The thesis contains the four chapters: Testing parameter constancy in unit root autoregressive models against continuous change; Dickey-Fuller type of tests against nonlinear dynamic models; Inference for unit roots in a panel smooth transition autoregressive model where the time dimension is fixed; Testing unit roots in nonlinear dynamic heterogeneous panels. In Chapter  1 we derive tests for parameter constancy when the data generating process is non-stationary against the hypothesis that the parameters of the model change smoothly over time. To obtain the asymptotic distributions of the tests we generalize many theoretical results, as well as new are introduced, in the area of unit roots . The results are derived under the assumption that the error term is a strong mixing. Small sample properties of the tests are investigated, and in particular, the power performances are satisfactory. In Chapter 2 we introduce several test statistics of testing the null hypotheses of a random walk (with or without drift) against models that accommodate a smooth nonlinear shift in the level, the dynamic structure, and the trend. We derive analytical limiting distributions for all tests. Finite sample properties are examined. The performance of the tests is compared to that of the classical unit root tests by Dickey-Fuller and Phillips and Perron, and is found to be superior in terms of power. In Chapter 3 we derive a unit root test against a Panel Logistic Smooth Transition Autoregressive (PLSTAR). The analysis is concentrated on the case where the time dimension is fixed and the cross section dimension tends to infinity. Under the null hypothesis of a unit root, we show that the LSDV estimator of the autoregressive parameter in the linear component of the model is inconsistent due to the inclusion of fixed effects. The test statistic, adjusted for the inconsistency, has an asymptotic normal distribution whose first two moments are calculated analytically. To complete the analysis, finite sample properties of the test are examined. We highlight scenarios under which the traditional panel unit root tests by Harris and Tzavalis have inferior or reasonable power compared to our test. In Chapter 4 we present a unit root test against a non-linear dynamic heterogeneous panel with each country modelled as an LSTAR model. All parameters are viewed as country specific. We allow for serially correlated residuals over time and heterogeneous variance among countries. The test is derived under three special cases: (i) the number of countries and observations over time are fixed, (ii) observations over time are fixed and the number of countries tend to infinity, and (iii) first letting the number of observations over time tend to infinity and thereafter the number of countries. Small sample properties of the test  show modest size distortions and satisfactory power being superior to the Im, Pesaran and Shin t-type of test. We also show clear improvements in power compared to a univariate unit root test allowing for non-linearities under the alternative hypothesis. / Diss. Stockholm : Handelshögskolan, 2004

The purpose of this study is to research the volume-price relationship and information transmission among Taiwan Stock Index, Electronic Industry Index, Financial Industry Index and Plastic Industry Index. This study uses the time series methods of ADF unit root test, variance decomposition, Granger causality and impulse response analysis to proceed empirical research. It covers the period June 2, 2003, through December 29, 2006 and uses the daily data for sample. The empirical results can be summarized as follows¡G (1) All the trading volume and stock return series are trend stationary at level, therefore, they are integrated of order 0 ~ I (0). (2) The variance decomposition shows that the major change of every variable comes from by itself. The explanatory power of trading volume is higher than stock returns. Among the stock returns of Taiwan Stock Index, Electronic Industry Index, Financial Industry Index and Plastic Industry Index, Taiwan Stock Index has the highest explanatory power. (3) According to the Granger causality test, it expresses that trading volume leads stock returns. Taiwan Stock Index is the leading indicator of the Electronic Industry Index and Financial Industry Index. (4) As to the impulse response functions, neither persistent nor overall. The effect of shocks on all variables is transitory.

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

This paper uses co-integration method and error-correction model to re-examine the relationship between real exchange rate and expected interest rate differentials, including cumulated current account balance, over floating exchange rate periods. As indicated by the dynamic model, I find that there is a long run relationship among the variables using Johansen co-integration method. Final conclusion is that the empirical evidence is provided to show that our error-correction model leads to a good real exchange rate forecast.

Purchasing Power Parity (PPP) is an important theory of exchange rate determination. The documents probing into the PPP theory are voluminous nowadays; however, there hasn¡¦t been an agreed conclusion yet. In this paper, we apply the Panel Lagrange Multiplier unit root test, a newly developed panel unit root test that allows for heterogeneous breaks, under both the null and the alternative, in both the level and trend of the series under investigation, addressed by Im, Lee and Tieslau (2010). The validity of PPP theory can be examined by testing the stationary of real exchange rates. We use the data chosen from the countries of Asia, including Taiwan, Japan, Korea, Tailand, Indonesia, Hong Kong and Singapore to proceed the positive analysis. The result shows that no matter we use CPI or WPI as the price index, both considering more about the structure breaks and using the panel unit root test strongly support the PPP theory. And it also shows that when using the WPI as the price index, there would be much more countries support the PPP theory.

