Risk aversion and time preference are fundamental variables when people make financial decisions, but there are numerous opinions for how to estimate them. Researchers frequently estimate the demand of financial products with an ordinary survey, where subjects provide self-perceptive information. Given that behavioral financial questions are included in the simple questionnaire, the subjects may misunderstand such questions, or may not be able to completely understand the importance of the concepts driving them. Therefore, subjective bias could be implicitly problematic in many surveys, rendering their results untrustworthy. Although researchers can draw their conclusions based on the data collected from the survey, the economic results may be distorted or prove insignificant. This study takes the behavioral and experimental economics explored in Kahneman and Tversky (1979) and applies those theories to a financial product, such as a single payment annuity. This is a relatively new product in Korea's aging population, thus demand for it has not been analyzed in the Korean context, despite the popularity of such products in the U.S. (Mitchell and Utkus, 2003). Following the method of eliciting risk aversion proposed by Holt and Laury (2002), we develop a new measure of risk aversion that is modified using the quantile normalization (Bolstad et al., 2003), and use the measure to check for subjective bias when choosing an annuity product. Time preference is also very critical in financial decisions. We propose a time preference measure that follows Coller and Williams (1999) and use it as an objective measure of the subject's time preference. We design an experiment in which the subjects are guided by the instruction and payoff schemes, and follow several sessions. The participants choose a lottery from a pair of lotteries whose payoffs and probabilities are different, revealing the participants' risk aversion preferences. In the next experiment on time preference, the participants choose a lottery from a pool of several featuring different interest rate payoffs with higher and lower payment spans, depending on the interest rates. During the experiment, the participants' choices reveal their time preferences for our analysis. In addition to the results of the aforementioned experiments, we collect the participants' background information, such as financial status, financial literacy, and intelligence. Given the dataset, we can then find that the subjective answers from the survey are not significantly related to the financial decision on single payment annuity. This allows us to verify that the subjective bias exists, and confirm that self-perceptive surveys are not trustworthy in choosing financial products. We also compare the self-perceptive answers and the experimental measures to test which methods are more reliable and significant. The results show that neither approach significantly determines time preferences and risk aversion in some model specifications. We construct the bias variables of risk aversion, time preference, life expectancy, financial literacy, and intelligence using the differences between the subjective answers and experimental results. Thus, when we execute econometric models with the bias variables of interest, we discover that the biased self-perceptive and experimental measures of the time preference, risk aversion, life expectancy, financial literacy, and pension literacy are significant determinants of the demand for single payment annuity. Therefore, the preferential and behavioral variables are critical in choosing financial products such as annuities, rather than the self-perceptive answers in the survey. We also run a Heckman two-step regression of the premium of the single payment annuity and find that financial status and portfolio are the most crucial determinants, regarding the moneywise incentive. Finally, the time preference and risk aversion experiments we design reveal that behavioral and preferential biases are critical in choosing financial products. Therefore, we conclude that researchers should take bias variables seriously when they estimate the demand for financial products, even after controlling for other variables.