Financial distress and restructuring strategies of Vietnamese firms by lifecycle

hey depend on each stage of corporate lifecycle. According to Mueller (1972), investors are hesitant to invest funds in young firms because the firm risks in this stage are too great. This implies restructuring of external funding is not the firm's preferred choice at birth stage and distressed firms in the birth stage are less likely to use it. In addition, firms in bith stage have a high ownership concentration, the directors are also owners so the firms have less pressure to change the management team. Instead, firms in this stage invest more assets to expand their business (Bowman and Singh, 1993), they are less likely to reduce assets and use M&A. Asquith et al (1994) argue that banks would loosen loan constraints for mature firms having finanical problems because banks believe in the firm age and firm scale of these firms. Therefore, compared with the distressed firms at the other stages of lifecycle, mature firms in distress are more likely to use debt based strategy. 2.4. Literature Review 2.4.1. Financial distress and restructuring strategies Managerial restructuring: Jensen (1989) argues that financial distress is the incentive for distressed firms to enhance actions to improve performance. Incompetent managers can make the wrong decisions, ruin performance of firms, so they must be replaced by new management teams to re-evaluate the cause of financial distress and reorient, implement strategies to revive the firms (Lohrke et al, 2004). Gilson (1989) argues that any change in the members of management (CEO) is considered to be a change in management division. Operational restructuring strategies aim to restore profitability and stabilize operations by pursuing strict cost reductions, reducing 7 overheads, such as: reducing investment, reducing cost of goods sold (Koh et al, 2015), laying off employees (Sudarsanam và Lai, 2001; Atanassov and Kim, 2009; Koh et al, 2015). It is a way to create cash flow quickly for a firm in short term. Asset restructuring allows a firm to re-evaluate unprofitable assets, or assets that do not create profit for the firm, so these assets need to be sold when in financial distress (Koh et al, 2015). Asquith et al (1994) argues that asset sales are an important way of resolving financial distress. Distressed firm can use the funding from the assets liquidation for loan payment, it helps distressed firm to reduce the pressure cash flow. Financing restructuring strategies are the process of organizing and changing in the firm’s capital sources to meet the operations of the firm. Sudarsanam and Lai (2001) argues financing restructuring strategies are considering firm’s capital structure to reduce payment pressures through equity-based and debt-based strategies replacement when in financial distress. Equity-based strategies involve dividend cuts to retain internal funding or issuarance of shares. DeAngelo and DeAngelo (1990), John et al (1992), Sudarsanam and Lai (2001), Koh et al (2015) find that the majority of companies when in distress are likely to cut dividend payments. In addition, the distressed firms can issue more shares because they are under pressure from creditors to ensure the safety of debts. On the other hand, by issuing equity, distressed firms can increase capital to improve their performance. Gilson (1989, 1990) defines debt-based strategies involve the replacement with new loan contracts or adjustment terms of credit contracts or conversion of debts (Kam et al, 2008). Equity-based and debt-based strategies focus on the external capital to restructure their financial resources. Therefore, financing restructuring strategies 8 generally refer to cut dividends, debt-based strategy, issue equity. M&A restructuring strategy: Schendel et al (1976); Slatter (1984); Sudarsanam and Lai (2001) approach acquisition of another firm as a new method of investment when in distress. Meanwhile, Clark and Ofek (1994), Kam et al (2008) define M&A (Mergers and Acquisitions) as an independent strategy for corporate restructuing. In this research, I study M&A deal as an independent strategy of a firm. Not all M&A deals success, sometimes some M&A deals do not successful restructure a distressed target for both parties. Clark and Ofek (1994) study the effectiveness of corporate strategy through M&A deals of distressed firms, they find that acquire firms had negative performance after the implementation of M&A. 2.4.2. The impact of financial distress, lifecycle on corporate restructuring strategies Miller and Friesen (1984) argue that firms in birth stage have a high ownership concentration, the managers are also the owners. Therefore, these firms have less external pressure for a change in management when in financial distress, meaning that firms in birth