Dissertations / Theses on the topic 'Vector autoregression'
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Brännström, Tomas. "Bias approximation and reduction in vector autoregressive models /." Stockholm : Economic Research Institute, Stockholm School of Economics [Ekonomiska forskningsinstitutet vid Handelshögsk.] (EFI), 1995. http://www.hhs.se/efi/summary/405.
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Dutta, Bordoloi Suwodi. "Interdependence of US Industry Sectors Using Vector Autoregression." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-theses/1073.
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"In this study, we explore the interdependence among different US industries by examining their correlations of the stock portfolios. Furthermore, we focus on the dynamics of their interdependent relations during peaceful and volatile periods; as such relations may change due to different sensitivities of each industry to the macroeconomic conditions. More specifically, we apply Vector Autoregression (VAR) methodology on the US industry portfolios and we use variance decomposition and generalized impulse response functions to identify the strength of the impact of each industry on the others. Based on different portfolio returns of the US industries during 1962 to 2008, we find if the pattern of the dynamic relations of the industries change in different periods. We also deduce the most influential and sensitive sectors in the US domestic market. In addition, we find the direction, strength and durability of the shocks using generalized impulse response function (GIRF)."
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Jeon, Kyung-Seong. "An examination of stock market properties : vector autoregression approach /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9841304.
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Unosson, Måns. "A Mixed Frequency Steady-State Bayesian Vector Autoregression: Forecasting the Macroeconomy." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-297406.
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This thesis suggests a Bayesian vector autoregressive (VAR) model which allows for explicit parametrization of the unconditional mean for data measured at different frequencies, without the need to aggregate data to the lowest common frequency. Using a normal prior for the steady-state and a normal-inverse Wishart prior for the dynamics and error covariance, a Gibbs sampler is proposed to sample the posterior distribution. A forecast study is performed using monthly and quarterly data for the US macroeconomy between 1964 and 2008. The proposed model is compared to a steady-state Bayesian VAR model estimated on data aggregated to quarterly frequency and a quarterly least squares VAR with standard parametrization. Forecasts are evaluated using root mean squared errors and the log-determinant of the forecast error covariance matrix. The results indicate that the inclusion of monthly data improves the accuracy of quarterly forecasts of monthly variables for horizons up to a year. For quarterly variables the one and two quarter forecasts are improved when using monthly data.
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Zhang, Wei. "A sensitivity study on identification schemes of the structural vector autoregression /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3025669.
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Petrov, Krassimir M. "Forecasting the dairy price complex : an application of Bayesian Vector autoregression modelling /." The Ohio State University, 2000. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488193272066522.
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Brännström, Tomas. "Bias approximation and reduction in vector autoregressive models." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 1995. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-878.
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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.
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Jordanov, Jordan V. "The size anomaly in the London Stock Exchange : an empirical investigation." Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/7067.
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This study tests the size effect in the London Stock Exchange, using data for all nonfinancial listed firms from January 1985 to December 1995. The initial tests indicate that average stock returns are negatively related to firm size and that small firm portfolios earn returns in excess of the market risk. Further, the study tests whether the size effect is a proxy for variables such as the Book-to- Market Value and the Borrowing Ratio, as well as the impact of the dividend and the Bid- Ask spread on the return of the extreme size portfolios. The originality of this study is in the application of the Markov Chain Model to testing the Random Walk and Bubbles hypotheses, and the Vector Autoregression (VAR) framework for testing the relationship of macroeconomic variables with size portfolio returns.
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White, Alexander B. "Pre- and post-retirement asset allocation: a simulation of retirement investment strategies for agricultural producers." Diss., Virginia Tech, 1995. http://hdl.handle.net/10919/38097.
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This research simulates pre-retirement investment scenarios for agricultural producers. Thirty-two investment scenarios are examined, with each scenario differing with respect to retirement vehicle, investment strategy of the producer, and the use of a cash margin for reinvestment in the operation versus prepaying term debt (cash preference). The retirement vehicles included in this study are Individual Retirement Accounts (IRAs), Simplified Employee Pension Plans (SEPs), and 401(k) plans. Investment strategies reflect the producer's preference for investing in conservative, balanced, or aggressive assets, or a combination of these assets. Further, these scenarios are examined for three methods of capitalization: Case I- an operation with a 50 percent debt/asset ratio; Case II - an operation with a 65 percent debt/asset ratio; Case III - an operation with a 65 percent debt/asset ratio with a majority of the farm land being leased.
The analytical model simulates the annual cash flows of a commercial agricultural operation for each investment scenario over a 30-year period. Stochastic rates of return, generated using a vector-autoregressive (VAR) model, are incorporated into the simulation model. Each scenario is replicated 100 times using different vectors of stochastic rates of return.
Results show investment in retirement vehicles does not significant reduce ending farm assets, regardless of investment strategy or cash preference of the producer. Use of retirement vehicles does have a significant positive impact on ending net worth for the producer. IRAs are not significant investment tools for producers (or spouses) who are participants in another qualified retirement plan.
Investment strategy has a major impact on ending net worth. Aggressive and dynamic (aggressive to conservative as retirement approaches) investment strategies dominate conservative and balanced strategies. Use of cash margin to prepay debt has no advantage over reinvesting in the farm.
Retirement vehicles greatly improve the probability of meeting estimated family living needs during retirement, and generate greater diversity and liquidity of the retirement portfolio. Further, retirement vehicles are more important for producer with highly-leveraged operations and for producers who lease a majority of their assets.Ph. D.
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Brüggemann, Ralf. "Model reduction methods for vector autoregressive processes /." Berlin [u.a.] : Springer, 2004. http://www.loc.gov/catdir/enhancements/fy0818/2003067373-d.html.
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Wong, Kin-man, and 黃健文. "A vector autoregression (VAR) model of housing starts and housing price in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hdl.handle.net/10722/194603.
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It is observed that there are many different models about housing price. Yet, this is relatively smaller number of studies about housing starts. This thesis is an empirical study to work out the relationship between housing starts, housing price and other economic and policy instrumental factors. To achieve this objective, a Vector Autoregression (VAR) model is built since there is inter-relationship between housing starts and housing price.
By applying previous models filled with the research gaps, a new VAR model about the housing starts and housing price in Hong Kong is built. Four hypotheses are tested in the thesis. The first and second hypotheses are if housing starts and housing price are affected by the given exogenous variables. The third hypothesis is if the past movement of economic variables reliable in predicting future values of that variable. The last hypothesis is to test if the “high-land-price” policy really pushes up the housing price.
