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 Research 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 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 Research Topic(s): Credit risk management, Econometric and statistical methods 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
Quantum Monte Carlo for Economics: Stress Testing and Macroeconomic Deep Learning Staff working paper 2022-29 Vladimir Skavysh, Sofia Priazhkina, Diego Guala, Thomas Bromley Using the quantum Monte Carlo algorithm, we study whether quantum computing can improve the run time of economic applications and challenges in doing so. We apply the algorithm to two models: a stress testing bank model and a DSGE model solved with deep learning. We also present innovations in the algorithm and benchmark it to classical Monte Carlo. Content Type(s): Staff research, Staff working papers Research Topic(s): Business fluctuations and cycles, Central bank research, Econometric and statistical methods, Economic models, Financial stability JEL Code(s): C, C1, C15, C6, C61, C63, C68, C7, E, E1, E13, G, G1, G17, G2, G21 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Economic models
Cash in the Pocket, Cash in the Cloud: Cash Holdings of Bitcoin Owners Staff working paper 2022-26 Daniela Balutel, Christopher Henry, Kim Huynh, Marcel Voia We estimate the effect that owning Bitcoin has on the amount of cash held by Canadian consumers. Our results question the view that adopting certain new technologies, such as Bitcoin, leads to a decline in cash holdings. Content Type(s): Staff research, Staff working papers Research Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, E, E4, O, O3, O33, O5, O51 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Cash and bank notes, Digital assets and fintech
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 Research Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C57 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Economic models
Nowcasting Canadian GDP with Density Combinations Staff discussion paper 2022-12 Tony Chernis, Taylor Webley We present a tool for creating density nowcasts for Canadian real GDP growth. We demonstrate that the combined densities are a reliable and accurate tool for assessing the state of the economy and risks to the outlook. Content Type(s): Staff research, Staff discussion papers Research Topic(s): Econometric and statistical methods JEL Code(s): C, C5, C52, C53, E, E3, E7 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting
More Than Words: Fed Chairs’ Communication During Congressional Testimonies Staff working paper 2022-20 Michelle Alexopoulos, Xinfen Han, Oleksiy Kryvtsov, Xu Zhang We measure soft information contained in the congressional testimonies of U.S. Federal Reserve Chairs and analyze its effect on financial markets. Increases in the Chair’s text-, voice-, or face-emotion indices during these testimonies generally raise stock prices and lower their volatility. Content Type(s): Staff research, Staff working papers Research Topic(s): Central bank research, Financial markets, Monetary policy communications JEL Code(s): E, E5, E52, E58, E7, E71 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods, Monetary policy, Monetary policy framework and transmission
Historical Data on Repurchase Agreements from the Canadian Depository for Securities Technical report No. 121 Maxim Ralchenko, Adrian Walton We develop an algorithm that extracts information about sale and repurchase agreements (repos) from disaggregated settlement data in order to generate a new historical dataset for research. Content Type(s): Staff research, Technical reports Research Topic(s): Econometric and statistical methods, Financial markets JEL Code(s): C, C5, C55, C8, C81, G, G1, G10 Research Theme(s): Financial markets and funds management, Market functioning, Models and tools, Econometric, statistical and computational methods
Equilibrium in Two-Sided Markets for Payments: Consumer Awareness and the Welfare Cost of the Interchange Fee Staff working paper 2022-15 Kim Huynh, Gradon Nicholls, Oleksandr Shcherbakov We construct and estimate a structural two-stage model of equilibrium in a market for payments in order to quantify the network externalities and identify the main determinants of consumer and merchant decisions. Content Type(s): Staff research, Staff working papers Research Topic(s): Bank notes, Digital currencies and fintech, Econometric and statistical methods, Financial services JEL Code(s): C, C5, C51, D, D1, D12, E, E4, E42, L, L1, L14 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Money and payments, Payment and financial market infrastructures, Retail payments
Macroeconomic Predictions Using Payments Data and Machine Learning Staff working paper 2022-10 James Chapman, Ajit Desai We demonstrate the usefulness of payment systems data and machine learning models for macroeconomic predictions and provide a set of econometric tools to overcome associated challenges. Content Type(s): Staff research, Staff working papers Research Topic(s): Business fluctuations and cycles, Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C53, C55, E, E3, E37, E4, E42, E5, E52 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting, Money and payments, Retail payments