6 resultados para Average velocity

em Repositório digital da Fundação Getúlio Vargas - FGV


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This paper presents an overview of the Brazilian macroeconomy by analyzing the evolution of some specific time series. The presentation is made through a sequence of graphs. Several remarkable historical points and open questions come up in the data. These include, among others, the drop in output growth as of 1980, the clear shift from investments to government current expenditures which started in the beginning of the 80s, the notable way how money, prices and exchange rate correlate in an environment of permanently high inflation, the historical coexistence of high rates of growth and high rates of inflation, as well as the drastic increase of the velocity of circulation of money between the 70s and the mid-90s. It is also shown that, although net external liabilities have increased substantially in current dollars after the Real Plan, its ratio with respect to exports in 2004 is practically the same as the one existing in 1986; and that residents in Brazil, in average, owed two more months of their final income (GNP) to abroad between 1995-2004 than they did between 1990 and 1994. Variance decompositions show that money has been important to explain prices, but not output (GDP).

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

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This paper presents an overview of the Brazilian macroeconomy by analyzing the evolution of some specific time series. The presentation is made through a sequence of graphs. Several remarkable historical points and open questions come up in the data. These include, among others, the drop in output growth as of 1980, the clear shift from investments to government current expenditures which started in the beginning of the 80s, the notable way how money, prices and exchange rate correlate in an environment of permanently high inHation, the historical coexistence of high rates of growth and high rates of inHation, as well as the drastic increase of the velocity of circulation of money between the 70s and the mid-90s. It is also shown that, although net external liabilities have increased substantially in current dollars after the Real Plan, its ratio with respect to exports in 2004 is practically the same as the one existing in 1986; and that residents in Brazil, in average, owed two more months of their final income (GNP) to abroad between 1995-2004 than they did between 1990 and 1994. Variance decompositions show that money has been important to explain prices, but not output (GDP).

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Macro-based summary indicators of effective tax burdens do not capture differences in effective tax rates facing different sub-groups of the population. They also cannot provide information on the level or distribution of the marginal effective tax rates thought to influence household behaviour. I use EUROMOD, an EU-wide tax-benefit microsimulation model, to compute distributions of average and marginal effective tax rates across the household population in fourteen European Union Member States. Using different definitions of ‘net taxes’, the tax base and the unit of analysis I present a range of measures showing the contribution of the tax-benefit system to household incomes, the average effective tax rates applicable to income from labour and marginal effective tax rates faced by working men and women. In a second step, effective tax rates are broken down to separately show the influence of each type of tax-benefit instrument. The results show that measures of effective tax rates vary considerably depending on incomes, labour market situations and family circumstances. Using single averages or macro-based indicators will therefore provide an inappropriate picture of tax burdens faced by large parts of the population.