Supplemental Appendix for “Does the Use of Imported Intermediates Increase Productivity? Plant-Level Evidence” (NOT FOR PUBLICATION)

In this section we outline how we control for endogeneous selection while using LP intermediate proxy approach. The idea is essentially the same as the one used in Olley and Pakes (1996); namely, we first identify the state variables that are relevant for endogneous exiting decisions and approximate the survival probabilities using the polynomials in the observable variables. Then, we can control for the endogenous exiting decision by including the polinomials in the survival probabilities when the moment conditions are constructed. First, the state variables that are relevant for the plant exit decision are the predetermined level of capital kit and the past import decision di,t−1. The model in section 2 implies that a plant chooses to continue to produce if the current realization of productivity term ωit is higher than the threshold value ωt(kit, di,t−1). One might think that the intermediate proxy approach is not applicable to control for the selection bias because we cannot “recover” ωit from observables given that we do not observe the current period intermediates if the plant chooses to exit. Note, however, that ωit follows the first order Markov process ωit = ξt + γdi,t−1 + ωi,t−1 + uit (equation (8) in the main text) and, thus, it is possible to approximate ωit using the observable variables (di,t−1, ωi,t−1), where ωi,t−1, in turn, can be proxied by the past value of intermediates, the past capital, and the past import decision so that ωi,t−1 = ω∗ t−1(xi,t−1, ki,t−1, di,t−1) (equation (10) in the main text). 1 ∗Department of Economics, the University of Western Ontario. E-mail: [email protected]. †Department of Economics, Queen’s University. E-mail: [email protected]. 1The linearity assumption can be relaxed. For instance, suppose that ωit follows the stochastic process ωit =