The Forest Resource Conservation and Shortage Relief Act of 1990 was the first federal attempt to impose a blanket restriction on export of roundwood to conserve existing forest cover and generate economic benefits from exporting processed wood. This study estimates the export demand equation for total export from United States Pacific Northwest, major species and destination countries using Johansen multivariate time series analysis. Cointegration rank is identified using Johansen cointegration test incorporating a structural breaks and normalized restriction is imposed to predict demand function under the framework of vector error correction model. All the variables under study are statistically significant with expected signs in the long run demand estimates. Roundwood export restriction policies are found to have impacted the export demand equation negatively. The study helps to understand the impact of log export restrictions policies along with other economic variables and assist in future policy formulations.

Yes / This paper uses panel cointegration with a corresponding vector error correction model (VECM) to investigate the changes in the value relevance of accounting information before and after the mandatory adoption of IFRS in Germany and the UK under three different valuation models. First, a basic Ohlson model, where our results indicate that despite the value relevance of the book values of equity has declined, it has been replaced by the increasing prominence of earnings in both Germany and the UK after the switch to the IFRS. Second, a modified model, which shows that the incremental value relevance of both earnings and book values are considerably higher in the long term for firms in the UK than in Germany. Third, a simultaneous addition of accounting and macroeconomic variables in an extended model, which indicates a significant rise in the relative predictive power of the book value of equity in the UK compared with the more noticeable impact on the value relevance of earnings in Germany. Collectively, the results of these models indicate that: (i) the explanatory power of linear equity valuation models is higher in UK than in the Germany, (ii) a long-run Granger-causal relationship exists between accounting variables and share prices in common law countries like the UK. Nevertheless, the implications of our findings lie in the knowledge that the potential costs of switching to the IFRS is completely nullified within three years by the benefits arising from a reduction in information asymmetry and earning mismanagement among firms which are listed on the stock exchanges of both common law and code law-based EU countries.

This thesis examines the validity of the cost of carry model for pricing FTSE100 futures contracts and the relationship between FTSE100 spot and futures markets during two sub-periods characterised by different market trading systems employed by the LSE and LIFFE. The empirical work is carried out using three approaches to econometric modeling: a basic VECM for spot and futures prices, a VECM extended with a DCCTGARCH framework to account for the conditional variance-covariance structure for spot and futures prices and a threshold VECM to capture regime-dependent spot-futures price dynamics. Overall, both the basic VECM and the DCC-TGARCH analysis suggest that there are deviations from the cost of carry relationship in the first sub-sample when transactions costs in both markets are relatively high but that the cost of carry relationship tends to be valid in the second sub-sample when transactions costs are lower. This is further confirmed by the evidence of higher conditional correlations between the two markets in the second sub-sample as compared with the first, using the DCC-TGARCH analysis. This implies that the no-arbitrage cost of carry relationship between spot and futures markets is more effectively maintained by index arbitrageurs in the second period when market conditions are closer to perfect market assumptions, and hence the cost of carry model could be more reasonably used as a benchmark for pricing stock index futures. The threshold VECM analysis depicts regime-dependent price dynamics between FTSE100 spot and futures markets and leads to some interesting and important findings: arbitrage may not be practicable under some market conditions, either because it is difficult to find counterparties for the arbitrage transactions, or because there is significant risk associated with arbitrage; as a result, the cost of carry model may not always be suitable for pricing stock index futures. Furthermore, the threshold values yielded from estimating the threshold VECM reflect the average transaction costs for most arbitrageurs that are more reliable and fair than subjective estimations.

本文探討匯率不確定性與台灣對中國大陸出口之關係，模型中參考Cushman (1986) 觀點加入第三國變數之效果。研究期間以1997年至2010年之季資料，同時考慮總合資料以及部門別資料，並以GARCH估計實質匯率波動性。第三國則利用出口近似度的計算選擇了前四大競爭國，分別為南韓，日本，馬來西亞及新加坡。此外，部門則以HS二碼分類選擇出口至中國大陸前四大之部門，包括機械與電子、精密儀器、橡膠與塑膠類產品及化學品。 本文檢定變數是否有單根。若有單根則進一步檢定這些變數是否存在共整合關係。在確定存在共整合關係後，利用完全修正最小平方法及誤差修正模型進行估計。本文實證結果顯示：匯率不確定性對出口量有負向之影響關係。就部門而言，本文探討的四個部門之結果也反映匯率不確定性對出口具有負向影響，但是以電子產品及塑膠橡膠類之影響最為顯著。 / This paper investigates the relationship between exchange rate volatility and Taiwan’s exports to Mainland China. In the empirical model, the third country effects suggested by Cushman (1986) are considered. GARCH model is employed to estimate real exchange rate volatility. Both aggregate and sectoral quarterly data covering 1997 to 2010 are used in our sample. The third countries are determined by export similarity. The top 4 countries with the highest degree of export similarity are chosen, including South Korea, Japan, Malaysia and Singapore. In addition, the top 4 Taiwan’s exporting sectors are examined respectively, including machinery and electronic equipment, precision equipment, rubber and plastics, chemicals industries. We first test for unit root of the variables used in the study, and then check the existence of co-integration between the variables with unit root. After confirming the existence of co-integration relationship, we use FMOLS (Fully Modified OLS) and VECM (Vector Error Correction Model) to estimate the coefficients. Our empirical results suggest that there is a significantly negative effect of exchange rate volatility on Taiwan’s total exports. They also indicate that there is a negative relationship between exchange rate volatility and Taiwan’s sectoral exports. Among the top 4 exporting sectors, exchange rate volatility tends to have higher impacts on the machinery and electronic industry as well as chemical industry.

