Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis Staff working paper 2023-45 Tony Chernis I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Generalized Autoregressive Gamma Processes Staff working paper 2023-40 Bruno Feunou We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C58, G, G1, G12 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods
Turning Words into Numbers: Measuring News Media Coverage of Shortages Staff discussion paper 2023-8 Lin Chen, Stéphanie Houle We develop high-frequency, news-based indicators using natural language processing methods to analyze news media texts. Our indicators track both supply (raw, intermediate and final goods) and labour shortages over time. They also provide weekly time-varying topic narratives about various types of shortages. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C5, C55, C8, C82, E, E3, E37 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Climate Variability and International Trade Staff working paper 2023-8 Geoffrey R. Dunbar, Walter Steingress, Ben Tomlin This paper quantifies the impact of hurricanes on seaborne international trade to the United States. Matching the timing of hurricane–trade route intersections with monthly U.S. port-level trade data, we isolate the unanticipated effects of a hurricane hitting a trade route using two separate identification schemes: an event study and a local projection. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C2, C22, C5, F, F1, F14, F18, Q, Q5, Q54 Research Theme(s): Structural challenges, Climate change, International trade, finance and competitiveness
Risk Amplification Macro Model (RAMM) Technical report No. 123 Kerem Tuzcuoglu The Risk Amplification Macro Model (RAMM) is a new nonlinear two-country dynamic model that captures rare but severe adverse shocks. The RAMM can be used to assess the financial stability implications of both domestic and foreign-originated risk scenarios. Content Type(s): Staff research, Technical reports JEL Code(s): C, C5, C51, E, E3, E37, E4, E44, F, F4, F44 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Economic models, Monetary policy, Real economy and forecasting
Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model Technical report No. 122 Gabriel Bruneau, Thibaut Duprey, Ruben Hipp We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress. Content Type(s): Staff research, Technical reports JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Models and tools, Economic models
Calculating Effective Degrees of Freedom for Forecast Combinations and Ensemble Models Staff discussion paper 2022-19 James Younker This paper derives a calculation for the effective degrees of freedom of a forecast combination under a set of general conditions for linear models. Computing effective degrees of freedom shows that the complexity cost of a forecast combination is driven by the parameters in the weighting scheme and the weighted average of parameters in the auxiliary models. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C0, C01, C02, C1, C13, C5, C50, C51, C52, C53 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Sectoral Uncertainty Staff working paper 2022-38 Efrem Castelnuovo, Kerem Tuzcuoglu, Luis Uzeda We propose a new empirical framework that jointly decomposes the conditional variance of economic time series into a common and a sector-specific uncertainty component. We apply our framework to a disaggregated industrial production series for the US economy. We identify unexpected changes in durable goods uncertainty as drivers of downturns, while unexpected hikes in non-durable goods uncertainty are expansionary. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C51, C55, E, E3, E32, E4, E44 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
Comparison of Bayesian and Sample Theory Parametric and Semiparametric Binary Response Models Staff working paper 2022-31 Xiangjin Shen, Iskander Karibzhanov, Hiroki Tsurumi, Shiliang Li We use graphic processing unit computing to compare Bayesian and sample theory semiparametric binary response models. Our findings show that optimal bandwidth does not outperform regular bandwidth in binary semiparametric models. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C14, C3, C35, C5, C51, C6, C63, D, D1 Research Theme(s): Financial system, Household and business credit, Models and tools, Econometric, statistical and computational methods
Nonparametric Identification of Incomplete Information Discrete Games with Non-equilibrium Behaviors Staff working paper 2022-22 Erhao Xie This paper jointly relaxes two assumptions in the literature that estimates games. These two assumptions are the parametric restriction on the model primitives and the restriction of equilibrium behaviors. Without imposing the above two assumptions, this paper identifies the primitives of the game. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C5, C57 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models