Iain G. Snoddy
I am a PhD job market candidate in the Vancouver School of Economics at the University of British Columbia. I expect to graduate in 2019, and will be available for interviews at the 2019 ASSA/AEA meetings in Atlanta and the 2018 CEEE meetings in Toronto.
My fields of interest are in labor, macroeconomics and applied econometrics. My work explores the role of general equilibrium effects in the labor market and examines methodological issues related to identification.
My job market paper leverages machine learning tools to better control for selection bias when individuals make choices across alternatives. This novel procedure represents a significant improvement over traditional methods which require more stringent identifying restrictions. With an application to cross state estimates of the returns to education I show how traditional methods often fail to fully account for selection bias.
JOB MARKET PAPER
Abstract: Machines learning tools are utilized to develop an improved non-parametric method to control for selection bias. Building on the insights of Lee (1983) and Dahl (2002), variable selection methods and prediction using the Random Forest algorithm are used to relax the Single Index Sufficiency Assumption (SISA) imposed by Dahl’s method and to improve the empirical implementation of the procedure. Monte Carlo experiments illustrate that this novel procedure performs well both when the SISA holds and when it is violated. In experiments using reasonable sample sizes it removes 75-99% of selection bias. As researchers cannot determine empirically whether the SISA holds in their data, this represents a significant improvement over traditional correction methods which perform poorly when the SISA is violated. I use this improved method to obtain new estimates of the return to education across states for the US I find that traditional methods can underestimate selection bias by as much as 20% of the OLS estimate compared to the improved procedure.
Abstract: Since 2000, US real average wages stagnated or declined while Canadian wages increased. We investigate the role of the Canadian resource boom in explaining this difference. We focus on wage spillovers to non-resource workers through a bargaining channel. We find that long-distance commuting to resource regions had substantial spillover effects on noncommuters in sending regions. Through spillovers, we account for 49% of the increase in the real mean wage in Canada between 2000 and 2012. We also find long-distance commuting effects in the US. We conclude that long-distance commuting integrates regions, spreading benefits and costs of booms across the economy
Revised and Resubmitted: Journal of Labor Economics.
Abstract: Since the seminal paper Pissarides (1985), the literature on search frictions has often adopted the assumption of free entry. In this paper we forgo this restriction by proposing a more realistic framework in which individuals are constantly making the decision whether or not to open a firm; namely, firms are created through endogenous choices; business-owners and workers are drawn from the same pool. We show that in this framework, the Nash bargaining parameter is crucial for internal dynamics. In particular, workers and business owners share the same outside-options. As a result, the wage is no longer unambiguously positively related to the value of unemployment. The constrained efficient solution to this model takes the same form as the standard search model implying the same form for the Hosios condition. However, as this efficient solution changes, the rate of unemployment is either exacerbated or muted conditional on the value of the match elasticity parameter.
WORK IN PROGRESS
Examining Union Wage Spillovers (with David Green)
Job Search and Immigrant Enclaves
Teaching Assistant Positions:
- ECON 102 Principles of Macroeconomics, UBC (2016, 2014)
- ECON 302 Intermediate Macroeconmics, UBC (2013)
- ECON 356 Introduction to International Finance, UBC (2014)
- ECON 562 Research Design & Policy Evaluation, UBC (2016)
- ECON 460 Economics of Labour Markets (lecture on Labor Market Signalling)