“Target capital structure for managerial decision making: Dynamics and determinants”

The study examines the dynamics and determinants of target capital structures among manufacturing firms listed on the Nigeria Stock Exchange during the period from 2012 to 2021. The study is motivated by the disparity in the Speed of Adjustment (SOA) to target leverage, which is influenced by firm-specific attributes largely dependent on macroeconomic indices. Therefore, understanding the determinants of SOA to target leverage is germane because no two macro-economic environments are the same. A longitudinal research design is used with a population of 75 manufacturing firms. The sample consists of 42 firms, drawn using a simple random technique. Secondary data is sourced from the annual report. Generalized Method of Moments is the estimation technique. The result shows that manufacturing firms adjust to a target capital structure with a high speed of 72%. This confirms the application of dynamic trade-off theory among listed manufacturing firms in Nigeria. Profitability, firm size, and asset tangibility are significant determinants of SOA to a target capital structure, confirming pecking order, agency, and static trade-off theories, respectively. Tax shelter and growth were not significant determinants. The study concludes that there is evidence of dynamic adjustment to the optimal capital structure of listed manufacturing firms in Nigeria. Governments and policymakers in firms should make effective policies that aid speedy access to long-term funds by these firms to increase their SOA to target capital structure.


INTRODUCTION
Dynamic trade-off theory, which is in contrast to static trade-off theory, suggests that firms' financial behavior is represented by a partial adjustment towards target leverage that maximizes their worth when there is deviation.Graham and Harvey (2001) posit that financial managers should pursue a target capital structure.The dynamic trade-off hypothesis explains how businesses deviate from their target capital structure over time and gradually re-adjust to the balance (target leverage) when the benefit outweighs the cost.Therefore, when the cost of adjustment is cheap, firms will desire to re-balance to such a target, but the speed of adjustment (SOA) to the target capital structure differs (Mukherjee & Mahakud, 2010).This suggests that financial managers are likely to be deliberate in choosing the amount of debt and equity that maximizes the value of a firm.
Prior literature generally agrees that long-run target leverage exists and that firms converge to it at a particular SOA.However, the extent of the SOA to target leverage is still a subject of controversy (Elsas & Florysiak, 2011;Fannery & Rangan, 2006;Huang & Ritter, 2009;Ozkan, 2001).Several studies have discussed the disparities in the SOA to target capital structure in both developed and developing countries.The exogenous shocks that necessitate firms' deviation from a target capital structure vary between economies and across different companies.Therefore, it is unlikely for the SOA and the time for adjustment to a target capital structure to be the same.Suffice it to say that the exogenous shocks, which account for the disparity in the SOA to target leverage, are influenced by macroeconomic factors such as stock market performance and firm-specific attributes.Cook and Tang (2010) posit that firms adjust more quickly when economic conditions are favorable.Also, a firm's borrowing capacity could be influenced by less lending and higher borrowing costs during times of recession or economic meltdown (Harrison & Widjaja, 2014).Furthermore, research has demonstrated that economic conditions affect company characteristics and adjustment behavior even within a single country (Harrison & Widjaja, 2014;Loof, 2004;Iqbal & Kume, 2015).The disparity in the SOA and the time of adjustment to the target capital structure has germane implications for firm value.Identifying the desired capital structure maximizes a firm's value, which is the crux for management and investors.Therefore, in choosing the desired capital structure, financial managers must pay close attention to factors that affect the dynamics of the SOA.The differences in firm-specific characteristics are important in understanding the varying levels of SOA of firms to target capital structure.

