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Since investor interest is not a directly measurable concept, search engine and social media data can be used to measure active investor interest. Google search volume data has the potential to help customers, investors, and policymakers make better decisions. When looking for information to make investment decisions, investors consider Google trends as they provide news about changes in prices. Studies examining investor interest in the literature have often been carried out with the applications of linear models. This suggests that possible structural changes are not taken into account in the time series. When we look at the literature, it has been shown that the prediction performance of nonlinear models is better than linear models. In addition, it is seen that the studies conducted to investigate the relationship between the return of the stock markets and the trading volume and the investor interest are frequently included in the international literature. In contrast, the studies are limited in the national literature. In this direction of the study, the relationship between the trade volume and the investor's discovery of information on the stock market by Google is examined through linear and nonlinear econometric techniques in the investor reputation hypothesis. According to the investor reputation hypothesis, investors only invest in stocks they are aware of without adequate research and knowledge. In this context, the study results were realized in a way that supports the investor recognition hypothesis within the scope of 2020. In the context of 2021, it is seen that it does not support the investor reputation hypothesis. In future studies to be carried out in this area, it seems possible to determine the degree of effect of nonlinear regression estimations and the relationship between variables.

Suicidal behaviour, like other human behaviours, is a result of socioeconomic and psychological conditions. The research, it is aimed to examine the relationship between socioeconomic factors such as economic income levels, social status and quality of life, and suicidal behaviour in comparison with classical and Bayesian negative binomial regression models. The findings showed that suicidal behaviour increased due to the decrease in economic status and inequality of income distribution among young people. At the same time, it has been determined that employment and divorce rates reduce suicidal behaviour. As a result, it was determined that social and economic factors affected suicidal behaviour in the 15-24 age group, and solutions were suggested.

This paper examines the determinants of young individuals' decision to leave their parental home in Turkey in the last decade. Using data from the Household Income and Living Conditions Survey (HILCS) from 2011 to 2021, we conduct a logit regression analysis to estimate the probability of young people leaving their parental home for reasons other than marriage. In this regard, we examine the household composition in the data, and we take the situation of living away from parental home as the dependent variable. We observe that the tendency to live independently of parents has increased slightly among young people over the past decade. We examine this new household trend at its outset, and our goal is to identify the factors that lead to the decision of young individuals to live independently. The results show the importance of income, education, gender, age, employment status, and regional differences in young individuals' residential choices. In particular, we show that personal income is a determining factor from mid-youth forward, while other factors predominate in early youth, and, for women, income and occupational status appear to be the dominant factors.