BANKŲ PELNINGUMO MODELIAVIMAS, TAIKANT DINAMINĮ SEKINIŲ DUOMENŲ VERTINIMO METODĄ

Purpose – to find and assess connection between banking sector profitability and real economy data, using panel data, and to display analysis capabilities of dynamic panel data estimation methods. sesign/methodology/approach – a panel, or longitudinal data set, consists of a sequ- ence of observations, repeated through time on a set of statistical units. Panel data and their estimation methods are frequently used in various economic research, as it gives more informa- tion than pure cross-section or time series data. Findings – dynamic panel data estimation methods are used to study relationship betwe- en income statement items (net interest income, net fee and commission income and operating expenses) and macroeconomic variables. Model estimation shows that included macroecono- mic variables are significant and there is interaction between banks profitability and real economy. Net interest income are found to be dependent on real investment and short term interest rate, net fee and commission income reacts to changes in real gross domestic product (GDP) and operating expenses are connected to real GDP and compensation per employee. Practical implications – the model is used to estimate income statement items changes after the external forecasted macroeconomic impact. The forecasts indicate that banks profita- bility reacts to changes in macroeconomic situation.