LITERATURE REVIEW AND HYPOTHESES
A company's capital structure, according to Aljamaah (2018), is the company's long-term financial composition, which is generally made up of long-term debt and equity.According to Frank and Goyal (2009), capital structure theories are grouped into the static and the dynamic framework.While the static framework believes that firms are already operating at their target levels, the dynamic capital structure concept, on the other hand, asserts that companies that depart from their target leverage will make upward or downward adjustments back to their target capital structure (Chaklader & Jaisinghani, 2017;Dang & Garrett, 2015;Haron, 2014;Loof, 2004, Cook & Tang, 2010).The dynamic adjustment to this target capital structure takes into account how far firms have departed from their target capital structure over time and how quickly they are adjusting to it.The degree to which a company's capital structure deviates from its target leverage is categorized as either over-leverage or under-leverage, and these deviations affect the SOA at which the firm adjusts back to its target leverage (Abdeljawad & Mat Nor, 2017;Lemmon et al., 2008).In the same vein, Cook and Tang (2010) classify companies' financial conditions as being in financial surplus or deficit, and their existing leverage as being over-leveraged or under-leveraged in relation to their target capital structure.When macroeconomic risk is high and firm risk is low, firms with leverage levels over the target will adjust their capital structure more quickly, resulting in a greater SOA than under-leveraged firms.Abdeljawad et al. (2017) opine that businesses are motivated by the desire to shield themselves from financial limitations.Firms with financial deficits and debt levels below their target capital structure will try to change their capital structure when macroeconomic and company risks are minimal.
The SOA to a target capital structure differs between companies, even in the same industry and across different economies.(Ngugi, 2008); and the SOA for Indian listed companies is 50% (Bhaduri, 2002).The study proceeds to examine the firm-specific attributes of a target capital structure, such as profitability, firm size, growth opportunities, tax shield, and asset tangibility.
According to Chen and Hammes (2004), profitability refers to how well management utilizes all of its resources to make profits.The relationship between profitability and leverage is imprecise.
According to the static trade-off theory, profitable businesses can use more debt, since they face fewer chances of insolvency and financial difficulties.Profitable firms can borrow more money, and debt lenders will be more eager to lend to them because they have a lower risk of default than non-profitable businesses.In the same vein, Baral (2004) posits that profitable businesses have a larger incentive to use more debt to take advantage of loan interest tax shelters.Also, Hutchinson and Hunter (1995) document that profitable firms will exploit debt as a tax shield.The most significant advantage of debt is that interest payments are tax deductible, resulting in a tax benefit.Profitable businesses have more clout because they can take advantage of tax breaks.Another reason that successful companies may take on more debt is to save money on agency fees.Huang and Ritter (2009) report that debt is used to cut agency costs because it is linked to mandatory interest payments.Bauer (2004) posits that using additional debt restricts management's actions and that it is used as a tool to penalize managers in terms of free cash flow.
According to the static trade-off hypothesis, a high level of profitability leads to a high level of borrowing capacity, which reinforces the tax-shield advantage.Businesses with more profitability are likely to have a larger degree of leverage as a result of better lending capacity, reduced agency costs, and the benefit of tax shields, resulting in a positive relationship between profitability and capital structure.In order to control managers' behavior, agency cost theories predict that profitable organizations will take on greater debt in their capital structure.This implies that the more profitable a company is, the more debt it will accumulate.As a result, the trade-off theory suggests that profitability and capital structure are linked (Frank & Goyal, 2003).On the other hand, for corporations with significant retained earnings, gearing is less prevalent (Vasiliou et al., 2005).This implies that profitability and capital structure have a negative relationship.Most studies indicate a negative relationship between profitability and leverage, supporting the pecking order theory, which asserts that businesses prefer internal funding to borrowing from external sources (Baral, 2004;Booth et al., 2001;Drobetz et al., 2007;Fama & French, 2002).This implies that profitability and capital structure have a negative relationship.In order of choice, retained earnings are the most desired source of investment capital, followed by debt.While external funding is the most expensive source of financing, it will be a