The empirical results found in this thesis are a little bit different to previous studies in Hong Kong and overseas. Factors which are frequently proved to be statistically significant are not significant in this study (e.g. interest rate and tender price index). Developers in Hong Kong are found to care more about the future market rather than the current market conditions. Many factors do not exert an influence directly on housing starts but indirectly through their impact to the change of the change of the housing price.
It is interesting to know that housing starts react negatively to a change in housing price. An increase in the change of housing price is a bullish signal for the developers. They will hold the land for a while until they expect the peak is coming upon the completion of a project. Therefore, the empirical results suggest the government has to introduce some policies which will lead to a fall in housing price in case that she wants to increase the supply of new private residential housing. Developers will accelerate the applications to commence construction when they expect there will be a downward trend in the housing price (which is shown by a negative change of the housing price..published_or_final_version
Real Estate and Construction
Master
Master of Philosophy
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Cheong, Onn Kee. "A Study of the Interdependence of Four Major Stock Markets Using a Vector Autoregression." Thesis, University of North Texas, 1989. https://digital.library.unt.edu/ark:/67531/metadc500682/.
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The question for this thesis is whether the four major stock markets--the United States, Great Britain, West Germany, and Japan are interdependent or segmented. The study period runs from February 1979 to June 1987, with the Wall Street Journal as a source of data. The Granger causality test is used to test for relationships among the four major stock markets. The thesis is divided into five chapters-- 1) statement of the problem; 2) survey of literature; 3) methodology; 4) results and 5) conclusions. The overall findings of this thesis indicate that there are few or no comovement similarities among all the four stock markets. However, the findings do point out the significant influence of the United States stock market on the other three stock markets.
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Sharp, Gary David. "Lag length selection for vector error correction models." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1002808.
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This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong support for the efficiency based criterion of Akaike and in particular the selection capability of the novel criterion, referred to as a modified corrected Akaike information criterion, demonstrates useful finite sample properties.
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Lee, Joo Young, and Youn Mi Lee. "Dynamic Impact of Aging on Income Inequality in the U.S. with Vector Autoregressive Model." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/secfr-conf/2020/schedule/57.
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Income inequality has been showing a steady increase for past decades and will be worsened in the future (Piketty, 2014). One of the most important factors to explain the worsening income inequality can be aging. Previous studies on aging focus on its impact on traditional issues such as health, retirement, and economic growth. This study finds the direct relationship between aging and income inequality using the vector autoregressive (VAR) model (Blanchard and Quah, 1989). The VAR model is useful to analyze the long-run response of aging on income inequality. The empirical results will verify the negative impact of aging on income inequality in the U.S. The governmental efforts to reduce the negative impact of aging on health care and pensions could delay the worsening income inequality.
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Afonso, Ana Catarina Leitão. "Bond fund runs: The financial crisis case." Master's thesis, NSBE - UNL, 2014. http://hdl.handle.net/10362/11686.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and EconomicsThis paper studies the monthly flows of bond fund geographically focused on Europe and on the United States in the period between 2002 and 2012, with special attention to the effect of the financial crisis of 2008. Through the usage of the panel quantile regression model, this study aims to identify which funds, in terms of their characteristics, are more likely to suffer a run. The main finding is that the impact of the characteristics of fund flows is not equal for all funds, varying with issuer entity, the state of the economy as well as the focus of the fund. During the financial crisis, runs were more pronounced, situation that still affects funds geographically focused on Europe.
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Gilleran, Sean. "Online Regime Switching Vector Autoregression Incorporating Spatio-temporal Aspects for Short Term Wind Power Forecasting." Thesis, KTH, Elkraftteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217117.
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This master thesis examines short term wind power forecasting time series models focusing on regimes conditioned to meteorological conditions and the incorporation of spatio-temporal aspects. Novel regime switching autoregressive and vector autoregressive models are proposed, implemented in a .NET framework, and evaluated. The vector autoregressive framework takes advantage of cross-correlation between sites incorporating upstream online production information from all wind farms within a given region. The regimes are formed using K-means clustering based on forecast meteorological conditions. Each of the proposed models are fit to hourly historical data from all of 2015 for 24 wind farms located in Sweden and Finland. Forecasts are generated for all of 2016 and are evaluated against historical data from that year for each of the 24 wind farms. The proposed models are successfully implemented into the .NET framework of Vitec Software’s Aiolos Forecast Studio, which is widely used in the Northern and Western Europe. Vitec’s Aiolos wind power forecast model is based on an ensemble of numerical weather prediction models and adaptive statistical machine learning algorithms. The proposed models are found to have significantly lower mean absolute error and root mean squared error compared to the Aiolos model and autoregressive model benchmarks. The improved short term wind power forecast will inform operation and trading decisions and translate to significant reductions in balancing costs for Vitecs customers. The improvement is valued at as much as between 9.4 million Euros to 42.3 million Euros in reduced balancing costs. Spatio-temporal aspects for wind power forecasting is shown to continue to be promising for improving current state-of-the-art wind power forecasting.I detta arbete undersöks och implementeras autoregressiva modeller för vindkraftprognoser för en kort tidshorisont. Metoden tar hänsyn till samvariationer i tid och rum mellan olika vindkraftanläggningar och använder regimer som baseras på väderförhållanden för att förbättra prognoserna. Vi föreslår nya autoregressiva regimer, implementerar modellerna i .NET och utvärderar dem. Vektor autoregressiva modeller utnyttjar korrelationen mellan olika anläggningar genom att ta med information i närtid från andra anläggningar i samma region i modellen och på så vis förbättra prognoserna. Regimerna skapas med en klustermetod för K-medelvärde som baseras på väderförhållandena. Alla föreslagna modeller anpassas till historiska data för 2015 för 24 vindkraftanläggningar i Sverige och Finland. Prognoser skapas för 2016 och används för att utvärdera modellerna för var och en av de 24 anläggningarna. De föreslagna modellerna har implementerats i .NET i miljön för Vitecs Aiolos Forecast Studio, vilket är ett program som används av många operatörer i norra och västra Europa för att göra vindkraftprognoser. Aiolos modell baseras på en rad olika numeriska väderprognosmodeller och adaptiva statistiska maskinlärningsalgoritmer. De föreslagna modellerna visar sig ha lägre fel jämfört med Aiolos modell och andra autoregressiva modeller som använts som riktmärken. De förbättrade kortsiktiga vindkraftsprognoserna kommer vara underlag för operativa och finansiella beslut för Vitecs kunder och innebära betydande minskningar av balanskostnader. Förbättringen uppskattas kunna minska kostnaderna för Vitecs kunder med så mycket som mellan 9.4 miljoner och 42.3 miljoner Euro. Att utnyttja korrelationer mellan olika vindkraftanläggningar visar sig ha fortsatt stor betydelse för att förbättra vindkraftprognoser.
