February 20th – 22nd, 2020
Empirical Methods in Causal Inference for Policy Analysts
The goal of this workshop is to provide a thorough introduction to recent methodological developments to study causal effects in a non-experimental setting, including Regression Discontinuity (RD) Designs, Synthetic Control Methods, Difference-in-Differences and Machine Learning. The main focus will be on methodology and empirical practice, with an emphasis of the key steps to follow when implementing the methods. The course is meant to be self-contained and hence most underlying econometric concepts and results will be introduced and explained in class.
Sebastian Calónico
Dr. Sebastian Calonico is an Assistant Professor in the Department of Health Policy and Management at Columbia University. His research focuses on program evaluation and causal inference, applying innovative quantitative methods to the study of relevant empirical problems in an interdisciplinary context, including economics as well as other social, medical and statistical sciences. His work has been published in leading journals in economics and statistics, including Econometrica, Journal of the American Statistical Association, and Review of Economics and Statistics.
Sebastian was born in Argentina, where he completed a B.A. in Economics at Universidad de Buenos Aires and an M.A. in Economics at Universidad Torcuato Di Tella. He later received a PhD in Economics from the University of Michigan, where he also obtained an MA in Statistics. Prior to joining Columbia University in 2019, he was a faculty member in the Department of Economics at the University of Miami.
February 24th – 28th, 2020
Empirical Topics in Labour Economics: identification issues, minimum wages and the impacts of immigration.
Research in labour economics in recent decades has been driven by large survey datasets. That has meant considerable focus on the supply side of the labour market, including human capital investment and decisions about labour force participation. But recent expanded access to matched worker and firm administrative data has shifted attention back to labour demand and questions about the existence and distribution of economic rents in the labour market. In this course, we will examine the expanding literature on labour demand. We will start with the historical literature on labour demand in order to form a base and as a basis for discussing issues of identification in empirical economics. As part of our examination of identification of labour demand elasticities, we will discuss the literatures on minimum wages and on the impacts of immigration on receiving and sending economies. We will then move to alternatives to the standard neoclassical model: implicit contracting models; efficiency wage models; and search and bargaining models of various types. Working from that empirical and theoretical underpinning, we will examine emerging results from the matched worker-firm data and what they imply for how labour demand, in particular, and labour markets, in general, operate.
David Green
Dr. David Green is a professor in the Vancouver School of Economics at UBC. He received his BA from Queen’s University and his PhD from Stanford. His areas of research interest include income inequality, immigration, the impact of technical change on the labour market, and policies affecting labour market outcomes. He is a former editor of the Canadian Journal of Economics and an International Research Associate with the Institute for Fiscal Studies in London. He has served on the editorial boards for the American Economic Review and the Journal of Political Economy. His work has been published in leading journals, including Econometrica, the American Economic Review, and the Review of Economic Studies. He is currently the chair of a provincial committee investigating the applicability of the basic income to British Columbia.
February 24nd to 28th, 2020
Economic Evaluation Methods in Health: Cost-Benefit Analysis (CBA) and Cost-Effectiveness Analysis (CEA)
Market failures in the healthcare sector create the need for methods that replicate the efficient resource allocation guaranteed by competitive markets. These economic evaluation methods are now supporting decision making in most national health systems, influencing the adoption of new medicines, technologies, and healthcare programs. This course presents the economic foundations of Cost-Benefit Analysis (CBA) and Cost-Effectiveness Analysis (CEA), the economic evaluation methods more widely used in healthcare decision making. The course discusses key concepts such as indirect costs, quality adjusted life years (QALYs), and uncertainty; and different modelling approaches such as decision trees and Markov models. The course combines theoretical concepts with real life applications, including a basic CEA Markov model for cardiovascular diseases that students will implement in Excel.
Alejandro Arrieta
Dr. Alejandro Arrieta is Associate Professor of health economics in the Department of Health Policy and Management at Florida International University, Miami, USA. He has been faculty at the School of Public Health of Indiana University, Indianapolis, and consultant to the World Bank, Inter-American Development Bank, the Pan American Health Organization and the American Medical Association. He received his Ph.D. in Economics from Rutgers University and his BA in Economics from Pontificia Universidad Católica del Perú. Dr. Arrieta has an active research portfolio in health economics and economic evaluations in health. A branch of his research focuses on how physician behavior and incentives affect the quantity and quality of health services, and how that shapes the role of the private sector in the health systems of Latin America. Another area of his research focuses on the economic value of new medicines and technologies in cardiovascular diseases.
