Essays in Labour, Monetary, and Experimental Macroeconomics

Abstract

This thesis brings together three essays that address central questions in applied macroeconomics and empirical labour economics, spanning the identification of job vacancies in the labour market using high-frequency data, the identification of monetary policy shocks in a small open economy, and the determinants of firm price-setting behavior under shocks. The first chapter examines the measurement of job vacancies, a fundamental input in the analysis of labour market dynamics. Traditional survey-based measures, such as the Job Vacancy and Wage Survey (JVWS), are subject to lags and limitations. By contrast, online job postings offer a timely alternative but raise concerns of accuracy. Using a rich dataset of Canadian job postings from Vicinity Jobs, this work compares online and survey-based vacancy measures and uses algorithms and robust regression with Huber weights to improve the mapping from postings to actual vacancies. Using machine learning forecast models, these methods reduce prediction error by an average of 15\% relative to existing approaches, demonstrating the potential of combining online data and econometrics to deliver more timely and reliable vacancy statistics for researchers and policymakers. The second chapter investigates the transmission of monetary policy shocks in Canada, a small open economy, through the use of factor-augmented models and machine learning. I propose a novel approach that filters economic variables using LASSO-based techniques before factor extraction, which enhances the reliability of the subsequent Factor-Augmented Vector Autoregression (FAVAR) estimates. Imposing sign restrictions and studying the impulse responses, I find that positive monetary policy shocks exert significant contractionary effects on employment, inflation, real GDP, and housing prices, though effects on the exchange rate remain ambiguous. I also highlight important structural breaks in Canada’s monetary policy regime and demonstrate the value of combining machine learning with factor models for small open economy analysis. The third chapter turns to experimental evidence on price-setting behavior, using a laboratory experiment where participants repeatedly set prices under Bertrand competition. The design varies market structure (duopoly versus monopolistic competition) and pricing frictions (flexible prices versus menu costs), and introduces four shocks: a demand shock and three cost shocks differing in size and uncertainty. The experiment shows that large shocks trigger disproportionately larger price adjustments, and that firms’ forecasts of market prices is a stronger determinant of pricing compared to their expectations of costs, highlighting the importance of expectations and strategic interaction. These findings contribute to the literature on nominal rigidities, expectations formation, and the transmission of shocks to inflation.