Bridging The Digital Divide And Mitigating Cyber Security Risks In Canada

Canada's rapid digital transformation has created significant opportunities but also intensified existing inequalities and cyber security vulnerabilities. To better understand these challenges, an analysis is conducted at both individual and firm levels using recent Statistics Canada data and advanced econometric methods. At the individual level, data from the 2020 Canadian Internet Use Survey reveal how socioeconomic and demographic characteristics such as age, education, income, gender, and Indigenous identity influence digital engagement. A survey-weighted debiased Lasso logit model captures complex interactions among these factors, while cluster analysis assesses how provincial pandemic measures affected internet use and digital adoption during COVID-19.

Firm-level analysis incorporates data from the 2021 Canadian Survey of Digital Technology and Internet Use and the 2021 Canadian Survey of Cyber Security and Cybercrime. A Business Digital Usage Score quantifies firms' adoption of advanced technologies such as cloud computing, data analytics tools, and artificial intelligence. Stochastic frontier analysis evaluates how close firms are to their technological frontier. A survey-weighted debiased Lasso logit model identifies factors associated with both digital adoption and cyber security vulnerabilities across industries and firm sizes.

The Independence of Irrelevant Alternatives assumption in Multinomial Logit models is critically evaluated through simulation experiments examining the performance of the Hausman-McFadden (HM) specification test. The HM test is assessed under a number of data-generating scenarios used to mirror real-world applied research scenarios. To address challenges posed by high-dimensional data, the study introduces a Hausman test based on a debiased Lasso estimator.