company's last resort.This implies that when profitable firms have larger retained earnings and choose to have less leverage, there is a negative relationship between profitability and leverage.The negative relationship between profitability and leverage has been confirmed by numerous studies ( Firm size is one of the most well-known determinants of capital structure.Vasiliou et al. (2005) report that the size of a company is proportional to the amount of risk it carries.Larger enterprises are less risky than smaller businesses.This implies that larger businesses are less likely to be declared bankrupt, resulting in lower financial distress costs, and are more likely to borrow money to fund their investment strategies.According to Ezeoha and Francis (2010), larger, well-known enterprises have better access to the capital market and stock market than smaller businesses.This is because the chances of a larger company defaulting are far lower than the chances of a smaller company defaulting.Due to their higher credit ratings, larger companies have a better reputation in the security market because they are more secure and are more likely to receive financing from financial institutions more frequently and at cheaper interest rates than smaller businesses.Small businesses may be unable to get long-term loans, since their growth potential exceeds the quantity of assets that can be used as security.Smaller businesses will borrow less, since they are more likely to fail, resulting in higher capital costs.Bauer (2004) claims that larger organizations have less asymmetric information.The general public is more aware of what is going on because larger corporations tend to release more information than smaller companies.This implies that asymmetry is lessened, and the chances of an undervalued new stock offering are reduced, encouraging larger enterprises to use equity financing.Based on the knowledge of asymmetry described above, a negative association can be predicted.In the same vein, the static trade-off theory argues that the relationship between company size and capital structure is positive because large organizations are more diversified, have lower transaction costs for issuing more shares, and are less likely to collapse than smaller ones.Frank and Groyal (2008) report that large organizations use debt more frequently to finance new initiatives, while small firms utilize equity more frequently, implying a proportional relationship with leverage.Similarly, Ege and Bayrakdaroglu (2013) claim that larger Turkish firms have a greater debt ratio than smaller firms.In the same vein, the study by Alipour et al. (2015) on the determinants of Iranian enterprises' capital structures finds a positive relationship.
A firm's growth opportunity is a significant factor in corporate finance.Modigliani and Miller (1958) posit that for a company with significant growth potential, owners may initially finance a new project with debt, but once it has proven viable by increasing actual earnings, the loan may be repaid by supplying shares at higher prices or reserves, resulting in a positive relationship.High-growth enterprises have higher long-term finance requirements and tend to hold more earnings (Pandey, 2001).
Companies with rapid sales growth often need to expand their fixed assets.To maintain the target debt ratio, a company must issue more debt as it grows, implying a significant correlation between capital structure and company growth.Byoun (2008) reports that growth opportunity and capital structure have a positive relationship.He claims that if a corporation has room to grow, it will require additional funds to accomplish it.The com-pany will be forced to take on more debt due to a lack of internal resources.Dasgupta  Below is a summary of the relationship between the independent variables and the dependent variable using the dynamic trade-off, trade-off, pecking order and agency theories.
Based on the extant literature, understanding the behavior of SOA with respect to firm-specific factors is germane for financial managers in formulating financial policies that will maximize the value of the firm.Therefore, the purpose of the study is to examine the firms' specific determinants of SOA to target capital structure among manufacturing firms listed on the Nigerian Stock Exchange (NSE) during the period 2012 to 2021.

The study formulates the following hypotheses:
H 01 : There is no significant level of dynamic adjustment to target leverage among manufacturing firms listed on the NSE.
H 02: Profitability has no significant relationship with SOA to the target capital structure of manufacturing firms listed on the NSE.
H 03: Firm size has no significant relationship with SOA to the target capital structure of manufacturing firms listed on the NSE.

METHODS
The where LEV* = target leverage, i =firm, t = time, X = firm attributes.
Since the target leverage is unobservable, it is proxied using fitted values from a regression of observed leverage.It can be expressed mathematically below: where LEV is the current leverage of the firm, while LEV it-1 is the 1-year lag leverage of the firm.
