<p>In system identification, different methods are often classified as parametric or non-parametric methods. For parametric methods, a parametric model of a system is considered and the model parameters are estimated. For non-parametric methods, no parametric model is used and the result of the identification is given as a curve or a function.</p><p>One of the non-parametric methods is the impulse response analysis. This approach is dynamic simulation. This thesis introduces a new paradigm for dynamic simulation, called impulse-based simulation. This approach is based on choosing a Dirac function as input, and as a result, the output will be equal to the impulse response. However, a Dirac function cannot be realized in practice, and an approximation has to be used. As a consequence, the output will deviate from the impulse response. Once the impulse response is estimated, a parametric model can be fitted to the estimation.</p><p>This thesis aims to determine the parameters in a parametric model from an estimated impulse response. The process of investigating the models is a critical aspect of the project. Correlation analysis is used to obtain the weighting function from the estimates of covariance functions.</p><p>Later, a relation formed between the parameters and the estimates (obtained by correlation analysis) in the form of a linear system of equations. Furthermore, simulations are carried out using Monte Carlo for investigating the properties of the two step approach, which involves in correlation analysis to find h-parameters and least squares and total least squares methods to solve for the parameters of the model. In order to evaluate the complete capability of the approach to the noise variation a study of signal to noise ratio and mean, mean square error and variances of the estimated parameters is carried out.</p><p>The results of the Monte Carlo study indicate that two-step approach can give rather accurate parameter estimates. In addition, the least squares and total least squares methods give similar results.</p>

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.

Detta examensarbete går ut på att jämföra två verktyg som ljuddesigners kan använda sig av för att placera ljud i önskade akustiska miljöer. Verktygen i fråga är båda två metoder för att applicera reverb på ljudfiler. Angreppsvinkel för jämförandet är främst frekvensanalys, men utöver rent tekniska detaljer finns även en rad andra inspelningsproblematiska detaljer att ta i beaktning. / The purpose of this degree work is to compare two sound design tools, which both are used to virtually place a sound in an acoustic environment. The tools in question are both methods to add reverb on sound files. The angle of the comparison is mainly frequency analysis. Above technicality, practical details are taken into consideration.

This paper analyzes empirically the effect of crude oil price change on the economic growth of Indian-Subcontinent (India, Pakistan and Bangladesh). We use a multivariate Vector Autoregressive analysis followed by Wald Granger causality test and Impulse Response Function (IRF). Wald Granger causality test results show that only India’s economic growth is significantly affected when crude oil price decreases. Impact of crude oil price increase is insignificantly negative for all three countries during first year. In second year, impact is negative but smaller than first year for India, negative but larger for Bangladesh and positive for Pakistan.

External economic shocks cause domestic macroeconomic aggregates to fluctuate. This may call for a macroeconomic policy intervention. Since the early 1990s an increasing number of countries have adopted an inflation targeting framework. In reality, inflation targeters do not have perfect information when determining the interest rate in order to maintain their goal of price stability and stable economic growth. Therefore it is relevant to understand how shocks affect the domestic macroeconomic aggregates theoretically and investigate whether the theoretical predictions hold empirically. I use the New Keynesian model by Clarida, Galí and Gertler from 1999 and investigate explicitly the theoretical effects of expected and unexpected supply and demand-side shocks on the monetary policy instrument and the two monetary policy target variables – the interest rate, output gap and inflation rate. By analysing the impulse-response functions of a structural VAR model applied to quarterly Swedish and British data from 1994 to 2011, I test empirically the theoretical predictions according to the New Keynesian model. I find that the empirical results are in line with the theoretical predictions.

