probit analysis for financial attitude: case of Kazakhstan
by Maya Katenova Both 2015 and 2019 surveys were performed by KIMEP University student groups as a class project in spring semester of each year, using face-to-face and paper-and-pencil surveys in different cities and towns of Kazakhstan. Excluding invalid and unsuitable answers for the analysis, the total number of survey responses resulted were 830 for 2015 and 983 for 2019 studies respectively. One of the weaknesses of survey data may be the possibility of mindless responses and random guess works. To reduce possible distortions of mindless answers and random guess works, we cut the middle portion of the literacy scores (2 and 3 points out of 5 points). The results provided us with a total sample of 529 observations for 2019 survey and 443 observations for 2015 survey. Then, we transform the data into 0 and 1 binary observations since we are still not sure the exact differences in financial knowledge between 0 and 1 and between 4 and 5 for literacy scores. We assigned 0 for the literacy scores of 0 – 1 and 1 for the literacy scores of 4 – 5. We simply treat the continuous knowledge difference as a latent variable, and the observation of respondents’ knowledge as two discrete alternatives, financially “illiterate” and “literate.” These trimmed binary data are analyzed for a series of probit analysis to find out the probability of being financially literate based on individual’s personal profiles and the probabilities of choosing proper financial attitude/behavior based on the level of basic financial literacy level, controlling the impacts of personal profiles. The following hypotheses are investigated: H1: Personal profiles such as gender, education level, ethnicity, hometown, marital status, and income will influence the probability of answering correct on the basic financial literacy questions. H2: The higher the level of basic financial literacy a person has, the higher the probability of making better financial decisions for retirement plan and delinquency in payment, and the more frequent in making money-related decisions. In 2019 survey, Business Education and Hometown are significant for positive impact on basic financial literacy level. A person with more than one year of business education and/or residing in a city is most likely acquired higher level of financial knowledge. Gender, Ethnicity, Marital Status, and Income do not impact significantly on the level of financial literacy. The 2015 survey shows, however, that females are more likely to have lower scores in financial literacy which is evidenced in many previous studies. There are no significant differences in financial knowledge between Kazakhs and non-Kazakhs, between village and city dwellers, and between Single and NonSingle. The marginal impacts of these variables assuming other variables are in the mean levels are provided in the δP/δX columns.
Intelligent Risk - April 2020
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