The standard partial adjustment model requires the following to capture the dynamic adjustment to a target leverage: ( ) where y is the adjustment required to reach a target leverage, the coefficient of the y measures the SOA to a target leverage, which is inversely related to the cost of transaction or the cost of adjustment.y takes the value between 0 and 1.It is 1 when a full adjustment occurs, which is hardly the case because no market is perfect, while y = 0 implies the absence of adjustment, which also hardly occurs.This implies that the partial model adjustment lies between 0 and 1.As a result, the SOA to a target leverage is given as 1 -y, and the time required to achieve that adjustment is given as 1/1-y.Equations ( 2) and ( 3) are written thus: Note that when y = 0, it implies that there is no adjustment to target leverage.That is, current leverage is equal to a one-year leverage lag (LEV it = LEV it-1 ).The reason for the non-adjustment could be high transaction costs.Therefore, they would want to maintain the current position.If y = 1, it shows adjustment.This implies that target leverage becomes the same as current leverage (LEV it *= LEV it ).This adjustment is due to the low transaction cost.When the target leverage, denoted as LEV it -LEV it-1 , is substituted into LEV it * = LEV it , we will have LEV it -LEV it.-1= LEV it.This can be rearranged as LEV it -LEV it = LEV it-1 .Therefore, LEV it = LEV it-1 .To estimate the partial adjustment model using only one equation, we have: Given that SOA to a target leverage is 1 -y, the equation is as follows: Where β= the unknown coefficient of variables, X it = the explanatory variables.The explanatory variables for this study are profitability (PROF), firm size (FS), growth opportunity (GROWTH), asset tangibility (TANG), and tax shield (TS).In inserting this variable into equation (vii), we have: ( )

RESULTS AND DISCUSSION
The presentation, analysis, and interpretation of the data stream collected for this study is the focus of this section.Consequently, it embodies the application of both statistical and econometric techniques to provide the basis for the research hypotheses testing and form the basis for the conclusion and recommendations at the end of this study.Table 2 reveals that the Instrumental Variables (IV) use are valid and satisfactory as indicated by the Sargan test (J-statistics value) of 17.61 approximately and it is highly not significant at a 5% confidence level with the related rank instrument of 21.This implies that the orthogonality condi-tions for the IV are used to satisfy their conditions and they are exogenously related to their stochastic error term.AR (2) coefficient is not significant at a 5% confidence level.This implies that there is no second-order serial correlation in the estimate, making the result more reliable and authentic for policy formulation.All the explanatory variables have a significant relationship with leverage when jointly considered as indicated by the Wald test F-statistics that is significant at a 5% confidence level.Only TS and GROWTH did not pass their significance test at a 5% confidence level, since their corresponding Prob.values are > 5%.Other independent variables pass their significant test at a 5% confidence level because their corresponding probability value is < 5%.The coefficient values in Table 2 show that the entire explanatory variables have various degrees of association with leverage, although in different magnitudes.Only LEV (-1) and TANG have a positive impact on leverage, while other variables inversely impacted leverage during the study period.Hence, the null hypotheses H 01, H 02, H 03 and H 06 are rejected, while H 04 and H 05 are accepted.
Also, it was determined that manufacturing firms fail to cover only 28% deviation from the desired capital structure decisions from the past period to the current period at a 5% confidence level as indicated by the lag LEV(-1) coefficient of 0.28 approximately.This implies that manufacturing firms adjust to their desired capital structure with a high speed of about 72%.This SOA was achieved within the period of one year, three (3) months, and nine (9) days.1/0.72 = 1.39.This finding also buttresses that manufacturing firms in Nigeria adjust partially and not instantaneously to achieve their expense re-balancing objective.Also, the high SOA is attributed to the benefit of adjustment being perceived as higher than the cost of adjustment (Flannery & Rangan, 2006;Tamirat et al., 2017), coupled with the fact that the cost of adjustment among manufacturing firms is minimal (Devos et al., 2017).This finding is of serious policy implications that government financing policy formulation and management implementation of such policies in this sector is going in the right direction.The finding is in tandem with that of Ngugi (2008), Ramjee and Gwatidzo (2012) in the literature, who report 65% and 71% SOA in South Africa and Kenya, re-spectively, and conclude that non-financial firms in developing economies are more responsive.