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Barassi, Marco Raffaele. "Identifying causal structures of cointegrated vector autoregression with an application to the G7 interest rates." Thesis, Imperial College London, 2001. http://hdl.handle.net/10044/1/8719.
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Singh, Isha. "Reinforcement Learning For Multiple Time Series." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1573223551346074.
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Andersson, Sebastian. "On the Specification of Local Models in a Global Vector Autoregression: A Comparison of Markov-Switching Alternatives." Thesis, Uppsala universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-226918.
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In this paper, focus is on the global vector autoregressive (GVAR) model. Its attractiveness stems from an ability to incorporate global interdependencies when modeling local economies. The model is based on a collection of local models, which in general are estimated as regular VAR models. This paper examines alternative specifications of the local models by estimating them as regime-switching VAR models, where transition probabilities between different states are studied using both constant and time-varying settings. The results show that regime-switching models are appealing as they yield inferences about the states of the economy, but these inferences are not guaranteed to be reasonable from an economic point of view. Furthermore, the global solution of the model is in some cases non-stationary when local models are regime-switching. The conclusion is that the regime-switching alternatives, while theoretically reasonable, are sensitive to the exact specification used. At the same time, the issue of specifying the regime-switching models in such a way that they perform adequately speaks in favor of the simpler, yet functional, basic GVAR model.
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Abdul-Hadi, Ahmad Ibrahim Malawi. "The impact of monetary policy on consumer durable goods : empirical study by using vector autoregression (VAR) models /." free to MU campus, to others for purchase, 1999. http://wwwlib.umi.com/cr/mo/fullcit?p9953841.
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Lytsenko, M., Тетяна Олександрівна Маринич, Татьяна Александровна Маринич, and Tetiana Oleksandrivna Marynych. "Econometric modeling of nonstationary processes." Thesis, Karazin National University, 2015. http://essuir.sumdu.edu.ua/handle/123456789/68631.
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Econometric research of nonstationary time series on causality, cointegration relation and adequate simulation methods was conducted. VAR and VEC models were found to be the most appropriate ways to make reliable prediction and scenario analysis of macro financial data under unstable economic conditions. These econometric techniques were approbated on the financial indicators of Ukrainian economy.
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Crawford, Claudia. "The Sectoral Impact of Monetary Policy in Australia: A Structural VAR Approach." Thesis, Discipline of Economics, 2008. http://hdl.handle.net/2123/2293.
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In recent years, the global resources boom has had a major impact on the Australian economy. In the mining rich state of Western Australia, rapid commodity price growth has contributed to strong economic conditions. However, state economies that rely heavily on manufacturing industries have fared less well, forced to cope with higher input costs as well as the effects of a stronger exchange rate. The resulting 'two-speed economy' presents a challenge for monetary policy, which must manage the diverging performances of different sectors and regions. In light of these issues, this thesis develops a small, open economy structural vector autoregression (SVAR) model of Australia in order to examine the impact of monetary policy on sectoral output. The results suggest that monetary policy shocks have uneven impacts across different sectors. The construction and manufacturing sectors show the most sizeable and rapid responses, while the mining sector is not as interest rate sensitive as the existing literature would suggest. This thesis also adds to our understanding of the transmission mechanism of monetary policy in a small, open economy. In particular, while the results indicate that global economic conditions account for a large proportion of the variation in mining sector output, there is evidence that the exchange rate channel of monetary policy does not play a dominant role in influencing output in this sector. One implication of these findings is that the Reserve Bank of Australia will find it difficult to stabilise output across regional economies in the face of a resources boom. The model also indicates that changes to monetary policy have long, non-trivial real impacts, and there is some suggestion that the credit channel of monetary policy has an important influence in propagating monetary policy shocks.Discipline of Economics
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Modin, Johan. "An Interest Rate Benumbed : Evidence from a structural VAR; can a structural break be found in recent monetary policy transmission?" Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-376792.
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The reliability of monetary policy as an economic stabilisation tool depends on the understanding of the empirical effects of policy intervention on macroeconomic aggregates. Since investigating the interdependencies between macroeconomic variables necessarily involves studying their interactions over time, time series analysis is an important tool. This thesis sets out to examine the presence and effects of nonstationarity in the form of a structural break in a basic VAR of four endogenous variables. Specifically, the transmission of a monetary policy shock on the macroeconomic aggregate of 11 Euro Area countries is estimated for the period 1999–2017, employing variables based on previous studies. A Quandt-Andrews breakpoint test is used to identify the break date, and a comparison is made between the periods. This study finds support for the presence of a break in the regression estimate from the breakpoint test, although the reults from the IRFs cannot be shown to be statistically significant, nor to be bias-free.
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Kalmár, Marcus, and Joel Nilsson. "The art of forecasting – an analysis of predictive precision of machine learning models." Thesis, Uppsala universitet, Statistiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-280675.
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Forecasting is used for decision making and unreliable predictions can instill a false sense of condence. Traditional time series modelling is astatistical art form rather than a science and errors can occur due to lim-itations of human judgment. In minimizing the risk of falsely specifyinga process the practitioner can make use of machine learning models. Inan eort to nd out if there's a benet in using models that require lesshuman judgment, the machine learning models Random Forest and Neural Network have been used to model a VAR(1) time series. In addition,the classical time series models AR(1), AR(2), VAR(1) and VAR(2) havebeen used as comparative foundation. The Random Forest and NeuralNetwork are trained and ultimately the models are used to make pre-dictions evaluated by RMSE. All models yield scattered forecast resultsexcept for the Random Forest that steadily yields comparatively precisepredictions. The study shows that there is denitive benet in using Random Forests to eliminate the risk of falsely specifying a process and do infact provide better results than a correctly specied model.
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Sumner, Steven W. "Bank equity and the monetary transmission mechanism /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2003. http://wwwlib.umi.com/cr/ucsd/fullcit?p3099930.
