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The of this paper is to analyze the effects of corruption on economic growth, human development and natural resources in Latin American and Nordic countries. Design/methodology/approach Using the hierarchical prior of Gelman et al. (2003), a Bayesian panel Vector AutoRegression (VAR) model is estimated. In addition, two alternative approaches are considered, namely, a panel error correction VAR model and an asymmetric panel VAR model. Findings The results reveal some relevant contrasts: (1) in Latin America there is support for the sand the wheels hypothesis in Bolivia and Chile, support for the grease the wheels hypothesis in Colombia and no significant impact of corruption on growth in Brazil and Peru, while in Nordic countries the response of growth to shocks in corruption is negative in all cases; (2) corruption negatively affects human development in all countries from both regions; (3) corruption tends to spur natural resources sector in Latin American countries, while it is detrimental for natural resources sector in Nordic countries. Research limitations/implications The panel VAR approach uses recursive scheme identification. The authors have analyzed robustness using alternative ordering of the variables. The authors also have followed two alternatives suggested by the Referee: a panel error correction VAR model and a panel asymmetric VAR model. However, another more sophisticated identification scheme could be used. Also other variables could be introduced in the VAR model. Practical implications Regardless of the issue of the “grease” vs the “sand the wheels” debate, corruption should be reduced because it is anyway harmful for human development. The differences in the results for Latin American and Nordic countries show that the effects of corruption have to be assessed considering the different institutional and economic conditions of the countries analyzed. Social implications Governments should seek to reduce corruption because, despite corruption can have mixed effects on economic growth in some contexts, it is anyway harmful for human development. Besides, the finding that in some Latin American countries more activity in the extractive industries is generated by means of corruption confirm the association between corruption and extractivism found by Gudynas (2017) and can explain why there are issues of environmental damage and social conflict linked to natural resources in those countries. Originality/value The present study contributes to the literature by presenting evidence on the effects of corruption on growth, human development and natural resources sector in Latin American and Nordic countries. It is the first study on economics of corruption which directly compares Latin American and Nordic countries. This is relevant because there are important differences between both regions since Latin American countries tend to suffer from widespread corruption, while the Nordic ones have a high level of transparency. It is also the first in using a Bayesian panel VAR approach in order to evaluate the effects of corruption.

This paper studies the evolution of the effects of fluctuations in mineral commodity prices on fiscal variables, especially those associated with fiscal revenues, in Peru by means of VAR models with time-varying parameters and stochastic volatility (TVP-VAR-SV). We compare different alternative specifications using the marginal likelihood and the deviance information criterion, which show that it is essential to consider stochastic volatility. It is found that an increase of 1% in the growth of mineral commodity prices generates increases of around 1.5 and 2.5% in the growth of taxes from mining and mining canon, respectively, thus reflecting a remarkable sensitivity of these variables to external shocks. In turn, these responses are increasingly more pronounced until reaching a peak around 2009 and then decrease, which is in line with the dynamics of the commodities boom. In the variance decomposition, the importance of shocks in mineral commodity prices in explaining fluctuations in taxes from mining and mining canon increases in line with the increasing tendency of mineral prices until the Great Recession, where shocks in mineral commodity prices explain between 40 and 50% of fluctuations in taxes from mining and mining canon, and then it is reduced. This shows the importance of allowing time-varying parameters and stochastic volatility in contrast with a standard VAR.

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