In the early years of human society, all natural resources such as agriculture, animals, forestry, and fisheries were considered to be public property and the treasure belonged to all people. One branch of these natural resources threatened by over-development is straddling and highly migratory fish species, like tuna, which cannot be protected by a single government. While discussing fishery management, we review the change in tuna catches of thirteen countries in Western and Central Pacific Fisheries Commission (WCPFC), as it represents the impacts from different policies and events during a specific period of time. We reference the method applied in economics science by testing for the existence of stochastic convergence and addressing these break points, which are the important targets due to external shocks or internal influence. The characteristic of the method is in testing both time series and panel data by following the traditional unit root tests methods and unit root tests while considering structural breaks. We are able to conclude in preliminary estimates that some serious historical fishery events happened at the break point time, and if we take these structural breaks into consideration, then the growth of tuna catches will be stationary. In other words, if shocks to relative tuna catches are temporary, then the series stochastically converges, meaning that the manager does not need to intervene in the development of tuna fishery, because temporary shocks do not affect the stationarity of tuna catches¡¦ levels. Once the structural breaks occurred in the past, it is not necessary for these government and international organizations to change fishery policies in order to respond to the breaks. They should realize the meaning of the stationary panel instead of enacting an over-intervening policy based on temporary shocks.

Considering the impact of transaction costs on trade volumes and prices in Europe, in our thesis, we carried out an overview of the costs of crossing borders and an assessment of the degree of fragmentation of the product market in this world area. Throughout the analysis, we paid attention to the country and/ or industry dimension and at how country- and sector-specific patterns affect the European product market integration process. A special attention is also devoted to the model specifications and estimation techniques. Having discussed extensively the foundations of the gravity equation and the properties of the gravity model with the aim of empirical works in the first chapter of our dissertation, chapter two provides a first assessment of the extent of the integration in Europe by measuring the trade intensity via an augmented gravity equation. The study measures the impact of regional trade agreements (RTAs) on Members’ trade in the European zone and highlights that despite the ongoing enlargement process of its free trade area, the European zone displays rather weak RTAs impacts - in comparison with what one could expect -. The chapter also highlights a number of caveats and difficulties when one wants to accurately measure the extent of trade creation brought about the RTAs in Europe. In particular, the existence of zero observations (non observed commodity flows) between country pairs might have important drawbacks in the estimations. Since disaggregated trade data can be very insightful, chapter three implements such an analysis. Using a gravity-like equation as well, it provides a border effect estimations carried out in a multi-country and multi-sector context. Our findings reveal that remaining technical barriers to trade, market structure and degree of product differentiation play an important role in the explanation of border effects. Furthermore, our results succeed to derive a strongly negative impact of nominal exchange rate volatility on trade, whereas traditional gravity specifications fail to identify this clearly – when regional dummies are introduced-. Hence, chapter two and three provide an overview, via the trade channel, of the degree of integration of the product market in Europe: While European agreements (EAs) in terms of trade are effective, bilateral trade relationships face steady impediments. As expected, intra-EAs trade increases and exports from Member States to non Member States decline. The trade obstacles have many sources. In particular, volatility of the nominal exchange rate is found to have trade-reducing effects. Our results also underscore the interest of using sector disaggregated date since we find that the degree of product differentiation and the market structure enter in the explanation of border effects. Moreover, the various approaches to harmonize the remaining technical barriers to trade on sector desegregation basis were found to act in reducing on the European Union border effect. As for chapter four, it re-visits the issue of price convergence within the EMU. Specifically, we test whether the Law of One Price (LOOP) can be validated over the period 1984-2004. Our results fail to support the LOOP for a large majority of sectors and countries under examination. Furthermore, our findings reveal half-lives of deviation from the LOOP suggesting a price adjustment which is globally less slow that commonly estimated in the literature. Indeed, the EMU is anticipated to affect the behaviour of trading firms that should result in a faster cross-border transmission of price movements across Member States. When attempting to explain the factors at work in the LOOP failure, we highlight that beside the European convergence process, the arbitrage channel explain a non negligible part of the country mean reversion in terms of relative prices. Nevertheless, mixed evidence is found for the impact of cross- country and cross-sector variables.

