Research and Writing
This page collects my working paper, dissertation research, and open source work. For shorter writing on applied economics, causal inference, pricing strategy, and marketplace economics, visit the blog.
Working Paper
Profit-Aware Pricing in Two-Sided Marketplaces: Demand Elasticity, Cost Uncertainty, and Customer Lifetime Value in Brazilian E-Commerce
Dinesh R Poddaturi | 2026
This paper develops an empirical pricing framework for two-sided e-commerce marketplaces, combining demand estimation, profit optimization under cost uncertainty, customer lifetime value modeling, customer propensity estimation, and sequential purchase pattern analysis. Applied to 110,840 transactions across 71 product categories from the Olist Brazilian marketplace, the analysis demonstrates that revenue maximization and profit maximization are fundamentally misaligned in elastic markets. A 40% price cut generates a 160% revenue increase but a 162% profit loss. A key methodological finding is that cost uncertainty dominates elasticity uncertainty. A 5-point COGS error forfeits 70 to 75% of potential profit gains, while a 20% elasticity error preserves profitability across all scenarios. The paper includes a complete implementation framework incorporating experimentation design, causal evaluation protocols, phased rollout sequencing, and risk mitigation procedures.
Keywords: Dynamic Pricing, Marketplace Economics, Causal Inference, Revenue Management, Customer Lifetime Value, Price Elasticity, Two-Sided Markets, Profit Optimization, Demand Estimation.
Open Source
Switchback Experiment Framework for Two-Sided Marketplaces
Dinesh R Poddaturi | 2026 | GitHub Repository
A Python simulation of switchback experiment design for two-sided marketplace pricing interventions. Implements the switchback methodology for settings where network effects prevent user-level randomization, including treatment assignment, outcome simulation, clustered standard error estimation, and power analysis. Designed to demonstrate how causal inference methods can be implemented for real marketplace pricing and policy evaluation problems.
Doctoral Dissertation
My doctoral dissertation at Iowa State University developed dynamic structural economic models of the U.S. beef cattle industry, with applications to disease outbreak scenarios and agricultural policy analysis. The work focuses on dynamic optimization, structural estimation, and demand systems — methods that transfer directly to pricing, industrial organization, and empirical market analysis. Co-authored with Chad E. Hart and Lee L. Schulz.
A Dynamic Assessment of the Economic Impacts of a Foot-and-Mouth Disease Outbreak on the U.S. Beef Cattle Industry
Dinesh R Poddaturi, Chad E Hart, Lee L Schulz | Presented at Western Agricultural Economics Association, 2022
Develops a dynamic framework integrating rancher optimization, cattle biology, stock replacement, age distribution, and market processes, calibrated to the U.S. beef cattle industry. Estimates the economic impacts of a hypothetical Foot-and-Mouth Disease outbreak by integrating trade, consumption, and supply shocks into the dynamic framework. The framework is generalizable to a variety of production and policy shifts beyond disease scenarios.
A Dynamic Model of U.S. Beef Cattle
Dinesh R Poddaturi, Chad E Hart, Lee L Schulz | Presented at Agricultural and Applied Economics Association, 2020
Develops a bottom-up dynamic economic model of the U.S. beef cattle industry incorporating farmer optimization behavior, cattle biology, age and gender composition, and micro-foundations. Calibrated under naive and rational price expectations to capture observed industry dynamics and project future prices and quantities.
Implementing a National Animal Identification and Traceability Program: Economic Assessment using a Dynamic Model of U.S. Beef Cattle
Dinesh R Poddaturi, Chad E Hart, Lee L Schulz | Presented at Agricultural and Applied Economics Association, 2021
Quantifies the short-run and long-run economic impacts of a mandatory national animal identification and traceability system on U.S. beef cattle producers, including producer surplus changes under different cost-sharing programs and adoption rates.
Additional Research
Autoregressive Tempered Fractionally Integrated Moving Average Model (2018)
Dinesh R Poddaturi | MS Statistics Creative Component
Analysis of the ARTFIMA time series model and its applications to real-world data, comparing model fit and predictive performance against ARFIMA and ARMA specifications.
Development of a CRUSH Margin Calculator for Beef and Pork Markets (2017)
Dinesh R Poddaturi, Garland Dahlke, Russ Euken, Lee L Schulz
Web-based application utilizing CME futures settlement price data to generate expected margins for beef and pork producers. Used daily by beef and pork producers for price risk management.
