الفهرس 
Research FrameworkOnly 14 pages are availabe for public view
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Abstract
There are three opinions about the relationship between FRQ
and TOD. Firstly, when the amount of debt increased the FRQ should
be increased because banks required audited financial statements in
order to give the borrowers more favorable terms (Kardan, Salehi, &
Abdollahi, 2016). Secondly, borrowers used to camouflage and
manipulate the financial information in order to show a stable
financial position and consequently raise their level of debt (Dichev
& Skinner, 2002). Thirdly, it‘s a combination of the two previous
opinions (Ghosh & Moon, 2010).
Thus, the research agrees with the third opinion because
banks required a higher level of FRQ in order to give the borrowers
more favorable terms. At the same time, borrowers need to raise their
level of debt by presenting a higher level of FRQ by using the actual
numbers or compensating it with earning management techniques.
In less developed markets the creditors’ protection and legal
enforcement are weak and they have a higher level of information
asymmetry (IA) between creditors and borrowers (Gomariz, &
Ballesta, 2014). So, creditors protect themselves by relying on the
financial statements (FS) and used it as an indicator of the company
performance and taking their decisions according to the level of FRQ
(Ding, 2016). A higher level of FRQ will lead to a decrease in the
level of IA and gives the creditors a better assessment of the
borrowers (Ding, 2016). Moreover, the crises and financial distress
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affect earnings quality by manipulating the earning numbers to show
the optimum image of the company (Francis, 2005).
The importance of debt markets has existed across the world.
Based on the study of (Shivakumar, 2013), the highest frequent type
of fundraising for firms is debt markets and especially bank loans.
Also, the study of (Armstrong, Guay, & Weber, 2010) predicted that
95% of all capital raised by firms in 2006 was from debt markets.
Moreover, the banking sector is the most reliable source of external
funding (Paiva, 2018).
According to the study of (Shivakumar, 2013), the variety of
factors like accounting regulation, institutional characteristics, legal
and cultural attributes will make the impact of FRQ on TOD vary
across the countries. Furthermore, banks rely on borrower‘s FS as a
kind of assessment in order to determine the pricing term like the cost
of debt and non-pricing terms like loan amount, maturity date, and
collateral requirements (Chen, 2011) (Ding, 2016).
According to the study of (Amiram & Kalay, 2017), all
previous studies agreed with the importance of IC to banks but there
are limited studies that investigated how these characteristics shaped
the TOD. Also, the study of (Amiram & Kalay, 2017) has found a
significant relationship between IC and pricing terms. However, it
ignored the importance of non-pricing terms.
According to the study of (Su, Yang, & Dutta, 2018), the
listed companies in the stock market are more likely to reveal more
information‘s about earnings and publish high FRQ to reassure all
external users especially banks about company performance and
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company financial position. Moreover, large companies are more
predictable, and earning quality is more ideal if it‘s compared with
other companies (Kardan, Salehi, & Abdollahi, 2016).
1.2 Research Problem
Nowadays it’s obvious that access to finance enhances the
growth and improvement of markets and firms. However, in
Emerging markets like Egypt, companies face a lot of struggles to
raise capital by using debt markets. According to the Egyptian stock
market, only 45 out of 248 of the listed companies take loans, which
means that the remaining companies (more than 80% of the listed
companies) cannot have access to debt markets.
The research problem is highlighted in the fact that most
listed companies cannot endure the terms of debt and at the same
time, due to the presence of trust issues between banks and
companies as a result of the existence of information asymmetry,
banks use stringent terms of debt in the form of pricing and nonpricing
terms to protect themselves from the risk of non-payment.
FRQ could be used to solve this problem. Banks could use it
as an indicator that reflects the real financial performance of the
borrower and predict the future cash flow accurately. FRQ might
provide a solid ground for banks to facilitate the TOD. Also, banks
facilitate the TOD according to the sector that the borrower belongs
to. Because companies in the same sector affected by the reputation
of the whole sector and they have the same nature of the industry.
This means that the IC play an important role in the relationship
between borrower and TOD.
