Kaplan, Muhittin
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Araştırma projeleri
Organizasyon Birimleri
Yönetim Bilimleri Fakültesi, İktisat Bölümü
İktisat Bölümü, başta Türkiye ve çevre ülkeler olmak üzere küresel ekonomileri anlayan, var olan sorunları analiz ederken, iktisadi kuramları ve kavramları yetkin ve özgün bir şekilde kullanma becerisine sahip bireyler yetiştirmeyi amaçlamaktadır.
Adı Soyadı
Muhittin Kaplan
İlgi Alanları
İş Ekonomisi, Çevre Bilimleri ve Ekoloji, Alan Çalışmaları, Uluslararası İlişkiler, Kamu Yönetimi
Kurumdaki Durumu
Aktif Personel
4 sonuçlar
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Yayın An evaluation of the impact of the pension system on income inequality: USA, UK, Netherlands, Italy and Türkiye(Springer Science and Business Media B.V., 2024) Verberi, Can; Kaplan, Muhittin; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study examines empirically the impact of various characteristics of pension systems, in particular their quality and integrity, on income inequality, utilizing micro-level data from the United States, United Kingdom, Netherlands, Türkiye and Italy. To this end, the income inequality model, which includes public pension (or public/private pension mix), age, education, gender, marital status and employment as independent variables, has been estimated using quantile regression. The results provide a number of valuable information on the impact of the pension system on income inequality: (i) Public pension income significantly reduces overall income inequality across almost all inequality groups in all countries, except for the UK and the Netherlands; (ii) Different types of pension systems vary significantly in their redistributive effects on income; (iii) The empirical results also show that the effect of different pension systems on inequality changes by inequality groups significantly.Yayın Exploring the impact of behavioural factors and personality traits on private pension system participation: A machine learning approach(İstanbul University Press, 2024) Verberi, Can; Kaplan, Muhittin; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study aims to investigate the effects of personality traits, in addition to basic financial literacy, private pension literacy and behavioural factors on Private Pension System (PPS) participation using machine learning algorithms. The PPS participation model was trained using both random forest and LightGBM algorithms, and the contributions of model inputs in the prediction of pension participation were interpreted using the Tree SHAP algorithms with swarmplots. The data employed in the empirical analysis is survey data collected from the Şırnak province of Türkiye with a sample size of 449. The findings of the study shows that: (i) PPS participation is more likely for females and middle-aged people; (ii) High basic financial literacy has a negative impact on PPS participation; (iii) Extraversion is the key personality trait affecting PPS participation; (iv) Advanced pension literacy has more impact on participation than simple pension literacy: (v) Present-fatalistic tendency is key behavioural factor and it negatively affects PPS; (vi) Present-hedonistic, conscientiousness, future-time orientation, and locus of control tendencies increase PPS participation. Furthermore, the distribution of colours in LightGBM has a greater degree of uniformity in both directions compared with the random forest algorithm. Finally, to increase PPS participation, the results of the study suggest the implementation of the following policy measures: Tailored pension literacy programmes can help to increase pension participation rates. Incentives should be created to prevent narrow-minded behaviour and establish a sense of protection and control around PPS, targeting middle-aged individuals and women.Yayın The impact of personality, behavior, and geography on participation in the private pension system in Türkiye: A machine learning approach(Borsa Istanbul Anonim Şirketi, 2025) Verberi, Can; Kaplan, Muhittin; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study examines regional disparities in the factors that affect participation in the Private Pension System (PPS) in Türkiye, focusing on sociodemographic characteristics, personality traits and behavior, and pension and financial literacy. The behavioral factors identified encompass procrastination, locus of control, pessimism, compulsive buying, and time perspective, and the personality traits include openness, agreeableness, extraversion, neuroticism, and conscientiousness. The study employs data on two provinces in Türkiye, Şırnak and Istanbul, and uses XGBoost and Tree SHAP algorithms and a probit model. Our findings indicate that personality traits such as openness, agreeableness, and conscientiousness have a positive influence on individual engagement in pension plans, whereas extraversion has a negative impact. Additionally, basic pension literacy is more influential than advanced pension literacy. The results also show that regional geography significantly influences personality and behavioral factors. Finally, a perception of protection is a critical factor in PPS participation.Yayın Beyond GARCH: Intraday insights into the exchange rate and stock price volatility dynamics in Borsa Istanbul sectors(Shaheed Benazir Bhutto Women University, 2024) Abdul-Rahman, Mutawakil; Khan, Asad ul Islam; Kaplan, Muhittin; Yönetim Bilimleri Fakültesi, İktisat BölümüThis study investigated the impact of exchange rate volatility on sectoral stock volatility by employing the intraday volatility measure directly calculated from the original data, using daily data from 27 Borsa Istanbul sectors between April 29, 2003, and April 25, 2023. In the literature, GARCH models are commonly used to study the volatility spillovers between exchange rates and stock prices, typically using aggregate data. However, the GARCH family models provide inefficient and biased estimates if they are misspecified. Moreover, using aggregate-level data may lead to biased and misleading conclusions. The research used intraday volatility measures to overcome the shortcomings of GARCH models. The ordinary least squares (OLS), GARCH (1,1) methods, and Garman and Klass (1980) volatility estimator are used. The empirical results showed that the estimates from each method vary significantly, and these disparities in the results might be due to misspecification in GARCH (1,1) models. The intraday volatility model estimation results showed that although stock price volatilities in all sectors are positively and significantly affected by exchange rate volatility, their magnitudes vary significantly. Taken together, this implies the presence of vast heterogeneities in the responses of sectoral stock price volatilities to exchange rate volatility. The results encourage policymakers to pay special attention to these heterogeneities to prevent capital flights and underinvestment. Additionally, the findings assist investors in making more effective decisions by helping them adapt their investment strategies to factor in exchange rate fluctuations and mitigate the impact of unexpected events in the exchange rate market.
