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Customer Finance Programs Key to Increasing Technology Sales

Customer Finance Programs Key to Increasing Technology Sales

Customer Finance Programs Key to Increasing Technology Sales


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Home Page > Finance > Credit > Customer Finance Programs Key to Increasing Technology Sales

Customer Finance Programs Key to Increasing Technology Sales

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Customer Finance Programs Key to Increasing Technology Sales

By: RJ Grimshaw

About the Author

(ArticlesBase SC #2362978)

Article Source: http://www.articlesbase.com/ - Customer Finance Programs Key to Increasing Technology Sales





While studies show that technology spending is once again on the rise, there's a reason you haven't heard a collective sigh of relief from the software industry. While many budgets are once again allowing for the purchase of enterprise software, hardware and peripherals, there's no question that today's purchasers are smarter, savvier and more selective than ever.

Even though the purse strings have loosened, competition is at an all-time high. It's no longer enough to provide a software solution that meets the potential customer's needs, or even to provide it at the best price. Today, smart vendors are constantly looking for ways to stay one step ahead of the competition.

While increasing sales is always part of a competitive business strategy, software development companies often overlook a simple method of accomplishing this objective - making it easier for customers to buy.

One option increasing in popularity among software vendors is to establish a customized finance program that provides no-hassle financing solutions for your prospective clients. In addition to "one-stop shopping," your customers can reap the other benefits of financing that make it easier for them to commit to technology purchases, including:

100 percent financing -- Many finance companies offer 100 percent financing for the cost of software and maintenance contracts, which requires no down payment. Because customers don't have to come up with a down payment, they can make a purchase immediately, rather than hold up the sale with a "wait and see" mentality that often accompanies a dip into cash reserves. It also allows your customers to invest more capital in revenue-generating activities.

Improved cash flow management - With software financing, your customers can conserve capital for reinvesting in their business and improve budgeting accuracy through fixed monthly payments. Financing also makes it easy for customers to access multiple-year budgets by paying for the benefit of your software over its useful life.

Flexible payment structures - Customers can optimize project budgets by taking advantage of the flexible payment structures available through financing to maximize the return on their investment. For example, with software financing, customers can ramp up payments to match the revenue generation of a new technology project that is utilizing the software being financed.

While financing provides a clear advantage for the buyer, when a program is well planned, the list of advantages for software developers, distributors and resellers can be even more beneficial.

Improved Customer Relations

As noted above, financing packages add value for the customer by enhancing their buying power, offering greater flexibility and providing convenience. It also increases their satisfaction through the ability to leverage their budget to acquire the total technology solution - which could include software, hardware, service, support, integration and training - rather than only the parts and pieces they could afford through an outright purchase.

Shorter Sales Cycles

On the sales side, any customer who expresses some interest in a product seems like a good lead. However, there are many times when the question of how to pay for the new software prevents the sale from happening. Time lost on dead-end deals can be eliminated when financing is part of the sale, as the ability to pay is immediately considered in the equation. In addition, many finance companies now offer fast, easy credit and documentation processes, so you can complete a sale quickly and avoid costly processing delays.

Another benefit is that as software needs are being discussed in the sales process, the finance specialist can work with the chief financial officer or accountant to determine which financing option and payment plan best suits business needs and cash flow.

Direct customer financing can also save software vendors millions of dollars each year by reducing the number of days a sale is outstanding. Consider a company with quarterly cash sales of million. On average, it can take 45 days to collect payment. Assuming a borrowing rate of 6 percent, the 45-day lag in payment results in a carrying cost of 1,204. If the same numbers are run with a leasing finance program that generates payment within 2 days, the carrying cost drops ,253, saving the company more than 8,951 in one business quarter.

The Big Picture

Overall, equipment financing programs can:

Generate larger, more profitable sales faster;

Increase account control;

Improve sales efficiency and productivity;

Lower days-sales-outstanding;

Improve cash flow;

Differentiate your company from its competition; and

Provide complete solutions for your customers.

Taking the Next Step

After identifying an interest in offering flexible financing as part of the sales process, the next step is to develop a finance program. By partnering with an experienced leasing company to develop a finance program for your customers, you can transfer all of the uncertainties of extending terms to your customer to the finance company.

Partnering with an experienced finance company also means you can concentrate on what your company does best - developing software - while letting a finance expert handle the intricacies of a finance program. Put simply, by working with a third party, your company will receive all of the benefits with none of the risk.

