Markups and Public Procurement.

Bachelor's thesis, Charles University in Prague. doi: dspace.cuni.cz

Abstract:

This thesis analyses the relationship between engagement in public procurement and markups charged by firms. While controlling for aggregate trends and individual firm characteristics, the effect is estimated in a multivariate regression framework as the percentage markup premium associated with engagement in public procurement. This approach contributes to the existing literature on public procurement, in that, rather than only making comparisons between different tenders, it benchmarks the competitiveness of public procurement against the competitiveness in markets serving private clients while not having to rely on data on expert cost estimates.

Submission: The Young Economist Award of the Czech Economic Society

Abstract:

I document the evolution of market power using firm-level data from the Czech construction sector since 2006. Contrary to the global trend of rising markups, I find that aggregate markups have decreased, declining from 40% above marginal cost in 2006 to 30% in 2021, driven primarily by firms in the upper tail of the markup distribution. By linking this data with government tenders, I examine the relationship between markups and public procurement. I find that markups are significantly higher when controlling for unobserved productivity; government contractors have price-to-marginal-cost ratios that are 0.3 higher than those of private-sector firms; and firm-level markups increase by 12% upon a firm’s entry into public procurement.

Master Thesis (in progress)

I adopt a methodology conditioning on lagged outcome values, drawing from recent replication materials by Yiqing Xu and Guido Imbens. In the data, firms entering public procurement in the current year already demonstrate higher markups in previous years, alongside larger sales, costs of goods sold, and capital. Using matched data, I achieve balance in these variables and pass placebo tests, confirming no effect on markups in the years prior to firms' acquisition of government contracts. I aim to compare the unconfoundedness approach outlined above by applying recent advances in causal panel data analysis, with a focus on the Difference-in-Differences (DID) methodology. This section will cover (1) heterogeneity-robust estimators, (2) tests and sensitivity analyses for parallel trends, and (3) alternative identification strategies such as synthetic DID, matrix completion, and potentially sufficient statistics, negative controls, and design-robust reweighting, inspired by recent work from Guido Imbens, Dmitry Arkhangelsky, and their coauthors

Methodology and replication package reference:

1. DLW 2012 Markups and Firm-Level Export Status

2. DLEU 2020 The Rise of Market Power and the Macroeconomic Implications

3. Guido Imbens, Yiqing Xu LaLonde (1986) after Nearly Four Decades: Lessons Learned