Randomized Experiments in International trade August 2018 Amit Khandelwal Columbia Business school
Randomized Experiments in International Trade August 2018 Amit Khandelwal Columbia Business School 1
Introduction RCTs are uncommon in international trade research but common in some fields, like development and labor economics Most recent BREAD conference featured 8 papers, 7 were RCTs In this talk, I'll present two RCTs conducted on export-oriented firms, with the following goals Why RCTs are a useful toolkit for research in international trade? What we can learn(and what we cannot hope to learn)? Practical and logistical challenges of implementing RCTs on firms will not discuss econometric/statistical issues in designing experiments See duflo et al 2007 for an extensive and highly useful discussion of these Issues
Introduction • RCTs are uncommon in international trade research, but common in some fields, like development and labor economics • Most recent BREAD conference featured 8 papers, 7 were RCTs • In this talk, I’ll present two RCTs conducted on export-oriented firms, with the following goals: – Why RCTs are a useful toolkit for research in international trade? – What we can learn (and what we cannot hope to learn)? – Practical and logistical challenges of implementing RCTs on firms • (I will not discuss econometric/statistical issues in designing experiments. See Duflo et al 2007 for an extensive and highly useful discussion of these issues) 2
Introduction The big empirical questions in trade What are the gains from trade? Who gains /loses from international trade? What are the mechanisms of the adjustment process? Remain active areas of work because they are difficult to study Trade policy is an endogenous outcome of lobbying and political economy Trade barriers look similar to technology shocks, and often correlated (i. e. innovations in logistics is both a technology shock and a shock to offshoring Inherent data limitations incomplete admin data, lack of price data, cannot directly observe technology use, and the general coarseness of data
Introduction • The big empirical questions in trade – What are the gains from trade? – Who gains/loses from international trade? – What are the mechanisms of the adjustment process? • Remain active areas of work because they are difficult to study – Trade policy is an endogenous outcome of lobbying and political economy – Trade barriers look similar to technology shocks, and often correlated (i.e., innovations in logistics is both a technology shock and a shock to offshoring) – Inherent data limitations • incomplete admin data, lack of price data, cannot directly observe technology use, and the general coarseness of data 3
Progress with RCTs RCTs can make progress on these questions in two key ways Causal inference Identified moments Nakamura Steinsson 18 Additionally, RCTs are almost always paired with primary data collection Allow researchers to tailor data collection to match outcomes of interest in models
Progress with RCTs • RCTs can make progress on these questions in two key ways: – Causal inference – “Identified moments” Nakamura & Steinsson 18 • Additionally, RCTs are almost always paired with primary data collection – Allow researchers to tailor data collection to match outcomes of interest in models
Causal Inference (in brief What does randomization do? Consider a linear model =BT+∑7 Bi is the treatment effect on firm i Consider treated firms=1)and control firms i=O), and subtract averages 7=32+∑(2- b is the average treatment effect Randomization guarantees the second term holds in expectation
Causal Inference (in brief!) • What does randomization do? • Consider a linear model – is the treatment effect on firm i • Consider treated firms ( ) and control firms ( ), and subtract averages • is the average treatment effect • Randomization guarantees the second term holds in expectation 5