The resource curse revisited: A Bayesian model averaging approach

被引:96
|
作者
Arin, K. Peren [1 ]
Braunfels, Elias [2 ]
机构
[1] Zayed Univ, Abu Dhabi, U Arab Emirates
[2] Oslo Econ, Oslo, Norway
关键词
Oil; Growth; Natural resource curse; Bayesian model averaging; NATURAL-RESOURCES; GROWTH NEXUS; INSTITUTIONS; PRIORS;
D O I
10.1016/j.eneco.2017.12.033
中图分类号
F [经济];
学科分类号
02 ;
摘要
The evidence for the effects of oil rents on growth is mixed, a result which can be explained with model uncertainty. We address the issue using Bayesian Model Averaging techniques and an updated cross-country data set for long-term growth in the period 1970-2014, including 91 countries and 54 potential growth determinants. We do not find empirical evidence for the existence of a "natural resource curse" in our sample. On the contrary, our results suggest a robust positive effect of oil rents on long-term economic growth. We then introduce interaction terms of oil rents with potential conditions under which oil dependency can lead to sub-standard growth. The results indicate that the positive effect of oil rents may be conditional on the quality of institutions. We test the robustness of our results using a panel data set and find neither a curse nor a positive effect of oil rents on short- to medium-run growth. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:170 / 178
页数:9
相关论文
共 50 条
  • [41] Forecasting seasonal time series data: a Bayesian model averaging approach
    Alexander Vosseler
    Enzo Weber
    Computational Statistics, 2018, 33 : 1733 - 1765
  • [42] Forecasting seasonal time series data: a Bayesian model averaging approach
    Vosseler, Alexander
    Weber, Enzo
    COMPUTATIONAL STATISTICS, 2018, 33 (04) : 1733 - 1765
  • [43] Growth, convergence and public investment.: A Bayesian model averaging approach
    León-González, R
    Montolio, D
    APPLIED ECONOMICS, 2004, 36 (17) : 1925 - 1936
  • [44] Bayesian Model Averaging Approach for Urban Drainage Water Quality Modelling
    Freni, G.
    Sambito, Mariacrocetta
    Piazza, Stefania
    ADVANCES IN HYDROINFORMATICS, VOL 2, SIMHYDRO 2023, 2024, : 217 - 228
  • [45] The resource curse revisited and revised: A tale of paradoxes and red herrings
    Brunnschweiler, Christa N.
    Bulte, Erwin H.
    JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT, 2008, 55 (03) : 248 - 264
  • [46] Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities
    Corani, Giorgio
    Zaffalon, Marco
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PART I, PROCEEDINGS, 2008, 5211 : 257 - 271
  • [47] Incorporating model uncertainty in cost-effectiveness analysis:: A Bayesian model averaging approach
    Negrin, Miguel A.
    Vazquez-Polo, Francisco-Jose
    JOURNAL OF HEALTH ECONOMICS, 2008, 27 (05) : 1250 - 1259
  • [48] Accounting for Disease Model Uncertainty in Mapping Heterogeneous Traits - Bayesian Model Averaging Approach
    Biswas, Swati
    Papachristou, Charalampos
    HUMAN HEREDITY, 2010, 69 (04) : 242 - 253
  • [49] A Bayesian approach to model selection and averaging of hydrostatic-season-temperature-time model
    Prakash, G.
    Balomenos, G. P.
    STRUCTURES, 2021, 33 : 4359 - 4370
  • [50] Bayesian model averaging and model search strategies
    Clyde, MA
    BAYESIAN STATISTICS 6, 1999, : 157 - 185