This article examines the nexus between financial inclusion index and economic growth in all eight South Asian Association for Regional Cooperation (SAARC) countries, using annual data from 2004 to 2017. In order to determine the possible long-run relationship between these variables, the study adopted the Pedroni panel co-integration test and two types of co-integration regression methods, the Fully Modified Ordinary Least Square (FMOLS) and the Dynamic Ordinary Least Square (DOLS) methods. The Pedroni panel co-integration test confirms the existence of a long-run relationship between financial inclusion and economic growth in the SAARC countries. The coefficients of FMOLS and DOLS indicate that the index of financial inclusion and selected control variables together support economic growth. In addition, the Granger causality test confirmed bi-directional causality between FI and economic growth.

U radu se analiziraju regulatorne i ekonomske varijable u bankarskom sektoru koje, u manjoj ili većoj meri, mogu da utiču na nivo problematičnih kredita u Srbiji. Iako bankarski sektor, za razliku od ostatka privrede ostvaruje pozitivne rezultate, istovremeno je prisutan i rastući trend problematičnih kredita koji preti da ugrozi celokupnu stabilnost finansijskog sistema. U tom smislu, u statističkoj i ekonometrijskoj analizi pošlo se od determinanti kao što su: kapitalna adekvatnost, iznos rezervisanja za potencijalne gubitke, profitabilnost, vlasnička struktura i koncentracija u bankarskom sektoru, kao i stopa rasta realnog bruto društvenog proizvoda. Koristeći definisane varijable, ispitana je stacionarnost posmatranih serija podataka pomoću proširenog Diki-Fulerovog (ADF) testa jediničnog korena, za period od poslednjeg kvartala 2008. godine do trećeg kvartala 2013. godine. Prema metodologiji Narodne banke Srbije, korišćeni su kvartalni podaci sa ukupno 20 opservacija. Osnovni izvor podataka predstavljaju različiti statistički izveštaji koje objavljuje Narodna banka Srbije.

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In the last decade, rising social media impact along with technological progress has given the potential for higher "democratization" of public voice. However, influential individuals, with hundreds of millions followers got the possibility to shape the public opinion and create herding behavior. Twitter activities, especially with financial markets-related content are gaining popularity as well. In that regard, the purpose of the paper is to analyze correlation between Elon Musk's Twitter activities and stock price performance of Tesla company, by using different models of sentiment analysis. Rapid Automatic Keyword Extraction tool was used in Phyton. Correlation analysis was done for the 3-year time period (Oct 2019-Oct 2022) in order to capture heightened volatility and various systematic risks, which had resulted in even more tweeting activities. Results showed that there is mid to high correlation between Elon Musk's tweets and share price of Tesla.