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1.3 Research gap
The research gap of this research includes two points; firstly,
previous studies that tested the relationship between FRQ and debt in
the Egyptian market had focused on the pricing term only which is
the COD and ignored the importance of the non-pricing terms. So,
there is a lack of investigation between FRQ and TOD in the
Egyptian stock market.
Secondly, no previous studies that tested the relationship
between FRQ and TOD with the existence of IC as a moderator
variable. Just the study of (Amiram & Kalay, 2017) had investigated
the relationship between IC with the debt pricing, without the
existence of FRQ, and ignored the impact of IC with the non-pricing
terms like maturity date and collateral requirements.
1.4 Research objective
This research will investigate directly the relationship
between FRQ and TOD. By testing the impact of FRQ with each
term individually; FRQ with loan size, COD, maturity date, and
collateral. Moreover, the research will add the IC as a moderator
variable and retests the relationship between the FRQ and each term
but with the existence of IC. Finally, the research will compare the
results and interprets the role of IC with the relationship between
FRQ and TOD.
So, the research classifies the objectives into the following points:
1. Investigate the relationship between Financial reporting
quality and loan size.
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2. Investigate the relationship between Financial reporting
quality and Cost of debt.
3. Investigate the relationship between Financial reporting
quality and maturity date.
4. Investigate the relationship between Financial reporting
quality and collateral.
5. Investigate the impact of Industry characteristics on the
relation between Financial reporting quality and Terms of
debt.
1.5 Research question
Based on the research problem, the research questions are:
1. Is there a positive relationship between Financial reporting
quality and loan size?
2. Is there a negative relationship between Financial reporting
quality and Cost of debt?
3. Is there a positive relationship between Financial reporting
quality and maturity date?
4. Is there a negative relationship between Financial reporting
quality and collateral?
5. Do the Industry characteristics influence the relation between
Financial reporting quality and Terms of debt?
1.6 Research Hypotheses
H1: There is a positive relationship between Financial
reporting quality and loan size.
H2: There is a negative relationship between Financial
reporting quality and Cost of debt.
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H3: There is a positive relationship between Financial
reporting quality and maturity date.
H4: There is a negative relationship between Financial
reporting quality and the existence of collateral requirements.
H5: Industry characteristics influence the relation between
Financial reporting quality and Terms of debt.
H5A: Industry characteristics influence the relation between
Financial reporting quality and Loan size.
H5B: Industry characteristics influence the relation between
Financial reporting quality and Cost of debt.
H5C: Industry characteristics influence the relation between
Financial reporting quality and Maturity date.
H5D: Industry characteristics influence the relation between
Financial reporting quality and Collateral.
1.7 Overview of research methodology
The research will conduct an applied study on all the listed
companies that relied on loans of the EGX, during the period from
2014 until 2018. This research is quantitative and uses secondary data
gathered from the annual reports from the companies‘ official
websites and publications, and official financial reports available on
the Mubasher website. The research model is based on data from the
balance sheet, income statement, cash flow statements, and footnotes.
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1.8 Research variables
Dependent variable
The research has four dependent variables which are pricing
and non-pricing terms of debt;
Loan size: Natural logarithm of loan amount Log(loan)
(Bharath, 2008).
COD = Interest expenses divided by average total debt*(1 –
effective tax rate) (Su, Yang, & Dutta, 2018).
Maturity date: Natural logarithm of loan maturity Log (M)
(Bharath, 2008).
Collateral: Dummy variable: Take value equals 1 if a loan is
secured, and 0 otherwise (Bharath, & Sunder, 2008).
And the research tests each of dependent variables individually.
Independent variable
The independent variable is FRQ. And the research uses
earning smoothing as a proxy for FRQ. It is measured as the
correlation between the standard deviation in income before taxes and
the standard deviation in operating cash flow (Paiva, 2018),
(Burgstahler, 2006), (Leuz, 2003).
SMOOTH i,t = σ(Net Income i,t)/σ(CFO i,t)
Where:
σ (Net Income i,t) is the standard deviation of net income before taxes
for firm i year t, divided by total of assets at the end of the year t
σ(CFO i,t) is the standard deviation of cash from operations for firm i
year t divided by total of assets at the end of the year t (Paiva, 2018).