stage are less likely to select managerial restructuring when in financial distress. However, in the later stages, the ownership structure and operating structure of firms are more complicated, there is a gradual separation between ownership and management rights, the firms’capital structure are more complicated because of leverage. Managers can be fired when they are incompetent to run the business and the company must replace the new management under pressure from outside investors. Kang and Shivdasani (1997) find that a positive relationship between the replacement of senior managers, and the presence of outside blockholders and creditors. Brown et al (1994) 9 suggest that initially, distress firms’shareholders are less incentive to sell assets because of the centralized ownership structure. However, in the later stages when the firm uses debt and there is a gradual separation between ownership and management rights, asset restructuring strategy is more likely chosen because creditors will pressure to sell assets for payment. Kang and Shivdasani (1997) find that the probability of asset restructuring strategy, laying off employees selected by Japanese companies will increase as the existence of outside blockholders and bankers. Koh et al (2015) find that compared with distress firms at other stages of lifecycle, those in the birth stage are less likely to reduce cost of goods sold. However, laying off employees is used throughout the lifecycle stages when in distress. Koh et al (2015) also find that compared with distress firms at other stages of lifecycle, distressed firms in the decline stage are more likely to cut dividend to preserve internal funds. Besides, distressed firms in the birth stage are less likely to use debt. Healy et al (1992), Clark et al (1994), Sudarsanam and Lai (2001), Kam et al (2008) demonstrate that firms are likely to select M&A deal when in distress. 2.4.3. The likelihood of recovery Many studies not only investigate firms’restructuring strategies when in financial distress, but also they analyze the likelihood of recovery. Kang and Shivdasani (1997) find that the reduction of employees helps to improve performance in Japanese. Asset restructuring is found to be effective strategy by Denis and Kruse (2000), which improves performance of firms, stock prices in the stock market respond positively; in contrast, cost cutting and employee layoffs are not effective for firms. Sudarsanam and Lai 10 (2001) find that recovery firms adopt growth-oriented and external- market focused strategies. Non-recovery firms are more likely to engage in cutting dividend and issuing shares. The similarity in these studies is that the authors did not investigate the likelihood of recovery in the relation to the lifecycle and restructuring strategies. Although Koh et al (2015) study a combination of restructuring strategies and lifecycle theory, but there is little influence of lifecycle. This is the limit of results. Koh et al. (2015) find that reducing investment and are associated with the recovery for distressed firms. In contrast, increasing debt reduces the likelihood of recovery. Based on the summary of the theoretical framework and literature review, this study finds research gaps (as presented in chapter 1); since then, it is the motivation to research this thesis, presented in the next chapter. CHAPTER 3: METHODOLOGY AND RESEARCH DATA 3.1. Research hypothesis H1: Firms are more likely to use restructuring strategies when in financial distress. H2: Distressed firms’restructuring strategies are associated with lifecycle. H3: Restructuring strategies used by distressed firms have a positive association with recovery. 3.2. Research methodology 3.2.1. Identify firm that is financially distressed The definition of financial distress in this study is based on two approaches: corporate financial data and market data. Based on corporate financial data, this research uses operating income conditions, conditions for payment of debt obligations. A firm in the current year (year t) is classified as financial distressed if: (i) the firm’s 11 operating income is negative in the three consecutive years (Gilbert et al, 1990; Denis and Denis, 1995; Denis and Kruse, 2000); or (ii) the firm’s earnings before interest, taxes, depreciation and amortization (EBITDA) is less than its interest expense in the two consecutive years (Asquith et al, 1994). The minimum of two consecutive years is also used by Robbins and Pearce II (1992), Koh et al (2015) to measure financial distress. FDit is the dummy variable for a distressed firm and takes the value 1 if a firm is distress and zero otherwise. The thesis also use alternative way to identify financial distress based on market data of firms according to KMV-Merton model. KMV-Merton model based on the basis of Merton model (1974). This