André Binette is a Senior Policy Advisor in the Canadian Economic Analysis Department (CEA). In this capacity, he participates in the department’s contribution to the Bank of Canada’s Monetary Policy Report. Also, he conducts analysis and research on current economic issues and monetary policy more generally. His primary interests include economic forecasting and Big Data.
Mr. Binette began his career at the Bank of Canada in 1999 as an Economist in the Current Analysis Division. For two years, he was a Senior Analyst in the Canadian Projection and Model Development Division. In 2009, he became Assistant Chief of the Current Analysis Division. Recently name Senior Policy Advisor and responsible for the new division in charge of better understanding the impact of new technologies on the economy.
The mandate of the new division (Digital Economy and Advanced Analytics) is far reaching, ranging from issues such as the size of the digital economy to the impact of technological progress on the functioning of the economy. The division will also explore the efficacy of Big Data to improve our ability to understand the Canadian economy better. We will also assist in the adoption of new and emerging technologies in CEA.
Born in Montréal, Mr. Binette obtained his Masters in Economics from UQAM.
This paper examines the quality of projections of real GDP growth taken from the Bank of Canada Monetary Policy Report (MPR) since they were first published in 1997. Over the last decade, it has become common practice among the central banking community to discuss forecast performance publicly.
Canadian exports have often disappointed since the Great Recession. The apparent disconnect between exports and the Bank of Canada’s current measure of foreign demand has created an impetus to search for an alternative.
In light of the fact that Canada was continuing to lose market share in the United States, Binette, de Munnik and Gouin-Bonenfant (2014) studied 31 Canadian non-energy export (NEX) categories to assess their individual performance.
Canada’s Short-Term Indicator (CSI) is a new model that exploits the information content of 32 indicators to produce daily updates to forecasts of quarterly real GDP growth. The model is a data-intensive, judgment-free approach to short-term forecasting. While CSI’s forecasts at the start of the quarter are not very accurate, the model’s accuracy increases appreciably as more information becomes available. CSI is the latest addition to a wide range of models and information sources that the Bank of Canada uses, combined with expert judgment, to produce its short-term forecasts.