DOI : https://doi.org/10.5281/zenodo.20038710
- Open Access
- Authors : Miss. Chaitrali Milind Godawale
- Paper ID : IJERTV15IS041510
- Volume & Issue : Volume 15, Issue 04 , April – 2026
- Published (First Online): 05-05-2026
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License:
This work is licensed under a Creative Commons Attribution 4.0 International License
The Characteristics and Determinants of External Commercial Borrowings
The Characteristics and Determinants of External Commercial Borrowings
Chaitrali Milind Godawale
MIT College of Management and Computer Application
ABSTRACT
Globalization drives foreign direct investment (FDI), international trade, etc. External debt is a major issue for every country including India. External commercial debt (ECBs) is the borrowing taken by companies from external sources for their commercial purposes. The objective of the study is to analyse the contractual data on ECBs, study the characteristics and determinants of ECBs. This paper focuses on the analysis of data on ECBs for the period from FY 2016-17 to FY 2024-25. The analysis is given in two parts, first gives an overall view, i.e., characteristics of ECBs and second an econometric model that proves the determinants of the flow of ECBs in India. For this, we have divided the entire period into 3 phases of COVID-19, i.e., pre-COVID period (FY 2016-17 to 2019-20), COVID period (FY 2020-21 and 2021-22) and post-COVID period (2022-23 to 2024-25). To understand the characteristics of ECBs, we have analysed data from different contexts based on purpose, economic sector, borrower patterns/movements, and tenure maturity. To study the determinants, we constructed a multiple linear regression model that examines the factors affecting the flow of ECBs. As a result of this model, institutional factors such as GE (government effectiveness) and PV (political stability and absence of violence/terrorism) influence the flow of ECBs.
Key Words: External Commercial Borrowings (ECBs), Reserve Bank of India (RBI), External Debt, Characterstics, Determinants
INTRODUCTION
Liberalization, Privatization and Globalization (LPG) reform fosters trade, investment with foreign companies, banks etc., In simply its open doors for the world. It gives us opportunities along with challenges. To sustain in this competitive environment, it requires capital. There are multiple internal as well external sources through with firm can raise capital. Like issuing of shares, take loan from bank, debentures, deposits, ADRs, GDRs, FDI etc.,
FDI be in form of borrowings, Grants, investment in specific industry/ sector etc., that help for economic growth. External Commercial Borrowings is one of the sources through with company can raise finance. It is the borrowings raised through external sources by companies to their commercial purposes. Over the years, the graph of ECBs in India is increasing (Kapoor 2023)
Figure – 1
(Source: RBI)
MEANING
Bank is the primary source for borrowing money for both companies as well as individuals. When we talk about companies, they need large amount of money. They have multiple options through which they can raise finance internally. Globalization fosters they can raise money through external sources as well. So, ECBs is one of the external sources through which companies can raise money to fulfil their requirements. It is one of the ways through companies can borrow money. As the name suggests that it is borrowing that raise through external sources. Two routes are available in India through which companies can go for ECBs. This are Automatic Route and Approval Route. There are different modes through which companies can raise ECBs. This are as follows:
-
Bank Loans
-
Buyers Credit
-
Suppliers Credit
-
Securitized Instruments, etc.
Regulation of ECBs under:
Two bodies play important roles for the regulations of ECBs. One is the Department of Economics Affairs under the ministry of fiancé of Government of India with Indias apex bank Reserve Bank of India.
Routes for issuing of ECBs:
-
Automatic Route
Under the automatic route, the entities who wish to raise borrowings need not gain the previous approval of the government to do so. The only thing which is needed is being in sync with certain guidelines laid down for raising capital through an automatic route. These guidelines relate to quantities allowed under the automatic route, the eligible diligence, the end- use of the finances, etc. The companies that meet these eligibility criteria can further raise finances without the authorization of the government through the automatic route.(Kapoor 2023)
The funds via ECB can only be raised by certain recognized lenders. The list of recognized lenders includes:
-
Multilateral financial institutions
-
International banks
-
Export credit agencies
-
Foreign equity holders
-
International capital markets
-
Foreign collaborators, etc.
-
-
Approval Route
Under this, the governments authorization is needed by a company each time it wants to raise the finances. There are certain companies or pre-defined sectors as specified by the RBI or the government which have to raise finances solely through the Approval route, they cannot raise finances without the previous authorization of the government or RBI.(Kapoor 2023)
Eligible Borrower Before raising the funds, the entities need to get permission from the government or the RBI and the proposal to raise funds is approved depending on each case.
Advantages of raising ECBs
-
Accessing funds from abroad through ECB also allows Indian companies to connect with Global Technology and technical expertise, which can support innovation and strengthen their competitive position. (Kapoor 2023)
-
ECB enables companies to widen their investor base and include lenders from the global market providing them with Global Exposure. (Krishnan and M 2024)
-
Raising funds through the ECB can also help in the Development of the Economy as a whole as government can control the sectors in which the investment can be sought and up to what extent. (Kapoor 2023)
-
The government can attract more foreign investment in Small and Medium Enterprises (SME) as well as the Infrastructure Industry, hence providing them with better opportunities.
-
ECB enables corporations to obtain finance from a Broader Range of international sources, thereby helping them secure larger amounts of capital that may not be available through domestic lending institutions.
-
ECBs are raised in form of Foreign Currencies it helps companies to get foreign currencies to fulfil the long-term, short-term requirement.(Kapoor 2023)
-
It helps for business to expand their operations, diversification etc. it is opportunity for business to expand operations.
-
It helps for the Economic Growth of the country.
Disadvantages of raising ECBs:
-
Obtaining finance from overseas exposes firms to currency fluctuations. If the Indian rupee depreciates against the foreign currency over time, the repayment cost of the loan increases, imposing an additional financial burden on the borrower. Thus, have Exchange rate risk.(Kapoor 2023)
-
Foreign borrowing is influenced by rules and policies introduced by regulatory authorities (Regulatory Risk). Since these policies depend on broader economic condiions, any change may adversely impact firms that rely on ECB as a source of finance. (Kapoor 2023)
-
Borrowing internationally can expose companies to higher credit risk because lenders may provide comparatively limited protection in situations of default.
-
Reliance on foreign capital may make companies vulnerable to fluctuations in global financial markets. If foreign funds become scarce or more expensive due to external conditions, firms may face financial stress. Additionally, lower interest rates may encourage excessive borrowing, potentially leading to a heavy burden of foreign debt.(Kapoor 2023) REVIEW OF LITERATURE
-
-
Dynamics Of External Commercial Borrowings In India(saxena, n.d.)
Researcher reveled in this paper that the ECBs flows in last 3 decades is highly volatile and the share of ECBs in external debt is increasing fast. The objective of the study was to understand the trends and overview of ECBs in India. He concluded while raising ECBs cautions must take by both companies as well as government as it is one of important source of foreign capital.
-
Foreign Currency Borrowing and Firm Financing Constraints in Emerging Markets: Evidence from India(Mohapatra and Nagar 2020)
In this article author analyzed the relationship between foreign currency borrowing and financing constraints in Indian non-financial firms. The objective of the study was to understand the impact of foreign currency borrowing and financing constraints in emerging economies like India. They concluded with on the role of internal and external macroeconomic conditions, firm financing constraints, and foreign currency borrowing, can provide directions for policy to better leverage the advantages of global financial integration.
-
External Commercial Borrowings and Outward Foreign Direct Investment: Evidence From Indian Manufacturing Firms(Krishnan and M 2024)
In this research researcher analyzed the effect of ECBs and Outward FDI by collecting data on Indian manufacturing firms from period 2008 to 2020. The objective of the analysis was to understand the impact of ECBs & outward FDI. They conclude with to understand this effect they used Heckman two-step procedure (1979), which explained a positive effect of ECBs on firms OFDI. The results reveled that firms using more leverage and ECB are firms with higher OFDI severity
-
A Critical Analysis Of The Framework Of External Commercial Borrowing Through FCCB In India(Kapoor 2023)
In this article author enlightened about the ECBs major focus with the Foreign Currency Convertible Bonds (FCCB). It explains the rules, regulations with the context to FCCBs. The objective of the analysis was to get in depth insights about ECBs guidelines with special focus on FCCBs. The researcher concludes with providers in depth information about Indian ECBs with focus on FCCBs, it covers all aspect related with ECBs like Methods, rules and regulations, compliances, routes, etc.,
-
How Firms Borrow in International Bond Markets: Securities Regulation and Market Segmentation(Fuertes and Serena 2016)
In this article author analyzed the how firms in emerging economies select the international bond market. The objective was to understand the on what basis firms in emerging economies take decision for international bond market, understand the behavior of firms. Author conclude with finding that firms with minimum credit quality, less ability to absorb flotation costs and high informational asymmetries they prefer debt in US144A and Eurobond markets, where the regulation is not stringent and information is less public. On the other hand, firms issuing global bonds subject to full SEC requirements are financially stable and have reliable position.
-
Corporate borrowing during crises: Switches in global markets(Didier et al. 2021) Researchers reveled in this paper that, movement of debt market during the crises period. The objective of researchers was to understand the how debt market reacts with the changes in the economy specifically during crises period. The researchers conclude with
It is important to create policies that help to mitigate the negative impact of crises, focus on providing liquidity to specific markets along with that create confidence for firms that they sustain in crises.