This paper examines the oil price-macro economy relationship by means of analyzing the impact ofoil price on Industrial production, real effective exchange rate, long term interest rate and inflation rate for a sample of ten OECD countries using quarterly data for the period 1970q1-2011q1.The impact of oil price shock on industrial production is negative and occurs with a lag of one year. However, the impact has weakened considerably compared to the 1970s. The impact on real effective exchange rate is negative/positive for a net importer/exporter, and the magnitude of the shock depends on the county´s share of net import/export of total world demand/supply. Interest rates are affected negatively, through increase in inflation rates following the oil price shock. The effect tends to die out after 5-8 quarters following the shock for most of the variables and countries. This paper also applies alternative methods to test for unit root and cointegration, which takes into account for structural breaks in the data. The weakness of Phillips-Peron test is clearly demonstrated in the case of inflation rates and interest rates, where the test falsely considered the series to be non-stationary when they in fact are stationary around a structural break. There is also strong evidence of cointegration between oil price and inflation rates and between oil price and interest rates, especially when taking account for structural breaks. / This study also highlights the relevance of oil scarcity and oil peak theory. It is shown that these two terms should receive more attention than they have received so far as more oilexporters have reached their production peaks and more are likely to be followed. According to the data, renewable source of energy are not likely to dominate OECD countries energy mix in the short term, instead, there is a trend of increasing natural gas consumption among most of OECD countries. Natural gas markets are likely to play an equal role in the future as oil markets do today. The dilemma that importing countries are facing today, particularly in Europe, is whether to expose their markets to Russia or to the Middle East.

This study discusses the monetary policy transmission mechanism in the different channels. The analysis is conducted using generalized impulse response functions derived from a factor-augmented vector error correction (FAVECM) model. The FAVECM methodology as developed by Lee (2009) extends the factoraugmented vector autoregression (FAVAR) model to analyze long-run and shortrun dynamics of non-stationary variables. This recenly derived FAVECM model combines the advantages of factor model and the VECM model. The estimations are conducted using 174 macroeconomic time series in monthly frequency for the period January 2000 to September 2009. Results indicate that interbank call loan rate, deposit rate and prime lending rate are conintegrated, which provides sufficient evidence of the existence of the credit channel in monetary transmission system. Other GIRF results are generally consistent of the expected monetary policy effectiveness.

This study revists Purchasing Power Parity (PPP) and discusses the monetary policy transmission mechanism in exchange rate channels. The analysis is conducted using generalized impulse response functions derived from a Factor- Augmented Vector Error Correction (FAVECM) model. The FAVECM methodology as developed by Lee (2009) extends the Factor- Augmented Vector Autoregression (FAVAR) model to analyze long-run and shortrun dynamics of non-stationary variables. This recently derived FAVECM model combines the advantages of factor model and the VECM model. The estimations are conducted using 157 macroeconomic time series in monthly frequency for the period January 2000 to September 2009. Results indicate that PPP exists and expansionary devaluation effect in Taiwan. Other GIRF results are generally consistent of the expected exchange rate effectiveness.

This paper discusses the factors that affect the share price index of Taiwan solar power industry, crude oil prices and the size of the solar manufacturers in Taiwan and Taiwan's market index into the consideration. In addition, considering whether the policies implemented by our government would change the solar industry in Taiwan¡¦s stocks structural .Using the correlation coefficient, the unit root test, Chow test, cointegration test , vector error correction model, impulse response and forecast error variance decomposition to explore their relationship respectively. The study period starts from January 3,2002 until December 30,2011, a total of 2450 daily data for empirical analysis. By Chow test , we find that there is no structural change of solar stock index after the implementation of the domestic policies. Three international crude oil prices and the total share capital of solar manufacturers in Taiwan and the Taiwan solar power industry stocks index has co-integration relationship, means the three international crude oil prices and solar companies total share capital of solar stock index has a long-run equilibrium relationship. By the error correction model of West Texas crude oil price of Brent crude oil prices, the total share capital of the solar companies in Taiwan and Taiwan solar stock index mutual interaction, and the relationship between changes in Taiwan's solar stock price index and Brent crude oil price, West Texas crude oil prices and the total manufacturers of solar energy manufacturers in Taiwan¡¦s share capital are positive, besides, I also found a positive relationship in the impulse response.

As the price level soars up, it become more important to study the dynamic relation between stock prices, price indices. In this paper we suspect that property stocks serve as tools of anti-inflation and examine whether there exists a positive correlation between the prices of property stocks and price indices, such as the Rent Index, CPI, and WPI. Our results confirm the positive correlation between the prices of property stocks and the price indices. More precisely, it is revealed by applying VAR and the impulse response analysis that the positive correlation between the prices of property stocks and CPI/WPI in the short run. Using the cointegration analysis, we detect the long-run relation between the prices of property stocks and the Rent Index.