Ph.D. Candidate in Economics

ParandAkbari

Carnegie Mellon University
Tepper School of Business

My research studies the economics of AI adoption and diffusion, with a focus on firm value, labor markets, and asset prices. I also develop deep-learning methods for scientific computing and high-dimensional economic models.

Economics of AI · Empirical Finance · Corporate Finance
Asset Pricing · Technology Diffusion · Labor Economics

Job market paper Explore the data

Parand Akbari, Carnegie Mellon University — Parand Akbari Carnegie Mellon University

01 / Research

All research

Job market paper

When Firms Adopt AI Matters: Diffusion and the Value of AI Deployment

How does the value of AI deployment depend on when a firm adopts? My job market paper places corporate AI adoption within the industry diffusion process.

Accepted for the 2027 AFA Ph.D. Student Poster Session.

Read the paper

Asset pricing · with Burton Hollifield

When Does the Market Value Corporate AI Capability? Evidence from Stock Returns

Internal labor markets · with Liyan Shi and Ali Shourideh

Flattening the Ladder

02 / The data

From AI discussion
to measured deployment.

A disclosure-based measurement system spanning 4,313 public firms and 60,382 annual firm observations, with views of diffusion, industry adoption, integration depth, applications, and named providers.

Explore the AI adoption data

2011—2024

Corporate disclosures.
Economic distinctions.
A view of diffusion.

Awards & honors

Recent recognition.

K&L Gates Presidential Fellowship · 2026–2027
TCS-funded Presidential Fellowship · 2026–2027
American Finance Association (AFA) Ph.D. Student Travel Grant · 2026
Homaira Akbari Endowed Fellowship · 2025–2026
PNC Fund for Research and Innovation · 2025

All honors & research support

Teaching & background

Economics, finance,
and quantitative methods.

Teaching About Google Scholar