-
Corporate Borrowing in Emerging Markets: Fairly Long Term, but Only for a Few(Cortina et al. 2018)
In this research researchers investigate about the behavior pattern of firms in emerging economies regarding tenure of debt. The objective of conducting this research was to get insights about the maturity structure of debt for emerging market firms. The researchers concluded research with firms in emerging market issue long term debt through global bond and syndicated loan markets.
-
Foreign currency borrowing and risk exposure of firms: An emerging market economy viewpoint(Chakrabarti and Sen 2023)
Researcher reveled in this paper that the firms who have high stock of foreign currency borrowings which also show in their financials then the financial risk with that firm increases. The objective of researchers was to understand the implications of firms who have high foreign currency borrowings. The conclusion is high foreign currency debt results in increase with the financial risk.
-
International capital flows and National Creditworthiness: Do the fundamental Things apply as Time Goes By?(Cashin and MC Dermott, n.d.)
Researchers analyzed the, Australias global borrowing pattern during their post capital control period. The objective of research was to understand the borrowing activities of Australis in its post capital control period. The researchers conclude with finding that the, relationship between consumptions and national cash flows. Showed that its global borrowing decisions increases with improvement in economic fundamentals.
-
Large international corporate bonds: Investor behavior and firm responses(Calomiris et al., n.d.)
In this research researcher analyzed the, the investors behavior and firm responses in the large global corporate bond markets. The objective of research was to understand the pattern of investors and firms in global market. It concludes with, foreign currency borrowing is pivotal for firms in emerging economies from 2008. It also revealed that, behavior of investors changes as per the benchmark of the market.
-
Why Do Emerging Economies Borrow Short Term?(Broner et al. 2004)
Researchers reveled in this paper that, reasons behind why emerging economies prefer the short-term borrowings by creating the model where the debt maturity structure is the outcome of a risk sharing problem between the government and the bondholders. The objective of research was to understand the behavior behind raising short term borrowings in emerging
economies by creating a statistical model. The model explained that, the relationship between risk premium and maturity tenure. That help to analyzed the behavior of investors.
-
Determinants Affecting External Commercial Borrowings: Pre and During Pandemic Analysis(Aloknath and Fernandes 2024)
In this research researcher analyzed the, domestic factors that provides impact on inflow of ECBs on basis of pre and during pandemic analysis. The objective was to understand the significance and influence of economic factors that affects the inflow of ECBs in before and during the covid-19 pandemic. They conclude with advantages and determinants of inflow of ECBs like interest rate, foreign currency volatility, maturity periods etc.,
-
Impact of Regulations on ECB Inflows(Agarwal and axena 2024)
In this article author analyzed the, influence of compliances on inflow of ECBs. The objective was how compliances affects the inflow of ECBs by using CHOW breakpoint analysis and ARIMA Modelling Methodologies. The conclusion was, using this modelling techniques researcher reveled the result that there is significant impact of policy changes on the Inflow of ECBs proven by chow break test. Along with that ARIMA model analyzed the gap between the actual and predicted inflow of ECBs.
OBJECTIVE
-
To study the concept of External Commercial Borrowings of India.
-
To study the data on External Commercial Borrowings and get meaningful insights out of it of period 2016-17 to 2024-25.
-
To study the Characteristics and Determinants of External Commercial Borrowings of period 2016-17 to 2024-25.
-
RESEARCH METHODOLOGY
This is a contractual data of ECBs. This data is collected from Reserve Bank of India site. It is type of secondary data. Several tools have been used to analyse this data. Data has been taken from various websites to build a multiple linear regression model. For analysis the financials of company the data collected from Annual Reports from that company. In this project for industry analysis, several reports have been used.
Data sources for the research are as follows:
Websites
-
Reserve Bank of India Website. The core part of data i.e., ECB data of firms collected from this website
-
World Bank Website. For Multiple linear regression model, creation of independent variables various indicators was collected from this website.
-
Federal Reserve Bank of ST. Louis (FRED). For independent variable interest rates. of USA is collected.
-
Searches. Data on search engine collected from google.
Reports
-
World Investment Report 2025, for Global FDI
-
Fiscal Affairs Department, IMF, For Global Debt
-
World Economic Outlook, for Trade, GDP etc.
-
Monthly, Quarterly reports release by RBI, use for FDI of India
-
Indias External Debt A Status Report 2024-25, use for Indias Debt information Tools
-
Microsoft Excel for data analysis
-
SPSS For Plots, Charts and Data Description
-
EViews For Regression model.
DATA ANALYSIS
-
Yearly Inflow of ECBs (USD Billion)
$47.80
$12.36
60.00
50.00
USD Billion
40.00
30.00
20.00
10.00
0.00
60.00
37.11
27.90
26.58
27.45
19.46
12.36
47.80
23.51
29.07
50.00
USD Billion
40.00
30.00
20.00
10.00
2019-20
2020-21
2024-25
2016-17
2017-18
2018-19
2019-20
2020-21
2021-22
2022-23
2023-24
2024-25
0.00
2016-17
2017-18
2018-19
2021-22
2022-23
2023-24
Pre-Covid Period Covid Period Post Covid Period
Figure 1 Figure -2
The above figure of 1 indicates the yearly (financial year) inflow of ECBs. All the values in USD Billion Form. It shows the yearly increasing trend. It starts from $12.36 in FY 2016-17 then it gradually increases. In FY 2020-21 shows the drop of ECB Inflow but again it recovers in FY 2021-22 and shows the gradually improvement. In FY 2024-25 indicates the highest that is $ 47.80. overall, this line chart explains the positive trend. Shows the inflow of ECBs increases over the years. This shows that the company has an increasing inclination towards ECBs over this period.
The above figure 2 cluster column chart shows the inflow of ECBs over the period from FY 2016-17 to FY 2024-25. All the values present in this chart is in USD Billion form. In this diagram it is clearly state the yearly flow of ECBs. Overall, it indicates the increasing trend. Shows positive trend. In this diagram we get a segregation about the periods into the context of Covid 19. In this figure we see the periods are divided into 3 phases of covid 19. This are
-
Pre Covid-Period (FY 2016-17 to FY 2019-20)
-
Covid Period (FY 2020-21 to 2021-22)
-
Post Covid Period (FY 2022-23 to 2024-25)
It is necessary to understand the what are the change take place on this covid 19. Therefore, the detail analysis of these three phases is given in next part.
Pre-Covid Period
-
The FY 2016-17 to FY 2019-20 represent the Pre- covid Period, in this period shows the Inflow of ECBs in USD Billion form.
-
It starts from $12.36 in FY 2016-17 to high at $ 37.11 in FY 2019-20.
-
Overall, it shows the increasing trend. ECB inflow increases over this period.
-
It indicates that environment, global and Indian economic conditions foster the inflow of ECBs during this time period.
-
It shows that in this time period there were no regulatory risk, credit risk etc. As if there is such risks then it affects the flow of ECBs.(Kapoor 2023)
-
Global Uncertainties also influence the FDI, Trade, Inflow of ECBs etc., so it creates the negative impact on this.
-
This phase indicates that there were factors in the economy that complemented this.
-
Both Indian economy and global economic conditions focus on development so it helps to fosters the debt.
-
Overall, this period was the opportunity for the Indian companies where they can raise the ECBs.
-
Covid Period
-
The FY 2020-21 and to FY 2021-22 represent the covid Period, in this period shows the Inflow of ECBs in USD Billion form.
-
From $ 37.11 billion decline to $26.58 billion in FY 2020-21.
-
In pandemic of covid 19 affects the operations of entire world including India. So, it also affects the Inflow of ECBs.
-
In this period, we saw the global uncertainties, financial risk, economies are not ready to give loan. There focuses shift from development to this sustain in pandemic environment.
-
Many businesses cannot sustain, many economies collapse. due to this pandemic
-
In FY 2020-21 ECBs inflow decline but in FY 2021-22 shows the recovery sign it increased with $27.45 billion.
-
Overall, it shows the decline and recovery phase.
Post Covid Period
-
The FY 2022-23 to FY 2024-25 represent the post- covid Period, in this period shows the Inflow of ECBs in USD Billion form.
-
It starts from $23.51 in FY 2022-23 to high at $ 47.80 in FY 2024-25.
-
After the covid period it shows the drop of Inflow of ECBs from $27.45 to $23.51.
-
The war between Russia and Ukraine was started during this period may be one reason for the decline.
-
But in 2023-24 it shows increase in flow of ECBs and in 2024-25 indicate the highest ECB that is 47.80 over the years.
-
During this period, the government took various decisions that were proactive in developing the economy, thus helpig to create a healthy environment that led to an increase in ECB flows.
-
For example, the government has focused more on products made in India to reduce foreign dependence, which will provide companies with opportunities to expand their operations, grow their business, and conduct research and development, which requires more funds, which may also have increased the inflow of ECBs.
-
Overall, it shows the increasing trend. ECB inflow increases over this period.
