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Tibor is a Ph.D. candidate in Statistics at the University of Salerno, focusing on time series models applied in macroeconomics and finance. His work is greatly motivated by the perception that risk, uncertainty, and unexpected events are inherent driving features of everyone's lives; thus, attitude towards these aspects is essential to one's life and economics. Hence, his primary interest is developing novel statistical approaches to capture unordinary episodes in economic activity and irregularities in the financial market driven by risk-related behaviors. Translating these elements into his life makes him keen to discover and live in unusual places where he can always bring some unique features into his daily life. He likes gastronomy, nature, and mountains, so traveling, cooking, and hiking are his favorite activities in his free time.
Areas of expertise
Dynamic conditional score models
Unobserved components models
State-space models - Kalman filter
Financial econometrics - volatility modeling
Macroeconomics - monetary transmission mechanism
Structural VAR - vector error correction models
Education
University of SalernoPhD in Statistical Methods (in progress)
Cracow University of EconomicsMaster’s degree in Economics
Professional background and credentials
Tibor's enthusiasm toward finance and macroeconomics began in the first year of his Bachelor's program when he became familiar with the discipline's fundamental concepts. Since the U.S. housing boom, reinforced by sophisticated financial innovations, and the following global financial crisis coincided with his early studies, he soon became fascinated by how speculative forces can derail the economy from its conventional path. As a result, after a scholarship spent abroad, he completed his thesis on the U.S. housing bubble and its aftermath. While following his first degree, he began his professional work in the financial sector abroad and remained eager to study macroeconomic events. The high motivation to continue his research led him to apply for a master's program besides his full-time job. The acquired additional knowledge in economics and statistics in a multicultural environment provided an excellent setting for further improvement. The central interest became evident: how could macroeconomic irregularities involving financial and behavioral aspects be analyzed through statistical models? His master's thesis was the first attempt to explore the subject more in-depth through this lens. He studied the interrelationship between the Spanish housing boom, lending activity, and monetary policy using an econometric approach, making him more interested in statistical methodologies. After his master's degree, his curiosity did not cease. As he continued his professional work as a financial analyst, he soon gained a one-year traineeship in Spain, where he began to work on a deeper analysis of the unusually prolonged stagnation experienced after the Great Recession. Since he has always been fascinated by what is in the black box behind the econometric models, he decided to apply for PhD in statistics, where he gained a fully funded scholarship at the University of Salerno. Combining his macroeconomic background with new knowledge of statistical methods, he started a promising research line on developing novel statistical methodologies tailored to macroeconomic and financial matters.
Featured in
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Publications
Gutiérrez-Diez PJ and Pál T. Monetary policy models: lessons from the Eurozone crisis; Nature - Humanities and Social Sciences Communications; Oct 2023
Pál T. The effects of monetary policy on house prices in Spain: the role of the economic and monetary union membership in the housing bubble prior to the great recession; Central European Review of Economics and Management; Jun 2018