Read more about: Time series analysis

Time series analysis has always been a part of the research and teaching at the department, with researchers contributing to both methodological developments and applied work. The department has close contact with Swedish policy institutions such as the Riksbank, the Ministry of Finance, and the National Institute of Economic Research, as well as other main users of time series methods at e.g. Statistics Sweden (SCB) and in the banking and financial sectors. These connections ensure that our research addresses relevant policy questions and that our teaching prepares students for careers where time series analysis is central.

Some recent and ongoing research themes in time series analysis at the department are:

• Dynamic factor models for macroeconomic nowcasting and forecasting with high-dimensional data
• State space models and Kalman filtering for extracting latent factors and business cycle indicators
• Estimation of time-varying macroeconomic relationships
• Heteroscedastic time series analysis and variance stabilization methods for improved parameter estimation and forecasting
• Computational methods for large-scale Bayesian VARs using Bayesian optimization and machine learning techniques
• Monetary policy transmission mechanisms and effects of quantitative easing programs
  Fiscal policy effects on inflation using structural time series methods
• Effects of data transformations on model results and policy decisions