Testing the long-run implications of the expectation hypothesis using cointegration techniques with structural change

This paper investigates whether or not multivariate cointegrated process with structural change can describe the Brazilian term structure of interest rate data from 1995 to 2006. In this work the break point and the number of cointegrated vector are assumed to be known. The estimated model has four regimes. Only three of them are statistically different. The first starts at the beginning of the sample and goes until September of 1997. The second starts at October of 1997 until December of 1998. The third starts at January of 1999 and goes until the end of the sample. It is used monthly data. Models that allows for some similarities across the regimes are also estimated and tested. The models are estimated using the Generalized Reduced-Rank Regressions developed by Hansen (2003). All imposed restrictions can be tested using likelihood ratio test with standard asymptotic 1 qui-squared distribution. The results of the paper show evidence in favor of the long run implications of the expectation hypothesis for Brazil.

On the long run effects of barriers to trade

We study the macroeconomic effects of international trade policy by integrating a Hecksher-Ohlin trade model into an optimal-growth framework. The model predicts that a more open economy will have higher factor productivity. Furthermore, there is a "selective development trap," an additional steady state with low income, to which countries may or may not converge, depending on policy. Income at the development trap falls as trade barriers increase. Hence, cross-country differences in barriers to trade may help explain the dispersion of per-capita income observed across countries. The effects are quantified and we show that protectionism can explain a relevant fraction of TFP and long-run income differentials across countries.

The long-run properties of a dynamic Mirrlees' model with aggregate shocks

Nós abordamos a existência de distribuições estacionárias de promessas de utilidade em um modelo Mirrlees dinâmico quando o governo tem record keeping imperfeito e a economia é sujeita a choques agregados. Quando esses choques são iid, provamos a existência de um estado estacionário não degenerado e caracterizamos parcialmente as alocações estacionárias. Mostramos que a proporção do consumo agregado é invariante ao estado agregado. Quando os choques agregados apresentam persistência, porém, alocações eficientes apresentam dependência da história de choques e, em geral, uma distribuição invariante não existe.

International integration and long- run persistence of the GNP distribution

We use the Ramsey model of g,Towth elaborated by Bliss [1995] and Ventlira [1997] to show how international integration results in long-nm persistellce Df GNPs distribution, while allowing, under certain conditions on parameters, for convergellce during the transition. First, we pi·ovide relationships which explicitly relate, in the neighborhood of the steady-state, the magnitude of conditional convergence or divergence to the fundamentaIs of the economies. Second, we present ali analysis of the Cobb Douglas case with a broad dass of utility functions and show that there is always transitional convergenee with this technology. Third, directions for testing the Illodel against the traditional dosed-ecollomy setting are proposed. These lead to adding specific and world-wide regTessors to traditional growth regressions.

A política monetária recente: alguns aspectos críticos

Este Artigo tem como Objetivo Apresentar uma Análise das Práticas Atuais da Política Monetária, a Política de Regras Monetárias . Discute o Contexto Histórico em que Tais Práticas Apareceram, e suas Implicações, Especialmente de que a Oferta Monetária Passa a ser é Endógena, e não Exógena, como na Visão Monetarista Tradicional. a Nova Doutrina Também Faz a Suposição Extrema de que Embora a Política Monetária Possa ser Efetiva no Curto Prazo, Ela é Neutra no Longo Prazo. esta Hipótese Bem como suas Implicações para a Política Monetária Podem ser Sujeitas a Várias Críticas que Serão Desenvolvidas neste Trabalho.

The long run economic impact of AIDS

This paper studies the long-run impact of HIV/AIDS on per capita income and education. We introduce a channel from HIV/AIDS to long-run income that has been overlooked by the literature, the reduction of the incentives to study due to shorter expected longevity. We work with a continuous time overlapping generations mo deI in which life cycle features of savings and education decision play key roles. The simulations predict that the most affected countries in Sub-Saharan Africa will be in the future, on average, a quarter poorer than they would be without AIDS, due only to the direct (human capital reduction) and indirect (decline in savings and investment) effects of life-expectancy reductions. Schooling will decline on average by half. These findings are well above previous results in the literature and indicate that, as pessimistic as they may be, at least in economic terms the worst could be yet to come.