Whether you choose to refer your clients directly to your financing program partner or to work with a third-party finance partner to develop an in-house program, it is essential to choose an experienced equipment finance partner. During the sales process, the finance expert will be working closely with your customers, and it's important that his or her actions and service levels reflect your company's ability to meet your customers' expectations. When searching for a finance partner, look for a company that:

Is flexible and willing to work with your management team to develop a program that will meet your financial objectives;

Is experienced in the IT and software finance world, since the sales process, client-decision criteria, and revenue recognition issues are different than that of capital asset sellers;

Provides marketing support and materials to help you promote your financing program

Is willing and able to provide your sales team with materials and training to ensure sales team members are comfortable and easily able to raise financing as an option with their clients; and
Is a financially stable, long-term business partner.

Companies in search of a leasing partner can visit Choose Leasing (www.ChooseLeasing.org), a Web site developed by the Equipment Leasing Association, where you can find answers to commonly asked questions about leasing and search for an experienced leasing company specializing in vendor finance programs.

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29Nov/100

Finance, Credit, Investments – Economical Categories

Finance, Credit, Investments - Economical Categories

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Finance, Credit, Investments - Economical Categories

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Finance, Credit, Investments - Economical Categories

By: jamesrake

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finance companies

Finance Functions

(ArticlesBase SC #3382849)

Article Source: http://www.articlesbase.com/ - Finance, Credit, Investments - Economical Categories





Scientific works in the theories of finances and credit, according to the specification of the research object, are characterized to be many-sided and many-leveled. The definition of totality of the economical relations formed in the process of formation, distribution and usage of finances, as money sources is widely spread. For example, in "the general theory of finances" there are two definitions of finances:

There are significant opportunities in Finance Functions within Police Forces to be transformed from a silo based culture that focuses largely on transactional activities to a process and metric based culture equally focusing on transactional processing, management information and strategic requirements. This transformation can deliver large cost savings, service improvement and better quality, faster processing.

Car buying has grown simpler by the time due to growth of car finance schemes. Financing your car appropriately takes into account your financial conditions and repayment capacity before giving you a car finance loan. Car financing is practical method to buy a car. Your can become a car owner in less time and own your kind of car at your kind of interest rates. With so many car finance options, there is one for every one.

100 percent financing - Many finance companies offer 100 percent financing for the cost of software and maintenance contracts, which requires no down payment. Because customers don't have to come up with a down payment, they can make a purchase immediately, rather than hold up the sale with a "wait and see" mentality that often accompanies a dip into cash reserves. It also allows your customers to invest more capital in revenue-generating activities.

Several specialized mortgage finance institutions offer mortgage finance products to home buyers. These savings and loan mortgage finance institutions were also called thrift associations because lenders take in deposits of their savers and use the money to make mortgage finance and loan products.

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Bad credit computer financing is often taken as something that does not have much range of products to offer. But reading about bad credit computer financing will open you eyes to the fact that the options with bad credit computer financing are no less. Acquaintance with your own credit status will definitely give you a chance to get a bad credit computer financing at rate of interest that your credit status warrants. Help yourself with bad credit computer financing with doing the right research.

Let's take a look at the facts: Housing prices are rising at a clip of 10-15% per year, tuition costs are rising by an average of 10% each fall, and energy costs - well, the average rise in prices depends on the week you happen to be looking at, but double-digit increases have been the norm for the past few years. And now, the really depressing fact: Average wage increases have hovered between a measly 3 and 4 percent for the past three years. Now what, you ask, does any of this have to do with car financing?

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28Nov/100

The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience

The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience

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Home Page > Finance > The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience

The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience

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The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience

By: Okoyeuzu chinwe

About the Author

(ArticlesBase SC #1926760)

Article Source: http://www.articlesbase.com/ - The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience





The Effects of Financing Deficit on Leverage Choice of Quoted Firms In A Developing Economy: The Nigerian Experience

                   ONWUMERE J.U.J Ph.D

                   OKOYEUZU CHINWE

 

 

