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Information sharing and state revenue forecasting performance
Author(s) -
Spreen Thomas L.,
Martinez Guzman Juan P.
Publication year - 2022
Publication title -
public budgeting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.694
H-Index - 30
eISSN - 1540-5850
pISSN - 0275-1100
DOI - 10.1111/pbaf.12329
Subject(s) - revenue sharing , information sharing , revenue , state (computer science) , tax revenue , business , economics , public economics , accounting , econometrics , microeconomics , computer science , algorithm , world wide web
Abstract This study evaluates whether intergovernmental information sharing enhances forecasting performance. This is accomplished by examining the accuracy of state revenue forecasts following the federal passage of the Tax Cuts and Jobs Act (TCJA) of 2017. The quantitative analysis suggests that states that shared information produced more accurate corporate income tax forecasts than nonsharing states. This result is consistent with surveys and interviews of federal and state officials that reported significant information‐sharing activity arising from uncertainty about the TCJA's corporate income tax provisions. This study demonstrates that information sharing plays an important yet overlooked role in mitigating forecast uncertainty.