Research

Working Papers

Do Productivity Shocks Cause Inputs Misallocation?

Under Review

Firms exhibit varying productivity levels even within narrowly defined industries and face uncertainty when predicting future performance. This paper investigates the link between productivity uncertainty, heterogeneity, and misallocation across all inputs. Using a model where heterogeneous firms face staggered productivity shocks, creating gaps between expected and actual productivity, I find a positive association between marginal revenue product dispersions and productivity variability. The analysis reveals that productivity shocks predominantly drive marginal revenue product dispersions. By comparing baseline estimates with those from the factor shares approach, I highlight the limitations of the latter method in analyzing the effects of productivity evolution.

[Preprint] [Versions Repo (arXiv)] 

Conference Presentations:

Factor-Biased Efficiency Gains from Exporting: Evidence from Colombia 

Joint with Joonkyo Hong

Submitted

This study examines whether exporting enhances efficiency and favors specific inputs. We develop a production function model within a dynamic exporting and investment framework, capturing factor-biased technical changes. Using Kalman filtering to address measurement error and propensity score matching to control for self-selection into exporting, we analyze Colombia’s manufacturing sectors from 1981 to 1991. New exporters achieve a 4% annual increase in labor-augmenting and unskilled labor relative productivity, with no change in Hicks-neutral productivity. Unskilled labor-augmenting productivity grows by 8% annually, aligning with machinery asset expansion, while TFP rises by 3% per year.

[Preprint] [Versions Repo (arXiv)] 

Conference Presentations:

Unveiling Plant-Product Productivity via First-Order Conditions: Robust Replication of Orr (2022)

Joint with Joonkyo Hong

Submitted

In this study, we evaluate the reproducibility and replicability of Scott Orr's (Journal of Political Economy 2022; 130(11): 2771–2828) innovative approach for identifying within-plant productivity differences across product lines. Orr's methodology allows the estimation of plant-product level productivity, contingent upon a well-behaved pre-estimated demand system, which requires carefully chosen instrumental variables (IVs) for output prices. Using Orr's STATA replication package, we successfully replicate all primary estimates with the ASI Indian plant-level panel data from 2000 to 2007. Additionally, applying Orr's replication codes to a sample from 2011 to 2020 reveals that the suggested IVs do not perform as expected.

[Preprint] [Versions Repo (arXiv)] [I4R Discussion Paper]

Work in Progress