Vektorfehlerkorrekturmodelle (VECM) erlauben es, Abhängigkeiten zwischen den Veränderungen mehrerer potenziell endogener Variablen simultan zu modellieren. Die Idee, ein langfristiges Gleichgewicht gleichzeitig mit kurzfristigen Veränderungen zu modellieren, lässt sich vom Eingleichungsansatz des Fehlerkorrekturmodells (ECM) zu einem Mehrgleichungsansatz für Variablenvektoren (VECM) verallgemeinern. Die Anzahl der kointegrierenden Beziehungen und die Koeffizientenmatrizen werden mit dem Johansen-Verfahren geschätzt. An einer einfachen Verallgemeinerung einer Konsumfunktion wird die Schätzung und Wirkungsweise eines VECM für Verbrauch, Einkommen und Aktienkurse in Deutschland gezeigt. Die Anwendung der Beveridge- Nelson-(BN)-Dekomposition auf vektorautoregressive Prozesse ermöglicht zudem, Abhängigkeiten zwischen den aus den kointegrierten Zeitreihen extrahierten zyklischen Komponenten zu schätzen. / Vector error correction models (VECM) allow to simultaneously model dependencies between the changes of several potentially endogenous variables. The idea is the modelling of a long-run equilibrium together with the short-run dynamics. Therefore a single equation approach (ECM) can be generalised to a multi equation approach (VECM) for variable vectors. The number of cointegration relations and the coefficient matrices are estimated with the Johansen procedure. The estimation of a VECM for income, consumption and stock prices for Germany is demonstrated by using a generalised consumption function. The Beveridge-Nelson-(BN)-Decomposition procedure for vectorautoregressive processes allows extracting cyclical components of cointegrated time series and estimating the degree of co-movement between these transitory components.

In der vorliegenden Arbeit soll der Zusammenhang zwischen Staatsverschuldung und Inflation untersucht werden. Es werden theoretische Übertragungswege von der Staatsverschuldung über die Geldmenge und die langfristigen Zinsen hin zur Inflation gezeigt. Aufbauend auf diesen theoretischen Überlegungen werden die Variablen Staatsverschuldung, Verbraucherpreisindex, Geldmenge M3 und langfristige Zinsen im Rahmen eines Vektor-Fehlerkorrekturmodells untersucht. In der empirischen Analyse werden die Variablen für Deutschland in dem Zeitraum vom 1. Quartal 1991 bis zum 4. Quartal 2010 betrachtet. In ein Vektor-Fehlerkorrekturmodell fließen alle Variablen als potentiell endogen in das Modell ein. Die Ermittlung der Kointegrationsbeziehungen und die Schätzung des Vektor-Fehlerkorrekturmodells erfolgen mithilfe des Johansen-Verfahrens. / In the following study the relation between the public debt and the inflation will be analysed. The transmission from the public debt to the inflation through the money supply and long term interest rate will be shown. Based on these theoretical thoughts the variables public debt, consumer price index, money supply m3 and the long term interest rate will be analysed within a vector error correction model. In the empirical part of this paper we will evaluate the timeperiod from the first quarter in 1991 until the fourth quarter in 2010 for Germany. In a vector error correction model every variable can be taken as endogenous. The variables in the model will be tested for cointegrated relationships and estimated with the Johansen-Approach.

