Columnist Challenges Competition Bureau's Approach to Algorithmic Pricing
In a recent commentary, economist and columnist Matthew Lau has issued a strong critique of the federal Competition Bureau's increasing scrutiny of algorithmic pricing practices. Lau argues that government intervention in this area is unnecessary and potentially harmful to market efficiency and consumer welfare.
Understanding Algorithmic Pricing Mechanisms
The Competition Bureau defined algorithmic pricing in a discussion paper last year as "the process of using automated algorithms to set or recommend prices for products or services, often in real time, based on a set of data inputs." The bureau noted that this practice is gaining momentum worldwide across various sectors including hospitality, concert tickets, and ridesharing services.
Following up on its initial discussion paper, the bureau recently published a new report summarizing public feedback on algorithmic pricing, indicating its intention to "respond swiftly and effectively" to what it perceives as potential market concerns.
Clear Consumer Benefits of Market-Driven Algorithms
Lau presents compelling examples from the bureau's own paper to illustrate the benefits of algorithmic pricing. A ridesharing application that charges more during peak hours or inclement weather actually improves economic efficiency by better matching supply with demand. Similarly, hotels using algorithms to provide personalized offers based on customer preferences help consumers by tailoring options to their specific needs and budget constraints.
"In both examples, the benefits of algorithmic pricing are clear," Lau writes. "The ridesharing application improves economic efficiency by matching supply with demand. The hotel helps the consumer by tailoring offers according to what the consumer prefers."
The bureau's own paper acknowledges that algorithmic pricing can help businesses innovate, improve efficiency, and make it easier for consumers to switch providers between competing services.
Questioning Regulatory Concerns
Lau systematically addresses the Competition Bureau's expressed concerns about potential negative aspects of algorithmic pricing. The bureau has suggested that algorithmic pricing could facilitate price coordination among competitors if they use common algorithms. However, Lau counters that collusive arrangements are inherently unstable because companies always have incentives to "cheat" by lowering prices to gain market share.
Furthermore, Lau questions the fundamental premise that government should prohibit price coordination in competitive markets, suggesting that market forces naturally correct such behavior without regulatory intervention.
Examining Alleged Harmful Practices
The Competition Bureau has raised concerns about companies potentially using algorithms to engage in "harmful practices" such as predatory pricing or tying and bundling strategies. Lau argues these concerns are largely theoretical and not supported by market realities.
Regarding predatory pricing, which involves companies setting aggressively low prices to drive out competitors, Lau notes that real-world examples are "exceedingly rare." Companies attempting such strategies typically suffer significant financial losses, often fail to eliminate competitors, and find it nearly impossible to maintain monopoly positions without government protection.
Similarly, Lau dismisses concerns about tying and bundling, noting that algorithms might help firms "target higher prices for tied or bundled offers to less price-sensitive customers, while offering discounts to more price-sensitive customers to prevent them from switching to competitors."
"So higher prices might be charged to less price-sensitive consumers and lower prices to more price-sensitive consumers," Lau observes. "How is that harmful? The answer is that it is not."
Market Efficiency Versus Regulatory Intervention
Lau draws parallels to everyday market behaviors to illustrate his point, noting that when prices are effectively set by consumers themselves through their purchasing decisions, those who are less price-sensitive naturally pay more than those who are more price-sensitive. He cites restaurant tipping as a clear example of this market-driven price differentiation in action.
The columnist concludes that if the Competition Bureau's goal is truly to benefit consumers, its "swift and effective" response to algorithmic pricing should be no response at all. Market-driven algorithms, according to Lau's analysis, create better price matches between buyers and sellers while improving overall economic efficiency without requiring government oversight or intervention.
This perspective challenges growing regulatory interest in technology-driven pricing mechanisms and raises important questions about the appropriate role of government in evolving digital marketplaces.
