Diss. Stockholm : Handelshögsk., 2004.

Keynes (1936) first brought up the relationship between consumption and national income, but Kuznets¡¦observation about the U.S. data was not supported by the Keynes consumption function form. So there are many macroeconomic theories trying to explain the phenomenon observed by Kuznets. This paper uses the way developed by Campbell (1987) to test the permanent income hypothesis suggested by Friedman with Taiwan data. In addition, this paper uses the stochastic cointegration developed by Harris, McCabe, and Leybourne (2002) to re-examine the relationship between consum-ption and national income because the traditional non-stochastic cointegration assumes that the error term is linear and homogeneous, which may be too strong to fit the real world. Besides, this paper compares the nonstochastic cointegration with the stochastic cointegration, and the evidence founded is that the permanent income hypothesis is not supported by Taiwan data with these two methods.

The law of one price (LOP) plays an important role as a building block in theories of international trade and exchange rate determination. It also serves as a measure of integration for international commodity markets. The LOP states that in competitive markets after adjustment for transportation costs and trade barriers, identical commodities sold in different countries should sell for the same price when their prices are defined in a common currency. The existing economic literature provides a vast body of theoretical and empirical investigations of the validity of the LOP. In general, previous evidence is mixed and there is no unanimous LOP support or refutation. The effects of exchange rate changes on agricultural outputs have been extensively studied, but the issue of the impacts on traded non-farm produced inputs has not been explored as much. This study investigates the impact of the exchange rate ($CN/$US) on the relative prices in U.S. and Canadian agricultural markets for five major farm outputs and four non-farm produced inputs, which are traded between these two closely integrated economies. Adherence to the LOP is evaluated by examining the pass-through effects of exchange rate changes on these prices using quarterly data. The sample covers the period of 1975 - 1999, when there were substantial exchange rate movements. Regression and cointegration techniques are utilized to estimate whether and at what rate exchange rate changes are transmitted to prices. The empirical results give rise to supportive evidence in favor of the LOP for the five farm outputs. The evidence is somewhat weaker for three of the four non-farm produced inputs, and the LOP is violated for one input. / Master of Science

In the last few decades, vector autoregressive (VAR) models have gained tremendous popularity as an all-purpose tool in econometrics and other disciplines. Some of their most prominent uses are for forecasting, causality tests, tests of economic theories, hypothesis-seeking, data characterisation, innovation accounting, policy analysis, and cointegration analysis. Their popularity appears to be attributable to their flexibility relative to other models rather than to their virtues per se. In addition, analysts often use VAR models as benchmark models. VAR modeling has not gone uncriticised, though. A list of relevant arguments against VAR modelling can be found in Section 2.3 of this thesis. There is one additional problem which is rarely mentioned though, namely the often heavily biased estimates in VAR models. Although methods to reduce this bias have been available for quite some time, it has probably not been done before, at least not in any systematic way. The present thesis attempts to systematically examine the performance of bias-reduced VAR estimates, using two existing and one newly derived approximation to the bias. The thesis is orginanised as follows. After a short introductory chapter, a brief history of VAR modelling can be found in Chapter 2 together with a review of different representations and a compilation of criticisms against VAR models. Chapter 3 reports the results of very extensive Monte Carlo experiments serving dual purposes: Firstly, the simulations will reveal whether or not bias really poses a serious problem, because if it turns out that biases appear only by exception or are mainly insignificant, there would be little need to reduce the bias. Secondly, the same data as in Chapter 3 will be used in Chapter 4 to evaluate the bias approximations, allowing for direct comparison between bias-reduced and original estimates. Though Monte Carlo methods have been (rightfully) criticised for being too specific to allow for any generalisation, there seems to be no good alternative to analyse small-sample properties of complicated estimators such as these. Chapter 4 is in a sense the core of the thesis, containing evaluations of three bias approximations. The performance of the bias approximations is evaluated chiefly using single regression equations and 3D surfaces. The only truly new research result in this thesis can also be found in Chapter 4; a second-order approximation to the bias of the parameter matrix in a VAR(p) model. Its performance is compared with the performance of two existing first-order approximations, and all three are used to construct bias-reduced estimators, which are then evaluated. Chapter 5 holds an application of US money supply and inflation in order to find out whether the results in Chapter 4 can have any real impacts. Unfortunately though, bias reduction appears not to make any difference in this particular case. Chapter 6 concludes. / Diss. Stockholm : Handelshögsk.

