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4a Defining Leverage

6. Partial Adjustment and Capital Structure

To empirically assess adjustment of capital structure, i start with the two basic equations (i.e. market leverage and book leverage). However, market leverage is the main focus of this research. it it it it E D D Leverage M   _ (1)

19 it it it TA D Leverage B_  (2) Where: TAitTotal_Assets

yr LTD Total LTD Dit  _  _1 ice Close Out Shrs Eit  _ * _Pr

M_Leverage = Market leverage, and B_leverage = Book Leverage LTD_Total = Total Long-Term Debt

LTD_1yr = Portion of Long Term Debt due within 1 yr (i.e. reclassified from long term to short term liabilities)

Shrs_Out = Total Common Shares Outstanding

Close_Price = Closing Price of the firms‟ shares at the end of the year

Leading up to the main comparative dynamic partial adjustment model, I started with

heteroskedastic consistent ordinary least squares (OLS) to preliminarily investigate

the effect of capital structure determinants and their statistically differential effect on

leverage for DCs relative to MNCs. Thus, the following linear equation is used:

(3)

(4)

Where: i = 1, 2..., N, and t=1, 2..., T

X‟ = (Size, Tangibility (Tang), Agency Costs (Q), Profitability (ROA), Cash

Flows (FCF), Non-Debt Tax Shield (NDTS), Investment (INV), Financial

Distress Costs (FDC)) MNCs*X‟ = interaction term of MNCs and capital

structure determinants. The empirical results are reported at table 8 & 9.

it t it it it MNCs MNCs Leverage M _ 

0

1' 

2

3 *' 

it t it it it MNCs MNCs Leverage B_ 

0

1' 

2

3 *' 

20 Following prior work in dynamic trade-off framework [e.g., Jalilvand and Harris

(1984), Fischer et al. (1989), DeMiguel and Pindado (2001), Hovakimian, Opler and

Titman (2001), Fama and French (2002), Mehotra, Mikkelsen, and Partch (2003),

Strebulaev (2004), Frank and Goyal (2005), Drobetz and Wanzenried (2006),

Flannery and Ranjan (2006)], I consider a dynamic leverage model in which desired

(target) capital structure of firm

i

at time

t

, M_Leverage*it , is modelled as a linear

function of both N observed covariates, χ17

,

( j = 1,2...,N) and the unobserved firm

fixed effects 18. The N observed covariates, χ

,

are among the well research factors in the capital structure literature and are found to be related with target leverage in

gauging the trade-off between costs and benefits of debt of capital structure (Flannery

and Ranjan, 2006, and Frank and Goyal, 2005). Thus, target leverage is formalized in

equation 5 and 6.

(5)

(6) ηi is the firm specific effect (i.e. heterogeneity).

The coefficients and unobserved heterogeneity in equations 5 & 6 are unknown. Thus,

it is crucial to note that target debt ratio cannot be observe, and should therefore be

estimated. It is equally imperative to note that, in a trade-off framework, the target

17See appendix for a definition and list of variables.

18 Existence of firm specific effects (heterogeneity) has been shown to be

crucial in the dynamic capital structure model[Flannery and Ranjan (2006) and Lemmon, Roberts, and Zender (2006)].This is a plausible and substantive proposition, given the operational diversity and divergent competitive environment of firms. i N j jit it Lev erage M



1 * _ i N j jit it Leverage B



1 * _

21 leverage ratio is what firms‟ desire and would have chosen if the markets are perfect -

that is, the absence of informational gap, transaction premium or adjustment costs

related to issuance and retirement of debt and equity. However, in the presence of

friction in the capital market, firms‟ actual capital structure, will likely not equal the

target leverage ratio, i.e. M_Leverage*it ≠ M_Leverageit

,

implying that, in a normal

cause of events or a shock to the capital structure, firms temporarily deviates from the

target debt ratio and due to transaction costs, only partially adjust back to the target

debt ratio.

Following Flannery and Ranjan (2006), the baseline partial adjustment model is

formalized with equation 7 & 8, to estimate and determine the difference in capital

structure adjustment speed between MNCs and DCs.

_ * _ 1

,0 1

1 _

_LeverageitM Leverageit  M LeverageitM Leverageit it   M (7)

_ * _ 1

,0 1 1 _

_LeverageitB Leverageit  B LeverageitB Leverageit it   B

(8)

Where γ measuresthe speed of adjustment towards the target capital structure,

starting from prior year‟s leverage. In another words, γ

,

explains the actual change in observed leverage (M_Leverageit - . M_Leverageit-1) relative to the firm‟s distance

from its target leverage (M_Leverage*it - M_Leverageit-1).

In prior studies, γ< 1, due to frictions in the broader financial markets19. Due to the associated costs of adjustment, a delay in adjustment to target from period t – 1 to

19An imperfection in capital markets inevitably creates cost for firms which tempered the speed of adjustment to target leverage. This is so, as firms balance the cost of deviating from the target and the benefit of

22 period t is expected. From equation 7 & 8, if γ= 1, firms have instantaneously

adjusted 100% to optimal leverage within one year, and if

γ

> 1, then firms‟ have overshoot their adjustment and are not at optimal leverage. Effectively, the speed of

adjustment is the portion of deviation from optimal leverage that is been eliminated in

each period. From the above partial adjustment model, if there is a marginal increase

in prior year deviation from target leverage, the difference between current and prior

year leverage increases by the speed of adjustment, γ. It is very unlikely to have γit =

0, which means, there is no adjustment at all. From equation 7 and 8, substituting the

target leverage from equation 5 and 6 for M_Leverage*it and B_Leverage*it yields

equation 9 and 10.

(9)

(10)