Behavioral Learning Equilibria in New Keynesian Models Staff Working Paper 2022-42 Cars Hommes, Kostas Mavromatis, Tolga Özden, Mei Zhu We introduce behavioral learning equilibria (BLE) into DSGE models with boundedly rational agents using simple but optimal first order autoregressive forecasting rules. The Smets-Wouters DSGE model with BLE is estimated and fits well with inflation survey expectations. As a policy application, we show that learning requires a lower degree of interest rate smoothing. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Economic models, Inflation and prices, Monetary policy JEL Code(s): C, C1, C11, D, D8, D83, D84, E, E3, E6, E62
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
Cash, COVID-19 and the Prospects for a Canadian Digital Dollar Staff Discussion Paper 2022-17 Walter Engert, Kim Huynh We provide an analysis of cash trends in Canada before and during the COVID-19 pandemic. We also consider the potential two scenarios for issuance of a central bank digital currency in Canada: the emergence of a cashless society or the widespread use of an alternative digital currency in Canada. Finally, we discuss the Canadian experience in maintaining cash as an efficient and accessible method of payment and store of value. Content Type(s): Staff research, Staff discussion papers Topic(s): Bank notes, Central bank research, Coronavirus disease (COVID-19), Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O54
Weather the Storms? Hurricanes, Technology and Oil Production Staff Working Paper 2022-36 Johan Brannlund, Geoffrey R. Dunbar, Reinhard Ellwanger, Matthew Krutkiewicz Do technological improvements mitigate the potential damages from extreme weather events? We show that hurricanes lower offshore oil production in the Gulf of Mexico and that stronger storms have larger impacts. Regulations enacted in 1980 that required improved offshore construction standards only modestly mitigated the production losses. Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Climate change, Potential output JEL Code(s): C, C2, C22, C23, Q, Q4, Q40, Q48, Q5, Q54
How Do People View Price and Wage Inflation? Staff Working Paper 2022-34 Monica Jain, Olena Kostyshyna, Xu Zhang This paper examines household-level data from the Canadian Survey of Consumer Expectations (CSCE) to understand households’ expectations about price and wage inflation, how those expectations link to views about labour market conditions and the subsequent impact on households’ outlook for real spending growth. Content Type(s): Staff research, Staff working papers Topic(s): Inflation and prices, Monetary policy communications JEL Code(s): C, C8, C83, D, D8, D84, E, E2, E21, E24, E3, E31
A Horse Race of Monetary Policy Regimes: An Experimental Investigation Staff Working Paper 2022-33 Olena Kostyshyna, Luba Petersen, Jing Yang How should central banks design monetary policy in stable times and during recessions? We run a horse race between five monetary policy frameworks in an experimental laboratory to assess how well the different approaches can manage the public’s expectations and stabilize the economy. Content Type(s): Staff research, Staff working papers Topic(s): Inflation targets, Monetary policy, Monetary policy communications, Monetary policy framework JEL Code(s): C, C9, D, D8, D84, E, E5, E52, E58
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
The Business Leaders’ Pulse—An Online Business Survey Staff Discussion Paper 2022-14 Tony Chernis, Chris D'Souza, Kevin MacLean, Tasha Reader, Joshua Slive, Farrukh Suvankulov This paper introduces the Business Leaders’ Pulse, a new online survey conducted each month. It is designed to provide timely and flexible input into the Bank of Canada’s monetary policy decision making by asking firms about their sales and employment growth expectations, the risks to their business outlook, and topical questions that address specific information needs of the Bank. Content Type(s): Staff research, Staff discussion papers Topic(s): Monetary policy and uncertainty, Recent economic and financial developments JEL Code(s): C, C8, C83, D, D2, D22, E, E3, E32
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 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