Includes abstract. Includes bibliographical references.

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Yes / We examine whether the inflation rates of the countries that pursueinflation targeting policies have converged as opposed to the expe-rience of the OECD non-inflation targeters. Using a methodologyintroduced by Pesaran (2007a), we examine the stationarity prop-erties of the inflation differentials. This approach has the advantageof avoiding setting arbitrarily a specific country as the benchmarkeconomy. Our results indicate that the inflation rates converge irre-spective of the monetary policy framework.

This paper examines the long-run relationship between exchange rates and prices in ten countries in Southwest Asia, Africa, and the Pacific Rim for the post-Bretton Woods period. It uses cointegration tests to investigate the thesis that relative purchasing power parity exists as a long-run equilibrium condition between country-pairs. It expands upon tests for relative purchasing power parity suggested by previous authors by pretesting price index time series for structural breaks, in addition to pretesting the price indices and exchange rates for compatible stochastic properties. It compares the results of conventional cointegration tests for parity with a weaker form of the relationship suggested by Pippenger (1993) and Patel (1990), and finally, examines purchasing power parity by testing real bilateral exchange rates for stationarity. / Master of Arts

This thesis consists of four papers and the main theme present is dependence, through time as in serial correlation, and across individuals, as in random effects. The individual papers may be grouped in many different ways. As is, the first two are concerned with autoregressive dynamics in a single time series and then a panel context, while the subject of the final two papers is parametric covariance modeling. Though set in a panel context the results in the latter are generally applicable. The approach taken is Bayesian. This choice is prompted by the coherent framework that the Bayesian principle offers for quantifying uncertainty and subsequently making inference in the presence of it. Recent advances in numerical methods have also made the Bayesian choice simpler. In the first paper an existing model to conduct inference directly on the roots of the autoregressive polynomial is extended to include seasonal components and to allow for a polynomial trend of arbitrary degree. The resulting highly flexible model robustifies against misspecification by implicitly averaging over different lag lengths, number of unit roots and specifications for the deterministic trend. An application to the Swedish real GDP illustrates the rich set of information about the dynamics of a time series that can be extracted using this modeling framework. The second paper offers an extension to a panel of time series. Limiting the scope, but at the same time simplifying matters considerably, the mean model is dropped restricting the applicability to non-trending panels. The main motivation of the extension is the construction of a flexible panel unit root test. The proposed approach circumvents the classical confusing problem of stating a relevant null hypothesis. It offers the possibility of more distinct inference with respect to unit root composition in the collection of time series. It also addresses the two important issues of model uncertainty and cross-section correlation. The model is illustrated using a panel of real exchange rates to investigate the purchasing power parity hypothesis. Many interesting panel models imply a structure on the covariance matrix in terms of a small number of parameters. In the third paper, exploiting this structure it is demonstrated how common panel data models lend themselves to direct sampling of the variance parameters. Not necessarily always practical, the implementation can be described by a simple and generally applicable template. For the method to be practical, simple to program and quick to execute, it is essential that the inverse of the covariance matrix can be written as a reasonably simple function of the parameters of interest. Also preferable but in no way necessary is the availability of a computationally convenient expression for the determinant of the covariance matrix as well as a bounded support for the parameters. Using the template, the computations involved in direct sampling and effect selection are illustrated in the context of a one- and two-way random effects model respectively. Having established direct sampling as a viable alternative in the previous paper, the generic template is applied to panel models with serial correlation in the fourth paper. In the case of pure serial correlation, with no random effects present, applying the template and using a Jeffreys type prior leads to very simple computations. In the very general setting of a mixed effects model with autocorrelated errors direct sampling of all variance parameters does not appear to be possible or at least not obviously practical. One important special case is identified in the model with the random individual effects model with autocorrelation. / <p>Diss. Stockholm : Handelshögskolan i Stockholm, 2004 viii s., s. 1-9: sammanfattning, s. 10-116: 4 uppsatser</p>

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