The debate on fiscal policy in Europe centers on how to let automatic stabilizers work while achieving fiscal consolidation. There is significant agreement on the importance of using fiscal policy as a counter-cyclical instrument, as monetary policy can no longer play this role. In contrast, most of the discussion on fiscal policy in Latin America and the Carribean region (LAC) deals just on solvency issues, largely ignoring the effects of the economic cycle. This is surprising as LAC economies are much more volatile than their European counterparts and have been generally applying pro-cyclical fiscal policies that exacerbate volatility. Some analysts and policymakers appear to think that counter-cyclical fiscal policies are a luxury that only industrial countries can indulge in or, at least, that LAC countries (with the exception of Chile) that have successfully put in place a counter-cyclical fiscal policy need to deal first with pressing adjustment and solvency issues before they attempt to reduce the highly pro-cyclical character of their fiscal policies. The author argues that this is a major mistake because the costs of pro-cyclical fiscal policies in LAC are huge in growth and welfare terms, especially for the poor, and because pro-cyclical policies and rules tend to develop a deficit bias, thus ending up being nonsustainable and noncredible. Perry illustrates both propositions. He then examines the causes of the pro-cyclicality of fiscal policies in LAC and discusses how well-designed fiscal rules may help to deal with the political economy and credibility factors behind pro-cyclicality. He also examines conflicts between flexibility and credibility in rules, showing how a good design can both facilitate the operation of automatic stabilizers while at the same time supporting solvency goals and enhancing credibility. Perry evaluates the experience with different fiscal rules and institutions in LAC to see the extent they have helped or can help to achieve the twin goals of avoiding deficit and pro-cyclical biases.
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