Using the monthly data between 1999 and 2007 in Taiwan, we examine the relationship of exchange rate, trade and capital flow in this paper. Granger causality test and impulse response from vector autoregressive model are employed to obtain the short-run dynamics among the variables, and Johansen cointegration test and error correction model are applied to study the long-run equilibrium. This paper reconfirms the J-curve effect in the short run and the validity of Marshall-Lerner condition in the long run. Our results also show the negative correlation of capital flow and the nominal effective exchange rate. Limited by the slow adjustment speed of trade balance, exchange rate and capital flow are the major drives back to equilibrium when the system deviates from the long-run equilibrium. Further, the capital flow variables are the leading indicators of the others in the most cases. However, different capital flow variables induce different patterns of dynamics in the short-run.

The main purpose of this thesis is to explore whether the Balassa-Samuelson hypothesis can effectively explain the long-term change of the real exchange. The recent panel unit root, panel cointegration tests and fully modified OLS are applied to examine the four tested equations that are based on the Balassa-Samuelson hypothesis. 1. Relative differential productivity between traded and non-traded sectors influences price differential in two sectors. 2. We extend the relative productivity in non-traded and traded sectors causing change in non-traded relative price into the two-country model. 3. The appreciation (depreciation) of the real exchange results from the different relative price of the two-country model. 4. The appreciation (depreciation) of the real exchange is caused by the different relative productivity of the two-country model. The data span is from 1971 to 1995, and includes 12 OECD countries. There are three main different points from the existing literatures. 1. We apply some newly developed panel unit root tests to estimate the equations based on Balassa-Samuelson hypothesis. 2. The previous documents only estimated the model of one variable, but the estimation of two variables was rare. In the equation 14 and 15, we examined the two variables in both. 3. In the calculation of the price, owing to the difficulties of collecting data from various sectors, we use a special way to measure the price. Finally, we can observe from the results of the empirical study: when productivity of the domestic sectors differentiates, that is, 1% increase in relative productivity between traded and non-trade sectors causes 0.53% increase in domestic relative prices. When it is taken into the two-country model, the increase of productivity will cause the appreciation of the real exchange rate. This can explain why in the developed countries like the U.S. and Japan, the faster increase in domestic relative productivity causes the appreciation of real exchange rates in the long run.

The main purpose of this thesis is to explore whether the Balassa-Samuelson hypothesis can effectively explain the long-term change of the real exchange. The recent panel unit root, panel cointegration tests and fully modified OLS are applied to examine the four tested equations that are based on the Balassa-Samuelson hypothesis. The data span is from 1985 to 2002, and includes 7 east asian countries. 1. Relative differential productivity between traded and non-traded sectors influences price differential in two sectors. 2. We extend the relative productivity in non-traded and traded sectors causing change in non-traded relative price into the two-country model. 3. The appreciation (depreciation) of the real exchange results from the different relative price of the two-country model. 4. The appreciation (depreciation) of the real exchange is caused by the different relative productivity of the two-country model. Finally, we can observe from the results of the empirical study: when productivity of the domestic sectors differentiates, that is, 1% increase in relative productivity between traded and non-trade sectors causes 0.28% increase in domestic relative prices. When it is taken into the two-country model, the increase of productivity will cause the appreciation of the real exchange rate.

Factors such as economical development, rapid increase in population and climate change increased electricity demand in Turkey as well as in other countries. Thus, using the correct methods to estimate short, medium and long term electricity demand forms a basis for the countries to develop their energy strategy. In this study, monthly electricity demand of Turkey is estimated. First, the effect of natural gas price and consumption to electricity demand and elasticities are searched with a simple regression model. Although, natural gas is known as a substitute of electricity, natural gas consumption and natural gas over electricity price ratio are found to be nearly inelastic. Second part includes two models and cointegration relation is investigated in nonstationary industry production index, electricity consumption per capita and electricity prices series in the first one. An error correction model is then formed with an additional average temperature variable and 12 months electricity demand is forecasted. In the second one, heating degree-days and cooling degree-days are used instead of the average temperature variable and a new error correction model is formed. The first model performs better than the second one, indicating the seasonality of electricity consumption during a year. The results of both models are also compared with previous studies to investigate the effect of different weather variables.

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.