[{"content":"I write about AI and economic growth at Beyond Imitation, and I write about art and fiction at The Other Tadepalli. You can also find my research.\n","externalUrl":null,"permalink":"/","section":"Karthik Tadepalli","summary":"I am an economist interested in navigating the future of transformative AI. I work as a Research Scholar at GovAI. Before that, I got a PhD in Economics at UC Berkeley in 2026.","title":"Karthik Tadepalli","type":"page"},{"content":" Economic Espionage and Innovation Restrictions Working paper with Andrew Kao\nPDF HTML Abstract We provide systematic evidence on the economic damages from espionage to US firms and industries. Compiling a comprehensive dataset of publicly disclosed espionage incidents from 1995-2024, we establish that espionage has substantial negative effects on targeted firms. In an event-study design, revenues and R\u0026amp;D expenditures at targeted firms decline by roughly 40% within five years, with effects persisting for up to a decade. These effects do not appear for firms unsuccessfully targeted for espionage, supporting a causal interpretation. These firm-level damages translate into measurable aggregate effects on US industry: exports in targeted sectors decline by 40% over a decade. Given these substantial damages, we investigate whether firms restrict knowledge sharing in response to espionage. Across a wide range of outcomes, we find little evidence of such restrictions. Firms do not reduce their patenting with foreign inventors, do not discriminate in employment based on perceived espionage risk, do not change the geography of their business, and do not discuss how they adapt to espionage incidents. Overall, espionage has clear economic harms to targeted firms and US industry, but firms are puzzlingly unresponsive in how they manage innovation.\nDetecting Researcher-Level p-Hacking: An Empirical Bayes Approach Working paper with Abel Brodeur\nPDF Abstract Statistical methods typically lack power to detect p-hacking and publication bias among individual researchers, making it difficult to detect how prevalent p-hacking is. We propose a novel empirical Bayes method to estimate researcher-level p-hacking prevalence. Using data from top medical journals, we find strong evidence these practices are widespread: at least 85% of researchers over-reject null hypotheses, with a conservative lower bound of 73%. Our approach identifies 20% of researchers as over-rejecting, whereas conventional tests detect none. These findings demonstrate that p-hacking and publication bias are systemic rather than isolated misconduct, underscoring the need for structural reforms in scientific practice.\n","externalUrl":null,"permalink":"/research/","section":"Karthik Tadepalli","summary":" Economic Espionage and Innovation Restrictions Working paper with Andrew Kao\nPDF HTML Abstract We provide systematic evidence on the economic damages from espionage to US firms and industries. Compiling a comprehensive dataset of publicly disclosed espionage incidents from 1995-2024, we establish that espionage has substantial negative effects on targeted firms. In an event-study design, revenues and R\u0026D expenditures at targeted firms decline by roughly 40% within five years, with effects persisting for up to a decade. These effects do not appear for firms unsuccessfully targeted for espionage, supporting a causal interpretation. These firm-level damages translate into measurable aggregate effects on US industry: exports in targeted sectors decline by 40% over a decade. Given these substantial damages, we investigate whether firms restrict knowledge sharing in response to espionage. Across a wide range of outcomes, we find little evidence of such restrictions. Firms do not reduce their patenting with foreign inventors, do not discriminate in employment based on perceived espionage risk, do not change the geography of their business, and do not discuss how they adapt to espionage incidents. Overall, espionage has clear economic harms to targeted firms and US industry, but firms are puzzlingly unresponsive in how they manage innovation.\n","title":"Research","type":"page"},{"content":"As an undergraduate, I collected a lot of good advice from smart people on applying to PhDs in economics, which I\u0026rsquo;m compiling here for anyone else who was in my position. Be warned; all of this is from 2021 or earlier, so it may be extremely outdated.\n\u0026ldquo;So I\u0026rsquo;m thinking about grad school in economics\u0026hellip;\u0026rdquo; The big picture: Susan Athey, Chris Blattman, Jesse Shapiro, John List, Andrew Johnston, Al Roth, Alex Eble Research Advice General compilations - Esther Duflo, David Weil, Steve Pischke, Paul Niehaus, Matt Lowe, Don Davis Undergrad course advice Any math course ever - Dexter Chua\u0026rsquo;s unbelievable notes and exercises Real analysis - Exercises, exercises and more exercises: A Problem Book in Real Analysis, Dexter Chua (part 2), MIT OCW exams and psets Notes - Dexter Chua (part 2), MIT OCW Grad micro Preparing for it Taking the class Predoctoral research opportunities About them - Is a predoctoral RAship a good idea? Fed RAship Fed vs university RAship How to find them Many of these links might expire with time - most recent iterations should be searchable on the internet Econ RA Listings, NBER job board, non-NBER job board - general aggregators of RA opportunities Opportunity Insights, SIEPR, JPAL, EPIC - specific RA positions How to get them - RA recruiting cycle Getting an RA position Stata resources for RAships Acing the Stata task JPAL guide How to use them - What makes a good RAship recommendation? Professor\u0026rsquo;s guide to being an RA What PhD programs want from your research experience Bonus: undergraduate research - Fed undergrad internship Standing out as an undergrad RA \u0026ldquo;How to use them\u0026rdquo; advice still applies Letters of recommendation Standing out as an undergrad RA Will it be a great letter? How to ask for a letter Recommendation sample NSF GRFP Application 2021 Solicitation and FAQ Compiled advice: Alex Lang, Mallory Ladd, Claire Bowen NSF proposal advice NSF winners: 1, 2, 3 Linkception More people have made these link compilations, so - Andrew Johnston, Masayuki Kudamatsu, Alex Eble, Jennifer Doleac, Charlotte Ostergaard, Raul Pacheco-Vega (again)\nAlbert Alex Zevelev links resources to study material.\nResearch workflow Gentzkow/Shapiro\u0026rsquo;s definitive guide Good data sharing Plain text tools for social science GitHub for academics ","externalUrl":null,"permalink":"/resources/","section":"Karthik Tadepalli","summary":"As an undergraduate, I collected a lot of good advice from smart people on applying to PhDs in economics, which I’m compiling here for anyone else who was in my position. Be warned; all of this is from 2021 or earlier, so it may be extremely outdated.\n","title":"Resources","type":"page"},{"content":"","externalUrl":null,"permalink":"/tags/","section":"Tags","summary":"","title":"Tags","type":"tags"}]