The Complexities of Measuring National Productivity Growth
Economist William Watson examines the fundamental challenges in measuring productivity growth, particularly as Canada launches a new $6 million research initiative aimed at accelerating national productivity through the Social Sciences and Humanities Research Council.
A High-Level Research Initiative
The University of Calgary economist Trevor Tombe, one of Canada's most respected policy economists, is leading a new national research network that has received $6 million in federal funding to expand existing productivity research. While Watson acknowledges this represents a potentially valuable use of public funds compared to many government expenditures, he raises critical questions about how such research output will be measured within productivity statistics themselves.
The fundamental problem lies in how productivity is typically calculated: output per hour, with output measured by the dollar value of what's being produced. Public sector research like Tombe's initiative presents a measurement conundrum since it won't be sold in markets but rather given away, making its economic value difficult to quantify.
The Public Sector Measurement Dilemma
Watson notes that attempts to measure public-sector productivity have typically resorted to valuing output at production cost, an approach widely recognized as unsatisfactory. This explains why productivity data almost exclusively focuses on the business sector, where market transactions provide clearer valuation through what buyers are willing to pay.
"The research generated by the Tombe group won't itself show up in productivity numbers," Watson observes. "Like most public and para-public sector output, it will be given away rather than sold, creating a valuation problem with no definitive answer."
Quality Improvements and Measurement Challenges
Even within the business sector, productivity measurement faces significant complications. Watson illustrates this with an automotive example: if 100 autoworkers produce the same number of cars today as they did two decades ago, traditional measures might suggest unchanged productivity. However, if today's cars represent higher quality and value, workers are actually producing more economic value despite similar physical output.
"There must be very few industries where what's currently being produced is exactly the same as what has always been produced," Watson notes. "Taking these product quality changes into account presents substantial measurement difficulties that complicate productivity analysis."
Academic Productivity Measurement
The Tombe research initiative faces additional measurement challenges specific to academic work. Academics don't typically track hours through conventional timekeeping methods, and research thinking can occur during any waking hour or even during sleep. This creates complications for both the numerator (output value) and denominator (hours worked) in productivity calculations.
Despite these measurement challenges, Watson acknowledges that research productivity has experienced genuine improvements through technological advances. Computing power and data availability have grown exponentially in recent decades, enabling more exhaustive and sophisticated economic analysis than previously possible.
Monitoring Research Output
The project leaders and granting agency will likely monitor individual researchers' productivity through traditional academic metrics: whether researchers complete promised work within agreed timelines and whether their output meets established quality standards through peer review processes.
Watson concludes that while the $6 million research initiative may generate valuable insights into productivity enhancement, the very act of measuring productivity—especially in non-market contexts—remains fraught with methodological challenges that complicate policy evaluation and economic analysis at both national and sectoral levels.
