Dr. Gu, Assistant Professor in the Department of Economics, University of Toronto, receives the Polanyi Prize for Economic Science.
Dr. Gu is working on novel statistical methods of accounting for unseen human factors in predicting social and economic outcomes – research that could lead to more accurate ways of evaluating teachers and understanding purchasing decisions.
Dr. Gu’s research focuses on the role of what economists call “unobserved heterogeneity” – differences between human subjects’ behaviours that cannot be directly measured, such as personal tastes and biases or innate abilities. She proposes that traditional assumptions used to factor in these differences in statistical modelling don’t always produce the most reliable results, and that her approach is to “let the data speak for itself.” As data sources become gradually more abundant in the Big Data era, her approach becomes more attractive.
In the case of teachers, performance evaluations are based largely on student grades, while the impact of their individual teaching style, being difficult to observe, is often not accurately factored in. Dr. Gu is analyzing a large dataset from United States primary schools to propose a fairer method of evaluating teachers. Her approach would identify with greater accuracy the teachers’ contribution, and lead to better policy recommendations on measuring teacher effectiveness.
Dr Gu, a Shanghai native who joined the University of Toronto after earning her PhD in the United States, will also be developing a new methodology to understand the extent to which individuals’ behaviour is driven by market conditions versus their own unique characteristics. One proposed application of the research is to develop better models to predict how consumers will react to market changes, such as the price increase or reduction of a product, or the introduction of a new product to market.