividend they distribute to resident shareholders, which is treated as a prepayment on

their

personal

income

tax

liability

(Deloitte

Touche

Tohmatsu,

2005,

PricewaterhouseCoopers, 2005). The following table illustrates the tax treatment of a profit distribution in Indonesia under the assumption of an average personal income tax-rate of 25%.

Corporate level Taxable income Corporate tax Net profit after tax

30%

100.00 30.00 70.00

Dividend payment Withholding tax Net dividend payment

15%

70.00 10.50 59.50

Investor level Taxable income Personal income tax 25% Less tax withheld Personal income tax payable

70.00 17.50 10.50 7.00

47.5029 52.50

Total taxes paid Net distribution to shareholders

27

Approximately 10,300 US-$ at the exchange rate prevailing at the end of 2005 (see Table1).

28

From 1997 to 2000, a taxable corporate income of 50 mio Rupiah or more was taxed at a corporate tax-rate of

30%. Starting from 2001, corporate income above 100 mio Rupiah is taxed at a rate of 30%. 29

47.50 = 30.00 corporate tax + 17.50 personal income tax.

34

Appendix 4 Over the whole sample period covered in this study, Malaysia employed a dividend imputation system according to which a company’s shareholders receive a tax credit for each dollar of dividends they receive and which have already been taxed at the corporate level (Petty et al., 2006). Resident shareholders can use those tax credits as an offset against their personal tax liability. The overall effect of this system is that dividends are taxed only once, at the personal level. The only tax change that occurred over the years from 1997 to 2005 was the reduction in the statutory corporate tax-rate on corporate profits from 30% to 28% in 1998 (KPMG, 2006, PricewaterhouseCoopers, 2006). The following table illustrates the tax treatment of a profit distribution in Malaysia after 1997 based on an average personal incometax-rate of 25% and by assuming that a company distributes it total profit.

Corporate Level Taxable income Corporate tax

28%

Net profit after tax

100.00 28.00 72.00

Investor Level Dividend income Imputation tax credit Taxable income Personal income tax Less credit for corporate tax Personal income tax payable

25%

Total taxes paid Net distribution to shareholders

72.00 28.00 100.00 25.00 28.00 -3.00

25.00 75.00

35

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