model considers asset volatility, with two important assumptions: the firm's asset market value moves in accordance with the Brown geometry and this company only has one type of debt with maturity date of T. The equity market value of this firm can be considered as a call option over the total value of the firm's assets with the strike price being the value of debt with the maturity date is T. Financial distress occurs when the value of the firm's asset market is less than the value of its debt at due date. Therefore, probability of financial distress is the probability that the market value of assets will fall lower than the value of debt at time T. This thesis uses method of Bharath and Shumway (2004, 2008) and Newton Raphson algorithm of Haidar (2010) through Matlab software to calculate the probability of financial distress. FDit is the dummy variable for a distressed firm and takes the value 1 if a firm is distress, has N(-d2) ≥ 0,5 and zero otherwise. 3.2.2. Identification of lifecycle This study adopt methods of Anthony and Ramesh (1992), Koh et al (2015) to classify a firm into the four lifecycle classifications: birth, 12 growth, maturity and decline, based on the following four lifecycle descriptors: (1) annual dividends, (2) percentage of sales growth, (3) capital expenditure and (4) firm age. This study control for industry effects when grouping firms into the four lifecycle categories. The four lifecycle descriptors (for each industry) are calculated for each year for each sample firm. First, using industry group, I split observations (firm-year) of each lifecycle descriptor into quartiles and group the firms by lifecycle category. Next, for each quartile is named a score, I base on cut off value of each quartile to compare the value of each observation. In case of annual dividend and firm age indicators: firm-year observation values less than Q1=1, between Q1 and less than Q2 =2, between Q2 and less than Q3=3, equal to Q3 and above =4. By contrast, in case of percentage of sales growth and capital expenditure indicators: firm-year observation values less than Q1=4, between Q1 and less than Q2 =3, between Q2 and less than Q3=2, equal to Q3 and above =1. Then, I sum up the scores of four lifecycle descriptors for each firm year and split all observations into quartiles again. After that, I base on cut off value of each quartile to classify four stages of lifecycle: firm-year observation values less than Q1 (lowest score value): birth stage, between Q1 and less than Q2 = growth stage, between Q2 and less than Q3=maturity stage, equal to Q3 and above (highest score value) = decline stage. 3.2.3. Identification types of restructuring strategies Managerial restructuring: the dummy variable CEO denote managerial restructuring, takes the value 1 if a firm has replaced one of its top management during the financial distress period (year t) in distress (the reason for leaving and age of management are examined 13 to ensure that a replacement is not due to illness, retirement or death), and zero otherwise. Operational restructuring strategies include reducing investing activities (INV), reducing the cost of goods sold (COG), laying off employees (EMP). Dummy variable INVit takes the value 1 if the distress firm’s net cash from investing activities in year t (in distress) is less than the industry mean, and zero otherwise. Dummy variable COGit takes the value 1 if the distress firm’s cost of goods sold (scales by net sales) in year t (in distress) is less than the industry mean, and zero otherwise. Dummy variable EMPit takes the value 1 if the distress firm’s number of employees in year t (in distress) is less than the industry mean, and zero otherwise. Asset restructuring: Comparing a decline in a company's net tangible fixed assets to the industry mean of net tangible fixed assets. Dummy variable ASSETit takes the value 1 if the distress firm’s net tangible fixed assets in year t (in distress) is less than the industry mean, and zero otherwise. Financing restructuring strategies: include cutting or omitting dividends (DIV), using debt (NetDebt), issue new equity (NetEquity). Dummy variable DIVit takes the value 1 if the distressed firm ommit dividends or the distress firm’s dividends in year t (in distress) is less than the industry mean, and zero otherwise. Dummy variable NetDebtit takes the value 1 if the distress firm’s net debt in year t (in distress) is more than the industry mean, and zero otherwise. Dummy variable NetEquityit takes the value 1 if the distress firm’s net equity in year t (in distress) is more than the industry mean, and zero otherwise. M&A restructuring strategy: This study observes successful M&A deal negotiations and considers target firm and acquiring firm in 14 sample Vietnamese firms. Dummy variable M&Ait takes the value 1 if the distress firm in year t (in distress) has successfully traded M&A deal, and zero otherwise. 