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Ribeiro, Teresinha Pontes. "Analysis of monetary policy on the collection of VAT in the state of Ceara using the model of vector autoregression." Universidade Federal do CearÃ, 2010. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=4773.
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nÃo hÃThis research aims to analyze quantitatively the impact of monetary policy promoted by the Central Bank of Brazil on the behavior of the tax revenue of ICMS in CearÃ. Thus, we considered information on the collection of industrial, retail and electric, beyond the rate of open unemployment in Fortaleza, and how the transmission mechanism of monetary policy used the Selic interest rate. The model used here is composed of vector autoregression and arguments based on Toda and Yamamoto (1995), and impulse response functions and variance decomposition. The results suggest that a positive shock in monetary policy has negative impact on the tax revenue of ICMS of industry and trade, while the effect on revenues in the electricity sector is positive. And the positive impact of interest rate on the unemployment rate in Cearà is positive, so increases in interest rates tends to increase unemployment in CearÃ.
Esta pesquisa se propÃe a analisar de maneira quantitativa os impactos da polÃtica monetÃria promovida pelo Banco Central do Brasil (BACEN) sobre o comportamento da arrecadaÃÃo setorial de ICMS no CearÃ. Para isso, foram consideradas informaÃÃes sobre a arrecadaÃÃo dos setores industrial, comÃrcio varejista e elÃtrico, alÃm da taxa de desemprego aberta de Fortaleza, e como mecanismo de transmissÃo da polÃtica monetÃria utilizou-se a taxa de juros SELIC. O modelo empregado aqui à composto por vetores autorregressivos e baseados nos argumentos de Toda e Yamamoto (1995), alÃm de funÃÃes impulso resposta e decomposiÃÃo da variÃncia. Os resultados sugerem que um choque positivo na polÃtica monetÃria exerce impacto negativo sobre as arrecadaÃÃes de ICMS da indÃstria e do comÃrcio varejista, enquanto que o efeito sobre arrecadaÃÃo do setor elÃtrico à positivo. E os choques positivos da taxa de juros sobre a taxa de desemprego cearense à positivo, sendo assim, aumentos na taxa de juros tende a aumentar o desemprego no CearÃ.
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Pilström, Patrick, and Sebastian Pohl. "Forecasting GDP Growth : The Case of The Baltic States." Thesis, Jönköping University, JIBS, Economics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-9776.
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The purpose of this thesis is to identify a general model to forecast GDP growth for the Baltic States, Estonia, Latvia and Lithuania. If the model provides reliable results for these states, then the model should be able to forecast GDP growth for other countries of interest. Forecasts are made by using a reduced vector autoregressive (VAR) model. The VAR models make use of past values of Gross Domestic Product-Inflation-Unemployment as explanatory variables.
The performed forecasts have provided good results for horizons up to t+8. The forecasts for 2009 (t+12) are in line with those of several other actors. It is reasonable to assume that some of the forecasts for t+16 have reliable results. The Lithuanian forecast show a fall in GDP with 12.51 per cent in 2009 and a GDP growth of 4.23 per cent in 2010. The forecast for Estonia show that the GDP will decrease with 1.49 per cent in 2009 and 12.72 per cent in 2010. Finally the forecast for Latvia show a fall in GDP of 3.1 per cent in 2009 and 18 per cent in 2010. From the findings it is possible to conclude that the model provided reliable estimates of future levels of GDP for the Baltic States and the benchmark countries. This indicates that the model should be applicable on other countries of interest.
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Ozdemir, Duygu. "Stock Market Liquidity Analysis: Evidence From The Istanbul Stock Exchange." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613789/index.pdf.
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The purpose of this thesis is to identify the factors playing a key role in the determination of the Turkish stock market liquidity in aggregate terms in a time series context and discuss the joint dynamics of the market-wide liquidity with its selected determinants and the trade volume. The main determinants tested are the level of return, the return volatility and the monetary stance of the Central Bank of the Republic of Turkey. The expected positive relationship between the liquidity and the return is confirmed, while the negative effect of the volatility on liquidity appears one-week later. The behavior of various liquidity variables are also examined around the macroeconomic data announcement dates, during the 2008 financial crisis, and after the tick size change in the Istanbul Stock Exchange (ISE). The time series dynamics between the trade volume, return, volatility and the liquidity are put forward within the Vector Autoregression analysis framework. The GARCH modeling of the return series, which is an input to the liquidity model estimations, is a byproduct of this thesis. It is observed that the return series exhibits volatility clustering, persistence, leverage effects and mean reversion. In addition, while the level of the ISE market return decreased, the volatility of the return increased during the 2008 crisis. Accordingly, EGARCH model assuming normally distributed error terms and allowing a shift in the variance during the crisis period is chosen as the best model.
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An, Lian. "THREE ESSAYS ON EXCHANGE RATE AND MONETARY POLICY." UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_diss/491.
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There are four chapters in my dissertation. Chapter one gives a brief introduction of the three essays. Chapter two empirically analyzes the interaction among conventional monetary policy, foreign exchange intervention and the exchange rate in a unifying model for Japan. I have several findings. First, the results lend support to the leaning-against-the-wind hypothesis. Second, conventional monetary policy has as great influence on the exchange rate as foreign exchange intervention in Japan. Third, intervention in Japan is ineffective or may be counter-effective, so escaping liquidity trap by intervention alone may not be a feasible way. Chapter three empirically identifies the sources of exchange rate movements of Japan vis--vis the US, and investigates the role of the exchange rate in the macro economy adjustment. It finds that real shocks dominate nominal shocks in explaining the exchange rate movements, with relative real demand shocks as the major contributor. And the exchange rate market does not create many shocks. The overall result supports that the bilateral exchange rate in Japan is a shock-absorber rather than a source of shock. Chapter four provides cross-country and time-series evidence on the extent of exchange rate pass-through at different stages of distribution - import prices, producer prices and consumer prices - for eight major industrial countries: United States, Japan, Canada, Italy, UK, Finland, Sweden and Spain. I find exchange rate pass-through incomplete in many horizons, though complete pass-through is observed occasionally. The degree of pass-through declines and time needed for complete pass-through lengthens along the distribution chain. Furthermore, I find that a greater pass-through coefficient is associated with an economy that is smaller in size with higher import shares, more persistent and less volatile exchange rate shocks, more volatile monetary shocks, higher inflation rate, and less volatile GDP.