-
-
Quarterly Inflow of ECBs (%)
Q4
28.5
20.6
31.3
34.3
30.3
27
36.4
30.8
32.7
Q3 19.4
22.1
16.6
37.8
26.4
21.4
24
18.9
25.3
100 %
28.7
14.3
Q2 38.7
30.5
21.7
28.3
26.8
26.6
28.7
33.9
Q1
22.4
24.2
13.2
15.9
19.6
9.4
16.7
14.8
2016-17
2017-18
2018-19
2019-20
2020-21
2021-22
2022-23
2023-24
2024-25
Figure 3
The figure 3 show the stacked column chart which indicates the quarterly view of ECBs from FY 2016-17 to 2024-25. All the values in percentage form as a total to that particular period. On left side shows the Q1 to Q4. Q1 is at bottom part after Q2 then Q3 and last at top part is Q4.
The Q1 in 2020-21 shows the lowest ECBs Inflow that is 9.4 % and highest in FY 2023-24 was 33.9%. The Q2 in FY 2023-24 shows the lowest raised of Inflow of ECB is 14.3 % and in FY 2016-17 showed highest inflow of ECBs that is 38.7%.
On the other hand, in Q3 lowest was FY 2019- 20 was 16.6 % and high was FY 2022-23 was
37.8 %. In Q4 the low Was 2022-23 was 20.6% and in FY 2020-21 high was 36.4 %. Overall, it indicates the quarterly flow of ECBs in period ranging FY 2016-17 to FY 2024-25. It helped to get more depth of inflow of ECBs.
-
Tenure Wise Analysis (USD Billion)
Aggregate Analysis
Short
Term
2%
3.82
( 1 years)
Long Term, 50%
(>= 5 Year)
Year On Year Analysis
0.36
0.34
0.11
0.03
2.64
0.14
25.09
0.14
19.14
12.30
13.85
7.07
16.10
11.92
11.19
4.43
7.93 12.25 11.46 17.62 12.02 15.04 12.18 15.20 22.63
0.08
Medium Term 48%
(1 -5 Year)
121.08
126.34
2016-17 2017-18 2018-19 2019-20 2020-21 2021-22 2022-23 2023-24 2024-25
Figure – 4
Long Term Medium Term Short Term
Figure – 5
The Figure 4 Donut Chart indicates the overall view of maturity of ECBs. It is clear from the above chart that companies raised ECBs for maximum long term with value of $ 126.34 billion which capture the share of 50%. Subsequently, Medium Term with Value of $ 121.08 with the share of 48%. The least is 2 % covered for short term with value of $ 3.82 billion. Overall, it shows that companies raised ECBs for maximum long term and medium-term maturity and very least for short term tenure.
On the other hand, the figure 5 stacked column chart indicates the year-on-year changes happened in ECBs on basis of maturity. It shows that maximum companys preference is for long term and medium term. In FY 2020-21 show the high short term as compare with other years. Its shows that maximum proportion ECBs raised for long term tenure and Medium-Term tenure.
Note:
In ECBs no such concept of Short Term, Medium Term. Here, for analysis purpose we segregated the maturity on basis of short term, medium term and long term.
|
2024-25 2023-24 2022-23 2021-22 2020-21 2019-20 2018-19 2017-18 |
0.08 0.03 0.14 0.11 2.64 0.36 0.34 0.14 |
||||||
|
2016-17 |
0.00 |
||||||
|
2024-25 |
25.09 |
||||||
|
2023-24 |
13.85 |
||||||
|
2022-23 |
11.19 |
||||||
Max – $ 2.64 Min $ 0.1 Average – $ 0.4
SHORT TERM
USD Billion
F.Y 2016-17 2024-25
Figure 6
Max – $ 25.09 Min $ 4.43 Average – $ 13.4
MEDIUM
TERM
USD Billion
F.Y 2016-17 2024-25
Figure 7
2021-22
12.30
11.92
16.10
7.07
4.43
2020-21
2019-20
2018-19
2017-18
2016-17
19.14
Max – $ 22.63 Min $ 7.93 Average – $ 14.03
LONG TERM
USD Billion
F.Y 2016-17 2024-25
Figure – 8
2024-25
15.20
12.18
15.04
12.02
17.62
11.46
12.25
7.93
2023-24
2022-23
2021-22
2020-21
2019-20
2018-19
2017-18
2016-17
22.63
-
Sectoral Breakdown (USD Billion, %)
Services (39%)
90.26
Agriculture (0.1%)
0.35
Other (1.9%)
4.56
49.43
Infrastructure (21.1%)
Manufacturing (38.3%)
Figure 9
The above figure 10.9, donut chart shows the "Sector-Wise Distribution of ECBs (US$ Billion,
%)" shows how ECBs are distributed across different sectors. Each segment of the chart represents both the absolute value (in billions of US dollars) and the percentage share of the total ECBs.
Services Sector is the largest borrower, accounting for 39% of ECBs (US$ 90.26 billion). Manufacturing closely follows with 38.3% (US$ 89.94 billion). Infrastructure accounts for 21.1% (US$ 49.43 billion).
Others category is relatively small (2%) at US$ 4.56 billion. Agriculture has the lowest share, with only US$ 0.35 billion (<1% of total), indicating limited reliance on external commercial funding in this sector. Hence, ECBs are heavily concentrated in the services and manufacturing sectors, together accounting for 77% of total borrowings.
As the Service sector contributes maximum share in GDP of India. Maximum companies raised ECBs for Services sector, Manufacturing sector and infrastructure sector. This are the top 3 sectors on the basis of ECBs raised by the firms.
-
Year On Year Analysis (USD Billion)
Agriculture Infrastructure Manufacturing Others Services
10.08
15.90
2.00
19.81
0.01
7.50
10.22 0.73
10.61
0.01
3.19 8.47
0.07
8.70
0.05
4.86
0.29
11.49
10.32
0.13
8.27
13.25
0.27
8.20
7.41
11.08
1.14
17.48
0.01
3.00
0.10
4.70
0.09
15.14
9.66
5.57
4.74
2024-25
2023-24
2022-23
2021-22
2020-21
2019-20
2018-19
2017-18
0.00 10.00 20.00 30.00 40.00 50.00 60.00
Figure – 9
The above figure 10.9 stacked bar chart shows the movement of sectors nder which ECBs was raised for the period ranging FY 2016-17 to FY 2024-25. All values in USD Billion form. There are five sectors namely Agriculture, Infrastructure, Manufacturing, Services and others. This chart shows the sector wise breakdown of ECBs.
The chart shows the very least share of Agriculture Sector in all the financial years. Which shows that ECBs provide very less impact on Agriculture Sector. From FY 2016-17 to FY 2024-25 it indicates that service sector increase with ECBs.
On the other hand, share of Manufacturing and Infrastructure also increased. From the above analysis, it clearly explains that companies raised ECBs for Service sector, Manufacturing Sector, Infrastructure Sector and very least for Agriculture sector.
Overall, this shows the year-on-year changes happened in terms of sector.
Service and Manufacturing Sector (USD Billion)
25.00
20.00
15.00
10.00
5.00
0.00
18.00
15.90
15.14
13.25
11.08
10.32
10.22
8.47
5.57
16.00
14.00
12.00
10.00
8.00
6.00
4.00
2.00
2022-23
2023-24
2024-25
0.00
2017-18
2018-19
2019-20
2020-21
2021-22
Services Manufacturing
Figure – 10
Service and Infrastructure Sector (USD Billion)
10.08
8.70
7.41
7.50
4.70
4.86
3.00
3.19
25.00 12.00
20.00
10.00
15.00
10.00
5.00
8.00
6.00
4.00
2.00
2017-18
2018-19
2019-20
2020-21
2021-22
2022-23
2023-24
2024-25
0.00 0.00
Services Infrastructure
Figure 11
Aggregate of all
sectors, $234.18
Agriculture, $0.35
Components under Sector
Min 0.02
Max 0.09
Agriculture Sector
USD Billion
F.Y 2017-18 to 2024-25
Figure 12
Tea Coffee
0.09
0.05
0.05
0.05
0.03
0.03
0.03
0.02
Fishing and aquaculture
Food and beverage service activities Sugar
Agricultural products
Other Agricultural products
Crop and animal production, hunting and related service activities
Min 0.02
Max 1.8
Others
USD Billion
F.Y 2017-18 to 2024-25
11.33
7.90
6.58
3.11
2.07
2.06
1.44
1.02
0.36
0.36
0.30
0.26
0.24
0.21
0.20
0.19
0.19
0.16
0.13
0.13
0.11
0.11
0.05
0.05
0.03
0.03
0.03
0.02
0.02
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
Figure 13
Sports Activities and Amusement and Recreation Activities
0.02
0.03
0.2
1.2
Creative, Arts and Entertainment activities
Broadcasting and programming
activities
1.8
1.3
Wholesale Trade, Except of Motor Vehicles and Motorcycles
Other Professional, Scientific and Technical Activities
Retail trade, except of motor vehicles and motorcycles
Aggregate of all
sectors, 229.97
Others, 4.56
Min 0.01
Max 51.55
Service Sector
USD Billion
F.Y 2017-18 to 2024-25
Figure 14
Financial services Telecommunication services
Water Transport omputer Programming, Consultancy And Related Activities Architecture And Engineering Activities; Technical Testing
Transport services Software development services Scientific Research And Development
Accommodation
Real estate activities
Education Repair And Installation Of Machinery And Equipment Technical engineering & consultancy services
Printing & publishing Security and investigation activities Postal and courier activities
Services To Buildings And Landscape Activities
Repair of computers and personal and household goods
Residential care activities
51.55
Min 0.01
Max 26.91
Manufacturing Sector
USD Billion
F.Y 2017-18 to 2024-25
Figure 15
Petroleum & petroleum products manufacturing Manufacture of chemicals and chemical products Manufacture of motor vehicles, trailers and semi-trailers
Manufacture of Pharmaceuticals, Medicinal Chemical And Botanical
Manufacture of rubber and plastics products Manufacture Of Other Non-Metallic Mineral Products
Ferrous (iron & steel)
Automobiles
Others of manufacturing
Manufacture of Fabricated Metal Products, Except Machinery and
Cement Manufacture Of Other Transport Equipment
Electrical Goods
Manufacture Of Paper And Paper Products
Others Machinery & tools
Rubber goods
Fertilizers
Chemicals & Allied products
Non-ferrous
Cables Manufacture of Furniture Transport equipment Breweries & distilleries Other Transport equipment
Other Chemicals & Allied products
Cotton textile Other Machinery & tools Other manufacturing n.e.c.
