Gianluca Pallante

gianluca[dot]pallante[at]unipi[dot]it

Via Cosimo Ridolfi 10

56124 Pisa, Italy

Macroeconomics
Fiscal policy
Technical change
Green transition
Financial stability
Agent-based modelling

I am Assistant Professor in Economics at the Department of Economics and Management of the University of Pisa.

I am a macroeconomist, interested in the analysis of technical change and the transformative role of industrial and innovation policies — such as those aimed at triggering a just and orderly green transition.

I use agent-based modeling techniques to analyze the complex interplay between technological progress, economic change and financial stability. I also explore methodological aspects for improving the validity and the reliability of agent-based models to provide realistic representation of economic dynamics and robust integrated scenarios.

For my latest, visit my LinkedIn page.

news

Sep 01, 2026	Joining the University of Pisa as Assistant Professor in Economics
May 11, 2026	New Publication in the Journal of Applied Econometrics
Dec 05, 2025	Starting Grant from Fondo Italiano per la Scienza (Italian ERC)
Oct 30, 2025	EAEPE 2025 @Athens wrap-up
Jun 10, 2025	ABM4 Policy workshop @ European Central Bank

selected publications

Research Policy

Does public R&D funding crowd-in private R&D investment? Evidence from military R&D expenditures for US states

Gianluca Pallante, Emanuele Russo, and Andrea Roventini

Oct 2023

DOI
Journal of Economic Dynamics and Control

Identification of Structural VAR Models via Independent Component Analysis: A Performance Evaluation Study

Alessio Moneta and Gianluca Pallante

Nov 2022

DOI
Journal of Financial Stability

Robust-less-fragile: Tackling systemic risk and financial contagion in a macro agent-based model

Gianluca Pallante, Mattia Guerini, Mauro Napoletano, and Andrea Roventini

Feb 2025

DOI
Journal of Applied Econometrics

Reassessing the Cross‐Sectional Fiscal Multiplier: Evidence From U.S. Defense Procurement, 1966–2019

Gianluca Pallante

May 2026

Abs DOI Replication

This paper revisits the empirical analysis of Nakamura and Steinsson (2014). I reconstructed and extended the original dataset to cover the period 1966–2019, harmonizing two major sources of data: the Defense Contract Action Data System (DCADS) and USAspending.gov. I discuss how to aggregate these contract-level data to better capture spending more directly tied to domestic stimulus. Estimated multipliers are slightly lower in narrow replications but increase when incorporating later fiscal episodes. I also assess the validity and stability of cross-sectional estimates. While some heterogeneity exists, dispersion in state-level responses remains within reasonable boundaries, especially when accounting for dynamic persistence.