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Lennman, Oscar. "The Fiscal Spending Multiplier in a Panel of OECD Countries." Thesis, Umeå universitet, Nationalekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-129233.
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This thesis sets out to explain the relationship between fiscal spending and economic growth. The relationship is established using a panel vector autoregression model estimated by GMM, using GDP growth and government spending on a panel of 30 OECD countries. The model used is tested with slight variations in specification which are concluded to be important in the finalized results. By altering the specification used in the model this thesis produces relatively different sizes on the multiplier effect both in the short run and in the long run effect. The size of the multiplier effect produced by this thesis is varying between 0.437 on the low side and 2.224 on the high side depending on a few alterations in model specification. Similarly, the long run multiplier effect is measured as 1.873 on the low side and 8.263 on the high side. The mean duration of the multiplier effect is estimated to be approximately 3 years.
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Dong, Juntao. "Reinforcement Learning for Multiple Time Series: Forex Trading Application." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613745680121778.
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Sålder, Christofer. "In search of a smoking gun : The repo rate’s effect on household debt-to-income ratio." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-217562.
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The Swedish households’ debt relative to income has increased for some time now, with the Riksbanks’ executive board expressing its concern for the risk it brings. It has been debated whether or not to take the high indebtedness into account when setting the policy rate. There is at the same time no consensus about the relationship between the repo rate and household debt. This study aims to examine the effect of a change in the repo rate on household debt-to-income ratio, using a VAR-model. The result is that a 1 percentage point shock to the repo rate for one quarter will have a negative impact on the household debt-to-income ratio by 1.75 percentage points after about 8 quarters. However this may not decrease the risk associated with the debt due to higher unemployment.
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Gudmundsson, Gudmundur Stefan. "Essays in network modelling." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/663096.
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This thesis consists of two chapters on time series modelling. The first chapter introduces a class of vector autoregressive (VAR) models with a community structure for large panels of time series. In the model, the series are parti-tioned into latent groups such that spillovers are stronger within groups than between them. We then propose an algorithm that uses the eigenvectors of a function of the estimated autoregressive matrices to recover the communities. We study the properties of the procedure and establish its consistency. The algorithm motivates us to suggest a regularised VAR estimator, which per-forms favourably relative to a number of alternatives in a forecasting exercise. The methodology is applied to study clustering in industrial production for a set of major economies. The second chapter introduces a class of partial correlation network models with a community structure. The series form unknown groups, where correlation is higher within groups than otherwise. We propose an algorithm that consistently detects the communities using the eigenvectors of the sample covariance matrix. The procedure is used to analyse real activity clustering in the U.S. and Europe.Aquesta tesi consisteix en dos capítols sobre models de dades de sèries temporals. El primer capítol introdueix una classe de models de vector autoregressius (VAR) amb una estructura de comunitat per panels de dades de sèries temporals. En el model, les sèries es parteixen en grups latents de tal manera que els spillover són ées forts dins de grups que entre ells. Llavors proposem un algoritme que utilitza el vector d’eigen d’una funció de les matrius autoregressives estimades per recuperar les comunitats. Estudiem les propietats del procediment i establim la seva consistència. L’algoritme ens motiva a suggerir un estimador regulat del VAR, el qual actua favorablement en relació a un nombre d’alternatives en una exercici d’ estimació. La metodologia s’aplica per estudiar el clustering en la producció industrial per un conjunt d’economies importants. El segon capítol introdueix una classe de models de xarxa de correlació parcials amb una estructura de comunitat. La èerie forma grups desconeguts, on la correlació és més alta dins de grups que altrament. Proposem un algoritme que detecta consistentment les comunitats que utilitzen els vectors d’eigen de la matriu de mostra de covariáncia. El procediment s’utilitza per analitzar el clustering en l’activitat real en els EUA i Europa.
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Hallberg, David, and Erik Renström. "PC Regression, Vector Autoregression, and Recurrent Neural Networks: How do they compare when predicting stock index returns for building efficient portfolios?" Thesis, KTH, Optimeringslära och systemteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252557.
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This thesis examines the statistical and economic performance of modeling and predicting equity index returns by application of various statistical models on a set of macroeconomic and financial variables. By combining linear principal component regression, vector autoregressive models, and LSTM neural networks, the authors find that while a majority of the models display high statistical significance, virtually none of them successfully outperform classic portfolio theory on efficient markets in terms of risk-adjusted returns. Several implications are also discussed based on the results.Detta examensarbete undersöker den statistiska och ekonomiska prestationen i att modellera och prognostisera aktieindexavkastning via applikation av flertalet statistiska modeller på en datamängd bestående av makroekonomiska och finansiella variabler. Genom att kombinera linjär huvudkomponentsregression (principal component analysis), vektorautoregression och den återkopplande neurala nätverksmodellen LSTM finner författarna att även om majoriteten av modellerna påvisar hög statistisk signifikans så överpresterar praktiskt taget ingen av dem mot klassisk portföljteori på effektiva marknader, sett till riskjusterad avkastning. Flera implikationer diskuteras också baserat på resultaten
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Lundberg, Otto. "GDP forecasting and nowcasting : Utilizing a system for averaging models to improve GDP predictions for six countries around the world." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-131718.
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This study was issued by Swedbank because they wanted too improve their GDP growth forecast capabilites. A program was developed and tested on six countries; USA, Sweden, Germany, UK, Brazil and Norway. In this paper I investigate if I can reduce forecasting error for GDP growth by taking a smart average from a variety of models compared to both the best individual models and a random walk. I combine the forecasts from four model groups: Vector autoregression, principal component analysis, machine learning and random walk. The smart average is given by a system that give more weight to the predictions of models with a lower historical error. Different weighting schemas are explored; how far into the past should we look? How much should bad performance be punished? I show that for the six countries studied the smart average outperforms the single best model and that for five out of six countries it beats a random walk by at least 25%.Den här studien beställdes av Swedbank eftersom de ville förbättra sin BNP-prediktionsförmåga. Ett dataprogram utvecklades och testades på sex länder; USA, Sverige, Tyskland, Storbritannien, Brasilien och Norge. I den här rapporten undersöker jag om jag kan minska felmarginalen för BNP-utvecklingsprognoser genom att ta ett smart genomsnitt från flera olika modeller jämfört med både den bästa individuella modellen och en random walk. Jag kombinerar prognoser från fyra modellgrupper: Vektor autoregression, principalkomponentanalys, maskininlärning och random walk. Det smarta genomsnittet skapas genom att ge mer vikt till de modeller som har lägst historiskt felmarginal. Olika viktningsscheman utforskas; hur långt bak i tiden ska vi mäta? Hur hårt ska dåliga prediktioner bestraffas? Jag visar att för de sex länderna i studien presterar det smarta genomsnittet bättre än den enskilt bästa modellen och fem av de sex länderna slår en random walk med mer än 25%.
