Econometric and statistical methods

• Earnings Dynamics and Intergenerational Transmission of Skill

  Staff Working Paper 2020-46 Lance Lochner, Youngmin Park

  How are your past, current and future earnings related to those of your parents? We explore this by using 37 years of Canadian tax data on two generations.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Labour markets, Potential output, Productivity JEL Code(s): C, C3, C33, J, J2, J24, J6, J62

• Understanding Trend Inflation Through the Lens of the Goods and Services Sectors

  Staff Working Paper 2020-45 Yunjong Eo, Luis Uzeda, Benjamin Wong

  The goods and services sectors have experienced considerably different dynamics over the past three decades. Our goal in this paper is to understand how such contrasting behaviors at the sectoral level affect the aggregate level of trend inflation dynamics.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Inflation and prices, Monetary policy transmission JEL Code(s): C, C1, C11, C3, C32, E, E3, E31, E5, E52

• On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity

  Staff Working Paper 2020-42 Ruben Hipp

  Various business interactions of banks create a network of hidden relationships, which cannot be directly inferred from the correlation of bank stock returns. Without causality, it remains unclear how policy interventions change the network. Thus, this paper aims to find the causal network as anticipated by investors.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, Financial markets, Financial stability JEL Code(s): C, C1, C3, C32, C5, C58, L, L1, L14

• The New Benchmark for Forecasts of the Real Price of Crude Oil

  Staff Working Paper 2020-39 Amor Aniss Benmoussa, Reinhard Ellwanger, Stephen Snudden

  How can we assess the quality of a forecast? We propose a new benchmark to evaluate forecasts of temporally aggregated series and show that the real price of oil is more difficult to predict than we thought.

  Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods, International topics JEL Code(s): C, C1, C5, C53, Q, Q4, Q47

• Cyclicality of Schooling: New Evidence from Unobserved Components Models

  Staff Working Paper 2020-38 Barbara Sadaba, Sunčica Vujič, Sofia Maier

  What is the time-varying impact of economic cycles on decisions to invest in human capital?

  Content Type(s): Staff research, Staff working papers Topic(s): Business fluctuations and cycles, Econometric and statistical methods JEL Code(s): C, C3, C32, E, E3, I, I2, J, J2

• 2019 Cash Alternative Survey Results

  Staff Discussion Paper 2020-8 Kim Huynh, Gradon Nicholls, Mitchell Nicholson

  The role of cash in Canadians’ lives has been evolving, as innovations in digital payments have become more widely adopted over the past decade. We contribute to the Bank of Canada’s research on central bank digital currency by monitoring Canadians’ use of cash and their adoption of digital payment methods.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Bank notes, Central bank research, Digital currencies and fintech, Econometric and statistical methods JEL Code(s): C, C1, C12, C9, E, E4, O, O5, O51

• Survival Analysis of Bank Note Circulation: Fitness, Network Structure and Machine Learning

  Staff Working Paper 2020-33 Diego Rojas, Juan Estrada, Kim Huynh, David T. Jacho-Chávez

  Using the Bank of Canada's Currency Information Management Strategy, we analyze the network structure traced by a bank note’s travel in circulation and find that the denomination of the bank note is important in our potential understanding of the demand and use of cash.

  Content Type(s): Staff research, Staff working papers Topic(s): Bank notes, Econometric and statistical methods, Payment clearing and settlement systems JEL Code(s): C, C5, C52, C6, C65, C8, C81, E, E4, E42, E5, E51

• Sample Calibration of the Online CFM Survey

  Technical Report No. 118 Marie-Hélène Felt, David Laferrière

  The Canadian Financial Monitor (CFM) survey uses non-probability sampling for data collection, so selection bias is likely. We outline methods for obtaining survey weights and discuss the conditions necessary for these weights to eliminate selection bias. We obtain calibration weights for the 2018 and 2019 online CFM samples.

  Content Type(s): Staff research, Technical reports Topic(s): Econometric and statistical methods JEL Code(s): C, C8, C81, C83

• Cash and COVID-19: The impact of the pandemic on demand for and use of cash

  Staff Discussion Paper 2020-6 Heng Chen, Walter Engert, Kim Huynh, Gradon Nicholls, Mitchell Nicholson, Julia Zhu

  Consumer spending declined significantly during the recent COVID-19 pandemic. This negative shock likely reduced spending across all methods of payment (cash, debit, credit, etc.). The mix of payment methods consumers use could also be affected. We study how the pandemic has influenced the demand for and use of cash. We also offer insights into the use of other payment methods, such as debit and credit cards.

  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

• The Term Structures of Loss and Gain Uncertainty

  Staff Working Paper 2020-19 Bruno Feunou, Ricardo Lopez Aliouchkin, Roméo Tedongap, Lai Xu

  We investigate the uncertainty around stock returns at different investment horizons. Since a return is either a loss or a gain, we categorize return uncertainty into two components—loss uncertainty and gain uncertainty. We then use these components to evaluate investment.

  Content Type(s): Staff research, Staff working papers Topic(s): Asset pricing, Econometric and statistical methods JEL Code(s): G, G1, G12