O objetivo deste trabalho é apresentar alguns testes de cointegração fracionária para séries integradas de ordem d (dR), i.e., séries I(d), comparando-os com os testes de cointegração, cujo parâmetro d assume valores inteiros. O procedimento para os testes de cointegração fracionária utiliza reamostragens de bootstrap com reposição para gerar séries sob a hipótese nula de não cointegração. Estas reamostragens são então utilizadas para calcular os p-valores de algumas estatísticas de testes de regressão, tais como a estatística de Durbin-Watson e a estimativa do parâmetro de memória longa (d) residual. O poder destes testes é apresentado e comparado com os testes de cointegração, mostrando sua consistência. A aplicação destes testes a dados reais compara o modelo de correção de erros de cointegração com o modelo de correção de erros de cointegração fracionária utilizando a medida de erros quadráticos médios dos modelos ajustados. / The purpose of this project is to present some fractional cointegration tests for integrated time series of order d (dR), i.e., I(d) time series, comparing them to cointegration tests, where the parameter d assumes integer values. The tests procedure is done by using bootstrap samples to obtain series under the null hypothesis of non-cointegration. These samples are then used to estimate the p-value of some regression-based test statistics, such as the Durbin-Watson statistic and estimates of residual d parameter. The application of these tests to real series compares the error correction model of cointegration to the error correction model of fractional cointegration by evaluating the mean squared errors over the residuals from the fitted models.

O setor sucroalcooleiro se torna cada vez mais importante para economia brasileira devido a sua presença estratégica em diversos segmentos da cadeia produtiva nacional. A contribuição que antes ocorria por meio das exportações de açúcar e do álcool anidro, hoje ocorre também através das vendas domésticas de álcool hidratado e da co-geração de energia elétrica. A maior complexidade da agroindústria de cana-de-açúcar veio acompanhada de maiores riscos nas suas operações. O presente trabalho aborda o risco de mercado, o qual está relacionado a variações indesejadas dos preços do açúcar. Os contratos futuros servem de proteção contra tais oscilações, porém, para que esse instrumento sirva de proteção adequada, é preciso que o mercado seja eficiente em assimilar e refletir todas as informações disponíveis no preço. Por esse motivo, o estudo verificou se a hipótese de eficiência dos mercados futuros e à vista do açúcar é válida. A base de dados foi constituída pelas séries de preços do contrato futuro negociado na New York Board of Trade (NYBOT) e dos preços à vista colhidos pelo Centro de Estudos Avançados em Economia Aplicada (CEPEA-ESALQ), todos em bases diárias no período que compreende junho de 1997 até fevereiro de 2008. Os resultados encontrados mostram indícios da eficiência de mercado. / The sugar-ethanol sector turns itself each more relevant to Brazilian economy due its strategic position at the several segments in the national productive chain. A time ago, the contribution of the sector occurred specially for the sugar and alcohol for normal cars foreign trade but today this value receive the contribution of alcohol for flex fuel cars and the generation of energy. Besides the huge complexity of the sugar cane sugar agricultural trade there are the all operational risks involved that can be due the market or due the production. This study broach the subject of market risk, specifically when there is a fluctuation in sugar price and the contracts financial futures work out against these changes. For the mechanism to be a real protection is necessary that the market has the efficiency in to absorb the all existing information about it and to reproduce the effect in the price. For this reason the study aims to analyze about the veracity of the financial futures and spot efficiency hypotheses and the instrument for that investigation was the Engle & Granger cointegration models. The method of Johansen was also used to confirm the robustness of the results found at the first model. The data base was constituted by the financial futures base of the New York Board of Trade (NYBOT) and the spot prices found at Centro de Estudos Avançados em Economia Aplicada (CEPEA-ESALQ), all of them at the daily base. The period used is July, 1997 until February, 2008. The founded results indicate for an existing market efficiency.

