Economic freedom determinants across US states: A Bayesian model averaging approach

被引:1
|
作者
Saunoris, James W. [1 ]
Payne, James E. [2 ,3 ]
机构
[1] Eastern Michigan Univ, Dept Econ, Ypsilanti, MI USA
[2] Univ Texas Paso, Woody L Hunt Coll Business, El Paso, TX USA
[3] Univ Texas El Paso, Woody L Hunt Coll Business, 500 W El Paso, El Paso, TX 79968 USA
关键词
Economic freedom; Bayesian model averaging; socioeconomic determinants; U; S; states; GROWTH; NATIONS; INSTITUTIONS; CORRUPTION; GOVERNMENT; ROBUST; PRIORS; PANEL; AID;
D O I
10.1080/00036846.2023.2211343
中图分类号
F [经济];
学科分类号
02 ;
摘要
This study examines the potential determinants of state-level economic freedom for a panel of the 50 U.S. states from 1994 to 2020. To address model uncertainty in the identification of robust determinants, we use Bayesian model averaging to test the robustness (to the inclusion and exclusion of other determinants) of 17 potential determinants that have been recognized in the extant literature. The results show robustness with respect to the positive impact of the level of per capita real income and its growth, fiscal decentralization and neighbouring state economic freedom, whereas per capita fossil fuel production, population density, unemployment rate and democratic governorships have a negative impact. The remaining determinants were not robustly associated with economic freedom.
引用
收藏
页码:4471 / 4480
页数:10
相关论文
共 50 条
  • [1] The Socioeconomic Determinants of Terrorism: A Bayesian Model Averaging Approach
    Sanso-Navarro, Marcos
    Vera-Cabello, Maria
    [J]. DEFENCE AND PEACE ECONOMICS, 2020, 31 (03) : 269 - 288
  • [2] The convergence dynamics of economic freedom across US states
    Payne, James E.
    Saunoris, James W.
    Nazlioglu, Saban
    Karul, Cagin
    [J]. SOUTHERN ECONOMIC JOURNAL, 2023, 89 (04) : 1216 - 1241
  • [3] Economic determinants of total factor productivity growth: The Bayesian modelling averaging approach
    Sobieraj, Janusz
    Metelski, Dominik
    [J]. ENTREPRENEURIAL BUSINESS AND ECONOMICS REVIEW, 2021, 9 (04) : 147 - 171
  • [4] Determinants of Non-price Competitiveness of New EU Member States: Bayesian Model Averaging Approach
    Michalikova, Eva
    [J]. VISION 2020: SUSTAINABLE ECONOMIC DEVELOPMENT AND APPLICATION OF INNOVATION MANAGEMENT, 2018, : 1625 - 1635
  • [5] Robust determinants of companies' capacity to innovate: a Bayesian model averaging approach
    Santa, Mijalche
    Stojkoski, Viktor
    Josimovski, Marko
    Trpevski, Igor
    Kocarev, Ljupco
    [J]. TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, 2019, 31 (11) : 1283 - 1296
  • [6] Determinants of county-level rent levels: a Bayesian model averaging approach
    Cebula, Richard J.
    Saunoris, James William
    [J]. APPLIED ECONOMICS LETTERS, 2024, 31 (16) : 1565 - 1568
  • [7] Examining the Industrial Energy Consumption Determinants: A Panel Bayesian Model Averaging Approach
    Borozan, Djula
    Borozan, Luka
    [J]. ENERGIES, 2020, 13 (01)
  • [8] Forecasting US Inflation by Bayesian Model Averaging
    Wright, Jonathan H.
    [J]. JOURNAL OF FORECASTING, 2009, 28 (02) : 131 - 144
  • [9] Structural Breaks in US Macroeconomic Time Series: A Bayesian Model Averaging Approach
    CHECK, A. D. A. M.
    PIGER, J. E. R. E. M. Y.
    [J]. JOURNAL OF MONEY CREDIT AND BANKING, 2021, 53 (08) : 1999 - 2036
  • [10] A new approach for Bayesian model averaging
    TIAN XiangJun1
    2 State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics
    3 Nansen-Zhu International Research Centre
    4 Meterological Bureau of Xi’an City
    [J]. Science China Earth Sciences, 2012, 55 (08) : 1336 - 1344