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Hassanzadeh, Mohammadtaghi. "A New State Transition Model for Forecasting-Aided State Estimation for the Grid of the Future." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64407.
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The grid of the future will be more decentralized due to the significant increase in distributed generation, and microgrids. In addition, due to the proliferation of large-scale intermittent wind power, the randomness in power system state will increase to unprecedented levels. This dissertation proposes a new state transition model for power system forecasting-aided state estimation, which aims at capturing the increasing stochastic nature in the states of the grid of the future. The proposed state forecasting model is based on time-series modeling of filtered system states and it takes spatial correlation among the states into account. Once the states with high spatial correlation are identified, the time-series models are developed to capture the dependency of voltages and angles in time and among each other. The temporal correlation in power system states (i.e. voltage angles and magnitudes) is modeled by using autoregression, while the spatial correlation among the system states (i.e. voltage angles) is modeled using vector autoregression. Simulation results show significant improvement in power system state forecasting accuracy especially in presence of distributed generation and microgrids.Ph. D.
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Wang, Ruolin. "Essays on the information flow between equity and credit markets: Before, during and after the financial crisis." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/200152/1/Ruolin_Wang_Thesis.pdf.
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This thesis examines the information flow between equity, credit default swap (CDS) and bond markets between 2003 and 2017 using firm-level data for developed and emerging countries. The findings suggest that the information flow between financial markets is dependent on the market condition. The research demonstrates that the relationship between equity and credit markets has been restructured since the global financial crisis with more rapid adjustment of CDS market to equity market returns. The strength of interaction between equity and credit markets is found to be related to the creditworthiness of the concerned firms.
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Fernandes, Pedro Manuel Ribeiro. "The role of banks in economic growth : an empirical application to Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19408.
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Mestrado em Economia Monetária e FinanceiraEsta dissertação avalia o contributo dos bancos para o crescimento económico em Portugal desde a adopção do Euro, usando testes de cointegração e causalidade, bem como funções de resposta a impulsos. Usando rácios de passivos líquidos (depósitos) dos bancos e empréstimos em percentagem do PIB nominal como medidas do desenvolvimento financeiro, encontramos forte evidência de que o crescimento económico exerce um impacto positivo no desenvolvimento financeiro, de acordo com Demetriades e Hussein (1996). Concluiu-se também que os empréstimos bancários não aumentam o produto real no longo e no curto prazo, também de acordo com Demetriades e Hussein (1996). Ao invés disso, estes têm um efeito negativo no PIB real per capita. Esses resultados corroboram a visão defendida por Robinson (1952), como citado em King e Levine (1993a) e Lucas (1988), de que o financiamento apenas evolui em resposta aos desenvolvimentos da economia.
This dissertation evaluates the role of banks in economic growth in Portugal since the adoption of the Euro, using cointegration and causality tests, as well as impulse response functions. Using ratios of banks? liquid liabilities (deposits) and loans to nominal GDP as a measure of financial development, we find strong evidence of economic growth exerting a positive impact on financial development, in line with Demetriades and Hussein (1996). It was also concluded that bank lending does not boost real output both in the long-run and in the short-run, also in line with Demetriades and Hussein (1996). Instead, it has a negative effect on real per capita GDP. These results support the view championed by Robinson (1952), as cited in King and Levine (1993a), and Lucas (1988), that finance only evolves in response to developments in the economy.
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Duong, Thithuy Nga. "Ciblage de l'inflation et politique monétaire au Vietnam." Thesis, Lyon 2, 2012. http://www.theses.fr/2012LYO22020.
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Le ciblage de l’inflation est le cadre le plus récent de la politique monétaire dans le monde. Il est désormais largement choisi par les pays avancés ainsi que par les pays émergents. Cependant, deux questions principales sont encore en débat particulièrement dans les pays émergent et en développement. Ils s’agissent des avantages du ciblage d’inflation et du respect de conditions préalables afin d’assurer le succès de ce régime. Empiriquement, on conclut que le ciblage d’inflation est un cadre de politique monétaire réussie pour les pays émergents. En plus, il n'est pas nécessaire pour ces pays de satisfaire toutes les conditions préalables strictes avant de réussir à l'adopter. La situation budgétaire et l'indépendance de la banque centrale jouent un rôle plus important que les autres conditions et doivent être préparées en premier lieu. Concernant le Vietnam, par l'approche structurelle vecteur autorégressif (VAR), la thèse montre que la politique monétaire de la banque centrale n’est pas efficace. Donc, il permet de confirmer la nécessité du changement de stratégie monétaire par rapport au cadre actuel. Cependant, notamment parce que la banque centrale n’est pas indépendante, le Vietnam ne peut pas adopter le ciblage d’inflation dans un bref délai. Les recommandations du durcissement de la contrainte budgétaire et de l’augmentation l’indépendance de la banque centrale sont suggérées avant la mise en œuvre de sa stratégie de ciblage d’inflationInflation targeting (hereafter IT) is the newest monetary policy framework in the world. The practice of IT has been chosen by both advanced countries and emerging countries. However, two main issues are still under debate particularly in emerging and developing countries. They are the benefits of IT and preconditions to success adoption. Empirically, we showed that IT is considered as a successful monetary policy framework for emerging countries. In addition, it is not necessary for emerging markets to satisfy all stringent preconditions to successfully adopt IT. In practice, the fiscal situation and the central bank independence play a more important role than other conditions and need to be prepared first.Basing on Structural Vector Autoregression (SVAR), the thesis concludes that Vietnamese monetary policy currently does not effectively control the inflation rate. Inflation targeting framework would be a solution to this. Nonetheless, this thesis concludes that at this moment in time Vietnam is not able to adopt the IT framework, as it still must prepare some of the preconditions required before official adoption. The recommendations of hardening the budget constraint and increase central bank independence in relationship with government are suggested before implementing IT strategy
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Perez, Tomas Rene. "Oil Price and the Stock Market: A Structural VAR Model Identified with an External Instrument." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595877677072786.