ABSTRACT:   This paper examines time-series patterns of external financing decisions consistent with the pecking order theory. Emerging  markets provide an excellent  laboratory to test the  explanatory power of financing deficit given the under developed markets for corporate control.The adverse selection problem of external financing automatically leads to the standard pecking order in which debt dominates equity.we run a regression with a firm's change in debt as the  dependent variable and its financing  deficit as explanatory variable.  we control for other determinants of debt issuance. Controlling for other determinants of debt issuance helps us to see whether the adverse selection model  falsely omits critical determinants of leverage. This allows a nesting of the conventional determinants of leverage from the trade-off theory within an adverse selection model. Our empirical results indicate that the financing deficit alone accounts for 40% of the variation in leverage  and that no single variable is as potent as the financing deficit in explaining the variations in leverage  over the period.    We predict that publicly traded Nigerian firms fund  a much larger proportion of their financing deficit with net external debt

 

 

 

 

 

    INTRODUCTION

 

The basic pecking order theory predicts that leverage is a decreasing function of profitability. Adverse selection problem is the basis for the theory and since liquid assets/ retained earnings do not have any adverse selection problem, they constitute the best source of funds from insiders' perspective.

Accordingly, the firm will fund all projects using retained earnings if possible. If there is an inadequate amount of retained earnings, then debt financing will be used. This argument leads to the standard pecking order in which debt dominates equity. Frank and Goyal (2003) assume that the adverse selection   problem of external financing automatically leads to the standard pecking order in which debt  dominates equity .

            ∆Dit  = a + bpo  DEFit  +    Eit                      

We run a pool panel regression where ∆Dit  represents net debt issues and   DEFit     represents  financing deficit.

Following the argument of Halov and Heider (2005), that the standard Pecking order is a special case only when there is no asymmetric information about risk, we control for other determinants of debt issuance. The basic trade-off theory states that the level of leverage is determined by trading off the tax benefit of debt against the costs of financial distress. Controlling for other determinants of debt issuance helps us to see whether the adverse selection model falsely omits critical determinants of leverage. This allows a nesting of the conventional determinants of leverage from the trade-off theory within an adverse selection model.The specification in a nested model  enables us to determine how the financing deficit performs when combined with conventional factors. The pecking order theory implies that the financing deficit ought to wipe out the effects of other variables. If the financing deficit is simply one factor among many that firms trade-off, then what is left is a generalized version of the trade-off theory. The pecking order theory financial behaviour is driven by adverse selection costs and the theory should perform best among firms that face particularly several adverse selection problems.  Small high growth firms are often thought of as firms with large information asymmetric .if internal financing is not adequate, then debt financing will be used.  Thus, for a firm in normal operations, equity will not be used and the financing deficit will match up net debt issues.

The remainder of the paper is organized as follows. section 11 provides an overview of capital structure theories. Section 111 describes the methodology. The empirical analyses of deficit are presented in section 1V.section V concludes our work.

 

SECTION 11

REVIEW OF RELEVANT LITERATURE

In finance capital structure refers to the way a corporation finances its assets through some combination of equity and debt or hybrid securities. The key division in capital structure is between debt and equity. The proportion of debt funding is measured by leverage. There are different factors that affect a firm's capital structure, and a firm should attempt to determine what its optimal or best mix of financing.

The pecking order predicts changes in mature firm's debt ratios. These companies' debt ratios increase when the firms have financial deficits and declines when they have surpluses. By implication, a firm may never have a preference for external finances as long as it is able to meet its investment needs via internal equity funds. But in the presence of financial deficit as mostly the practical case, the need for external finance becomes pressing.

The pecking order theory is formally proposed in Myers (1984) and Myers and Majluf (1984).in the theoretical framework of Myers and majluf, investors are willing to buy risky securities only at a discount because of the information asymmetry between managers and outside investors. Expecting this problem, managers prefer internally generated funds .when external funds have to be raised, firms prefer straight debt, and then a convertible debt, with external equity issued as last resort.

Despite extensive investigations into how firms determine their capital structures, the capital structure puzzle prevails. One of the difficulties researchers face in these studies is that a firm may deviate from its target leverage ratio. these deviations arise because operating  and financial decisions push leverage above or below the firm's target and transaction costs and market conditions may prevent immediate corrections. This financing deficit is attributed to factors that cause a firm to deviate from its target capital structure.

Shyam-sunder and Myers (1999), provide an influential empirical test of the pecking theory against the tradeoff theory. Using a sample of 157 firms, that had traded continuously from 1971 to 1987, they find that the basic pecking order model which predicts external debt financing driven by the financing deficit, has much greater explanatory power than the static trade off model. They argue that firm's need for external financing and their internally generated funds may have time-series properties that lead to mean reversion of the debt ratio when firms follow a pecking order financing.

