I am an econometrician at the Bank of Israel’s Statistical Methods and Data Science Unit. In my current role, I have led the development of advanced econometric tools designed to address the bank's primary needs. My projects include a GDP nowcasting model that integrates real-time data from multiple sources to support economic monitoring and policy decision-making (Ginker and Suhoy, 2022). I also oversee the development of short-term inflation forecasting models, tools for risk management and cash demand forecasting, and methodological and software solutions for the seasonal adjustment of high-frequency data (Ginker, 2024; CRAN).

In parallel, I am leading several research initiatives that leverage big data to generate empirical insights into macroeconomic dynamics  (Ginker et al., 2025).

Prior to joining the Bank, my research focused primarily on theoretical contributions to time series econometrics.  During my graduate studies, I developed asymptotic theory for estimation and inference in nonstationary random coefficient autoregressive models (Ginker and Lieberman, 2021). I also addressed issues of model misspecification in qualitative response time series models  (Ginker and Lieberman, 2017).

In addition to my research, I have extensive experience teaching advanced courses in econometrics and data science to academic and industry audiences. My teaching approach emphasizes the integration of rigorous analytical methods with real-world applications, ensuring that complex models yield actionable insights. 

You can find my full CV here.