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Achsani, Noer Azam, and Hans Gerhard Strohe. "Dynamische Zusammenhänge zwischen den Kapitalmärkten der Region Pazifisches Becken vor und nach der Asiatischen Krise 1997." Universität Potsdam, 2002. http://opus.kobv.de/ubp/volltexte/2007/1214/.
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Dynamische Zusammenhänge zwischen den internationalen Kapitelmärkten sind seit
Anfang 90-er Jahre erforscht worden. Die meisten dieser Untersuchungen betrafen dieUSA und die anderen entwickelnden Märkte. Es gibt nur wenige Untersuchungen zu diesem Thema in den sich entwickelnden Märkten. Mit Hilfe von vektorautoregressiven(VAR) Modellen überprüft diese Arbeit den dynamischen Zusammenhang zwischen den Börsen der Region Pazifisches Becken vor und nach der Asiatischen Krise 1997.Unsere Studie zeigt, dass alle Börsen in der Region Asien-Pazifik mit den anderen Börsen statistisch zusammenhängen, mit Ausnahme von China. Nach der Asiatischen Krise 1997 wurden die Märkte noch stärker integriert. Die Asiatische Krise hatte einen weltweiten Einfluß auf alle Börsen der Region Pazifisches Becken: Die Verbindungen zwischen den Börsen nach der Krise sind stärker als vor der Krise. Die Märkte, die zueinander geographisch und ökonomisch nahe liegen, haben deutlich stärkere Wechselbeziehungen.Das Ergebnis zeigt, dass der USA-Markt nicht der einzige dominierende Markt in der Region ist. Die Studie stellt fest, dass die anderen entwickelten Märkte wie z.B.Neuseeland, Australien, Hongkong und Singapur, weitere vorherrschende Märkte neben USA sind. Ein Schock in einem Markt wird schnell zu den anderen Märkten übertragen. Schocks in den sich entwickelnden Märkten werden zu anderen Märkten schnell übertragen, aber ohne einen solchen großen Einfluß wie die aus den entwickelten Märkten.International capital markets linkages have been studied since the early 90-es. Most of these studies have focused on the US and other developed markets. There are only few researches on this topic in the emerging markets. This paper examines the dynamic linkages between Pacific-Basin stock markets before and after the Asian Crisis 1997, using the vector autoregressive (VAR) approach. Our study shows that all Asia-Pacific stock markets are integrated with each other,except China. Following Asian Crisis 1997, the markets became more integrated. The Asian crisis had a global effect on all stock markets in Pacific-Basin region. The linkages between stock markets after the crisis are stronger than those before the crisis. Markets that are geographically and economically closer to each other tend to have a stronger correlation The result shows that the US market is not the only dominant market in the region. The study notes that the other developed markets such as New Zealand, Australia, Hongkong and Singapore are further comparatively dominant markets besides US market. A shock in one market is rapidly transmitted to other markets. Shocks in the emerging markets are also swiftly passed to other markets, but without having such a big effect compared to those in the developed markets.
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Dahlberg, Magnus, and Gombrii Anders. "Vart är kronan på väg? : Utmaningen med växelkursprognoser - en jämförelse av prognosmodeller." Thesis, Uppsala universitet, Nationalekonomiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-439138.
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Riksbanken har under senaste åren blivit kritiserade för deras bristande prognoser av svenska valutakurser. I denna uppsats undersöks det om slumpvandring (RW) är den mest framgångsrika prognosmodellen eller om alternativa ekonometriska prognosmodeller (AR, VAR och VECM) kan estimera framtida växelkurser mer korrekt på kort sikt, ett kvartal fram, och medellång sikt, fyra kvartal fram. I dessa prognosmodeller behandlas fem Svenska makroekonomiska variabler som endogena; KPI, BNP, arbetslöshet, 3 månaders statsobligationer (T-bonds), samt en exogen variabel, Amerikansk-BNP. Den data som används är kvartalsdata från första kvartalet 1993 till andra kvartalet 2020 för respektive variabel. Resultaten från studie visar på att RW är mer ackurat än de multivariata modellerna (VAR och VECM) på både kort sikt och medellång sikt. Residualerna utvärderas genom att kolla på rotmedelkvadratfel (RMSE) från respektive prognos.In recent years, the Riksbank has been criticized for their underperforming forecasts of Swedish exchange rates. This thesis examines whether the random walk (RW) is the most successful forecasting model when forecasting the exchange rate (SEK / USD) or whether alternative economic forecasting models (AR, VAR and VECM) can estimate future exchange rates more accurately. Both in the short and medium term, one respectively four quarters ahead. In these forecast models, five Swedish macroeconomic variables are treated as endogenous; CPI, GDP, unemployment, three-month Treasury-bonds (T-Bonds), and an exogenous variable, US GDP. The data used is quarterly data from the first quarter of 1993 to the second quarter of 2020 for each variable. Results from the study show that RW is more accurate than the multivariate models (VAR and VECM) in both the short and medium term. The residuals are evaluated by looking at root mean square error (RMSE) from the respective forecast.
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naz, saima. "Forecasting daily maximum temperature of Umeå." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112404.
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The aim of this study is to get some approach which can help in improving the predictions of daily temperature of Umeå. Weather forecasts are available through various sources nowadays. There are various software and methods available for time series forecasting. Our aim is to investigate the daily maximum temperatures of Umeå, and compare the performance of some methods in forecasting these temperatures. Here we analyse the data of daily maximum temperatures and find the predictions for some local period using methods of autoregressive integrated moving average (ARIMA), exponential smoothing (ETS), and cubic splines. The forecast package in R is used for this purpose and automatic forecasting methods available in the package are applied for modelling with ARIMA, ETS, and cubic splines. The thesis begins with some initial modelling on univariate time series of daily maximum temperatures. The data of daily maximum temperatures of Umeå from 2008 to 2013 are used to compare the methods using various lengths of training period. On the basis of accuracy measures we try to choose the best method. Keeping in mind the fact that there are various factors which can cause the variability in daily temperature, we try to improve the forecasts in the next part of thesis by using multivariate time series forecasting method on the time series of maximum temperatures together with some other variables. Vector auto regressive (VAR) model from the vars package in R is used to analyse the multivariate time series. Results: ARIMA is selected as the best method in comparison with ETS and cubic smoothing splines to forecast one-step-ahead daily maximum temperature of Umeå, with the training period of one year. It is observed that ARIMA also provides better forecasts of daily temperatures for the next two or three days. On the basis of this study, VAR (for multivariate time series) does not help to improve the forecasts significantly. The proposed ARIMA with one year training period is compatible with the forecasts of daily maximum temperature of Umeå obtained from Swedish Meteorological and Hydrological Institute (SMHI).