[pt] Com este trabalho, objetivou-se quantificar as relações entre a demanda de energia elétrica e alguns de seus determinantes na classe Residencial do Brasil. Inicialmente, é feita uma breve discussão sobre o consumo residencial de energia no País ao longo das quatro últimas décadas, a fim de se conhecer o mesmo dentro de um contexto mais amplo. Posteriormente, adotou-se uma modelagem econométrica objetivando estimar as elasticidades-preço, renda e preço de eletrodomésticos. Após identificar que as séries temporais das variáveis estudadas são não estacionárias, optou-se pela utilização do conceito de Cointegração. Em seguida, foram estimados os Modelos de Correção de Erros Vetoriais (VECM) os quais foram utilizados para projetar o consumo de energia elétrica para o período 2011-2020. Num terceiro momento, entendendo o crescimento populacional e o número de domicílios como fatores importantes na determinação do número de unidades consumidoras residenciais e, consequentemente, na demanda de energia elétrica, foi adotado o método Taxa de Chefia baseado no modelo idade-período-coorte (IPC) objetivando projetar a Taxa de Chefia e o número de domicílios que deverão ser atendidos pelas concessionárias de distribuição durante o período 2011-2020. Por fim, diante das informações obtidas junto às referidas projeções, aplicou-se o método de decomposição do índice de Divisia de média logarítmica I (LMDI I) a fim de explicar a variação da demanda de energia sob a ótica de três variáveis, aqui denominadas Consumo Médio, Taxa de Atendimento e Domicílio. / [en] This work aims to quantify the relations between the electricity demand and some of its determinants in the Residential sector of Brazil. To begin with a short discussion is carried out on the Residential energy consumption in the country throughout the last four decades so as to get to know the residential consumption within a wider context. After, we adopted an econometric modeling aiming to estimate price elasticities, income and price of home appliances. As the series of the variables studied were proved non-stationary, the Cointegration approach was adopted. Vector Error Correction Models (VECM) were estimated and used to project the consumption of electric energy during the 2011-2020 period. The third point concerns, understanding the population growth and the number of households as important factors in determining the number of residential consumer units and, consequently, the demand for electricity, has been adopted the method leadership rate based on age-period-cohort model (APC) aiming to projecting the rate at the leadership rate and the number of homes that should be attended by energy concession during the period 2010-2020. Finally, in face of information obtained from these forcasts, we applied the logarithmic mean Divisia index decomposition method I (LMDI I) in order to explain the variation in energy demand on the optics of the three variables, called Average Consumption, Attendance rate and Household.