Manufacture Of Other Fabricated Metal Products N.E.C.
26.91
9.74
7.59
5.80
5.73
4.32
2.82
2.82
2.38
2.35
2.33
1.99
1.65
1.58
1.45
1.24
1.23
0.99
0.94
0.84
0.59
0.50
0.49
0.37
0.31
0.29
0.25
0.24
0.23
0.18
0.16
0.15
0.15
0.15
0.14
0.13
0.10
0.10
0.09
0.09
0.07
0.07
0.06
0.06
0.05
0.05
0.04
0.04
0.02
0.02
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
7.50
5.46
2.34
0.93
0.90
0.68
0.60
0.52
0.39
0.35
0.34
0.23
0.20
0.20
0.11
0.11
0.09
0.09
0.07
0.01
0.01
0.00
Electricity, Gas, Steam And Air Conditioning Supply Power generation, transmission & distribution Specialized Construction Activities
Land transport and transport via pipelines
Mining of metal ores
Human Health Activities
Utilities 07 Mining of metal ores Mining of coal and lignite
28.30
Min 0.01
Max 28.30
Infrastructure Sector
USD Billion
F.Y 2017-18 to 2024-25
Figure 16
Water collection, treatment and supply
Other mining and quarrying
Other Utilities
-
Purpose Wise Breakdown
Aggregate Analysis (%)
23.8%
18.7%
10.9%
10.6%
6.2%
6.0%
5.9%
5.4%
4.0%
5.7%
1.4%
1.1%
0.4%
On-lending /
Sub-lending
Working Capital
Local Sourcing of Capital Goods (Rupee Expenditure)
Modernization
Infrastructure Development
Overseas investment in JV/ WOS
Micro Finance
Refinancing of Earlier ECB
New Project
Import of Capital Goods
Refinancing of Rupee loans
Other
Overseas Acquisition
Figure 17
The above figure 17 indicates the overall purpose wise changes happened for raising ECBs from period FY 2016-17 to 2024-25. It shows the overall view. All values are in percentage form. It is clear from above chart that maximum companies raised ECBs for on lending / sub lending purpose. That is 23.8 %. Subsequently for Refinancing of Earlier ECBs 18.7% as well as for Working Capital Purpose 10.9 %.
Least for micro finance which was 0.4%. In this diagram shows the combinatio of existing as well as for fulfil new purpose Maximum companies raised ECBs. Like for on lending / sub lending along with refinancing of earlier ECBs. New project along with that Refinancing of rupee loans.
Overall, this shows the purpose wise changes happened over the years.
Pre-Covid Period (%)
Covid
Period (%)
Post Covid Period (%)
Import of Capital Goods
5.79
2.96
6.58
Infrastructure Development
7.62
3.15
2.98
Local Sourcing of Capital Goods (Rupee Expenditure)
7.76
2.92
5.04
Modernization
7.30
2.81
4.81
Micro Finance 0.23 0.11 0.66
Other
On-lending / Sub-lending
New Project
7.72
5.59
13.69
8.15
30.14
22.50
1.26
6.30
2.70
Overseas Acquisition
2.03
0.83
0.07
Refinancing of Earlier ECB
17.72
10
19.84
Overseas investment in JV/ WOS
0.61 0.02 2.90
Refinancing of Rupee loans
Working Capital
6.99 4.46 3.01
13.03 6.73 7.97
Figure 18
Pre-Covid Period
-
The FY 2016-17 to FY 2019-20 represent the Pre- covid Period, in this period shows the Inflow of ECBs for which specific purposes.
-
All the values in percentage form as a total.
-
From this chart it explains that, in pre covid period maximum companies raised ECBs for on lending / sub lending that is 22.50%.
-
Subsequently, for Refinancing of Earlier ECBs for 17.72% as well as for Working capital with 13.03% respectively.
-
Least for raised ECBs for micro finance.
-
In this period shows the mixture of raised ECBs for long tenure as well as for short tenure like raised for import of capital goods along with that working capital.
-
It shows that maximum companies focus for development as the new project for 7.72%, infrastructure development for 7.62%.
-
Overall, this chart helps to understand for what specific purpose companies raised ECBs.
-
Covid Period
-
The FY 2020-21 and FY 2021-22 represent the covid Period, in this period shows the Inflow of ECBs for which purposes.
-
All the values in percentage form as a total.
-
This chart show that, in covid period companies raised ECBs for maximum Refinancing of Earlier ECBs purpose.
-
As in the covid period, there was restrictions on operations of business so its simply, no sources for generating money so companies raised ECBs to finance their earlier loans.
-
Subsequently, for on lending/ sub lending for 8.15 %, for working capital 6.73% etc.,
-
Overall, it shows the pattern of raised ECBs in covid Period.
-
It gives insights about what are the purpose wise shift in raising the ECBs.
Post Covid Period
-
The FY 2022-23 to FY 2024-25 represent the post covid Period, in this period shows the Inflow of ECBs for which specific purposes.
-
All the values in percentage form as a total.
-
This chart explained that, maximum companies raised ECBs for on lending / sub lending purpose which was 30.14 %.
-
Subsequently for, Refinancing of Earlier ECBs which is 19.84%
-
New project 13.69%, For Import of capital goods with 6.58%, for working capital 7.97% etc.
-
As we compare with pre covid and covid period there is increase in percent of new project along with Overseas investment in JV / WOS, which indicates that companies focus for development, help to creates employment opportunities, beneficial for economic growth of the country as well.
-
Overall, it shows the purpose wise changes happened by companies who raised ECBs.
-
Borrower wise Analysis
Share of Listed and Unlisted ECB Borrowers (USD Billion, %)
Top Borrowers by Frequency of ECB Raising
77.1, 30%
177.9, 70%
32
30
28
27
23
Nagata Auto Engineering India Pvt ltd
Listed JSW Steel limited
Unlisted
Reliance Industries Limited
Indian Oil Corporation Limited
Figure – 19
Satin Creditcare Network Limited
0 5 10 15 20 25 30 35
Figure – 20
25.00
Top Five Companies with Highest ECBs (USD Billion)
20.00
15.00
10.00
5.00
0.00
19.14
8.48
7.07
6.32
6.27
Reliance Industries Limited
Indian Oil Corporation Limited
Export-Import Bank of India
NTPC Limited ONGC Vides
Limited
Figure – 21
The above figures show the insight of borrowers in terms of ECBs, it shows that listed companies raised the maximum number of ECB and also analysed the companies which have done ECBs frequently along with that the top 5 companies which have raised highest number of ECBs.
This chapter provides an in-depth insight into the borrowers who have raised ECB during the period 2016-17 to 2024-25. First, we have an overall view of the borrowers. A more detailed analysis of the top 2 companies is given. Including company analysis, financial analysis, analysis based on ECB etc., this chapter will give you in-depth information about the companies which have done ECB
-
Reliance Industries Limited –
7.11
3.20
2.65
2.46
1.10
1.50
0.94
0.18
0.00
8.00
7.84, 41%
8.85, 46%
2.46, 13%
7.00
6.00
USD Billion
5.00
4.00
3.00
2.00
1.00
2016-17
2017-18
2018-19
2019-20
2020-21
2021-22
2022-23
2023-24
2024-25
0.00
Long Term Medium Term Short Term
Figure -22 Figure – 23
C) Purpose Wise D) Sector Wise
13.19
4.46
1.50
14.00
12.00
25.00
10.00
8.00
6.00
4.00
2.00
20.00
15.00
10.00
5.00
0.00
Import of Capital Goods Other Refinancing of Earlier ECB
0.00
19.14
Manufacturing
Annual Snapshot Income Statement (Rs. Crores)
Figure – 24 Figure – 25
From the above analysis it states that, it raised maximum number of ECBs in FY 2020-21 with $ 7.11 billion. They raised ECBs for maximum medium term maturity period. Subsequently, mostly they raised ECBs for refinancing of earlier ECBs purpose. Along with that they raised, only for manufacturing Sector.