The study also finds that PROF, FS, and TAN are significant determinants of SOA to the desired capital structure of listed manufacturing firms in Nigeria.First, PROF did not conform to the trade-off and agency theories because it was not correctly signed.However, being negatively correlated is in conformity with the pecking order theory.Therefore, it is safe to say that it meets a priori expectations, since it satisfies one of the theories in the study.The coefficient is negative and significant at a 5% confidence level.This implies that a unit increase in PROF reduces SOA to the desired optimal capital by approximately 30%, as indicated by its coefficient of -0.30.This finding demonstrates that Nigerian manufacturing firms are profitable; the more profitable they become, the less desire they have to use debt in their financing decisions.Therefore, upholding the assertion of the pecking order theory.This finding is in line with that of Booth et al. (2001), Fama and French (2002), Baral (2004), and Chen and Strange (2005) in the literature that suggests businesses prefer internal funding to borrowing from external sources in both developed and emerging economies.This finding is contrary to that of Frank and Goyal (2004), who uncovered a positive association between profitability and leverage to confirm the trade-off theory.
Second, FS has a significant inverse impact on SOA on the target capital structure of listed manufacturing firms in the NSE.This variable behaves contrary to the predictions of the trade-off theory.Rather, it confirms agency theories' prediction of the inverse relationship between FS and a firm's leverage.Therefore, it is safe to say that it meets a priori expectations, since it satisfies one of the theories in the study.The negative coefficient of -0.094 approximately shows that a unit increase in FS significantly reduces SOA to the desired LVR by 9% approximately.This inverse relationship is attributed to high earnings that are associated with large firms, due to their less desire to finance investment with more debt because they are highly diversified.Also, larger companies tend to disclose more, and, as such, stakeholders have sufficient information about them.This reduces information asymmetry, which favors equity financing.Similarly, the difficulty in accessing longterm loans in Nigeria could also be a fundamental factor why firm size is negatively correlated.This finding corroborates that of Myer (1984), Titman and Wessel (1988), who also found a similar result in their study that FS is a significant determinant of capital structure.However, this finding is contrary to that of Vasiliou et al. (2005), Rayam and Zingaales (2015), and Frank and Groyal (2008), among others.
Third, asset Tangibility (TANG) has a significant direct impact on SOA and the optimal capital structure of manufacturing firms listed on the NSE.The variable conforms to the static trade-off theory.A unit increase in TANG will result in an 11.87-unit increase in SOA to satisfy the desired capital structure.This finding corroborates that of Frank and Goyal (2004) Tax shield (TS) has a non-significant inverse impact on SOA to target leverage.This is not in line with the a priori expectation.The inverse relationship implies that an increase in the tax shield decreases SOA to the target capital structure in an insignificant manner at a 5% confidence level.This could be attributed to the high debt tax shield among Nigerian listed manufacturing firms.This finding is in line with that of Mbulawa (2014), who found that firms with high tax shields and marginal tax rates use lower debt.Similarly, growth opportunities (GROWTH) have a non-significant negative correlation with SOA to the desired capital structure of manufacturing firms listed on the NSE.This variable conforms to a priori (trade-off argument) expectation, but it is not significant at a 5% confidence level.The finding is contrary to that of Benuo (2003) and Billet (2007), who report a positive relationship between growth and leverage.From the empirical result, it is observed that the trade-off theory and pecking order theory suggestions are endemic in the financing decisions of manufacturing firms listed on the NSE; and policy direction has been effectively implemented to encourage various stakeholders to manage a firms' activities to maximize shareholders' wealth.