Information learning and the stability of fiat money

We analyze the stability of monetary regimes in a decentralized economy where fiat money is endogenously created, information about its value is imperfect, and agents only learn from their personal trading experiences. We show that in poorly informed economies, monetary stability depends heavily on the government's commitment to the long run value of money, whereas in economies where agents gather information more easily, monetary stability can be an endogenous outcome. We generate a dynamics on the acceptability of fiat money that resembles historical accounts of the rise and eventual colIapse of overissued paper money. Moreover, our results provide an explanation of the fact that, despite its obvious advantages, the widespread use of fiat money is a very recent development.

The long-run economic impact of AIDS

This paper studies the long-run impact of HIV / AIDS on per capita income and education. We introduce a channel from HIV / AIDS to long-run income that has been overlooked by the literature, the reduction of the incentives to study due to shorter expected longevity. We work with a continuous time overlapping generations mo deI in which life cycle features of savings and education decision play key roles. The simulations predict that the most affected countries in Sub-Saharan Africa will be in the future, on average, a quarter poorer than they would be without AIDS, due only to the direct (human capital reduction) and indirect (decline in savings and investment) effects of life-expectancy reductions. Schooling will decline on average by half. These findings are well above previous results in the literature and indicate that, as pessimistic as they may be, at least in economic terms the worst could be yet to come.

Infrastructure and productivity in Latin America: is there a relationship in the long run?

This article analyses the relationship between infrastructure and total factor productivity (TFP) in the four major Latin American economies: Argentina, Brazil, Chile and Mexico. We hypothesise that an increase in infrastructure has an indirect effect on long-term economic growth by raising productivity. To assess this theory, we use the traditional Johansen methodology for testing the cointegration between TFP and physical measures of infrastructure stock, such as energy, roads, and telephones. We then apply the Lütkepohl, Saikkonen and Trenkler Test, which considers a possible level shift in the series and has better small sample properties, to the same data set and compare the two tests. The results do not support a robust long-term relationship between the series; we do not find strong evidence that cuts in infrastructure investment in some Latin American countries were the main reason for the fall in TFP during the 1970s and 1980s.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian inflation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in different measures of forecasting accuracy are substantial, especially for short horizons.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian in ation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in di¤erent measures of forecasting accuracy are substantial, especially for short horizons.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.

Forecasting multivariate time series under present-value-model short- and long-run co-movement restrictions

It is well known that cointegration between the level of two variables (e.g. prices and dividends) is a necessary condition to assess the empirical validity of a present-value model (PVM) linking them. The work on cointegration,namelyon long-run co-movements, has been so prevalent that it is often over-looked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. This amounts to investigate whether short-run co-movememts steming from common cyclical feature restrictions are also present in such a system. In this paper we test for the presence of such co-movement on long- and short-term interest rates and on price and dividend for the U.S. economy. We focuss on the potential improvement in forecasting accuracies when imposing those two types of restrictions coming from economic theory.

Forecasting Multivariate Time Series under Present-Value-Model Short- and Long-run Co-movement Restrictions

This paper has two original contributions. First, we show that the present value model (PVM hereafter), which has a wide application in macroeconomics and fi nance, entails common cyclical feature restrictions in the dynamics of the vector error-correction representation (Vahid and Engle, 1993); something that has been already investigated in that VECM context by Johansen and Swensen (1999, 2011) but has not been discussed before with this new emphasis. We also provide the present value reduced rank constraints to be tested within the log-linear model. Our second contribution relates to forecasting time series that are subject to those long and short-run reduced rank restrictions. The reason why appropriate common cyclical feature restrictions might improve forecasting is because it finds natural exclusion restrictions preventing the estimation of useless parameters, which would otherwise contribute to the increase of forecast variance with no expected reduction in bias. We applied the techniques discussed in this paper to data known to be subject to present value restrictions, i.e. the online series maintained and up-dated by Shiller. We focus on three different data sets. The fi rst includes the levels of interest rates with long and short maturities, the second includes the level of real price and dividend for the S&P composite index, and the third includes the logarithmic transformation of prices and dividends. Our exhaustive investigation of several different multivariate models reveals that better forecasts can be achieved when restrictions are applied to them. Moreover, imposing short-run restrictions produce forecast winners 70% of the time for target variables of PVMs and 63.33% of the time when all variables in the system are considered.