What Is Behind the Weakness in Global Investment? Staff discussion paper 2016-5 Maxime Leboeuf, Robert Fay The recovery in private business investment globally remains extremely weak more than seven years after the financial crisis. This paper contributes to the ongoing policy debate on the factors behind this weakness by analyzing the role of growth prospects and uncertainty in explaining developments in non-residential private business investment in large advanced economies since the crisis. Content Type(s): Staff research, Staff discussion papers JEL Code(s): C, C2, C23, C3, C33, D, D2, D24, D8, D80, D84, E, E2, E22, F, F0, F01, G, G3, G31 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Economic models, Monetary policy, Inflation dynamics and pressures, Real economy and forecasting
Agency Costs, Risk Shocks and International Cycles Staff working paper 2016-2 Marc-André Letendre, Joel Wagner We add agency costs as in Carlstrom and Fuerst (1997) into a two-country, two-good international business-cycle model. In our model, changes in the relative price of investment arise endogenously. Content Type(s): Staff research, Staff working papers JEL Code(s): E, E2, E22, E3, E32, E4, E44, F, F4, F44 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Economic models, Structural challenges, International trade, finance and competitiveness
Computing the Accuracy of Complex Non-Random Sampling Methods: The Case of the Bank of Canada's Business Outlook Survey Staff working paper 2009-10 Daniel de Munnik, David Dupuis, Mark Illing A number of central banks publish their own business conditions surveys based on complex non random sampling methods. The results of these surveys influence monetary policy decisions and thus affect expectations in financial markets. To date, however, no one has computed the accuracy of these surveys because their respective non-random sampling method renders this assessment non-trivial. This paper describes a methodology for modeling complex non-random sampling behaviour, and computing relevant measures of statistical confidence, based on a given survey’s historical selection practice. We apply this framework to the Bank of Canada’s Business Outlook Survey by describing the sampling method in terms of rules-based criteria, historical practices, and Bayesian probabilities. This allows us to replicate the firm selection process using Monte Carlo simulations on a comprehensive micro-dataset of Canadian firms. We find, under certain assumptions, no evidence that the Bank’s firm selection process results in biased estimates and/or wider confidence intervals. Content Type(s): Staff research, Staff working papers JEL Code(s): C, C4, C8, C81, C9, C90 Research Theme(s): Models and tools, Econometric, statistical and computational methods