C1 - Econometric and Statistical Methods and Methodology: General

• Partial Identification of Heteroskedastic Structural Vector Autoregressions: Theory and Bayesian Inference

  Staff Working Paper 2025-14 Helmut Lütkepohl, Fei Shang, Luis Uzeda, Tomasz Woźniak

  We consider structural vector autoregressions that are identified through stochastic volatility. Our analysis focuses on whether a particular structural shock can be identified through heteroskedasticity without imposing any sign or exclusion restrictions.

  Content Type(s): Staff research, Staff working papers Research Topic(s): Econometric and statistical methods, Fiscal policy JEL Code(s): C, C1, C11, C12, C3, C32, E, E6, E62

• Estimating Discrete Choice Demand Models with Sparse Market-Product Shocks

  Staff Working Paper 2025-10 Zhentong Lu, Kenichi Shimizu

  We propose a novel approach to estimating consumer demand for differentiated products. We eliminate the need for instrumental variables by assuming demand shocks are sparse. Our empirical applications reveal strong evidence of sparsity in real-world datasets.

  Content Type(s): Staff research, Staff working papers Research Topic(s): Econometric and statistical methods, Market structure and pricing JEL Code(s): C, C1, C3, D, D1, L, L0, L00

• Estimating the impacts on GDP of natural disasters in Canada

  Staff Analytical Note 2025-5 Tatjana Dahlhaus, Thibaut Duprey, Craig Johnston

  Extreme weather events contribute to increased volatility in both economic activity and prices, interfering with the assessment of the true underlying trends of the economy. With this in mind, we conduct a timely assessment of the impact of natural disasters on Canadian gross domestic product (GDP).

  Content Type(s): Staff research, Staff analytical notes Research Topic(s): Climate change, Domestic demand and components, Econometric and statistical methods, Fiscal policy, Regional economic developments JEL Code(s): B, B2, B23, C, C1, C13, C2, C23, E, E1, E17, E3, E37, E6, E62, H, H6