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Title: Essays on exchange rate pass through
Author: Han, Lu
Awarding Body: University of Cambridge
Current Institution: University of Cambridge
Date of Award: 2018
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This dissertation contributes to the theoretical and empirical understandings of international transmissions of exchange rate shocks. It consists of three chapters. The first chapter extends Corsetti and Dedola (2005) and further allows for competition in retail networks. In the model, there are four types of firms interacting with each other including retailing manufacturers, non-retailing manufacturers, specialised retailers and nontradable good producers. The equilibrium depends on the interaction among these four types of firms, which leads to a dynamic and incomplete exchange rate pass through (ERPT) depending on the firms’ share of retail networks. With the standard calibration, the model can generate a high (4-5) long-run trade elasticity without conflicting with a low (0.5-1) short-run elasticity, suggesting that the dynamics of retail networks offer a potential explanation of the trade elasticity puzzle. Chapter 2 investigates the ERPT of Chinese exporters. We propose an estimator that utilises orthogonal dimensions to control for unobserved marginal costs and estimate destination specific markup adjustments to bilateral and multilateral exchange rate shocks. Our estimates suggest that the cost channel accounts for roughly 50% of conventional EPRT estimates. We offer new channels of heterogeneity in firms’ pricing behaviour and provide supporting evidence on the international pricing system. Chapter 3 aims to bridge the gap between theoretical and empirical works on ERPT. I propose a machine learning algorithm that systematically detects the determinants of ERPT. The proposed algorithm is designed to work directly with highly disaggregated firm-level customs trade databases as well as publicly available commodity trade flow datasets. Tested on the simulated data from a realistic micro-founded multi-country trade model, my algorithm is proven to have accuracies around 95% and 80% in simple and complex scenarios respectively. Applying the algorithm to China’s customs data from 2000 to 2006, I document new evidence on the nonlinear relationships among market structures, unit value volatility and ERPT.
Supervisor: Corsetti, Giancarlo Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: exchange rates ; pass through ; exports ; trade elasticity ; machine learning ; China