Report Date Mar-21 Mar-22 Mar-23 Mar-24 Mar-25
|
Sales |
486326 |
717635 |
891311 |
914472 |
980136 |
|
% Growth YOY |
48% |
24% |
3% |
7% |
|
|
Total Expenses |
426778 |
623773 |
768720 |
775357 |
838961 |
|
Total Expenses % Sales |
88% |
87% |
86% |
85% |
86% |
|
EBTDA |
59548 |
93862 |
122591 |
139115 |
141175 |
|
EBITDA Margins (%) |
12% |
13% |
14% |
15% |
14% |
|
Other Income |
16327 |
14943 |
11734 |
16057 |
17978 |
|
Other Income as % of sales |
3.4% |
2.1% |
1.3% |
1.8% |
1.8% |
|
Depreciation |
26572 |
29782 |
40303 |
50832 |
53136 |
|
EBIT |
32976 |
64080 |
82288 |
88283 |
88039 |
|
EBIT Margin (%) |
6.8% |
8.9% |
9.2% |
9.7% |
9.0% |
|
Interest |
-18340 |
-26349 |
-21650 |
-37173 |
-41024 |
|
Profit Before Tax (PBT) |
55461 |
82154 |
94046 |
104727 |
106539 |
|
% Growth YOY |
48.1% |
14.5% |
11.4% |
1.7% |
|
|
PBT Margin |
11.4% |
11.4% |
10.6% |
11.5% |
10.9% |
|
Tax |
1722 |
15970 |
20376 |
25707 |
25230 |
|
Net Profit |
53739 |
66184 |
73670 |
79020 |
81309 |
Annual Snapshot Cash Flow Statement (Rs. Crores)
|
Report Date |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Cash from operating Activity (CFO) |
26958 |
110654 |
115032 |
158401 |
178703 |
|
% Growth YOY |
310.5% |
4.0% |
37.7% |
12.8% |
|
|
Cash from Investing Activity |
-142409 |
-110103 |
-91235 |
-113581 |
-137535 |
|
Cash from Financing Activity |
101904 |
17289 |
10455 |
-16646 |
-31891 |
|
Net Cash Flow |
-13547 |
17840 |
34252 |
28174 |
9277 |
Annual Snapshot Balance Sheet (Rs. Crores)
|
Report Date |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Assets cash & cash Equivalent |
17397 |
36174 |
68664 |
97225 |
106502 |
|
Accounts Receivable |
19014 |
23640 |
28448 |
31628 |
42121 |
|
Other Current Assets |
336600 |
287201 |
328184 |
341247 |
350647 |
|
Total Current Assets |
373011 |
347015 |
425296 |
470100 |
499270 |
|
Property, Plant & Equipment |
451066 |
500454 |
570503 |
606084 |
683102 |
|
Intangible Assets |
90192 |
47640 |
78951 |
104049 |
169169 |
|
other Non-current Assets |
406943 |
604552 |
532681 |
575753 |
598580 |
|
Total Assets |
1321212 |
1499661 |
1607431 |
1755986 |
1950121 |
|
Liabilities & Equity Accounts Payable |
108897 |
159330 |
147172 |
178377 |
186789 |
|
other current liability |
108590 |
70726 |
117781 |
117080 |
156317 |
|
Short-Term Debt |
60081 |
78606 |
130790 |
101910 |
110631 |
|
Total Current Liabilities |
277568 |
308662 |
395743 |
397367 |
453737 |
|
Long- Term Debt |
163683 |
187699 |
183176 |
222712 |
236899 |
|
other non-current liability |
80529 |
114320 |
199631 |
210119 |
249859 |
|
Total Non- Current Liabilities |
244212 |
302019 |
382807 |
432831 |
486758 |
|
Share Capital |
6445 |
6765 |
6766 |
6766 |
13532 |
|
Other Equity |
693727 |
772720 |
709106 |
786715 |
829668 |
|
Non-Controlling Interest |
99260 |
109499 |
113009 |
132307 |
166426 |
|
Total Equity |
799432 |
888984 |
828881 |
925788 |
1009626 |
|
Total Liabilities & Equity |
1321212 |
1499665 |
1607431 |
1755986 |
1950121 |
Ratio Analysis
Profitability Ratios
|
Particular |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Gross Margin |
19.6% |
17.7% |
18.7% |
20.5% |
19.8% |
|
EBITDA Margin |
11.8% |
12.8% |
13.6% |
15.0% |
14.1% |
|
PBT Margin |
11.0% |
11.2% |
10.4% |
11.3% |
10.7 |
|
Net Margin |
10.7% |
9.0% |
8.2% |
8.5% |
8.1% |
|
Sales Growth |
47.6% |
24.2% |
2.6% |
7.2% |
|
|
Expenses Growth |
44.2% |
23.8% |
2.1% |
8.0% |
|
|
Gross profit Growth |
33.1% |
31.3% |
12.5% |
3.2% |
|
|
EBITDA Growth |
57.6% |
30.6% |
13.5% |
1.5% |
|
|
EBIT Growth |
94.3% |
28.4% |
7.3% |
-0.3% |
|
|
PBT Growth |
48.1% |
14.5% |
11.4% |
1.7% |
|
|
Net Profit Growth |
23.2% |
11.3% |
7.3% |
2.9% |
|
Efficiency Ratios
|
Particular |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
|
Debtor Turnover 14.27 12.02 11.65 |
12.62 15.69 |
|||||
|
Net Fixed Asset Turnover 0.51 0.62 0.75 |
0.71 0.68 |
|||||
|
Total Asset Turnover 0.37 0.48 0.55 |
0.52 0.50 |
|||||
|
Sales / Capital Employed |
0.47 |
0.60 |
0.74 |
0.67 |
0.66 |
|
Leverage Ratios
|
Particular |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Debt / Equity |
0.32x |
0.34x |
0.43x |
0.40x |
0.41x |
|
Debt / Assets |
16.9% |
17.8% |
19.5% |
18.5% |
17.8% |
|
Debt / EBITDA |
375.8% |
283.7% |
256.1% |
233.3% |
246.2% |
|
Debt / Capital |
24.2% |
25.5% |
30.5% |
29.0% |
29.2% |
|
CFO / debt |
12.0% |
41.6% |
36.6% |
48.8% |
51.4% |
|
Interest Coverage Ratio (Times) |
2.81 |
6.44 |
6.26 |
6.02 |
5.82 |
|
Operating Leverage |
1.98 |
1.17 |
2.80 |
-0.04 |
|
|
Financial Leverage |
0.59 |
0.78 |
0.87 |
0.84 |
0.83 |
Capital Allocation Ratios
Particular Mar-21 Mar-22 Mar-23 Mar-24 Mar-25
ROCE 5.1% 5.6% 6.1% 5.8% 5.4%
ROE 6.7% 7.4% 8.9% 8.5% 8.1%
ROA 4.1% 4.4% 4.6% 4.5% 4.2%
Dupont Analysis
Return on Equity (ROE)
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
53739 |
66184 |
73670 |
79020 |
81309 |
|
Average Shareholders Equity |
630389.5 |
844208 |
858932.5 |
877334.5 |
967707 |
|
Return on Equity (ROE) |
8.5% |
7.8% |
8.6% |
9.0% |
8.4% |
|
ROE – Dupont Equation |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
53739 |
66184 |
73670 |
79020 |
81309 |
|
Revenue |
486326 |
717635 |
891311 |
914472 |
980136 |
|
Net Profit Margin (A) |
11.0% |
9.2% |
8.3% |
8.6% |
8.3% |
|
Revenue |
486326 |
717635 |
891311 |
914472 |
980136 |
|
Average Total Assets |
1243563.5 |
1410436.5 |
1553546 |
1681708.5 |
1853053.5 |
|
Asset Turnover Ratio (B) |
0.39x |
0.51x |
0.57x |
0.54x |
0.53x |
|
Average Total Assets |
1243563.5 |
1410436.5 |
1553546 |
1681708.5 |
1853053.5 |
|
Average Shareholders Equity |
630389.5 |
844208 |
858932.5 |
877334.5 |
967707 |
|
Equity Multiplier (C) |
1.97x |
1.67x |
1.81x |
1.92x |
1.91x |
|
Return on Equity (A*B*C) |
8.5% |
7.8% |
8.6% |
9.0% |
8.4% |
|
Return on Asset (ROA) |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-2 |
Mar-25 |
|
Net Profit |
53739 |
66184 |
73670 |
79020 |
81309 |
|
Average Total Assets |
1243563.5 |
1410436.5 |
1553546 |
1681708.5 |
1853053.5 |
|
Return on Asset (ROA) |
4.3% |
4.7% |
4.7% |
4.7% |
4.4% |
|
ROA – Dupont Equation |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
53739 |
66184 |
73670 |
79020 |
81309 |
|
Revenue |
486326 |
717635 |
891311 |
914472 |
980136 |
|
Net profit Margin (A) |
11% |
9% |
8% |
9% |
8% |
|
Revenue |
486326 |
717635 |
891311 |
914472 |
980136 |
|
Average Total Asset |
1243563.5 |
1410436.5 |
1553546 |
1681708.5 |
1853053.5 |
|
Asset Turnover Ratio (B) |
0.39x |
0.51x |
0.57x |
0.54x |
0.53x |
|
Return on Asset (A*B) |
4.3% |
4.7% |
4.7% |
4.7% |
4.4% |
Net Profit
Total Equity
90,000
80,000
70,000
60,000
50,000
40,000
30,000
20,000
10,000
53,739
66,184
73,670
79,020
81,309
2,00,000
0,00,000
8,00,000
6,00,000
4,00,000
2,00,000
7,99,432
8,88,984
8,28,881
9,25,788
10,09,626
–
2021 2022 2023 2024 2025
–
2021 2022 2023 2024 2025
Figure – 26 Figure – 27
Financial Leverage
Asset Turnover
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
0.59
0.78
0.87 0.84 0.83
0.60
0.50
0.40
0.30
0.20
0.10
0.00
0.37
0.48
0.55
0.52 0.50
2021 2022 2023 2024 2025
Figure – 28
2021 2022 2023 2024 2025
Figure – 29
Return On Equity % Return On Asset %
9.2%
9.0%
8.8%
8.6%
8.4%
8.2%
8.0%
7.8%
7.6%
7.4%
7.2%
8.5%
7.8%
8.6%
9.0%
8.4%
4.7%
4.6%
4.5%
4.4%
4.3%
4.2%
4.1%
4.0%
3.9%
3.8%
4.1%
4.4%
4.6%
4.5%
4.2%
2021 2022 2023 2024 2025
2021 2022 2023 2024 2025
Figure – 30 Figure – 31
Disaggregated Revenue
70.00
60.00
50.00
40.00
30.00
61.63
59.35
29.28
29.43
20.00
10.00
0.00
2.00
1.99
2.81
2.39
4.28
6.83
Oil to Chemicals Oil and Gas Retail Digital Services Others
2024-25 2023-24
Figure – 32
Domestic vs. Foreign Revenue: Sectoral Breakdown
2024-25
36%
Within India
64%
Outside India
Figure – 33
2023-24
35%
65%
Within India
Shareholding Pattern, March 25
Outside India
Shareholding Pattern
1.99%
Promoter
49.11%
48.90%
Public Shareholding
Non Promoter Non Public
Figure – 34
Strength
-
Wide Geographic Presence
-
Market Leadership Position
-
Diverse Revenue Model
-
Strong Market Share
Weakness
High cost of replacing experts.
