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- Articles and reports: 18-001-X2020002Description:
This paper presents an open-source system that was developed for automatic estimation of building height from street-view images using Deep Learning (DL), advanced image processing techniques, and geospatial data. The goal of the developed system is to ultimately be used to enrich the Open Database of Buildings (ODB), that was published by Statistics Canada, as a part of the Linkable Open Data Environment (LODE). Some of the obtained results for building-height estimation are presented. Some challenging cases and the scalability of the system are discussed as well.
Release date: 2020-12-08 - Articles and reports: 11-626-X2020024Description:
Recent improvements in robotics have rekindled ancient fears about the impact of robotics on humankind. Unfortunately, existing data seldom distinguishes robots from other types of automation, so research into their impact so far has been difficult. This article introduces research from a new Statistics Canada dataset, Robots!, on the impact of robots at the firm-level. The article examines the impact of robot investment on firm performance and employment at the enterprise level.
Release date: 2020-11-02 - Articles and reports: 11-626-X2020025Description:
Prior to the COVID-19 pandemic, advances in artificial intelligence and robotics raised concerns that automation might lead to relatively high unemployment rates in the coming years. This Economic Insights article examines the degree to which Canadians’ views about the impact of automation on net job creation in 1989 materialized three decades later.
Release date: 2020-11-02 - Articles and reports: 11-633-X2020004Description:
Recent advances in artificial intelligence have rekindled ancient fears that robots will replace humans in the economy. Previous waves of automation changed but did not reduce labour’s role, but robots’ human-like flexibility could make this time different. Whether or not it will is an empirical question that has lacked suitable data to answer. This paper describes the creation of a dataset to fill the evidence gap in Canada. Robots! is firm-level panel data on robot adoption created using Canadian import data. The data identify a substantial amount of the robot investment in the Canadian economy from 1996 to 2017. Although many robots are imported by robotics wholesalers or programmers for resale, the majority of them can be attributed to their final (direct) adopting firm. The data can be used to study the impact of robot adoption at the economic region, industry or firm-level.
Release date: 2020-11-02 - Articles and reports: 11F0019M2020017Description:
This study examines how employment and organizations have changed in response to robot adoption. As robotics and artificial intelligence (AI) become increasingly used by firms as the next engine of innovation and productivity growth, their effects on labour, firm practices and productivity have become a subject of growing importance. The study provides the most comprehensive evidence possible at the level of individual businesses on the employment and organizational effects of robot investments.
Release date: 2020-11-02 - Articles and reports: 11F0019M2020015Description:
Recent advances in artificial intelligence and machine-learning technologies have fuelled fears of potential job losses among some workers. While the net impact of new technology on total jobs can be negative, positive or neutral, some workers may be more affected than others depending on how easily robots and algorithms can replace them, or how easily their skills complement the new technology. In the case of women and men, it is not clear who is likely to be most affected. This study estimates the risk of job transformation as a result of automation technology faced by women and men.
Release date: 2020-09-24 - Articles and reports: 11F0019M2020011Description:
The recent development of several artificial intelligence applications—such as driverless vehicles, robo-writers and computer-aided medical diagnostics—has led to concerns about the role of human workers in the future workforce. The COVID-19 pandemic has added to these concerns, as businesses may turn to new artificial intelligence technologies to perform work activities not traditionally regarded as automatable, such as social tasks. While previous studies have estimated the share of Canadian workers at high risk of automation-related job transformation, this study is the first to examine in great detail the automation risks faced by different groups of workers.
Release date: 2020-06-29 - Articles and reports: 11F0019M2020009Description:
The main objective of this paper is to determine whether the immigration status of the owner of a small or medium-sized enterprise (SME) affects the likelihood of a company implementing an innovation. This paper uses data from a survey of Canadian small and medium-sized enterprises (SMEs) in 2011, 2014 and 2017, and asks whether immigrant-owned SMEs were more likely to innovate during the three years prior to the survey than those owned by Canadian-born individuals.
Release date: 2020-06-09 - Articles and reports: 11F0019M2020008Description:
Multinationals play an important role in the world economy because they are larger, innovate more, are more productive and pay higher wages compared with non-multinationals. Multinationals (i.e., firms that have established affiliates or subsidiaries in other countries) have played an increasingly important role in many economies. In Canada, multinationals accounted for only 0.8% of all enterprises in 2016, but they held 67% of all assets in the Canadian economy (Schaffter and Fortier-Labonté 2019). Given the importance of multinationals to the Canadian economy, it is essential for policy makers to understand the economic performance and productivity advantage of multinationals operating in Canada.
To address policy-relevant research questions, a rich micro dataset covering all industries from 2000 to 2014 has been constructed for this study, using several administrative microdata files at Statistics Canada. This dataset is used to delve deeper into and estimate the productivity advantage of multinationals, including the selection and learning effects associated with multinationality. In addition, this study investigates whether and how research and development (R&D) investment contributes to the superior productivity performance of multinationals.
Release date: 2020-05-26 - Articles and reports: 11F0019M2020002Description:
Labour productivity growth in the business sector in Canada started to decline in 2000, from 2.3% per year in the period from 1991 to 2000 to 1.0% per year in the period from 2000 to 2015. This paper examines how innovation, innovation diffusion across firms, and business dynamism affected the productivity slowdown.