Η παρούσα μελέτη εξετάζει τη δυναμική σχέση μεταξύ των τιμών των ζωοτροφών και παραγωγού, καταναλωτή για τέσσερα είδη κρέατος: μοσχάρι, χοιρινό, αρνί και κοτόπουλο. Η σχετική βιβλιογραφία δείχνει ότι πολλοί παράγοντες επιδρούν στις τιμές των αγροτικών προϊόντων αλλά οι τιμές των ζωοτροφών είναι ο κυριότερος. Αυτό συμβαίνει γιατί οι ζωοτροφές αποτελούν πρώτη ύλη για την παραγωγή κρέατος και κατ΄επέκταση θα επηρέασουν τις τιμές παραγωγού και καταναλωτή. Τα δεδομένα αποτελούνται από 279 μηνιαίες τιμές που εκτείνονται από τον Ιανουάριο 1990 έως τον Ιανουάριο 2013. Χρησιμοποιώντας Johansen cointegration tests, Granger causality tests και impulse response functions τα εμπειρικά αποτελέσματα επιβεβαιώνουν πως οι τιμές των ζωοτροφών, οι τιμές παραγωγού και οι τιμές καταναλωτή δεν είναι ανεξάρτητες μεταξύ τους. / The present paper studies the relationship among feed prices, producer prices and consumer prices of meat: beef, pork, poultry and lamb. The literature indicates that there are many factors which affect agricultural commodity prices but the feed prices are the main. This is why feed has a principal role in the production of meat and will affect producer and consumer prices. The data consists of 279 monthly observations extending from January 1990 to January 2013. Using Johansen cointegration tests, Granger causality tests and impulse response functions, the empirical findings confirm that feed prices, consumer prices and producer prices are interdependent.

The supervising institutions do not give to commercial banks indications what models have to be used for stress testing. This research was done in order to find out which mathematical/statistical models are and can be used in credit risk stress testing. Credit risk is one of the biggest financial risks that every bank faces. Stress testing is a tool of credit risk assessment that helps to estimate the consequences of the events that have really small probability to happen but if they occur, banks can have significant losses. This study determined that the most plausible event is adverse macroeconomic conditions. For this reason, models that include macroeconomic impact were presented. Vector autoregression and vector error correction model were tested using the empirical data received from Swedish central bank, Swedish statistics and Eurostat. For financial stability it is worth using vector autoregression or vector error correction model as they describe the macroeconomic environment in the most suitable way and they are appropriate for shock analysis by showing how the impact of any factor can change the whole system. Structure: introduction, main part (credit risk, methods and empirical analysis), publication, conclusions, references. Thesis consists of: 50 p. text without appendices, 13 pictures, 11 tables, 26 bibliographical entries. Appendices included. / Kredito įstaigų priežiūros institucijos nepateikia komerciniams bankams kokius metodus jie turėtų naudoti testavime nepalankiomis sąlygomis. Tiriamasis darbas buvo atliktas tuo tikslu, kad būtų išsiaiškinta kokie matematiniai ir statistiniai metodai yra ir gali būti naudojami kredito rizikos vertinime testuojant nepalankiomis sąlygomis. Kredito rizika yra viena iš didžiausių finansinių rizikų su kuria bankai susiduria. Testavimas nepalankiomis sąlygomis yra kredito rizikos vertinimo įrankis, padedantis nustatyti įvykių, kurių realizavimosi tikimybės yra mažos, tačiau jiems įvykus, bankai patirtų reikšmingus nuostolius, pasekmes. Šis tyrimas nustatė, jog labiausiai tikėtinas įvykis gali būti ypatingai nepalankios ekonominės sąlygos. Dėl šios priežasties darbe yra pristatyti metodai, kurie įvertina makroekonominių veiksnių įtaką. Vektorinė autoregresija ir vektorinis paklaidų korekcijos modelis buvo patikrinti naudojant Švedijos centrinio banko, Švedijos statistikos departamento ir Eurostat empirinius duomenis. Finansinio stabilumo įvertinimui vertėtų naudoti vektorinį autoregresijos ar vektorinį paklaidų korekcijos modelius, nes šie modeliai geriausiai aprašo ekonominę aplinką bei yra labai tinkami šokų analizei, kadangi įvertina bet kurio veiksnio įtaką visai sistemai. Struktūra: įvadas, pagrindinė dalis (kredito rizika, metodai ir empirinė analizė), publikacija, išvados, literatūros sąrašas. Tiriamasis darbas sudarytas iš: 50 psl. teksto be priedų, 13 paveikslų, 11... [toliau žr. visą tekstą]

