7 resultados para Models, Economic

em Repositório digital da Fundação Getúlio Vargas - FGV


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Using vector autoregressive (VAR) models and Monte-Carlo simulation methods we investigate the potential gains for forecasting accuracy and estimation uncertainty of two commonly used restrictions arising from economic relationships. The Örst reduces parameter space by imposing long-term restrictions on the behavior of economic variables as discussed by the literature on cointegration, and the second reduces parameter space by imposing short-term restrictions as discussed by the literature on serial-correlation common features (SCCF). Our simulations cover three important issues on model building, estimation, and forecasting. First, we examine the performance of standard and modiÖed information criteria in choosing lag length for cointegrated VARs with SCCF restrictions. Second, we provide a comparison of forecasting accuracy of Ötted VARs when only cointegration restrictions are imposed and when cointegration and SCCF restrictions are jointly imposed. Third, we propose a new estimation algorithm where short- and long-term restrictions interact to estimate the cointegrating and the cofeature spaces respectively. We have three basic results. First, ignoring SCCF restrictions has a high cost in terms of model selection, because standard information criteria chooses too frequently inconsistent models, with too small a lag length. Criteria selecting lag and rank simultaneously have a superior performance in this case. Second, this translates into a superior forecasting performance of the restricted VECM over the VECM, with important improvements in forecasting accuracy ñreaching more than 100% in extreme cases. Third, the new algorithm proposed here fares very well in terms of parameter estimation, even when we consider the estimation of long-term parameters, opening up the discussion of joint estimation of short- and long-term parameters in VAR models.

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This paper develops background considerations to help better framing the results of a CGE exercise. Three main criticisms are usually addressed to CGE efforts. First, they are too aggregate, their conclusions failing to shed light on relevant sectors or issues. Second, they imply huge data requirements. Timeliness is frequently jeopardised by out-dated sources, benchmarks referring to realities gone by. Finally, results are meaningless, as they answer wrong or ill-posed questions. Modelling demands end up by creating a rather artificial context, where the original questions lose content. In spite of a positive outlook on the first two, crucial questions lie in the third point. After elaborating such questions, and trying to answer some, the text argues that CGE models can come closer to reality. If their use is still scarce to give way to a fruitful symbiosis between negotiations and simulation results, they remain the only available technique providing a global, inter-related way of capturing economy-wide effects of several different policies. International organisations can play a major role supporting and encouraging improvements. They are also uniquely positioned to enhance information and data sharing, as well as putting people from various origins together, to share their experiences. A serious and complex homework is however required, to correct, at least, the most dangerous present shortcomings of the technique.

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In this article we study the growth and welfare effects of fiscal and monetary policies in economies where public investment is part of the productive process we present four different models that share the same technology with public infrastructure as a separate argument of the production function. We show that growth is maximized at positive levels of income tax and inflation. However, unless there are no transfers or public goods in the economy, maximization of growth does not imply welfare maximization we show that the optimal tax rate is greater than the rate that maximizes growth and the optimal rate of money creation is below the growth maximizing rate. With public infrastructure in the production function we no longer obtain superneutrality in the Sidrausky model.

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This work presents a fully operational interstate CGE model implemented for the Brazilian economy that tries to quantify both the role of barriers to trade on economic growth and foreign trade performance and how the distribution of the economic activity may change as the country opens up to foreign trade. Among the distinctive features embedded in the model, modeling of external scale economies, port efficiency and land-maritime transport costs provides an innovative way of dealing explicitly with theoretical issues related to integrated regional systems. In order to illustrate the role played by the quality of infrastructure and geography on the country‟s foreign and interregional trade performance, a set of simulations is presented where barriers to trade are significantly reduced. The relative importance of trade policy, port efficiency and land-maritime transport costs for the country trade relations and regional growth is then detailed and quantified, considering both short run as well as long run scenarios. A final set of simulations shed some light on the effects of liberal trade policies on regional inequality, where the manufacturing sector in the state of São Paulo, taken as the core of industrial activity in the country, is subjected to different levels of external economies of scale. Short-run core-periphery effects are then traced out suggesting the prevalence of agglomeration forces over diversion forces could rather exacerbate regional inequality as import barriers are removed up to a certain level. Further removals can reverse this balance in favor of diversion forces, implying de-concentration of economic activity. In the long run, factor mobility allows a better characterization of the balance between agglomeration and diversion forces among regions. Regional dispersion effects are then clearly traced-out, suggesting horizontal liberal trade policies to benefit both the poorest regions in the country as well as the state of São Paulo. This long run dispersion pattern, on one hand seems to unravel the fragility of simple theoretical results from recent New Economic Geography models, once they get confronted with more complex spatially heterogeneous (real) systems. On the other hand, it seems to capture the literature‟s main insight: the possible role of horizontal liberal trade policies as diversion forces leading to a more homogeneous pattern of interregional economic growth.

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The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

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How do the liquidity functions of banks affect investment and growth at different stages of economic development? How do financial fragility and the costs of banking crises evolve with the level of wealth of countries? We analyze these issues using an overlapping generations growth model where agents, who experience idiosyncratic liquidity shocks, can invest in a liquid storage technology or in a partially illiquid Cobb Douglas technology. By pooling liquidity risk, banks play a growth enhancing role in reducing inefficient liquidation of long term projects, but they may face liquidity crises associated with severe output losses. We show that middle income economies may find optimal to be exposed to liquidity crises, while poor and rich economies have more incentives to develop a fully covered banking system. Therefore, middle income economies could experience banking crises in the process of their development and, as they get richer, they eventually converge to a financially safe long run steady state. Finally, the model replicates the empirical fact of higher costs of banking crises for middle income economies.

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Recent models of economic voting assume that citizens can discount exogenous factors when assessing government's economic performance. Yet there is evidence that Latin American voters do not behave in such way, and attribute to presidents outcomes that are beyond their control. This paper presents three survey experiments designed to explore mechanisms that could potentially correct such misattribution, and therefore contribute to debiasing individual behavior towards government evaluation. Our results provide individual-level evidence of the misattribution found in aggregate studies of electorate behavior, and reinforce psychologist's skepticism towards prospects of mental decontamination, as we found very scant evidence that providing information, raising awareness, or increasing motivation to correct biases infuenced individual's evaluation of president's performance.