Losing niche and local dominance.
Diminishing market share with an increasing revenue
SWOT Analysis
Threats
-
Urban markets saturated; rural growth stagnant.
-
Rising tech skills increasing competition.
O
Opportunities
Local partnerships.
Growing low-income customer base.
Online growth potential. Cheaper product launches via partners and social media.
In this part, we study about the Reliance Industries Limited in depth. First, we started with its brief introduction then towards the business segments highlights and credit rating scores. We also analysed on context of ECBs. Financial analysis includes analysis of 3 pivotal financial statements and also performed the DuPont analysis along with information of shareholding structure and conclude with SWOT analysis
-
Indian oil Corporation Limited –
External Commercial Borrowings Trends
-
Year Wise B) Tenure Wise
-
2.6
2.55
1.83
0.6
0.3
0.3
0.2
0
0.1
3
5.43, 64%
3.05, 36%
2.5
2
1.5
1
0.5
0
2016-17
2017-18
2018-19
2019-20
2020-21
2021-22
2022-23
2023-24
2024-25
Long Term Medium Term
Figure – 35 Figure – 36
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
-
Purpose Wise D) Sector Wise
3.93
3.6
0.35
0.3
0.3
8.48
9
8
7
6
5
4
3
2
1
0
Refinancing of Earlier ECB
Working Capital Local Sourcing of
Capital Goods
(R.E)
Annual Snapshot Income Statement (Rs. Crores)
Figure – 37
Modernisation Other
Manufacturing
Figure – 38
The above data indicates that the company raised the highest number of ECBs during the year 201819. Most of the loans were obtained for medium-term purposes, followed by long-term borrowings. The majority of these loans were associated with the manufacturing sector and were utilized for various purposes, with the largest share allocated to the refinancing of earlier ECBs and the next significant portion for meeting working capital requirements.
|
Report Date |
Mar-20 |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Sale |
575990 |
520237 |
736716 |
951410 |
881235 |
859363 |
|
% Growth YOY |
-9.7% |
41.6% |
29.1% |
-7.4% |
-2.5% |
|
|
Total Expenses |
576609.99 |
483240.93 |
694412.42 |
928252.31 |
813466.04 |
832634.1 |
|
Total Expenses % Sales |
100.11% |
92.89% |
94.26% |
97.57% |
92.31% |
96.89% |
|
EBITDA |
-620 |
36996 |
42304 |
23158 |
67769 |
26729 |
|
EBITDA Margins (%) |
-0.11% |
7.11% |
5.74% |
2.43% |
7.69% |
3.11% |
|
Other Income |
2773.62 |
3499.54 |
3096.76 |
4198.92 |
3838.56 |
3513.73 |
|
Other Income as % of sales |
0.48% |
0.67% |
0.42% |
0.44% |
0.44% |
0.41% |
|
Depreciation |
16165.4 |
10941.45 |
12347.58 |
13181.05 |
15866.11 |
16777.34 |
|
EBIT |
-16786 |
26054 |
29956 |
9977 |
51903 |
9951 |
|
EBIT Margin (%) |
-2.9% |
5.0% |
4.1% |
1.0% |
5.9% |
1.2% |
|
Interest |
-4393.85 |
-4506.3 |
-4660.13 |
-7009.51 |
-7768.86 |
-8723.21 |
|
Profit Before Tax (PBT) |
-23950.62 |
30750.73 |
34288.62 |
15037.69 |
57287.79 |
17063.45 |
|
% Growth YOY |
-228.4% |
11.5% |
-56.1% |
281.0% |
-70.2% |
|
|
PBT Margin |
-4.2% |
5.9% |
4.7% |
1.6% |
6.5% |
2.0% |
|
Tax |
-5300.69 |
8988.51 |
8562.02 |
3333.43 |
14126.64 |
3274.62 |
|
Net Profit |
-18650 |
21762 |
25727 |
11704 |
43161 |
13789 |
Annual Snapshot Cash Flow Statement (Rs. Crores)
|
Report Date |
Mar-20 |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Cash from operating Activity (CFO) |
9853.23 |
49861.73 |
25746.67 |
29643.72 |
71146.41 |
34699.28 |
|
% Growth YOY |
406.0% |
-48.4% |
15.1% |
140.0% |
-51.2% |
|
|
Cash from Investing Activity |
-29100.76 |
– 24244.89 |
-21283.6 |
-28029.56 |
-31511.53 |
-31848.19 |
|
Cash from Financing Activity |
22456.03 |
– 26270.21 |
-4057.7 |
-1794.4 |
-39384.64 |
-3424.51 |
|
Net Cash Flow |
3208.5 |
-653.37 |
405.4 |
-180.24 |
250.24 |
-573.42 |
Annual Snapshot Balance Sheet (Rs. Crores)
|
Report Date |
Mar 2020 |
Mar 2021 |
Mar 2022 |
Mar 2023 |
Mar 2024 |
Mar 2025 |
|
Assets |
||||||
|
cash & cash Equivalent |
1434.61 |
781.24 |
1176.59 |
996.35 |
1246.59 |
673.17 |
|
Accounts Receivable |
13259.48 |
13800.28 |
18700.42 |
16271.21 |
13831.45 |
18550.96 |
|
Other Current Assets |
96041.19 |
101627.17 |
126983.68 |
141597.93 |
143364.58 |
138419.02 |
|
Total Current Assets |
110735.28 |
116208.69 |
146860.69 |
158865.49 |
158442.62 |
157643.15 |
|
Property, Plant & Equipment |
144076.3 |
153698.39 |
157194.98 |
176532.05 |
192159.52 |
197162.03 |
|
Intangible Assets |
2944.79 |
3385.36 |
3318.33 |
3514.48 |
3837.23 |
3979.1 |
|
other Non-current Assets |
71980.46 |
81623.48 |
103250.85 |
102850.07 |
127922.63 |
148082.77 |
|
Total Assets |
329736.83 |
354915.92 |
410624.85 |
441762.09 |
482362 |
506867.05 |
|
Liabilities & Equity |
||||||
|
Accounts Payable |
27576.26 |
37247.97 |
49061.85 |
54734.1 |
59454.1 |
60534.94 |
|
other current liability |
64044.14 |
77346.91 |
76197.21 |
75122.35 |
80289.16 |
79275.32 |
|
Short-Term Debt |
69897.44 |
47580.01 |
67605.56 |
76801.88 |
76660.67 |
90804.15 |
|
Total Current Liabilities |
161517.84 |
162174.89 |
192864.62 |
206658.33 |
216403.93 |
230614.41 |
|
Long- Term Debt |
56070.61 |
60934.9 |
55944.54 |
6332.94 |
46792.9 |
51755.75 |
|
other non-current liability |
15874.2 |
18992.14 |
26689.04 |
28576.48 |
31002.19 |
33472.23 |
|
Total Non- Current Liabilities |
71944.81 |
79927.04 |
82633.58 |
91889.42 |
77795.09 |
85227.98 |
|
Share Capital |
9181.04 |
9181.04 |
9181.04 |
13771.56 |
13771.56 |
13771.56 |
|
Other Equity |
86216.87 |
102657.01 |
124354.14 |
125948.68 |
169644.71 |
172715.76 |
|
Non-Controlling Interest |
876.27 |
975.94 |
1591.47 |
3494.1 |
4746.71 |
4537.34 |
|
Total Equity |
96274.18 |
112813.99 |
135126.65 |
143214.34 |
188162.98 |
191024.66 |
|
Total Liabilities & Equity |
329736.83 |
354915.92 |
410624.85 |
441762.09 |
482362 |
506867.05 |
|
Profitability Ratios |
||||||
|
Particular |
Mar-20 |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Gross Margin |
11.9% |
17.0% |
13.9% |
9.9% |
15.6% |
11.8% |
|
EBITDA Margin |
-0.1% |
7.1% |
5.7% |
2.4% |
7.7% |
3.1% |
|
PBT Margin |
-4.1% |
5.9% |
4.6% |
1.6% |
6.5% |
2.0% |
|
Net Margin |
-3.2% |
4.2% |
3.5% |
