The Dependent variable (DV) that has been selected for this assignment is “The value of investment decisions.” The variable is closely related to the variable selected for assignment 2, “The value of selected investment(s).” However, unlike the variable in assignment 2, the study by ED Radianto et al., (2020) presents the variable in this case as a ratio variable whereby the value of investment decision is presented as the ratio of real asset percentage against financial asset percentage in the portfolio of investments. There is a concern with respect to the measurement of this variable. First, the measurement ignores the absolute size of an investment as a plausible measure of the value of investment decisions. For example, according to the measurement, an individual with a higher percentage of real investments compared to financial investment would be considered to have made superior investment decisions irrespective of their absolute size of the investment. Second, it would be plausible to categorize the value of investment decisions as an ordinal variable whereby classes are crated on the premise of the overall value of investments. Lastly, the use of ratio scale to measure the variable creates few classes, thereby limiting the deductions that can be made concerning the value of investment decisions.
The first independent variable (IV1) presented by ED Radianto et al., (2020) is financial literacy which is ratio variable because it is derived from dividing the number of correct with the number of wrong questions administered during the study. The different classes of the variable are then ranked in an ordinal manner. In light of the fact that the respondents do not know the answers to the questions asked until the end of the interview, it is plausible to contend that the variable is correctly measured as a ratio variable. Classifying it as an ordinal value would be flawed because it would incentivize the respondents to skew their answers to fit into particular ordinal classes.
The second independent variable (IV2) is education which was incorrectly measured as a nominal variable in GSS but should be an ordinal variable. The ranking of education using several classes in line with the prevalent levels of the education system implies that education is an ordinal variable.
The third independent variable (IV3) is occupation. The variable is not discussed in the GSS or the study by ED Radianto et al., (2020). Occupation is a critical factor in influencing the value of investment decisions and should be explored. The variable is nominal because it cannot be ranked. However, the underlying rationale is that some occupations whereby employees become more acquainted with expert investment decisions making are likely to incentivize individuals to make superior investment decisions.
Hypothesis 1 contends that the level of financial literacy influences investment decisions. Financial literacy is one of the pivotal factors in making investment decisions. The rational expectation is that a higher level of financial literacy will yield a higher value of investment decisions. Therefore, there is a causal relationship between financial literacy and the value of investment decisions. In operationalizing financial literacy as a ration variable in this study, it would be expected that respondents with a higher number of correct answers compared to the wrong answers would demonstrate superiority in their investment decisions. Additionally, the metric of superior investment decisions is diversification as measure by the balance between real and financial assets in a portfolio. In appreciation of the fact that the respondents may lack background finance knowledge, comprehension of the diversification concept would require tailored financial literary training. Therefore, it is plausible that a rise in the financial literary level is correlated with a rise in the value of investment decisions.
Hypothesis 2 contends that the level of education influences investment decisions. The implication is that individuals with higher education levels are likely to demonstrate superior investment decisions. The rationale is that education imparts knowledge and skills requisite in evaluating the plausibility of investment alternatives. Further, education enables individuals to forecast volatility in the value of some investments and imparts skills on how to pre-empt the adverse effects of such volatility through diversification. Therefore, it is valid to contend that a rise in the education level for the respondents would be associated with superior investment decisions.
The third hypothesis contends that an individual’s occupation influences investment decisions. Occupation affects investment decisions in two ways. First, individuals in the finance sector are likely to be acquainted with expert investment valuation frameworks, hence demonstrate superior investment decisions. Second, some occupations are associated with higher income levels. Ideally, sufficient diversification is contingent upon enough financial resources to commit to real and financial assets. Therefore, it is plausible to contend that the nature of occupation influences investment decisions.
Financial literacy is measured using knowledge on several concepts including insurance, general financial knowledge on interest rates, economic growth, as well as investment knowledge including the effect of interest rates on investments and the role of investment vehicles such as mutual funds. A total of 9 questions are designed from the mentioned topics and are presented in a simple language. Additionally, the questions are open-ended meaning that it is subjective on the interviewer to determine what constitutes a correct of a wrong answer. The administration of the question using this method yields valuable information because the objective is to compare the financial literacy score with the balance of investments between real and financial assets.
The question will improve on the GSS education variable whereby in this case the variable is classified as an ordinal variable. Additionally, unlike the GSS ranking that has 12 classes, the question will be designed with 5 classes. In effect, an individual whose highest level of education in year 12 and below will be classified under one class, whereas all certificate qualifications would be merged into one class. The rationale is that individuals with this level of education are denominated by a lack of technical knowledge on investments; hence none is likely to demonstrate superior investment decisions compared to others. Any variations in investment decisions for individuals, in this case, would be attributed to other factors other than education level. Similarly, the merging of certificate qualifications is premised on the rationale that individuals at this level have uniform knowledge and skills. The question is, therefore, reworded to give the respondents 5 choices concerning their education level. The respective classes are 1 for Post Graduate level, 2 for Bachelor’s degree, 3 for Advanced Diploma, 4 for Certificate level, and 5 for Year 12 and below.
The questions under the occupation variable are designed using the mainstream classification of economic activities in the economy. The various categories for the respondents to select from include education, finance, real estate, public sector, agriculture, healthcare, and others. It is important to note that the variable cannot be ranked because it is a nominal variable. Further, the “others” category will accommodate all occupations that are not listed in the other categories. The rationale for the classification is the overall level of experts mainstreamed in occupations such as real estate and finance that would influence the quality of investment decisions. Additionally, the level of income in some occupations such as real estate, finance, and health care provides an opportunity for people in these occupations to diversify their investments compared to other occupations.
Pre-testing of the questionnaire is an important element of the research process to ensure that the research questions and instruments yield the data desired by the researcher. In this particular case, pre-testing would be done using the focus group method. The pivotal advantage of using a focus group is that it helps to explore what the respondents think and how they think concerning the survey questions. This method is superior to other methods of pre-testing such as expert views because the ideal study would include respondents from broad sectors of the economy. Consequently, pre-testing using a focus group of about 10 respondents would be more cost-efficient and representative of the actual research process.
The focus group would be diversified with respect to age, gender, and ethnicity. Further, the focus group members would be randomly selected from employees of various companies who engaged in investment activities. It is projected that the members of the focus group involved in investment activities would voluntarily answer investment-related questions to determine their financial literary level. Further, the best source of data on education level is the respondents, thereby making focus groups the best pre-testing method for the second survey question. Finally, the researcher would select the members of the focus groups from diversified occupations sectors in the economy.
References
ED Radianto, W., Lianoto, Y., Christian Efrata, T., & Dewi, L. (2020). The Role of Financial Literacy, Gender, Education, and Ethnicity towards Investment Decisions. Kne Social Sciences, 12(4). https://doi.org/10.18502/kss.v4i3.6401
Online Survey Version: Web Link
https://www.surveymonkey.com/r/3GYFC3J