3.2.4. Identification recovery firms To investigate the likelihood of recovery for firms, for the sample of distress firms only, this study continue to examine the effectiveness of restructuring strategies used. This research identifies a recovered firm as one that: - The distance to distress increased in two consecutive years after the year in distress (or N (-d2) <0.5 in the two consecutive years after the year in distress) (in case financial distress is determined according to KMV-Merton model). - At least three consecutive years of positive operating income (t+1, t+2, t+3) after the year in distress or EBITDA is more than interest expense in the 2 consecutive years (t+1, t+2) after the year in distress (in case financial distress is determined according to corporate financial data) Dummy variable Recoveryit takes the value 1 if a distress recovers from distress, and zero otherwise 3.2.5. Control variables: Control variables include TobinsQ, LnAsset, Institutional, Volatility, Return, Leverage and CashFlow, respectively, control for growth opportunities, size effects, institutional ownership, firm’s risk, firm’s stock returns, firm’s financial leverage and firm’s cash flow. 3.3. Research models 3.3.1. The impact of financial distress, lifecycle on restructuring strategies 15 Model examines the impact of financial distress on restructuring strategies: Restructuringit = α1+ α2Birthit + α3Growthit + α4Matureit + α5FDit + α6Birth*FDit + α7Growth*FDit + α8Mature*FDit + α9TobinsQit + α10LnAssetit + α11Institutionalit + α12Volatilityit + α13Returnit + α14Leverageit + α15CashFlowit + εit (3.6) Model (3.6) to answer the first and second questions of this research. Dummy variable Restructuringit takes the value 1 if the distress firm uses restructuring strategy and zero otherwise. The restructurings include managerial restructuring (CEO), reducing investing activities (INV), reducing cost of goods sold (COG), laying off employees (EMP), asset sales (ASSET), dividend cuts (DIV), using debt (NetDebt), issue of equity (NetEquity), M&A restructuring (M&A). Birth variable takes the value 1 if a firm is in birth lifecycle and zero otherwise. Growth variable takes the value 1 if a firm is in growth lifecycle and zero otherwise. Mature variable takes the value 1 if a firm is in mature lifecycle and zero otherwise (decline stage is base group). 3.3.2. The likelihood of recovery for financial distressed firms Model examines the likelihood of recovery for distressed firms: Recoveryit = α1+ α2BirthitFD + α3GrowthitFD + α4MatureitFD + α5RestructuringitFD + α6Birth*RestructuringitFD + α7Growth*RestructuringitFD + α8Mature*RestructuringitFD + α9TobinsQitFD + α10LnAssetitFD + α11InstitutionalitFD + α12VolatilityitFD + α13ReturnitFD + α14LeverageitFD + α15CashFlowitFD + εi (3.7) Model (3.7) to answer the third question of this thesis. Dummy variable Recoveryit is represented the recovery of the financial distress firm. The Restructuring variable is defined as a model (3.6). 16 3.4. Research methodology To test the models (3.6) and (3.7), this study run the following panel logit regression with random effects and fixed effects, based on MLE. Using the Hausman test, this study select the panel logit regression with random effects. Besides, this study uses bootstrapped standard errors to ensure the estimated coefficients are robust. 3.5. Research Data The study uses the sample consists of 526 Vietnamese non – financial listed firms, for the period 2005 - 2016. Firms are classified according to the Industry Classification Benchmark (ICB). Data collected from vietstock, vndirect, IFS database of IMF. M&A data taken from Zephyr data. In addition to mitigating the effect of outliers, data is subtracted by 1% (winsorized) at each tail of distribution. CHAPTER 4: RESULTS AND DISCUSSION The results of sections from 4.1 to 4.5 are summarized in Table 4.10: 4.1. The impact of financial distress, lifecycle on managerial restructuring In column 2, the coefficient of birth is -0.456 and significant, indicating that, compared with firms at other stages of the lifecycle, those in birth stage are less likely to engage in managerial restructuring, consistent with the viewpoint of Miller and Friesen (1984). This indicates that at the birth stage, due to the high concentration of ownership, the manager is also the owner, so the companies are less exposed to outside pressure to replace management human. However, firms in distress are likely to engage in managerial restructuring (the coefficients of FD in column 1 and 2 are respectively 2,4349 and 0,6817; and significant). The results of this thesis are consistent with the findings of Koh et al (2015) and prior studies of 17 Hofer (1980), Pearce and Robbins (1993), Sudarsanam and Lai (2001), Kam et al (2008), Atanassov and Kim (2009). The replacement one of top management when firms face financial distress is the evidence that Vietnamese firms adopt to restructure from management teams. This is a positive signal to improve their performance. 