Indonesian companies have implemented good corporate governance

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This research will provide information to decision makers and other interested parties regarding the degree to which Indonesian companies have implemented good corporate governance. Besides financial performance, both firm-level and country-level GCG implementation has become an important issue and increasingly caught stakeholders' attention.

This research is also intended to help decision makers in determining which firms have good corporate governance quality by looking at particular firm characteristics. The selected firm characteristics in this study are firm growth opportunity, firm external financing, firm age, firm size, firm ownership structure, firm ownership status, and firm asset structure.

3.2 The Time and Place of Research

This research is conducted in Jakarta, Indonesia, from February to June, 2010.

Figure 3.1 Research Process Flowchart (Cooper & Schindler, 2008)

Figure 3.2 Descriptors of Research Design (Cooper & Schindler, 2008)

Category

Option

The degree to which the research question has been formulated

Formal Study

The method of data collection

Monitoring

The power of the researcher to produce effects in the variables under study

No control over the variables

The purpose of the study

Descriptive

The time dimension

Cross-sectional

The topical scope of the study

Statistical

The units of analysis

Organization

The research environment

Field Setting

The sampling strategy

Non probability - purposive sampling

3.3 Research Design

3.3.1 Degree of Research Question Formulation

This research is categorized as a formal study, which begins with hypotheses related to Good Corporate Governance (GCG) implementation and involves organized processes and data source specifications. This research involves testing of formulated hypotheses in order to satisfy the research objectives.

3.3.2 Method of Data Collection

Monitoring is involved in collecting the data, which means that the author examines required data without attempting to obtain responses from anyone. In this research, the author obtains secondary sources which take form of company's annual report as required material for data analysis. The annual report is downloaded from respective company's website and retrieved from Indonesian Stock Exchange (IDX) database library. The author also reviews the textbooks and related journal articles to support the research processes.

3.3.3 Researcher Control of Variables

The author analyzes annual reports and other related figures of companies selected as sample and reports the findings. As process of data collection only involves direct retrieval of annual report and other related figures, the author has no control over the variable and hence, there is no influence that might results in biased findings. The manipulation is only limited to sample selection and statistical procedures.

3.3.4 The Purpose of the Study

This research is considered as a descriptive study because the hypotheses are structured and clearly stated. Based on the hypotheses, the author attempts to describe firm characteristics as potential determinants of corporate governance quality in Indonesian companies which are selected as a sample. Moreover, the theoretical framework related to the study is explained comprehensively to support the findings and conclusion.

3.3.5 The Time Dimension

The data collection and analysis are carried out once. In this case, the author examines the snapshot of corporate governance quality of Indonesian companies and their associations with firm-level characteristics only at one point in time. Thus, this research is categorized as a cross-sectional study.

3.3.6 The Topical Scope

This study is categorized as a statistical study because the hypotheses are tested using quantitative method. The findings and conclusions are presented based on the results of quantitative method performed on the sample. In this research, the author performs scoring technique on each company's corporate governance disclosure and uses multiple regressions by selecting firm characteristics as independent variables.

3.3.7 The Units of Analysis

The units of analysis explain the major entity that is being chosen for the study. Therefore, the author uses organization as the units of analysis since the author examines firm-level corporate governance quality.

3.3.8 The Research Environment

The author collects the annual report of respective company selected as the sample. The information on annual report represents the company's condition in real environment. Thus, this study is performed under field condition.

3.3.9 The Sampling Strategy

In collecting the data, the author chooses Kompas-100 companies in the end of 2008. The companies categorized as Kompas-100 index have large market. Those companies are expected to outperform the market and have greater corporate governance quality. Taking into account the criteria fulfilled by those companies, the author adopts purposive sampling approach. Therefore, this study uses non-probability sampling strategy.

3.4 Type of Data Used in the Research

The secondary data comprises of annual report, journal articles, textbooks, and related materials. In developing hypotheses and writing theoretical framework to support the findings, the author reviews journal articles and textbooks related to corporate governance. The data used for analysis in this research is obtained from respective company's annual report. The data includes disclosure of corporate governance which is used to determine corporate governance quality and related internal firm characteristics as potential determinants of corporate governance quality.

3.5 Data Analysis Method

This research will consist of two data analysis approach:

3.5.1 Corporate Governance Scoring Method

In this study, the author uses the GCG scoring template which takes form of questionnaires. This scoring instrument is originally prepared by BPKP in collaboration with the Ministry of SOE to evaluate GCG quality of SOE.(1) According to the Head of BPKP's decree (KEP-06.02.00-268/K/2001), GCG team established by BPKP is responsible to formulate principles and guidance related to evaluation, implementation, and socialization of GCG implementation. Furthermore, the GCG team must provide recommendation to the government in improving the reporting system requirement in order to achieve GCG implementation in SOE and other business entities. Therefore, the scoring instrument developed by the GCG team of BPKP and Ministry of SOE can be used to assess GCG implementation of both SOE and other business entities in Indonesia.

There are five main categories to be examined in the scoring questionnaire. Each category is weighted accordingly based on its significance in overall corporate governance implementation quality. The categories and their respective significance are 1) Shareholder's Rights / Annual General Meeting (RUPS) 9%, 2) GCG Policy 8%, 3) GCG Implementation 66%, 4) Disclosure 7%, and 5) Commitment 10%.

Source: BPKP Official Website (http://www.bpkp.go.id)

GCG implementation is further divided into 5 parts, which consist of Board of Commissioners (BOC) 27%, BOC Committee 6%, Board of Directors (BOD) 27%, Internal Audit 3%, and Corporate Secretary 3%. High percentage assigned to GCG implementation category indicates that the actual GCG practice adopted by the commissioners and directors significantly affect the company's GCG value in general. Thus, weaknesses in implementation category will greatly reduce the corporate governance score.