1.2% |
4.9% |
1.6% |
|
Sales Growth |
-9.7% |
41.6% |
29.1% |
-7.4% |
-2.5% |
|
|
Expenses Growth |
-16.6% |
43.0% |
33.2% |
-11.9% |
2.4% |
|
|
Gross profit Growth |
28.9% |
15.7% |
-8.1% |
46.2% |
-26.3% |
|
|
EBITDA Growth |
-6064.3% |
14.3% |
-45.3% |
192.6% |
-60.6% |
|
|
EBIT Growth |
-255.2% |
15.0% |
-66.7% |
420.3% |
-80.8% |
|
|
PBT Growth |
-228.4% |
11.5% |
-56.1% |
281.0% |
-70.2% |
|
|
Net Profit Growth |
-216.7% |
18.2% |
-54.5% |
268.8% |
-68.1% |
|
|
Efficiency Ratios |
||||||
|
Particular |
Mar-20 |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Debtor Turnover |
8.40 |
9.68 |
9.26 |
6.24 |
5.73 |
7.88 |
|
Net Fixed Asset Turnover |
2.63 |
2.18 |
2.79 |
3.36 |
2.72 |
2.46 |
|
Total Asset Turnover |
1.75 |
1.47 |
1.79 |
2.15 |
1.83 |
1.70 |
|
Sales / Capital Employed |
3.42 |
2.70 |
3.38 |
4.05 |
3.31 |
3.11 |
|
Leverage Ratios |
||||||
|
Particular |
Mar-20 |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Debt / Equity |
1.32x |
0.97x |
0.93x |
1.00x |
0.67x |
0.76x |
|
Debt / Assets |
38.2% |
30.6% |
30.1% |
31.7% |
25.6% |
28.1% |
|
Debt / EBITDA |
– 20307.9% |
293.3% |
292.1% |
605.0% |
182.2% |
533.4% |
|
Debt / Capital |
56.9% |
49.2% |
48.1% |
50.1% |
40.2% |
43.3% |
|
CFO / debt |
7.8% |
45.9% |
20.8% |
21.2% |
57.6% |
24.3% |
|
Interest Coverage Ratio |
-0.09x |
10.31x |
7.80x |
3.07x |
8.66x |
2.89x |
|
Operating Leverage |
0.36 |
-2.29 |
-56.77 |
32.32 |
||
|
Financial Leverage |
0.7 |
0.85 |
0.87 |
0.66 |
0.91 |
0.58 |
|
Capital Allocation Ratios |
||||||
|
Particular |
Mar-20 |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
ROCE |
-0.37% |
19.19% |
19.43% |
9.85% |
25.48% |
9.68% |
|
ROE |
-19.4% |
19.3% |
19.0% |
8.2% |
22.9% |
7.2% |
|
ROA |
-5.7% |
6.1% |
6.3% |
2.6% |
8.9% |
2.7% |
|
Return on Equity (ROE) |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
21572.25 |
26054.41 |
13652.66 |
45545.52 |
15399.86 |
|
Average Shareholders Equity |
104544.1 |
123970.3 |
139170.5 |
165688.7 |
189593.8 |
|
Return on Equity (ROE) |
20.6% |
21.0% |
9.8% |
27.5% |
8.1% |
|
ROE-Dupont Equation |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
21572.25 |
26054.41 |
13652.66 |
45545.52 |
15399.86 |
|
Revenue |
520236.8 |
736716.3 |
951409.9 |
881235.5 |
859362.7 |
|
Net Profit Margin (A) |
4.1% |
3.5% |
1.4% |
5.2% |
1.8% |
|
Revenue |
520236.8 |
736716.3 |
951409.9 |
881235.5 |
859362.7 |
|
Average Total Assets |
342326.4 |
382770.4 |
426193.5 |
462062 |
494614.5 |
|
Asset Turnover Ratio (B) |
1.52x |
1.92x |
2.23x |
1.91x |
1.74x |
|
Average Total Assets |
342326.4 |
382770.4 |
426193.5 |
462062 |
494614.5 |
|
Average Shareholders Equity |
104544.1 |
123970.3 |
139170.5 |
165688.7 |
189593.8 |
|
Equity Multiplier (C) |
3.27x |
3.09x |
3.06x |
2.79x |
2.61x |
|
Return on Equity (A*B*C) |
20.6% |
21.0% |
9.8% |
27.5% |
8.1% |
|
Return on Asset (ROA) |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
21572.25 |
26054.41 |
13652.66 |
45545.52 |
15399.86 |
|
Average Total Assets |
342326.4 |
382770.4 |
426193.5 |
462062 |
494614.5 |
|
Return on Asset (ROA) |
6.3% |
6.8% |
3.2% |
9.9% |
3.1% |
|
ROA – Dupont Equation |
|||||
|
Particulars |
Mar-21 |
Mar-22 |
Mar-23 |
Mar-24 |
Mar-25 |
|
Net Profit |
21572.25 |
26054.41 |
13652.66 |
45545.52 |
15399.86 |
|
Revenue |
520236.8 |
736716.3 |
951409.9 |
881235.5 |
859362.7 |
|
Net profit Margin (A) |
4.1% |
3.5% |
1.4% |
5.2% |
1.8% |
|
Revenue |
520236.8 |
736716.3 |
951409.9 |
881235.5 |
859362.7 |
|
Average Total Asset |
342326.4 |
382770.4 |
426193.5 |
462062 |
494614.5 |
|
Asset Turnover Ratio (B) |
1.52x |
1.92x |
2.23x |
1.91x |
1.74x |
|
Return on Asset (A*B) |
6.3% |
6.8% |
3.2% |
9.9% |
3.1% |
Net Profit Total Equity
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
–
21,572
26,054
13,653
45,546
15,400
2,50,000
2,00,000
1,50,000
1,00,000
50,000
–
1,12,814
1,35,127 1,43,214
1,88,163 1,91,025
2021 2022 2023 2024 2025 2021 2022 2023 2024 2025
Figure – 39 Figure – 40
Financial Leverage Asset Turnover
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0.85 0.87
0.66
0.91
0.58
2.50
2.00
1.50
1.00
0.50
0.00
1.47
1.79
2.15
1.83
1.70
2021 2022 2023 2024 2025 2021 2022 2023 2024 2025
Figure – 41 Figure – 42
Return on Equity % Return on Asset %
25.0%
22.9%
10.0%
8.9%
|
20.0% 1 |
9.3% 19.0% |
9.0% 8.0% |
|||
|
7.0% |
|||||
|
15.0% |
6.0% |
||||
|
5.0% |
|||||
6.1% 6.3%
10.0%
5.0%
0.0%
8.2%
7.2%
4.0%
3.0%
2.0%
1.0%
0.0%
2.6%
2.7%
2021 2022 2023 2024 2025 2021 2022 2023 2024 2025
Figure – 43 Figure – 44
Disaggregated Revenue
99.45
99.49
0.04
0.02
0.49
0.51
100%
100%
100%
99%
99%
99%
2024-25 2023-24
Sale of Products and Crude Sale of Services Other Operating Revenues
Figure – 45
Domestic vs. Foreign Revenue: Sectoral Breakdown
2024-25 2023-24
5%
India
95%
Outside Ind
Figure –
95%
5%
India
Outside
SWOT Analysis
Shareholding Pattern March 2025
46
Sharehoding Pattern
0.11%
51.50%
Promoter
Public Shareholding
Figure – 47
Strength
-
Large Distribution Network
-
Majority Share in Petroleum Products
Weakness
-
High Competition from Competitors
-
High Operation Cost
SWOT Analysis
Threats
-
High Competition
-
Regulatory constraints.
O
Opportunities
-
Natural Gas Market
-
Global Expansion
In this chapter, we learned in depth about borrowers who raised ECBs. First, we saw an overall view then specific top 2 companies who raised maximum number of ECBs. Initially We studied the details of both the companies in depth, which included introduction, financial statement analysis, Ratio Analysis, ECBs analysis, shareholding pattern and SWOT analysis.
-
Statistical Modal
Up to this point we get insights about ECBs on different parameters like on basis of purpose, on basis of tenures, on basis of economic sector etc., all this analysis helps to understand the data on ECB and get meaningful insights from it. In this part we are going to analyze the factors that influence the inflow of ECBs. To do this we created one statistical model that is Multiple Linear Regression Model. To understand the factors that affecting the flow of ECBs in India.