This dissertation can be broadly divided into two independent parts. The first three chapters analyse issues related to temporal and contemporaneous aggregation of econometric models. The fourth chapter contains an application of Bayesian techniques to investigate whether the post transition fiscal policy of Poland is sustainable in the long run and consistent with an intertemporal budget constraint. Chapter 1 surveys the econometric methodology of temporal aggregation for a wide range of univariate and multivariate time series models. A unified overview of temporal aggregation techniques for this broad class of processes is presented in the first part of the chapter and the main results are summarized. In each case, assuming to know the underlying process at the disaggregate frequency, the aim is to find the appropriate model for the aggregated data. Additional topics concerning temporal aggregation of ARIMA-GARCH models (see Drost and Nijman, 1993) are discussed and several examples presented. Systematic sampling schemes are also reviewed. Multivariate models, which show interesting features under temporal aggregation (Breitung and Swanson, 2002, Marcellino, 1999, Hafner, 2008), are examined in the second part of the chapter. In particular, the focus is on temporal aggregation of VARMA models and on the related concept of spurious instantaneous causality, which is not a time series property invariant to temporal aggregation. On the other hand, as pointed out by Marcellino (1999), other important time series features as cointegration and presence of unit roots are invariant to temporal aggregation and are not induced by it. Some empirical applications based on macroeconomic and financial data illustrate all the techniques surveyed and the main results. Chapter 2 is an attempt to monitor fiscal variables in the Euro area, building an early warning signal indicator for assessing the development of public finances in the short-run and exploiting the existence of monthly budgetary statistics from France, taken as "example country". The application is conducted focusing on the cash State deficit, looking at components from the revenue and expenditure sides. For each component, monthly ARIMA models are estimated and then temporally aggregated to the annual frequency, as the policy makers are interested in yearly predictions. The short-run forecasting exercises carried out for years 2002, 2003 and 2004 highlight the fact that the one-step-ahead predictions based on the temporally aggregated models generally outperform those delivered by standard monthly ARIMA modeling, as well as the official forecasts made available by the French government, for each of the eleven components and thus for the whole State deficit. More importantly, by the middle of the year, very accurate predictions for the current year are made available. The proposed method could be extremely useful, providing policy makers with a valuable indicator when assessing the development of public finances in the short-run (one year horizon or even less). Chapter 3 deals with the issue of forecasting contemporaneous time series aggregates. The performance of "aggregate" and "disaggregate" predictors in forecasting contemporaneously aggregated vector ARMA (VARMA) processes is compared. An aggregate predictor is built by forecasting directly the aggregate process, as it results from contemporaneous aggregation of the data generating vector process. A disaggregate predictor is a predictor obtained from aggregation of univariate forecasts for the individual components of the data generating vector process. The econometric framework is broadly based on Lütkepohl (1987). The necessary and sufficient condition for the equality of mean squared errors associated with the two competing methods in the bivariate VMA(1) case is provided. It is argued that the condition of equality of predictors as stated in Lütkepohl (1987), although necessary and sufficient for the equality of the predictors, is sufficient (but not necessary) for the equality of mean squared errors. Furthermore, it is shown that the same forecasting accuracy for the two predictors can be achieved using specific assumptions on the parameters of the VMA(1) structure. Finally, an empirical application that involves the problem of forecasting the Italian monetary aggregate M1 on the basis of annual time series ranging from 1948 until 1998, prior to the creation of the European Economic and Monetary Union (EMU), is presented to show the relevance of the topic. In the empirical application, the framework is further generalized to deal with heteroskedastic and cross-correlated innovations. Chapter 4 deals with a cointegration analysis applied to the empirical investigation of fiscal sustainability. The focus is on a particular country: Poland. The choice of Poland is not random. First, the motivation stems from the fact that fiscal sustainability is a central topic for most of the economies of Eastern Europe. Second, this is one of the first countries to start the transition process to a market economy (since 1989), providing a relatively favorable institutional setting within which to study fiscal sustainability (see Green, Holmes and Kowalski, 2001). The emphasis is on the feasibility of a permanent deficit in the long-run, meaning whether a government can continue to operate under its current fiscal policy indefinitely. The empirical analysis to examine debt stabilization is made up by two steps. First, a Bayesian methodology is applied to conduct inference about the cointegrating relationship between budget revenues and (inclusive of interest) expenditures and to select the cointegrating rank. This task is complicated by the conceptual difficulty linked to the choice of the prior distributions for the parameters relevant to the economic problem under study (Villani, 2005). Second, Bayesian inference is applied to the estimation of the normalized cointegrating vector between budget revenues and expenditures. With a single cointegrating equation, some known results concerning the posterior density of the cointegrating vector may be used (see Bauwens, Lubrano and Richard, 1999). The priors used in the paper leads to straightforward posterior calculations which can be easily performed. Moreover, the posterior analysis leads to a careful assessment of the magnitude of the cointegrating vector. Finally, it is shown to what extent the likelihood of the data is important in revising the available prior information, relying on numerical integration techniques based on deterministic methods.

If there is currency substitution, the central bank will lose independence in monetary policy even if the flexible exchange rate system is adopted. In this paper, we investigate the existence of currency substitution between Taiwan and the United States in an open economy during the period of the managed floating exchange rate system, and examine the role of the factor influencing monetary policy and domestic money demand function derived from a small-country portfolio balance approach. To take account of currency substitution, we use quarterly data over 1981-2005 period on the demand for money and include data on the real exchange rate in addition to real income, domestic nominal interest rate and foreign nominal interest rate. The methodology is based on an application of the Johansen and Juselius¡]1990¡^cointegration technique. Also use error correction model to discuss short-run dynamic adjustment processes of these variables. Application of the Augmented Dickey-Fuller test and Phillips-Perron test indeed reveal that all variables are integrated of order one. The result from the Johansen¡¦s maximum likelihood mehtod reveal that there is only one cointegrating vector among the variables. This implies that there is long-run equilibrium relationship among the variables. There is clear evidence that demand for money is affected not only by changes in domestic variables such as real income, domestic nominal interest rate but also by fluctuations in foreign nominal interest rate and real exchange rate. And the coefficiect of the real exchange rate is negative and statistically significant. That means currency substitution is significant factor in the domestic money demand equation and currency substitution indeed exists in Taiwan. This paper successfully provides a consistent result, currency substitution indeed exists in Taiwan. Therefore, to have an effective monetary policy, the monetary authorities should take into account the international factors.