There are 50 GCG indicators grouped based on related categories. Every indicator is further elaborated into a number of parameters which addresses detailed issues to be evaluated. In total, there are 160 parameters that made up this scoring questionnaire. Each indicator is also allocated particular percentage according to its importance in respective category.

Further, the group of parameter determines the weight of each parameter under its indicator. There are three group of parameter established by the Ministry of SOE and BPKP. The parameters under Group A (significant group) measures the company's ability in implementing GCG principles, including its commitment, guidance, and communication as part of GCG socialization to all of its stakeholders. The absence of this group will lead to poor corporate governance practice. Group B (medium significant group) includes parameters that assess the company's GCG formal implementation and the characteristics of company's BOC, BOD, Internal Audit, and Corporate Secretary. The formal implementation takes form of written manual and other supporting documents related to GCG. Lastly, Group C (the least significant group) includes parameters that measure supporting activities as part of GCG implementation.

Manual content analysis on annual report will be conducted to score all parameters available in the questionnaire. If the issue addressed in each parameter is available in the annual report, 1 (one) as the score for that parameter. Conversely, if the information is not available, 0 (zero) will be given.

Due to scope and time limitation, subjectivity becomes the limitation of this study since the author relies on content analysis on the annual report while there are some parameters that require interview and direct observation of company's boards and management. Lack of information in the annual report may cause bias in performing the scoring technique. In this regard, no score (zero) will be assigned to those parameters since the information is considered not available in the annual report.

Besides corporate governance ratings, the author will also retrieve other available data from these companies, including net income, book value of total assets and fixed assets, book value of total liabilities, sales figure in three years, market value of shares, book value of shares, firm age, and number of shares owned by managers, institutions, and the state.

3.5.3 Statistical Method

All required data will be analyzed by using multiple regression analysis. According to Cooper and Schindler (2008), multiple regression serves as a descriptive tool relevant in three types of situations. First, it is used for formulating a self-weighting estimating model to predict values for a criterion variable (dependent variable) from the values for several predictor variables (independent variables). Second, it controls complicated variables to provide better assessment of other variables' contribution. Third, multiple regression is used to test and explain causal theories.

According to DeFusco et.al. (2004), to ensure the validity of the test, there are several assumptions to be satisfied before performing statistical inference on the multiple linear regression models:

The linear relationship exists between independent variable and dependent variable

There is no exact linear association between two or more independent variables

The independent variables are not random

The expected value of the error term is zero and its variance is the same for all observations

The error term is uncorrelated across observations and normally distributed

Based on the above assumptions, there are three common problems arise in multiple regression analysis which greatly affect statistical inference:

Heteroskedasiticy occurs if variance of the error term differs across observations

Serial correlation occurs when the error term is correlated across observations

Multicollinearity arises when two or more independent variables are highly correlated

In this study, the dependent variable is corporate governance score while the independent variables are the internal firm characteristics; consist of external financing, growth opportunities, firm size, firm age, level of managerial ownership, level of institutional investors' ownership, ownership status, and firm asset structure.

Based on the above discussion, the regression model in this research is:

CGSi = αi + β1 FUNDi + β2GROWi +β3 SIZEi + β4 AGEi + β5 MANi +

β6 INSTi + β7 STATi + β8 TANi + εi

Where:

αi = a constant, the value of CGSi when all other variables are zero

CGS = Corporate governance score

FUND = Measured by percentage of book value of total liabilities to book value of total assets

GROW = Measured by sales growth in the last three years.

SIZE = Total assets in natural logarithm

AGE = Represents years since the company was founded until 2008, expressed in natural logarithm

MAN = Percentage of share ownership by managers and commissioners

INST = Percentage of share ownership by institutional investors

STAT = A dummy variable taking the value of one (1) if it is SOE and zero (0) otherwise

TAN = Measured by percentage of book value of fixed assets to book value of total assets.

εi = an error term

3.5.3 Sample Selection

The preliminary sample in this research is companies that are included in Kompas-100 index at the end of 2008. Kompas-100 index consists of 100 public company shares which are traded in Indonesian Stock Exchange (IDX). The index was officially published by IDX in collaboration with Kompas in August 10, 2007. The index is renewed every 6 months. The stocks included in Kompas-100 index are selected based on their frequencies and values of transaction, market capitalizations and fundamental performances quality.

IDX sets the following factors to consider in determining which stocks to be included as part of Kompas-100 index:

The stocks have been listed in IDX for at least 3 months

The transaction activities in regular market, which includes transaction value, transaction frequency, and market capitalization

The sum of trading day in regular market

Market capitalization in specified period

Evaluation and consideration of the company's fundamental factor and trading pattern

Investors' and other stakeholders' interest consideration

Kompas-100 index involves stocks that have high transaction value, representing companies in Indonesia and frequently traded. Thus, the investors, portfolio managers, and fund managers often use this index as a reference for stock-based fund management. Furthermore, it will be easier to collect the data required in this research.

In this preliminary sample, companies in financial sector will be excluded since they have different method of reporting and require additional supervision by Bank Indonesia.

3.6 Data Interpretation

In this research, the author uses Microsoft Excel to prepare the data, tables, and figures. For analyzing and interpreting the data, the author will use Statistical Packages for the Social Sciences (SPSS) and Eviews to determine the relationship between the independent variables and the dependent variable in this study.

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