Multiple Linear Regression Model help for analysis of independent variables with respect to their dependent variables. It helps to understand the relationship between these two variables. This is the important part of this project, where we create multiple linear regression model to understand the ECBs and their factors that influence the inflow of ECBs. To perform this model, we collected data from multiple platforms. Detail explanation about this model and their data sources is given as follows:
Data Source:
Variables Source Name
-
US Interest Rate Federal Reserve Bank of ST. Louis
-
FDI Data Reserve Bank of India
-
GE Indicator World Bank
-
PV Indicator World Bank
-
RI Indicator World Bank
-
Dummy Variables:
-
Covid Dummy Variable – 1 for 2020 Q1 to 2021 Q4, and 0 for others.
-
Russia Ukraine Dummy Variable – 1 for 2022 Q1 to 2022 Q3, and 0 for others.
-
Description of Variables
-
GE (Government Effectiveness) –
A World Bank Governance Indicator reflecting perceptions of the quality of public services, policy formulation, and implementation credibility. A higher value implies more effective governance, which may attract foreign borrowing.
-
PV (Political Stability and Absence of Violence/Terrorism)
Captures political risk and the likelihood of political unrest or terrorism. Greater stability (higher value) is expected to positively influence ECB inflows by reducing perceived risk.
-
Covid Dummy –
A binary (dummy) variable that equals 1 for quarters from 2020 Q1 to 2021 Q4, and 0 otherwise. Captures the disruptive impact of the COVID-19 pandemic on borrowing behavior (supply and demand side).
-
Russia-Ukraine Dummy –
Equals 1 for quarters from 2022 Q1 to 2022 Q3, and 0 otherwise. Captures the short-term global uncertainty due to the war and its potential impact on investor sentiment and capital flows.
-
RL (Rule of Law)
Another institutional quality indicator, reflecting confidence in the legal system, property rights, contract enforcement, etc. A higher value may encourage lenders to provide capital.
-
Interest Difference (Lagged Interest Rate Differential)
Measures the difference between Indias interest rate and the U.S. interest rate, with a 1-period lag. A higher differential implies that borrowing in foreign currency might be more attractive (or vice versa depending on hedging costs and exchange expectations).
-
LFDI (Log of Foreign Direct Investment)
Indicates the level of foreign investor confidence and long-term capital flows. Higher FDI may correlate with more favorable external financing conditions, or signal economic stability that boosts ECB inflows.
Formula
LTECBt=0+1(GEt)+2 (PVt)+3(Covid Dummyt)+4(Russia Ukraine Dummyt)+5 (Rlt)+6 (Interest Diff-1)+ 7(LFDIt)+
Independent Variables
-
GEt = Government Effectiveness Indicator
-
PVt = Political stability and Absence of violence / Terrorism
-
Covid Dummyt = Dummy variable for the COVID-19 pandemic period 2020 q1 to 2021 q4 for 1. and 0 for others
-
Russia Ukraine Dummyt = Dummy variable for the Russia-Ukraine war period 2022 q1 to 2022 q3 for 1 and 0 for others
-
RLt = Rule of Law Indicator
-
Interest Difference -1 = Difference of interest rate between India and USA lag
-
LFDIt = Log Foreign Direct Investment
-
0 = Intercept term
-
1 to 7 = Coefficients measuring the impact of each independent variable
-
= Error term capturing unobserved factors
Dependent Variable
– LTECBt = Long Term External Commercial Borrowing at time t
Frequency Distribution
|
Statistics |
||||||
|
COVID_DU M |
IND_US_INT_1 00 |
LFDI |
RUSSIA_U KR |
RL |
||
|
N |
Valid |
32 |
32 |
32 |
32 |
32 |
|
Missing |
0 |
0 |
0 |
0 |
0 |
|
|
Mean |
.25 |
.045618854189 405 |
2.47336660 4631799 |
.09 |
-.0037 |
|
|
Median |
.00 |
.047963156887 434 |
2.45042198 6886050 |
.00 |
-.0450 |
|
|
Mode |
0 |
.027838388547 788a |
1.711690753 76946a |
0 |
-.06 |
|
|
Std. Deviation |
.440 |
.007338372248 582 |
.290324879 454336 |
.296 |
.09718 |
|
|
Variance |
.194 |
.000 |
.084/p> |
.088 |
.009 |
|
|
Minimum |
0 |
.027838388547 788 |
1.711690753 76946 |
0 |
-.11 |
|
|
Maximum |
1 |
.055810248647 541 |
3.14949302 202034 |
1 |
.19 |
|
|
Sum |
8 |
1.45980333406 0947 |
79.1477313 4821758 |
3 |
-.12 |
|
Figure 48
Statistics
|
PV |
LTECB |
GE |
|||
|
N |
Valid |
32 |
32 |
32 |
|
|
Missing |
0 |
0 |
0 |
||
|
Mean |
-.790000000000000 |
1.08872012671 6609 |
.2450 |
||
|
Median |
-.785000000000000 |
1.07013300618 5775 |
.2550 |
||
|
Mode |
-1.000000000000000a |
.250448109374 486a |
.37 |
||
|
Std. Deviation |
.133150412158823 |
.382610334734 466 |
.15078 |
||
|
Variance |
.018 |
.146 |
.023 |
||
|
Minimum |
-1.000000000000000 |
.250448109374 486 |
.04 |
||
|
Maximum |
-.620000000000000 |
1.92690266255 6860 |
.48 |
||
|
Sum |
-25.279999999999990 |
34.8390440549 31480 |
7.84 |
||
Figure 49
Variable Explanation Mean Std Dev Min Max
|
RL |
Rule of Law |
-.00 |
.097 |
-.11 |
.19 |
|
LFDI |
Log Foreign Direct Investment |
2.47 |
.290 |
1.71 |
3.14 |
|
IND_US_INT |
Interest Difference(USA &IND) |
.04 |
.007 |
.027 |
.05 |
|
GE |
Government Effectiveness |
.24 |
.15 |
.04 |
.48 |
|
PV |
Political stability & Absence of violence |
.79 |
.133 |
-1 |
-0.62 |
|
LTECB |
Long Term ECB |
1.08 |
.382 |
250 |
1.92 |
Dummy Variable Explanation Mean Std Dev Min Max
COVID_DUM = 1 Covid Period Otherwise 0 .25 .440 0 1
RUSSIA_UKR =1 Russia Ukraine War period Otherwise 0 .09 .296 0 1
Figure 50
Result
Figure 51
The above figure indicates that, R² is 0.3139 / (or 31.4%) this means that 31.4% of the variation in Long-Term ECB is explained by the independent variables: Government Effectiveness (GE), Political Stability (PV), Covid Dummy, Russia-Ukraine Dummy, Rule of Law (RL), Interest Rate Differential, and Log FDI. The above result state that the instituitional Factors like GE, PV provide the impact on inflow of ECBs. Covid Dummy is marginally significant as it provides the negative impact on inflow of ECBs.
We always assumed that because of low interest rates companies go for ECBs but in this research we get different answer that the instituitional factors affects the inflow of ECBs. That out political conditions, Government Stability create confidence that we will repay our loan so help foe increase the flow of ECBs.
-
Findings of the study
-
Overall, it shows the increasing trend of inflow of ECBs over the years from FY 2016-17 to 2024-25.
-
Maximum companies raised ECBs for long term maturity period.
-
Maximum ECBs raised for Service sector along with Manufacturing Sector.
-
Maximum Companies raised ECBs for on lending / sub lending purpose.
-
Reliance Industries limited and Indian Oil corporation limited raised highest number of ECBs.
-
Listed companies raised ECBs for maximum number of times.
-
Institutional Factors like GE Indicator and PV Indicator affects the inflow of ECBs.
-
It is necessary to work on these factor as it creates confidence among foreign investors.
-
Covid 19 pandemic creates negative impact on inflow of ECBs.
-
RECOMMENDATIONS
-
As per the analysis, it shows that global uncertainty causes the impact on operations of the economy in entire world including India, so try to necessary steps not cause any global uncertainties so that help to boost trade, investment, create healthy, competitive environment where all the economies in the world can flourish and develop.
-
From the analysis it proves that political stability, government effectiveness helps for the development of the economy that create confidence among foreign investors for investment.
-
International debt helps for expand operations, diversification, research and development etc., but excess debt causes negative impact on overall operations of the companies.
-
While taking external debt we consider the interest factor but apart from that is equally important the economic conditions that whether we will repay that loan is also important.
CONCLUSION
This project provides a structured analysis, which helps in understanding the concepts easily and clearly It starts from introduction and meaning of the topic Then we analysed the data on ECBs there we get meaningful insights that help to understand the ECBs easily. In statistical modelling section, gave evidence that what factors that influence the inflow of ECBs. We always assumed that because of low interest rates companies go for ECBs but in this research we get different answer that the instituitional factors affects the inflow of ECBs. That out political conditions, Government Stability create confidence that we will repay our loan so help foe increase the flow of ECBs. Multiple Linear Regression Model Result state that the instituitional Factors like GE, PV provide the impact on inflow of ECBs. CovidDummy is marginally significant as it provides the negative impact on inflow of ECBs. Overall, this structural approach help to understand the concept of ECBs along with factors that determines the inflow of ECBs.
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-
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