<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Eugene Tan | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/eugene-tan/</link><description>Eugene Tan</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://macropaperwarehouse.com/authors/eugene-tan/index.xml" rel="self" type="application/rss+xml"/><item><title>Entrepreneurial Investment Dynamics and the Wealth Distribution</title><link>https://macropaperwarehouse.com/papers/entrepreneurial-investment-dynamics-and-the-wealth-distribution/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://macropaperwarehouse.com/papers/entrepreneurial-investment-dynamics-and-the-wealth-distribution/</guid><description>&lt;p&gt;This paper investigates how the illiquidity of entrepreneurial capital shapes investment dynamics and wealth inequality. The central question is whether entrepreneurship drives wealth heterogeneity or merely attracts the already-wealthy — and, specifically, whether the investment behavior of nascent entrepreneurs can be rationalized by frictions on capital reallocation rather than financial constraints alone.&lt;/p&gt;
&lt;p&gt;The empirical foundation is the restricted Kauffman Firm Survey (KFS), a single-cohort panel of 3,140 U.S. firms founded in 2004 and tracked through 2011. The key measurement is the log average revenue product of capital (log ARPK), residualized on two-digit NAICS industry fixed effects and time dummies. Two striking facts emerge. First, the cross-sectional distribution of log ARPK is left-skewed (skewness approximately -0.33, mean -0.49, standard deviation 1.75, kurtosis 5.7). Second, the distribution shows asymmetric persistence: the autocorrelation of log ARPK in the bottom quintile (ρ₁ = 0.897) is statistically significantly larger than in the top quintile (ρ₅ = 0.443), and the diagonal entry of the estimated transition matrix for the first quintile (0.614) substantially exceeds that for the fifth (0.568). These facts are inconsistent with standard models: a frictionless dynamic investment model with time-to-build predicts i.i.d. ARPK; one with collateral constraints predicts right-skewness and right-tail persistence.&lt;/p&gt;</description></item><item><title>Quantifying the allocative efficiency of capital: The role of capital utilization</title><link>https://macropaperwarehouse.com/papers/quantifying-the-allocative-efficiency-of-capital-the-role-of-capital-utilization/</link><guid>https://macropaperwarehouse.com/papers/quantifying-the-allocative-efficiency-of-capital-the-role-of-capital-utilization/</guid><description>&lt;p&gt;Standard measures of capital allocative efficiency—based on the dispersion of the average revenue product of capital (ARPK)—are severely biased when capital utilization is endogenous. When utilization is flexible, firms can bypass physical adjustment constraints by varying intensity, so that the correct efficiency measure requires the dispersion of average revenue product of capital services (ARPKS), defined as the log difference between revenue and utilized capital, not of ARPK. Contrary to the standard view that higher ARPK dispersion signals lower allocative efficiency, the paper demonstrates that when efficiency improvements arise from greater utilization flexibility, ARPK dispersion can increase alongside efficiency gains. An application to India&amp;rsquo;s capital market liberalization reform shows that the standard approach (ignoring utilization) predicts allocative efficiency gains of 5.25% (statistically significant), while the corrected approach accounting for utilization finds gains of only 0.04% (not statistically significant).&lt;/p&gt;</description></item></channel></rss>