4.2. The impact of financial distress, lifecycle on M&A restructuring: In column 3, the coefficient of the interaction of Mature and FD is -0,8834 and significant, this suggest that compared with distress firms at other stages of lifecycle, those in the mature stage are less likely to engage in M&A restructuring. Because mature firms do not have many opportunities for investment, less effective performance and when mature firms face financial distress, they are more afraid of the likelihood of success from M&A deal. Therefore, those firms are less likely to engage in M&A restructuring. 4.3. The impact of financial distress, lifecycle on operational restructuring: This study finds that Vietnamese firms in distress are more likely to engage operational restructuring: reducing investment activities, laying off employees (the coefficients of FD in column 5 and 6, 9 and 10 are positive and significant). By reducing investment activities, distress firms focus on core investment portfolio to enhance profitability for firms, reduce operation. By reducing investment activities, distress firms can control and reduce fixed costs. Laying off employees is considered as a “belt tightening” policy because it does not require capital or resources. However, if laying off employees is used regularly will cause a great loss for the company in terms of human resource training policy. Reducing cost of goods sold may not be viable for firms in distress. This thesis also finds that mature firms 18 in distress are less likely to lay off employees (the coefficient of the interaction of Mature*FD is negative in column 10). Meanwhile, distressed firms in the birth stage and growth stage are less likely to reduce investment activities (both coefficients of the interaction of Birth*FD, Mature*FD are negative, and significant in column 6). 4.4. The impact of financial distress, lifecycle on asset restructuring: This study finds that firms in distress are more likely to engage asset restructuring (the coefficients of FD in column 10 and 12, are respectively 0,4236 and 0,7253). This results are consistent with the findings of Koh et al (2015), Kam et al (2008). This finding implies that financial distress caused Vietnamese companies to make decisions to sell off ineffective assets, re-orient core portfolio to create competition in the market (Shleifer and Vishny, 1992; Koh et al, 2015). The liquidation of assets, the sale of projects with low profitability helps the company get cash, resolves financial difficulties, reduce pressure on distress firm’s cash flow. 4.5. The impact of financial distress, lifecycle on financial restructuring This study finds that firms in distress are more likely to cut or ommit dividends, use debt and issue equity (the coefficients of FD in column 13 and 14, column 16, column 17 and 18 are positive). Reducing dividends help distressed firms retain internal funding. Using external financing from debt, new equity help distressed firms to raise capital, maintain operations and overcome financial difficulties. When combining the relationship with the lifecycle, this study finds that compared with the distressed firms at other stages of lifecycle, mature firms in distressed are less likely to use debt (the coefficient of the interaction of Mature*FD is negative in column 16). 19 According to lifecycle theory, the study argues that the market share of firms begins to decline, and when there are large fluctuations in financial risks, banks will tighten loans to limiting risks affecting bank benefits. Besides, distressed firms in growth stage are less likely to engage in dividend cuts (the coefficient of the interaction of Growth*FD is negative and significant in column 14). 4.6. The impact of corporate restructuring strategies on the likelihood of recovery The details are presented in table (Table 4.23). This study finds that managerial restructuring, reducing investments, assets restructuring and reducing dividend payments have statistically significant positive associations with recovery for distress firms (the coefficients for Resructuring in columns 2, 5 and 6, 12, 13 and 14 are positive and significant). The result indicates that changes in top management in distressed firms play an important role, analyze the current state of distressed firms, they suggest new directions and specific plans to revive firms; This result is consistent with the findings of Hofer (1980), Gopinath (1991), Pearce and Robbins (1993), Lohrke et al (2004). Reducing investment activities, asset restructuring and reducing dividend pay