In recent years,Frank and Goyal (2003)find that the financing deficit is positively related to changes in leverage which indicates pecking order financing behaviour. In other words, managers prefer issuing debts to issuing equity when firms tend to make a financial decision by taking external funds. If asymmetric information makes major equity issues or retirements rare, this behaviour is nearly inevitable. The pecking order suggests that managers try to time issues when shares are fairly priced or overpriced. Investors understand this, and interpret a decision to issue stock as bad news. That explains why stock price usually fall when a stock issues is announced. The pecking order theory stresses the value of financial slack. Without sufficient slack, the firm may be caught at the bottom of the pecking order and be forced to choose between issuing undervalued shares, borrowing and risking financial distress, or passing up valuable investment opportunities. Financial slack is most valuable to firms with plenty of positive –NPV growth opportunities. This is another reason why growth companies usually aspire to be conservative in capital structures. Heaton documents some benefits and costs of free cash flow (Heaton, 2002:40-41).

Ho, et al (2006) shows that a firm's ability to reap growth opportunities from research and development (R&D) investments depends on its size, leverage, and the industry concentration. The authors shed further important insights on the size- leverage interaction. They reveal that large firm's advantages over small firms disappear as their leverage increases. In general, the pecking order should work well for small young nonpayer of dividend since they face more asymmetric information

 

SECTION 111

METHODOLOGY            A cross section of 60 firms was investigated. Data was obtained from annual financial reports and securities and exchange commission over a ten year period (1996-2005) A cross section of 60 firms was investigated. Data was obtained from annual financial reports and securities and exchange commission over a ten year period (1996-2005)

(The financing deficit variable)

The basic pecking order theory predicts that leverage is a decreasing function of profitability. Adverse selection problem is the basis for the theory and since liquid assets/ retained earnings do not have any adverse selection problem, they constitute the best source of funds from insiders' perspective.

Accordingly, the firm will fund all projects using retained earnings if possible. If there is an inadequate amount of retained earnings, then debt financing will be used. This argument leads to the standard pecking order in which debt dominates equity. Frank and Goyal (2003) run the following pooled panel regression

      ∆Dit  = a + bpo  DEFit  +    Eit                                         … (3.1)

 

Where ∆Dit represents net debt issues and DEFit  represents financing deficit. They argue that there is a support for the standard pecking order if  a = 0 and b = 1.

∆Dit  =net debt issued in year t(∆Di =long-term debt issuance-long-term debt reduction)

DEFit =Divt/+ It + ∆wt- ct……..(11)

Divt= cash dividends in year t.

It= net investment in year t(simply put, changes in fixed assets and long term investments).

∆wt = change in working capital in year t

Ct =cash flow after interest and taxes.

According to theory, the specification in equation (1) is defined in levels. When actually estimating equation (1),it is conventional to scale the variables by assets or by sales.Ayla Kayhan et al,(2007).The pecking order theory does not require such scaling. Of course, in an algebraic equality, if the right-hand side and the left-hand side are divided by the same value, the equality remains intact.however, in a regression, the estimated coefficient can be seriously affected if the scaling is by a variable that is correlated with the variables in the equation. Scaling is most often justified as a method of controlling for differences in firm size. When this variable is positive the firm invests more than it internally generates. When it is negative, the firm generates more cash than it invests; in other words, the firm has positive free cash flow. The interpretation of the pecking order hypothesis, described in Shyam-sunder and Myers(1999) and Frank and Goyal(2003),is that since debt is likely to be marginal source of financing; firms with high financial deficits are likely to increase their debt ratios

Following the argument of Halov and Heider (2005), that the standard Pecking order is a special case only when there is no asymmetric information about risk, we control for other determinants of debt issuance. The basic trade-off theory states that the level of leverage is determined by trading off the tax benefit of debt against the costs of financial distress. Controlling for other determinants of debt issuance helps us to see whether the adverse selection model [that is,(3.1)]  falsely omits critical determinants of leverage. This allows a nesting of the conventional determinants of leverage from the trade-off theory within an adverse selection model. Following Frank and Goyal   (2003) and Halov and Heider (2005), the set of regressions becomes:

∆Dit   = ao bpo DEFit   + bc    ∆Cit  + bv ∆Vit  + bπ ∆πit  + bs ∆LOGS +   Eit                                                    

                                                                       …(3.2).