CONCLUSION AND RECOMMENDATIONS
The study investigates the level of SOA to desire capital structure and its determinants for manufacturing firms listed on the NSE.Panel data consisting of forty-two (42) listed manufacturing firms within the period 2012 to 2022 is collected from the audited annual publication of each firm as published by the NSE.Several statistical and econometric techniques of descriptive statistics, correlation analysis, panel group unit root test, Kao and Pedroni co-integration test, and System GMM methodology within a dynamic panel estimation process are used.The result shows that manufacturing firms adjust with a high speed of approximately 72% to desire capital structure after deviation.Thereby, confirming the application of dynamic trade-off theory among listed manufacturing firms in Nigeria.Also, PROF, FS and TANG are shown to be significant determinants of SOA to desire capital structure in Nigeria, with PROF, FS and TANG in line with pecking order, agency and static trade-off theories, respectively.TS and GROWTH were not significant determinants of SOA to target capital structure.The study concludes that there is evidence of dynamic adjustment to the optimal capital structure of listed manufacturing firms in Nigeria.
Various policy recommendations are based on the findings of this study as follows: (i) government and policymakers in firms should make effective policies that aid speedy access to long-term funds by these firms to increase their SOA to target capital structure; (ii) managers of manufacturing firms must strive to balance the cost and advantage of using the marginal unit of debt to maximize shareholder's wealth; (iii) regulatory authorities like the Security and Exchange Commission (SEC), and the NSE should implement policies which would enable manufacturing firms to increase cash inflow, and reduce the cost of debt and bankruptcy risk in the sector to signal to investors that listed manufacturing firms are financially independent; (iv) manufacturing firms that lack tangible assets should be assisted by the government to increase their long-term debt-absorbing capacity; (v) managers should be effective and efficient in using their size to access long-term debt in the stock market to take advantage of the tax shield to maximize firm value; and (vii) in the face of future growth opportunities, reliable evaluation techniques should be employed by manufacturing to identify profitable investments and finance such investments with long-term debt.Note: * and ** = 1% and 5% level of significance.
, Vasiliou et al. (2005), and Drobetz et al. (2007) in the literature; they found a positive nexus between TANG and leverage to back up the trade-off theory.
This study supports the theory that the larger the non-debt tax shield, the smaller the tax benefits from interest deductions.Enterprises with a high tax shield and marginal tax rate, according to Mbulawa (2014), use less debt in their leverage structure.Lei (2020) investigates the influence of the tax shield on the capital structure of businesses in China and finds a negative relationship between the non-debt tax shield and capital structure.The trade-off theory shows that a corporation with a high tax rate should take on greater debt so that it can deduct more tax from its income.
(Akhtar 2005., 2001;Vasiliou et al., 2005)the study byAwan et al. (2010)on the influence of growth potential on leverage of Pakistani manufacturing firms finds a positive relationship.On the contrary, companies that are experiencing rapid growth, in line with trade-off theory, will take on less debt because the value of their future growth potential is close to zero in the event of bankruptcy.Firms with high future investment prospects invest more to protect their loan capacity and financial slack or liquidity while keeping low leverage.A tax shield lowers the effective marginal tax rate on interest deductions.A company with a big nondebt tax shield is less likely to take on debt(Fisseha 2010).This is due to the fact that, unlike dividends, interest on debt is a tax-deductible expense (Odunai et al., 2013).Odunai et al. (2013) also report that firms with a large non-debt tax shield will choose to be debt free.When firms choose to take on greater debt, they benefit from the hightio.Tesfaye and Mings (2013) report that the relationship between the non-debt tax shield and the capital structure varies by tax type; they believe it has a negative influence on short-term debt but a Investment Management and Financial Innovations, Volume 19, Issue 3, 2022 http://dx.doi.org/10.21511/imfi.19(3).2022.27beneficialimpact on total leverage.A company's asset structure has a significant impact on its capital structure.Companies having a lot of tangible assets have a greater liquidity value and will be able to provide more debt collateral.A similar relationship is suggested by the agency theory.The cost of equity is reduced when debt is secured by a tangible asset owned by a corporation(Booth et al., 2001;Vasiliou et al., 2005).Assets show a company's defining features(Akhtar 2005).