Using seventeen years of data from 1991 to 2008, I derive a pricing model for farmland values. This valuation model is the first using agricultural commodity futures as a proxy for “ex ante” income projections for the crops grown or livestock grazed on United States farmland. While not all inclusive, the model is tested regionally including the Corn Belt, Delta States, Lake States, Mountain, Pacific Northwest, Pacific West and Southeast Regions. Additionally, I test whether interest rate futures contracts have a relationship with farmland values as interest rates have been proven to be a reliable predictor in past research. Farmland capitalization rates and anticipated inflation have hypothesized relationships, but are mainly used as control variables in the study. In general, agricultural commodity futures contracts are a poor predictor of changes in farmland market values. When examining relationships with quarterly percentage change regression models of the included variables, I find the Mountain region provides the most reliable pricing model where both live cattle and Minnesota wheat futures contracts has a positive statistically significant relationships with farmland market values. Also, wheat futures prices have a significant relationship with farmland values in the Corn Belt region. Interest rate futures contracts, farmland capitalization rates and anticipated inflation are not statistically significant in the majority of the regions. As a robustness check, I model the price levels of the variables using Johansen’s cointegration procedure. This time-series econometric methodology provides results in regards to long-run equilibrium relationships between the variables. The results are only slightly better. Corn, orange juice and sugar futures contracts have positive statistically significant relationships with farmland market values in multiple regions. Again, wheat has a statistically significant positive relationship with farmland values in the Corn Belt region. The Mountain region and interest rate futures contracts are not applicable for the cointegration tests as they are not integrated to the order of one.

This study investigates the causal relationship among comparative advantage, exports and economic growth by using the time series annual data for the period of 1980-2009 on 13 developing countries. The purpose is to develop an understanding of causal relationship and explore the differences or similarities among different sectors of several developing countries that are in different stages of development and how their comparative advantage influences the exports, which further effect the economic growth of the country. The co-integration and the vector error correction techniques are used to explore the causal relationship among the three variables. The results suggest bi-directional or mutual long run relationship between comparative advantage, exports and economic growth in most of the developing countries. The overall long run results of the study favour the export led growth hypothesis that exports precede the growth in case of all countries except for Malaysia, Pakistan and Sri Lanka. The short run mutual relationship exists mostly among the three variables except for Malaysian exports and growth and its comparative advantage and GDP and for Singapore‟s exports and growth. The short run causality runs from exports to gross domestic product (GDP). So overall, short run results favour export led growth in all cases except for Malaysia, Nepal and Sri Lanka.

This paper empirically investigates the exchange rate effects of Swedish krona against euro (SEK/Euro) on stock prices in Sweden. The sample period for the study has been taken from March, 2001 to March, 2011 using monthly nominal exchange rate of SEK/Euro and monthly closing values of OMX Stockholm All Share (OMXPI) Index. The developed unit root test and cointegration technique have been applied for the research. It was found that both data series were nonstationary and integrated of order 1. The test result also showed there was no cointegrating relationship between stock prices and exchange rates. Further investigation into their contemporaneous relationship highlighted a statistically significant negative linear relationship between the said variables, suggesting that an appreciation of the Swedish krona against euro leads to a contemporaneous increase in the value of the Swedish stock market.

No description available.

Purchasing power parity (PPP) is considered as an important theory of explaining how exchange rate varies in the long run. Most of empirical studies in the past adapted linear cointegration method to test the purchasing power parity. However, there are papers point out that exchange rate exists non-linear cointegration and unexplainable bias might exist in testing the purchase power parity theory while using linear cointegration test. The methodology of this study is based on an application of ESTR ECM proposed by Kapetaniosetet al. to enhance the inadequate of linear cointegration test. We analyze the dynamic adjusting behavior of short-term nominal exchange rate with ESTR ECM model while the non-linear cointegratoin exists. The empirical result indicates that the purchase power parity between Taiwan and its major trading countries is confirmed. Among the trading countries, American, Japan and Hong Kong are suitable for using linear error correction model and non-linear error correction model for Singapore and Korea.