 

          The logic of (3.2) is simple. The pecking order theory is a competitor to other mainstream empirical models of corporate   leverage. The specification in a nested model as in (3.2) above enables us to determine how the financing deficit performs when combined with conventional factors. The pecking order theory implies that the financing deficit ought to wipe out the effects of other variables. If the financing deficit is simply one factor among many that firms trade-off, then what is left is a generalized version of the trade-off theory.

  Thus, for a firm in normal operations, equity will not be used and the financing deficit will match up net debt issues.

The pecking order in terms of the relative explanatory power of the financing deficit in observed capital structures can be stated thus:

ßpo =  ßs  =    ßr   =   ßc =    ßp            

ßpo >  ßs  v, c, p        = (Financing deficit dominates).

 

Our version of the regression analysis follows five stages thus

Į t     =        α +  ßpo DEFt        

Į t     =        α +  ßpo DEFt   =   ßs St  +  ßvVt

Į t     =        α +  ßpo DEFt   =   ßs St  +  ßvVt   +   ßcCt

Į t     =        α +  ßs St   =   ßv Vt  +  ßcCt   +   ßp      pt

Į t     =        α +  ßpo DEFt   =   ßs St  +  ßvVt   +   ßcCt   + ßp pt

Where       Į t       =        Market leverage at time t

                 DEFt =         Financing deficit at time t

       St       =        Proxy for size at time t

       Vt       =        Growth opportunities at time t

       Ct       =        Tangibility of assets at time t

       pt       =        Profitability at time t 

 

Our model of target leverage was computed thus:

Į*t       =     Į t      +    DEFt

 

SECTION   IV

Presentation And Analysis

 

TABLE 4.1a: EMPIRICAL RESULTS ON THE STANDARD PECKING ORDER

Constant

Deficit

R2

Adjusted R2

Std. Error of Estimate

F

DW

0.20

0.98

0.40

0.03

5.32

1.11

(4.29)+

(2.31)++

0.32

 

 

 

 

F        represents F  Ratio, while DW Dursin-Watson.

t         values are in brackets     n = 10

+        signifies one percent (0.01) significance

++      signifies five percent (0.05) significance.

The pecking order hypothesis can be stated statistically as

H1: a = 0      (pecking order holds)

          Hi:  a ≠ 0      (pecking order does not hold)

And

Ho: b = 1      (pecking order holds)

          H1: b ≠ 0      (pecking order does not hold)

Table 4.1a indicates that the constant a is statistically different from zero. However, the slope coefficient b is close to one in support of the pecking order. The coefficient of determination indicates that the deficit explains forty percent (40%) of the variation in market leverage, our proxy for net borrowing.

It is important to stress that the variables used above were scaled by assets in line with empirical method. Scaling is most often justified as a method of controlling for differences in firm size.

The pecking order test implicitly makes different exogeneity assumptions and uses slightly different information set than is conventional in empirical research on leverage and leverage-adjusting behaviour. The conventional set of explanatory factors for leverage is the conventional set for a reason. The variables have survived many tests. As explained in our literature review, these variables also have conventional interpretations. Excluding such variables from consideration may (potentially) be a significant omission. More so, the result above indicates an unexplained variation in leverage of about sixty percent. Including such variable further poses a tough test for the pecking order theory.

Our version of the regression analysis follows five stages thus:

lt = a +bpo DEFt               ……………………………..                  (as in 4.1)

lt = a +b po  DEFt +bsSt  + BvVt    ……………………..                   (4.2)

lt = a +bpo  DEFτ +bsSt +  BvVt  + bcCt…………………                (4.3)

lt = a +bsSt  + bvVt +bcCt + bππt …………………..             (4.4)

lt = a +bpoDEFt + bsSt +bvVt + bcCt + bππt ……..…..                   (4.5)

 

Where         lt        =        market leverage at time t.

DEFt  =        financing deficit at time t.

St       =        Proxy for size at time t.

 Vt      =        Growth opportunities at time t.

Ct       =        tangibility of assets at time t.

πt       =        profitability at time t.

 

Our empirical results are tabulated in 4.5b below.