This thesis, which consists of four chapters, focuses on three topics: discriminating between stationary and nonstationary time series, testing the constancy of the error covariance matrix of a vector model, and estimating density functions over bounded domains using kernel techniques. In Chapter 1, “Testing the unit root hypothesis against the logistic smooth transition autoregressive model”, and Chapter 2, “A nonlinear alternative to the unit root hypothesis”, the joint hypothesis of unit root and linearity allows one to distinguish between random walk processes, with or without drift, and stationary nonlinear processes of the smooth transition autoregressive type. This is important in applications because steps taken in modelling a time series are likely to be drastically different depending on whether or not the unit root hypothesis is rejected. In Chapter 1 the nonlinearity is based on the logistic function, while Chapter 2 considers the second-order logistic function. Monte Carlo simulations show that the proposed tests have about the same or higher power than the standard Dickey-Fuller unit root tests when the alternative exhibits nonlinear behavior. In Chapter 1 the tests are applied to the seasonally adjusted U.S. monthly unemployment rate, giving support to the hypothesis that the unemployment rate series follows a smooth transition autoregressive model rather than a random walk. Chapter 2 considers testing the so called purchasing power parity (PPP) hypothesis. The test results complement earlier studies, giving support to the PPP hypothesis for 44 out of 120 real exchange rates considered. Chapter 3. “Testing the constancy of the error covariance matrix in vector models”Estimating the parameters of an econometric model is necessary for any use of the model, be it forecasting or policy evaluation. Finding out thereafter whether or not the model appears to satisfy the assumptions under which it was estimated should be an integral part of a normal modelling exercise. This chapter includes the derivation of a Lagrange Multiplier test of the null hypothesis of constant variance in vector models when testing against three specific parametric alternatives. The Monte Carlo simulations show that the test has good size properties, very good power against a correctly specified alternative, but low or only up to moderate power in cases for a misspecified alternative hypothesis. Chapter 4. “ Estimating confidence regions over bounded domains”Nonparametric density estimation by kernel techniques is a standard statistical tool in the estimation of a density function in situations where its parametric form is assumed to be unknown. In many cases, the data set over which the density is to be estimated exhibits linear, or nonlinear, dependence. A solution to this problem is to apply a one-to-one transformation to the considered data set in such a way that the dependence in the data vanishes, but too often such a unique transformation does not exist. This chapter proposes a method for estimating confidence regions over bounded domains when no one-to-one transformation of the considered data exists, or if the existence of such a transformation is difficult to verify. The method, simple kernel estimation over a nonlinear grid, is illustrated by applying it to three data sets generated from the GARCH(1,1) model. The resulting confidence regions cover a reasonable area of the definition space, and are well aligned with the corresponding data sets. / Diss. Stockholm : Handelshögsk., 2003

Dividend Valuation Model is a well-known stock pricing model. However, many empirical studies of foreign stock markets do not support the Dividend Valuation Model; most of these studies think stock price is too volatile to explain by expected dividend. Therefore, this article would like to use Stochastic Cointegration to reexamining Taiwan stock market, and observe whether Taiwan stock market supports Dividend Valuation Model. The empirical results showed that stock price and dividends exist a positive comovements relationship in the plastic, steel, electronic, and the banking & insurance industries, but empirical results does not completely support the theoretical value of cointegration vector. Therefore, this study has not been sufficient evidence to support Taiwan stock market is efficient.

No description available.

No description available.

No description available.

In an effort to assess the predictive ability of exchange rate models when data on African countries is sampled, this paper studies nonlinear modelling and prediction of the nominal exchange rate series of the United States dollar to currencies of thirty-eight African states using the smooth transition autoregressive (STAR) model. A three step analysis is undertaken. One, it investigates nonlinearity in all nominal exchange rate series examined using a chain of credible statistical in-sample tests. Significantly, evidence of nonlinear exponential STAR (ESTAR) dynamics is detected across all series. Two, linear models are provided another chance to make it right by shuffling to data on African countries to investigate their predictive power against the tough random walk without drift model. Linear models again failed significantly. Lastly, the predictive ability of nonlinear models against both the random walk without drift and the corresponding linear models is investigated. Nonlinear models display useful forecasting gains over all contending models.

This work concerns the creation of automatized procedure of ARIMA and SARIMA class model choice according to Box-Jenkins methodology and in this connection, also deals with force testing of unit roots and analysis of applying of informatics criteria when choosing a model. The goal of this work is to create an application in the environment R that can automatically choose a model of time array generating process. The procedure is verified by a simulation study. In this work an effect of values of generating ARMA (1,1) model processes parameters is examined, for his choice and power of KPSS test, augmented Dickey-Fuller and Phillips-Peron test of unit roots.

本研究根據Phillips, Wu and Yu (2011)以及後續相關文獻所提出的檢測泡沫模型對台灣市場以及NASDAQ指數進行實證研究。本文使用的模型分別為PWY模型、PSY模型、Rolling Window ADF，以及我們參考PSY模型與Rolling Window ADF所建構出的Rolling Window BSADF。我們利用上述四種模型對NASDAQ指數進行泡沫檢測，以及在台灣上市公司股票中建構投資泡沫投資組合與不投資泡沫投資組合。實證結果顯示投資泡沫投資組合績效優於不投資泡沫投資組合，此結果與Guenster et al. (2009)相同，同時本研究所建構的Rolling Window BSADF在投資績效上優於另外三種模型；此外對NASDAQ指數的檢測發現Rolling Window BSADF 具有檢定結果獨立於起始點的選取與不受週期性泡沫破裂影響等優點，故綜合以上實證結果，Rolling Window BSADF 對於泡沫的檢測與建構泡沫投資組合的績效明顯優於另外三種模型。 / This paper used the bubble examination model according to Phillips, Wu and Yu (2011) and following papers to conduct empirical research on Taiwan market and NASDAQ index. The models used in this paper are PWY model, PSY model, Rolling Window ADF and Rolling Window BSADF that referred to the PSY model and the Rolling Window ADF. We tested NASDAQ index through the above models to test the bubbles, and constructed the portfolio of investing bubbles against not investing. The result shows that the portfolio of investing bubbles performs better than not investing bubbles, which is the same as the result of Guenster et al. (2009). In addition, the Rolling Window BSADF constructed by this paper are superior to the other three models on the performance of investment. Moreover, the examination of NASDAQ index finds that there are some advantages of Rolling Window BSADF including that the test result is independent of the selection of the initial point and not affected by the broken of cyclical bubbles and so on. To sum up, this paper concludes that the bubble examination and the construction of bubble investing portfolio of the Rolling Window BSADF are significantly better than the other three models.