Research Plan Presented By Bedri Tas Department of
Description: Research Plan Presented By Bedri Tas Department of Economics and Finance Past Track of Research Research Areas Empirical Analysis of Public Procurement Competition Cost-effectiveness Entry and survival of Small Businesses Monetary Economics
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slide2. Research Plan Presented By Bedri Tas
Department of Economics and Finance<br>
slide3. Past Track of Research Research Areas
Empirical Analysis of Public Procurement
Competition
Cost-effectiveness
Entry and survival of Small Businesses
Monetary Economics and Macroeconomics
Inflation Targeting
Monetary policy and financial markets
Financial Markets
Manipulation
Stock return prediction<br>
slide4. Recent Research Publications “How you describe procurement calls matters: Predicting outcome of public procurement using call descriptions”, Natural Language Engineering, 2023. doi:10.1017/S135132492300030X (with Utku Umur Acikalin, Mustafa Kaan Gorgun and Mucahid Kutlu)
“Information is essential for competitive and cost-effective public procurement”, Journal of Information Science, 2022. https://doi.org/10.1177/01655515221141042 (with Mustafa Kaan Gorgun, Mucahid Kutlu)
“Bunching below thresholds to manipulate public procurement”, Empirical Economics, 2022. https://doi.org/10.1007/s00181-022-02250-4.<br>
slide5. Recent Research Publications “Time-varying effect of uncertainty shocks on unemployment”, Economic Modelling, 110, 2022. https://doi.org/10.1016/j.econmod.2022.105810. (with Ozan Ekşi)
“Procurement policy and SME participation in public purchasing”, Small Business Economics, 2020. https://doi.org/10.1007/s11187-020-00414-z (with Bernard Hoekman)
“Effect of public procurement regulation on competition and cost-effectiveness”, Journal of Regulatory Economics, 58, 59–77, 2020.<br>
slide6. Future research agenda Current Research:
Economic Effects of Advertisement Content on Public Procurement: Implementation of Natural Language Processing and Machine Learning
Predicting Stock Returns using Big Macroeconomic Data: Machine Learning Analysis
Identifying Productive and Corrupt Connections in Public Procurement: A Bipartite Network Analysis
Can FinTech-based Financial Inclusion Promote Sustainable Development? (Joint work with Dr. Sami Al Kharusi)<br>
slide7. RESEARCH INTEREST US and EU have public detailed publicly available data about public procurement contracts.
More than 50 million contracts for US.
More than 40 million contracts for the EU.
Implement AI and machine learning to identify collusion and corruption in public procurement.
Using NLP to identify Green Public procurement and its determinants.
Predicting inflation using big macro data and machine learning.
FinTech adaption and its effect on the economy.<br>
slide8. Under Review Papers Performance of small firms in public procurement of innovation: Analysis of competition and success in the U.S. public procurement market (with Dr. Ramo Palalic)
A Machine Learning Approach to Detect Collusion in Public Procurement with Limited Information
Discretion and Public Procurement Outcomes in Europe (with Bernard Hoekman)
Identifying Productive and Corrupt Connections in Public Procurement: A Bipartite Network Analysis (with Dr. Adil Al Busaidi)<br>
slide9. Thank you Sultan Qaboos University<br>
Department of Economics and Finance<br>
slide3. Past Track of Research Research Areas
Empirical Analysis of Public Procurement
Competition
Cost-effectiveness
Entry and survival of Small Businesses
Monetary Economics and Macroeconomics
Inflation Targeting
Monetary policy and financial markets
Financial Markets
Manipulation
Stock return prediction<br>
slide4. Recent Research Publications “How you describe procurement calls matters: Predicting outcome of public procurement using call descriptions”, Natural Language Engineering, 2023. doi:10.1017/S135132492300030X (with Utku Umur Acikalin, Mustafa Kaan Gorgun and Mucahid Kutlu)
“Information is essential for competitive and cost-effective public procurement”, Journal of Information Science, 2022. https://doi.org/10.1177/01655515221141042 (with Mustafa Kaan Gorgun, Mucahid Kutlu)
“Bunching below thresholds to manipulate public procurement”, Empirical Economics, 2022. https://doi.org/10.1007/s00181-022-02250-4.<br>
slide5. Recent Research Publications “Time-varying effect of uncertainty shocks on unemployment”, Economic Modelling, 110, 2022. https://doi.org/10.1016/j.econmod.2022.105810. (with Ozan Ekşi)
“Procurement policy and SME participation in public purchasing”, Small Business Economics, 2020. https://doi.org/10.1007/s11187-020-00414-z (with Bernard Hoekman)
“Effect of public procurement regulation on competition and cost-effectiveness”, Journal of Regulatory Economics, 58, 59–77, 2020.<br>
slide6. Future research agenda Current Research:
Economic Effects of Advertisement Content on Public Procurement: Implementation of Natural Language Processing and Machine Learning
Predicting Stock Returns using Big Macroeconomic Data: Machine Learning Analysis
Identifying Productive and Corrupt Connections in Public Procurement: A Bipartite Network Analysis
Can FinTech-based Financial Inclusion Promote Sustainable Development? (Joint work with Dr. Sami Al Kharusi)<br>
slide7. RESEARCH INTEREST US and EU have public detailed publicly available data about public procurement contracts.
More than 50 million contracts for US.
More than 40 million contracts for the EU.
Implement AI and machine learning to identify collusion and corruption in public procurement.
Using NLP to identify Green Public procurement and its determinants.
Predicting inflation using big macro data and machine learning.
FinTech adaption and its effect on the economy.<br>
slide8. Under Review Papers Performance of small firms in public procurement of innovation: Analysis of competition and success in the U.S. public procurement market (with Dr. Ramo Palalic)
A Machine Learning Approach to Detect Collusion in Public Procurement with Limited Information
Discretion and Public Procurement Outcomes in Europe (with Bernard Hoekman)
Identifying Productive and Corrupt Connections in Public Procurement: A Bipartite Network Analysis (with Dr. Adil Al Busaidi)<br>
slide9. Thank you Sultan Qaboos University<br>