Table 4.1b:  RESULTS ON CONVENTIONAL LEVERAGE REGRESSION WITH FINANCING DEFICIT IN NESTED MODELS.

Regression Equation

Constant

DEF

Size

(S)

Growth

(V)

Collateral

(C)

Profit

(π)

R2

F

DW

4.4

0.20

(4.29)+

0.98

(2.31)++

 

 

 

 

0.40

5.32

1.11

4.5

0.36

(5.90)+

0.73

(2.44)++

-0.13

(-1.26)

-0.23

(-2.47)++

 

 

0.70

8.08

1.45

4.6

0.40

(9.04)+

0.53

(2.43)+++

-0.19

(-2.55)++

-0.30

(-4.35)+

-0.06

(-2.78)++

 

0.86

14.81

1.93

4.7

0.45

(7.47)+

 

-0.18

(-1.66)

-0.34

(-3.26)++

-0.08

(-2.58)++

-0.01

(-0.42)

0.70

6.36

2.27

4.8

0.39

(7.44)+

0.52

(2.12)+++

-0.19

(-2.23)++

-0.31

(-3.78)++

-0.06

(-2.50)++

-0.01

(-0.15)

0.83

9.53

1.88

n  =   10

+        Significant at one percent (0.01)

++      Significant of five percent (0.05)

+++    Significant at ten percent (0.10) 

Confirming predictions shared by the trade-off model and the standard pecking order model, firms with more growth opportunities have less market leverage. Confirming the pecking order model but contradicting the trade-off model, more profitable firms are less levered. However, the profitability coefficient is statistically insignificant.

          On the explanatory power of deficit on observed debt ratios, table 4.1b indicates its dominance over the remaining conventional variables both by the partial derivatives and the coefficient of determination (R2 ).

Again, the financing deficit alone accounts for 40 percent of the variation in leverage while size and growth (put together) make up the balance of 30 percent. Collateral, our proxy for tangibility of assets explains 16 percent of the variations in leverage while the explanatory power of the regression once profitability is added. Table 4.1b indicates that no single variable is as potent as the financing deficit in explaining the variations in leverage over the period. A one percent increase in financing deficit leads to a .73% increase in market leverage. A one percent increase in size leads to a .19% decline in market leverage. A one percent increase in growth opportunities leads to a .3% decline in market leverage. A one percent rise in tangible assets leads to a decrease of .06% in leverage while a one percent rise in profitability leads to a decline of .01% in leverage. Though the profitability coefficient is consistent with the pecking order theory, it is not significant at all. This casts doubt on the plausibility of the pecking order. However, the statistically significant deficit coefficient that dominates other coefficients at all levels indicates that the pecking order is a strong theory in the Nigerian corporate environment. Empirical research along this line includes Graham and Harvey (2001), Fama and French (2002). Halov and Heider (2005).

To test for the degree of multicollinearity amongst the explanatory variables, the table below hereby presents our intercorrelation matrix.  

TABLE 4.1c: INTERCORRELATION MATRIX OF MARKET LEVERAGE (L) WITH   DEFICIT, SIZE, GROWTH, COLLATERAL AND PROFITABILITY.

 

L S V C Π

DEF

PPMCC.        L.

1.00

 

 

 

 

 

                   S

0.63

1.00

 

 

 

 

                   V

-0.76

-0.92

1.00

 

 

 

                   C

                   π 

-0.28

0.49

0.02

0.75

-0.14

-0.77

1.00

0.12

 

1.00

 

                  DEF

0.63

0.32

-0.31

-0.28

0.13

1.00

Sig (I-tailed) L

.

 

 

 

 

 

                                        S             

 

0.03

 

.

 

 

 

 

                     V

0.01

0.00

 

 

 

 

                    C

0.21

0.48

0.35

 

 

 

                      π    

0.08

0.01

-0.01

0.37

.

 

                   DEF

0.03

0.18

-0.20

0.22

0.36

1.00

 

 

 

SECTION V

SUMMARY/CONCLUSION.

