<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Giovanni Morzenti | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/giovanni-morzenti/</link><description>Giovanni Morzenti</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/giovanni-morzenti/index.xml" rel="self" type="application/rss+xml"/><item><title>The Hitchhiker's Guide to Markup Estimation: Assessing Estimates From Financial Data</title><link>https://macropaperwarehouse.com/papers/the-hitchhikers-guide-to-markup-estimation-assessing-estimates-from-financial-data/</link><guid>https://macropaperwarehouse.com/papers/the-hitchhikers-guide-to-markup-estimation-assessing-estimates-from-financial-data/</guid><description>&lt;p&gt;Using matched data combining physical production records (EAP survey) and financial statements (FARE) for 147,403 firm-years across 18 two-digit manufacturing industries in France (2009–2019), the paper audits the production-approach markup estimator — μ = α × (PY/WV) — when α must be estimated from revenue rather than quantity data. The central analytical result is that revenue-based markup estimates are positively correlated with true markups whenever the estimated output elasticity falls strictly between zero and the revenue elasticity (the Bond et al. 2021 knife-edge case). For firms sharing the same production function, the correlation is exactly one — revenue markups rank firms identically to quantity markups up to an additive constant. Monte Carlo simulations in an Atkeson–Burstein (2008) oligopoly model with translog production confirm this: correlation between revenue and true markups is 0.94 (SD 0.05) across 200 simulations with 1,600 firms, 180 markets, and 40 periods. In the French matched data, within-sector Pearson correlations between quantity and revenue markup estimates are 0.61 in levels and 0.80 in first differences; rank correlations reach 0.62 and 0.83 respectively, with medians above 0.65 and 0.84 across sectors. Cross-sectional relationships between markups and profit rates, labor shares, material shares, and market shares are qualitatively robust across estimation methods (Table VI). However, average log markup levels differ sharply: 0.37 (quantity) vs 0.13 (revenue); aggregate French manufacturing markups average 1.45 (quantity) vs 1.08 (revenue). The policy implication: revenue-based financial data are adequate for studying markup dispersion, trends, and firm-level correlates; they cannot identify markup levels.&lt;/p&gt;</description></item></channel></rss>