SEMESTER: Spring2020

COURSE NUMBER: EWMBA217.11

COURSE TITLE: Big Data and Better Decisions

UNITS OF CREDIT: 3

INSTRUCTOR: Jonathan Kolstad, Paul Gertler

E-MAIL ADDRESS: jkolstad@berkeley.edu, gertler@berkeley.edu

MEETING DAY(S)/TIME: Saturdays, 9am-1pm. 3/7, 3/14, 3/21, 4/4, 4/11, 4/18, 5/9

PREREQUISITE(S): Data and Decisions

CAREER FIELD: Good for any field that uses data and evidence. Examples from health finance, development, policy, energy, and many other fields

CLASS FORMAT: Lectures, in class exercises, online programming sessions (using r programming language):

REQUIRED READINGS: Business Data Science by Matt Taddy

BASIS FOR FINAL GRADE: Homework 30% Exam 30% Group Project 30% Participation 10%

ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES:

This course will introduce students to advanced methods for data driven decision making in business. Building on the content in Data and Decisions, this course will cover methods designed to provide evidence for two types of fundamental business issues. The first is forecasting and the second is evaluating alternative possible strategies.

The course is intended to train business leaders to i) understand the value of data-based decision making ii) evaluate analytics tools and products and iii) conduct richer analysis of randomized and naturally occurring experiments.

Topics include designing randomized controlled trials in the field, evaluating natural experiments (e.g. differences-in-differences, instrumental variables and regression discontinuity) and machine learning tools for forecasting (e.g. linear regularization, tree models and random forest).

The course work will include problem sets evaluating experimental and non- experimental data, writing code and making business decisions using the results. The

goal of the course is not to train you as a Data Scientist but to be able to read and evaluate empirical/analytic approaches and products from any level including reading code to evaluating experimental design. All problem sets will be in R and the course will introduce the programming language.

BIOGRAPHICAL SKETCH:

Jonathan Kolstad is an Associate Professor of Economic Analysis and Policy at Berkeley Haas and a Research Associate at the National Bureau of Economic Research. He is also the Co-director of the Health Initiative at the UC Berkeley Opportunity Lab.

He is an economist whose research interests lie at the intersection of health economics, industrial organization, and public economics. He is particularly interested in finding new models and unique data that can account for the complexity of markets in health care, notably the role of information asymmetries and incentives. He has studied the impact of quality information on demand, as well as intrinsic surgeon incentives. In a series of papers, he has evaluated the impact of the Massachusetts health insurance expansion on a variety of outcomes. He has also gathered unique data to understand the role of information frictions in consumer decision making in insurance markets and on medical treatments.

Kolstad was awarded the Arrow Award from the International Health Economics Association for the best paper in health economics in 2014 and the NIHCM Foundation Research Award in 2016. He is also a Co-founder and was Chief Data Scientist at Picwell. He received his PhD from Harvard University and BA from Stanford University.

Paul Gertler is the Li Ka Shing Professor of Economics at the University of California, Berkeley, where he holds appointments at the Haas School of Business and the School of Public Health. He is also the Scientific Director of the Center for Effective Global Action. Gertler is an internationally recognized expert in impact evaluation. He was Chief Economist of the Human Development Network of the World Bank from 2004-2007 and the Founding Chair of the Board of Directors of the International Initiative for Impact Evaluation (3ie) from 2009- 2012. At the World Bank, he led an effort to institutionalize and scale up impact evaluation for learning what works in human development.

At Berkeley he teaches courses in applied impact evaluation at both the graduate and undergraduate levels, as well as in an executive education program for policy-makers. He is the author of the best-selling textbook “Impact Evaluation in Practice” and the recently released second edition, published by The World Bank Press. He has been a Principal Investigator on a large number of at-scale multisite impact evaluations, including Mexico’s CCT program Progresa/Oportunidades and Rwanda’s Health Care Pay-for-Performance scheme. He has published results from impact evaluations extensively in both

scientific and policy journals on early childhood development, education, fertility and contraceptive use, health, HIV-AIDS, energy and climate change, housing, job training, poverty alleviation, labor markets, and water and sanitation.

He was awarded the Kenneth Arrow Award for best paper in health economics in 1996. He received his PhD in Economics from the University of Wisconsin in 1985, and, prior to UC Berkeley, he held academic appointments at Harvard University, RAND, and SUNY Stony Brook.