 

DEBT AND THE FINANCING DEFICIT

          We now look at the analysis of the capital structure decision from a different point of view, the pecking order theory of Myers and Majluf (1984) and Myers (1984). As can be recalled, Myers and Majluf analyzed a firm with assets – in – place and a growth opportunity requiring additional financing. They assumed perfect financial markets, except that investors do not know the true worth of either the existing assets or the new opportunity. Therefore, investors cannot precisely value the securities issued to finance the new investment; If the firm announces an issue of common stock. This is good news for investors if it reveals a growth opportunity with positive net present value. It is bad news if managers believe the assets –in-place are overvalued by investors and decide to try to issue overvalued shares. (Issuing shares at too low a price transfers value from existing shareholders to new investors if the new shares are overvalued, the transfer goes the other way). The interested reader is referred to Myers (2001), Fama and French (2002) and the references cited in these papers for excellent exposition.

          The pecking order theory predicts that the firm will fund all projects using internal equity if possible (Information asymmetries are assumed relevant only for external financing). If internal finance is not adequate, then debt financing will be used. Thus, for a firm in normal operations, equity will not be used and the financing deficit will match the net debt issues.

          The empirical specification for the test of the standard pecking order is given as

          lit = a + bpo D

 

 

CONCLUSION.A statistically significant deficit coefficient that dominates other coefficients in a nested regression model indicates that no single variable is as potent as the financing deficit in explaining the variation in leverage over the period of the financing deficit provides a strong support for the standard pecking order. The result is well in line with the empirical findings of Titman and Wessels(1988)our result was a strong confirmation of the pecking order in the financing behaviours of Nigeria quoted firms.

 

 

 

REFERENCES

 

 

Fama, E.F. and K.R. French (2002a) "Testing trade-off and pecking order predictions About Dividends and Debt," Review of financial studies,  15, (1):1-33.

Frank, M.Z and V.K Goyal (2003) "Testing the Pecking Order Theory of Capital Structure," Journal of Financial Economics, 67: 217-248.

Graham, J.R and C.R Harvey (2001)"The Theory and Practice of Corporate Finance: Evidence from the Field, " Journal of financial Economics,  60, ( 2-3)May: 187-243.

 

Halov, N. and F. Heider (2005) "Capital Structure, risk and Asymmetric Information, "Working Paper NYU Stern School of Business. (December 1st, 2005).

Heaton, J.B. (2002) "Management, Optimism and Corporate Finance, "Financial Management,  31(2 )(summer) :33-45.

 

Ho, Y.K, M. Tjahjapranata and C.M Yap (2006) "Size, Leverage, Concentration, and R&D Investment in Generating Growth Opportunities", Journal of Business  79, ( 2):851-876.

 

Myers, S.C. (1984) "The Capital structure puzzle", Journal of Finance, 39, July,  575 – 592.

Myers, S.C. and N.S. Majluf (1984) "Corporate Financing and

Investment Decisions When Firms Have Information Investors Do Not Have", Journal of Financial Economics,  13, June, 187 – 222.

 

 

 

Titman, S. and R. Wessels (1988) "The Determinants of Capital Structure Choice, " Journal of Finance,  43, (1): 1-19

 

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If you'd equivalent to get outdo results in the incoming 30 life or fewer, inform how to speedily and easily make delicious alimentation plans in meet 14 transactions and release heads when grouping see the new slant habitus you've developed, then this faculty be the most useful grapheme you'll ever interpret.

By:
These Higginsl
Financel
Nov 27, 2010

The Effects Of Financing Deficit On Leverage Choice Of Quoted Firms In A Developing Economy: The Nigerian Experience

ABSTRACT: This paper examines time-series patterns of external financing decisions consistent with the pecking order theory. Emerging markets provide an excellent laboratory to test the explanatory power of financing deficit given the under developed markets for corporate control.The adverse selection problem of external financing automatically leads to the standard pecking order in which debt dominates equity.we run a regression with a firm's change in debt as the dependent variable and i

By:
Okoyeuzu chinwel
Financel
Mar 02, 2010
lViews: 104

Corporate Tax And Capital Structure In An Emerging Market : An Empirical Analysis Of Quoted Firms In Nigeria

Abstract: The purpose of this study is to carry out empirical testing using dynamic panel data methodology, to analyse the relationship between corporate taxation and debt. The choice of Nigeria is that Nigeria economy is a strong force in Africa. We adapt a standard model of capital choice under corporate taxation. We controlled for other leverage determinants. Our dataset covers a cross-section of 60 quoted firms from Nigerian stock markets over a ten year period (1996-2005), we find that

By:
Okoyeuzu chinwel
Financel
Mar 02, 2010
lViews: 338

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