Release date: 2020-01-17
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Articles and reports (10)
Articles and reports (10) ((10 results))
- Articles and reports: 18-001-X2020002Description:
This paper presents an open-source system that was developed for automatic estimation of building height from street-view images using Deep Learning (DL), advanced image processing techniques, and geospatial data. The goal of the developed system is to ultimately be used to enrich the Open Database of Buildings (ODB), that was published by Statistics Canada, as a part of the Linkable Open Data Environment (LODE). Some of the obtained results for building-height estimation are presented. Some challenging cases and the scalability of the system are discussed as well.
Release date: 2020-12-08 - Articles and reports: 11-626-X2020024Description:
Recent improvements in robotics have rekindled ancient fears about the impact of robotics on humankind. Unfortunately, existing data seldom distinguishes robots from other types of automation, so research into their impact so far has been difficult. This article introduces research from a new Statistics Canada dataset, Robots!, on the impact of robots at the firm-level. The article examines the impact of robot investment on firm performance and employment at the enterprise level.
Release date: 2020-11-02 - Articles and reports: 11-626-X2020025Description:
Prior to the COVID-19 pandemic, advances in artificial intelligence and robotics raised concerns that automation might lead to relatively high unemployment rates in the coming years. This Economic Insights article examines the degree to which Canadians’ views about the impact of automation on net job creation in 1989 materialized three decades later.
Release date: 2020-11-02 - Articles and reports: 11-633-X2020004Description:
Recent advances in artificial intelligence have rekindled ancient fears that robots will replace humans in the economy. Previous waves of automation changed but did not reduce labour’s role, but robots’ human-like flexibility could make this time different. Whether or not it will is an empirical question that has lacked suitable data to answer. This paper describes the creation of a dataset to fill the evidence gap in Canada. Robots! is firm-level panel data on robot adoption created using Canadian import data. The data identify a substantial amount of the robot investment in the Canadian economy from 1996 to 2017. Although many robots are imported by robotics wholesalers or programmers for resale, the majority of them can be attributed to their final (direct) adopting firm. The data can be used to study the impact of robot adoption at the economic region, industry or firm-level.
Release date: 2020-11-02 - Articles and reports: 11F0019M2020017Description:
This study examines how employment and organizations have changed in response to robot adoption. As robotics and artificial intelligence (AI) become increasingly used by firms as the next engine of innovation and productivity growth, their effects on labour, firm practices and productivity have become a subject of growing importance. The study provides the most comprehensive evidence possible at the level of individual businesses on the employment and organizational effects of robot investments.
Release date: 2020-11-02 - Articles and reports: 11F0019M2020015Description:
Recent advances in artificial intelligence and machine-learning technologies have fuelled fears of potential job losses among some workers. While the net impact of new technology on total jobs can be negative, positive or neutral, some workers may be more affected than others depending on how easily robots and algorithms can replace them, or how easily their skills complement the new technology. In the case of women and men, it is not clear who is likely to be most affected. This study estimates the risk of job transformation as a result of automation technology faced by women and men.
Release date: 2020-09-24 - Articles and reports: 11F0019M2020011Description:
The recent development of several artificial intelligence applications—such as driverless vehicles, robo-writers and computer-aided medical diagnostics—has led to concerns about the role of human workers in the future workforce. The COVID-19 pandemic has added to these concerns, as businesses may turn to new artificial intelligence technologies to perform work activities not traditionally regarded as automatable, such as social tasks. While previous studies have estimated the share of Canadian workers at high risk of automation-related job transformation, this study is the first to examine in great detail the automation risks faced by different groups of workers.
Release date: 2020-06-29 - Articles and reports: 11F0019M2020009Description:
The main objective of this paper is to determine whether the immigration status of the owner of a small or medium-sized enterprise (SME) affects the likelihood of a company implementing an innovation. This paper uses data from a survey of Canadian small and medium-sized enterprises (SMEs) in 2011, 2014 and 2017, and asks whether immigrant-owned SMEs were more likely to innovate during the three years prior to the survey than those owned by Canadian-born individuals.
Release date: 2020-06-09 - Articles and reports: 11F0019M2020008Description:
Multinationals play an important role in the world economy because they are larger, innovate more, are more productive and pay higher wages compared with non-multinationals. Multinationals (i.e., firms that have established affiliates or subsidiaries in other countries) have played an increasingly important role in many economies. In Canada, multinationals accounted for only 0.8% of all enterprises in 2016, but they held 67% of all assets in the Canadian economy (Schaffter and Fortier-Labonté 2019). Given the importance of multinationals to the Canadian economy, it is essential for policy makers to understand the economic performance and productivity advantage of multinationals operating in Canada.
To address policy-relevant research questions, a rich micro dataset covering all industries from 2000 to 2014 has been constructed for this study, using several administrative microdata files at Statistics Canada. This dataset is used to delve deeper into and estimate the productivity advantage of multinationals, including the selection and learning effects associated with multinationality. In addition, this study investigates whether and how research and development (R&D) investment contributes to the superior productivity performance of multinationals.
Release date: 2020-05-26 - Articles and reports: 11F0019M2020002Description:
Labour productivity growth in the business sector in Canada started to decline in 2000, from 2.3% per year in the period from 1991 to 2000 to 1.0% per year in the period from 2000 to 2015. This paper examines how innovation, innovation diffusion across firms, and business dynamism affected the productivity slowdown.
Release date: 2020-01-17
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