C1 - Econometric and Statistical Methods and Methodology: General
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Non-Parametric Identification and Testing of Quantal Response Equilibrium
We show that the utility function and the error distribution are non-parametrically over-identified under Quantal Response Equilibrium (QRE). This leads to a simple test for QRE. We illustrate our method in a Monte Carlo exercise and a laboratory experiment. -
Parallel Tempering for DSGE Estimation
I develop a population-based Markov chain Monte Carlo algorithm known as parallel tempering to estimate dynamic stochastic general equilibrium models. Parallel tempering approximates the posterior distribution of interest using a family of Markov chains with tempered posteriors. -
Predictive Density Combination Using a Tree-Based Synthesis Function
This paper studies non-parametric combinations of density forecasts. We introduce a regression tree-based approach that allows combination weights to vary on the features of the densities, time-trends or economic indicators. In two empirical applications, we show the benefits of this approach in terms of improved forecast accuracy and interpretability. -
Three things we learned about the Lynx payment system
Canada transitioned to a new wholesale payment system, Lynx, in August 2021. Lynx is based on a real-time settlement model that eliminates credit risk in the system. This model can require more liquidity; however, Lynx’s design allows Canada’s wholesale payments to settle efficiently. -
Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis
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. -
Unmet Payment Needs and a Central Bank Digital Currency
We discuss the payment habits of Canadians both in the current payment environment and in a hypothetical cashless environment. -
Global Demand and Supply Sentiment: Evidence from Earnings Calls
This paper quantifies global demand, supply and uncertainty shocks and compares two major global recessions: the 2008–09 Great Recession and the COVID-19 pandemic. We use two alternate approaches to decompose economic shocks: text mining techniques on earnings calls transcripts and a structural Bayesian vector autoregression model. -
What Can Earnings Calls Tell Us About the Output Gap and Inflation in Canada?
We construct new indicators of demand and supply for the Canadian economy by using natural language processing techniques to analyze earnings calls of publicly listed firms. Our results indicate that the new indicators could help central banks identify inflationary pressures in real time. -
From LVTS to Lynx: Quantitative Assessment of Payment System Transition
We quantitatively assess the changes in participants’ payment behaviour from modernizing Canada's high-value payments system to Lynx. Our analysis suggests that Lynx's liquidity-saving mechanism encourages liquidity pooling and early payments submission, resulting in improved efficiency for participants but with slightly increased payment delays.