Page 53 - SUSTAINABILITY ISSUES & COVID-19

relative correlation magnitude. In a credit analysis/assessment for a corporate loan, the bank naturally would be heavily
relying on the information obtained through the credit analyst and the Relationship Manager, such as the borrower
historical repayment, profitability, the assets pledged for collateral or other business considerations. Not merely the
public information that the bank uses to justify the credit risk, as in the case of the public bond, but also other bank’s
internal tools/methods existence. Whereas in contrary, the bondholder would act similarly as the investor in the market
by accessing the company’s information on public domain and analyze to determine the firm’s credit risk (perception)
based on other publicly available information. Due to these differences, it is expected that the correlation between ESG
and the cost of debt from bank borrowing has less magnitude than the bond. Based on the reasoning, the hypotheses
H2 and H3 are developed:

H .The firm ESG disclosure index is negatively associated with the bonds YTM (Yield To Maturity).
2
H .The firm ESG disclosure index is negatively associated with the bank loans EIR (Effective Interest Rate).
3
3. RESEARCH METHOD

1.1 Data and Samples
In the attempt to obtain some insight/evidence within ASEAN to understand the effects of ESG (disclosure) to the cost
of debt from both debt securities (bond) and the bank loan, the quantitative research involves measurements overtime
for the number of firms selected. Total panel data used are 177 companies in ASEAN from 2014 until 2018, selected by
using below purposive sampling method criteria:
a. Companies that are listed in the stock exchange or its benchmark index in ASEAN during period observation 2014
until 2018 which consist of Indonesia (IDX), Singapore (STI), Malaysia (KLCI), Philippines (PSEI) and Thailand (SETI).
STI, KLCI and PSEI are the capitalisation-weighted stock market index that is regarded as the benchmark index for
the country stock exchange that tracks the top 30 companies listed on the exchanges.
b. Excluding the financial sector, Companies that are within the 10 (ten) industries according to the Bloomberg classi-
fication are Communication Services, Consumer Discretionary, Consumer Staples, Energy, Health Care, Industrials,
Information Technology, Materials, Real Estate, and Utilities;
c. Companies that have complete ESG Disclosure Score data from Bloomberg during the observation period from
2014 to 2018.

Table 1A and 1B present the distribution of firms by country and the number of observations used by year for each
Hypothesis. There are gaps between the five ASEAN countries in the sustainability reporting practices through ESG
Disclosure (Loh et al., 2018) that naturally led to the incomplete (missing) data of the key independent variables of
ESG index within the observation years. Additionally, the key dependent variables data, i.e. the cost of debt proxy, only
incurred upon those companies sampled utilised the public bond and the bank loan. Therefore, this also naturally led
to additional incomplete (missing) data of the key dependent variables of Yield to Maturity (YTM), Effective Interest
Rate (EIR) and the Cost of Debt (COD) for the observation years when the public bond funding or the bank loan are not
utilised. See Table 1B for the number of observations found.

Table 1A Research Samples
Sample ID SG MY PH TH Total
Determination (IDX) (STI) (KLCI) (PSEI) (SETI) Samples
Criteria
Number of Companies 681 30 30 30 604 1375
(-/-) Financial sector caompanies: (174) (!2) (7) (9) (162) (364)
(-/-) Companies with completely missing ESG
data for five year observation (438) 0 0 (2) (394) (834)
Companies that meet the sample selection
criteria 69 18 23 19 48 177
Total Research Samples 69 18 23 19 48 177
ID= Indonesia; SG= Singapore; MY= Malaysia; PH= Phillipines; TH= Thailand
Source: Bloomberg dara 2014-2018

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