C5 - Econometric Modeling

• Forecasting Risks to the Canadian Economic Outlook at a Daily Frequency

  Staff Discussion Paper 2023-19 Chinara Azizova, Bruno Feunou, James Kyeong

  This paper quantifies tail risks in the outlooks for Canadian inflation and real GDP growth by estimating their conditional distributions at a daily frequency. We show that the tail risk probabilities derived from the conditional distributions accurately reflect realized outcomes during the sample period from 2002 to 2022.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C3, C32, C5, C58, E, E4, E44, G, G1, G17

• 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 Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37

• 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 Topic(s): Asset pricing, Econometric and statistical methods JEL Code(s): C, C5, C58, G, G1, G12

• Turning Words into Numbers: Measuring News Media Coverage of Shortages

  Staff Discussion Paper 2023-8 Lin Chen, Stephanie 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 Topic(s): Coronavirus disease (COVID-19), Econometric and statistical methods, Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C5, C55, C8, C82, E, E3, E37

• 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 Topic(s): Climate change, International topics JEL Code(s): C, C2, C22, C5, F, F1, F14, F18, Q, Q5, Q54

• 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 Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Financial stability, Monetary policy transmission JEL Code(s): C, C5, C51, E, E3, E37, E4, E44, F, F4, F44

• 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 Topic(s): Economic models, Financial institutions, Financial stability, Financial system regulation and policies JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28

• 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 Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C02, C1, C13, C5, C50, C51, C52, C53

• 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 Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Monetary policy and uncertainty JEL Code(s): C, C5, C51, C55, E, E3, E32, E4, E44

• 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 Topic(s): Credit risk management, Econometric and statistical methods JEL Code(s): C, C1, C14, C3, C35, C5, C51, C6, C63, D, D1