本研究以新台幣兌美元之匯率日資料作為主要研究標的，同時加入台灣加權股價指數及金融業隔夜拆借利率之日資料作為股價與利率之代理變數，利用Beveridge-Nelson分解趨勢的方法將變數資料拆解成趨勢項與循環項之時間序列資料，藉此捕捉匯率資料具有景氣循環的特性。在循環項的序列資料，以向量自我迴歸模型來分析並予以估計，趨勢項的部分，利用共整合檢定來探討趨勢項變數間長期的均衡關係，再以向量誤差修正模型予以估計，得到未來30天期之匯率走勢。接著，再以RMSE與MAE指標來衡量不同模型之匯率預測績效，以期能找出最適之匯率預測模型。 實證研究結果發現，將匯率資料先透過Beveridge-Nelson分解趨勢的方法予以拆解後，再利用時間序列模型進行分析及預測，時間序列模型的預測能力都比原始匯率利用時間序列模型進行預測或透過ARIMA模型進行預測還要來的好。因此，根據實證研究的結果，若企業與政府在進行匯率預測的分析時，能夠考慮先將匯率資料透過Beveridge-Nelson分解方法予以處理，便能更有效提升模型的預測能力，除了企業能夠降低避險成本來提高公司整體績效，對於國家而言，有效的掌握匯率的趨勢便能夠迅速且正確的制定政策，提升國家的經濟發展。

Tourism is currently the third largest industry within South Africa. Many African countries, including South Africa, have the potential to achieve increased economic growth and development with the aid of the tourism sector. As tourism is a great earner of foreign exchange and also creates employment opportunities, especially low–skilled employment, it is identified as a sector that can aid developing countries to increase economic growth and development. Accurate forecasting of tourism demand is important due to the perishable nature of tourism products and services. Little research on forecasting tourism demand in South Africa can be found. The aim of this study is to forecast tourism demand (international tourist arrivals) to South Africa by making use of different causal models and to compare the forecasting accuracy of the causal models used. Accurate forecasts of tourism demand may assist policy–makers and business concerns with decisions regarding future investment and employment. An overview of South African tourism trends indicates that although domestic arrivals surpass foreign arrivals in terms of volume, foreign arrivals spend more in South Africa than domestic tourists. It was also established that tourist arrivals from Africa (including the Middle East), form the largest market of international tourist arrivals to South Africa. Africa is, however, not included in the empirical analysis mainly due to data limitations. All the other markets namely Asia, Australasia, Europe, North America, South America and the United Kingdom are included as origin markets for the empirical analysis and this study therefore focuses on intercontinental tourism demand for South Africa. A review of the literature identified several determinants of tourist arrivals, including income, relative prices, transport cost, climate, supply–side factors, health risks, political stability as well as terrorism and crime. Most researchers used tourist arrivals/departures or tourist spending/receipts as dependent variables in empirical tourism demand studies. The first approach used to forecast tourism demand is a single equation approach, more specifically an Autoregressive Distributed Lag Model. This relationship between the explanatory variables and the dependent variable was then used to ex post forecast tourism demand for South Africa from the six markets identified earlier. Secondly, a system of equation approach, more specifically a Vector Autoregressive Model and Vector Error Correction Model were estimated for each of the identified six markets. An impulse response analysis was undertaken to determine the effect of shocks in the explanatory variables on tourism demand using the Vector Error Correction Model. It was established that it takes on average three years for the effect on tourism demand to disappear. A variance decomposition analysis was also done using the Vector Error Correction Model to determine how each variable affects the percentage forecast variance of a certain variable. It was found that income plays an important role in explaining the percentage forecast variance of almost every variable. The Vector Autoregressive Model was used to estimate the short–run relationship between the variables and to ex post forecast tourism demand to South Africa from the six identified markets. The results showed that enhanced marketing can be done in origin markets with a growing GDP in order to attract more arrivals from those areas due to the high elasticity of the real GDP per capita in the long run and its positive impact on tourist arrivals. It is mainly up to the origin countries to increase their income per capita. Focussing on infrastructure development and maintenance could contribute to an increase in future tourist arrivals. It is evident that arrivals from Europe might have a negative relationship with the number of hotel rooms available since tourists from this region might prefer accommodation with a safari atmosphere such as bush lodges. Investment in such accommodation facilities and the marketing of such facilities to Europeans may contribute to an increase in arrivals from Europe. The real exchange rate also plays a role in the price competitiveness of the destination country. Therefore, in order for South Africa to be more price competitive, inflation rate control can be a way to increase price competitiveness rather than to have a fixed exchange rate. Forecasting accuracy was tested by estimating the Mean Absolute Percentage Error, Root Mean Square Error and Theil’s U of each model. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was estimated for each origin market as a benchmark model to determine forecasting accuracy against this univariate time series approach. The results showed that the Seasonal Autoregressive Integrated Moving Average model achieved more accurate predictions whereas the Vector Autoregressive model forecasts were more accurate than the Autoregressive Distributed Lag Model forecasts. Policy–makers can use both the SARIMA and VAR model, which may generate more accurate forecast results in order to provide better policy recommendations. / Thesis (M.Com. (Economics))--North-West University, Potchefstroom Campus, 2011.