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Akpan, Nkereuwem I. "The Impact of External Shocks on Nigeria’s GDP Performance within the Context of the Global Financial Crisis." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17454.
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This research examines the impact of external shocks on Nigeria’s output performance for the period 1981 – 2015. It aims to bring to the fore the importance of considering external shocks during policy design and implementation. The multivariate VAR and VECM frameworks were used to evaluate the impact of the shock variables on Nigeria’s output performance and to achieve the stated objectives. Findings show that the external shock and domestic policy variables have short-run effects on Nigeria’s output performance. Also, all the measures of external shocks and domestic policies display some viable information in explaining the variabilities in Nigeria’s output performance over the horizon. The comparison between the results of the VECM and the unrestricted VAR shows that the unrestricted VAR model outperformed the VECM.
The overall result of the study confirms the view about the vulnerability of the Nigerian economy to external shocks. These shocks explain more than half of the variance in real output performance and have varying effects on output performance in Nigeria. The dynamic response of output performance to each of the defined shock variables show that output performance responds rapidly to the shock variables, while its response to the domestic economic variables is seemingly moderate. Finally, the variance decomposition show that international crude oil price and terms of trade have the largest share in accounting for the variability in output performance, followed closely by the shares of capital inflows and monetary policy.
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Kim, Gil. "THREE ESSAYS ON EXCHANGE RATE ECONOMICS." UKnowledge, 2009. http://uknowledge.uky.edu/gradschool_diss/752.
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A country’s economy is becoming more and more dynamic and complicated in its scale and mobility. So, the concerns of exchange rate economics have become more popular. My research interest is in international economics with its major factor, exchange rates and other macroeconomic variables. Chapter 1 presents a brief introduction of the three studies.
Chapter Two investigate the role of exchange rate changes with particular attention to international capital flows. With liberalization of capital movements, international capital movements became free and unrestricted in many emerging market economies as well as developed countries. Using a Vector Auto-regressive (VAR) model for a small open economy in which the endogeneity of exchange rate changes is fully taken into account, I find that capital movements are more likely to be a cause of output fluctuations and current account deficits in developing countries than a channel of equilibrium changes. I also find that domestic currency depreciation is far more likely to be contractionary on domestic output in developing countries than in developed countries. Interestingly, the trade balance improves after depreciation regardless of its output consequence. These findings suggest that there are important differences between developed and developing economies in the way capital movements and exchange rate changes affect and are affected.
Chapter Three demonstrates the dynamic relationship between the current account and the real exchange rate in response to permanent and temporary shocks using structural VAR models for seven developed countries and five developing countries. Special focus is given to the issue of the stationarity of the current account. Capital flows are also included to capture external shocks as well as potential structural breaks due to financial liberalization. I find that the results for unit root tests for the current account are ambiguous. By testing two different VAR models, each taking an opposing stance on the stationarity of the current account, I conclude that responses based on a stationary current account are a better fit to the current theoretical view than those based on a nonstationary current account process. Additionally, the real exchange rate and the current account are positively correlated under a permanent shock while two variables are negatively correlated under a monetary shock. I also find that real exchange rate is an endogenous variable, which is not closely related to the temporary factors that affect the current account in the short run.
Chapter Four examines the long-run mean reverting behavior of the real exchange rates with its six different definitions for 27 economies using annual data from 1974 to 2003. I find that Purchasing Power Parity (PPP) holds better, and the half-life of the real exchange rates is shorter when the wholesale price index, rather than consumer price index, is used as price level measure. Somewhat surprisingly, there is no evidence that PPP holds better with trade-weighted real exchange rates than with bilateral ones regardless of the price index used. Strong evidence for PPP emerges only with the use of Im, Pesaran, and Shin (2003) panel tests but not with the Levine, Lin, and Chu (2002).
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Wichmann, Roberta Moreira. "Ensaios econométricos sobre política fiscal no Brasil." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/54598.
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O presente artigo apresenta um estudo econométrico da política fiscal brasileira com o objetivo de avaliar, no período que se estende de 2001 a 2010 utilizando dados mensais, como os diferentes componentes da política fiscal respondem à dinâmica do produto. Primeiramente é feito a identificação e a análise dos componentes da política: impulso fiscal e regra fiscal seguindo a orientação de distintas metodologias (OCDE, FMI, método Holandês e filtro de Kalman). Dessa forma, é possível avaliar se a política é oportuna e ágil, observar qual o tamanho do impacto da resposta de cada componente a choques negativos no produto e, por fim, comparar os resultados fiscais com os encontrados para a política monetária. Para tanto, foi utilizado a técnica da autorregressão vetorial. Os resultados das estimações indicam que a regra fiscal apresenta-se de forma oportuna e reage mais rapidamente, em termos gerais, à redução do hiato quando comparados aos juros e ao impulso fiscal. Em relação ao impulso fiscal os resultados das estimações não foram tão homogêneos. A política monetária apresenta resultados levemente díspares quando se trata da velocidade da adoção de medidas contracíclicas. A decomposição da política fiscal via filtro de Kalman pareceu ser a mais indicada.This article presents an econometric study of the Brazilian fiscal policy with the objective of evaluating, in the period extending from 2001 to 2010, using monthly data, how the different components of fiscal policy respond to the dynamics of the product. Firstly, the identification and analysis of the components of the policy are made: fiscal impulse and fiscal rule following the guidance of different methodologies (OECD, IMF, Dutch method and Kalman filter). Thus, it is possible to assess whether the policy is timely and responsive, to observe how big the impact of each component of the response to negative shocks is in the product and, lastly, compare the fiscal results with the results also found for monetary policy. For this purpose it used the technique of vector autoregression. The estimation results indicate that the fiscal rule is presented in a timely manner and react more quickly, in general terms, to reduce the gap when compared to interest rates and fiscal stimulus. In relation to fiscal impulse the estimation results were not as homogeneous. Monetary policy has slightly differing results when it comes to the speed of adoption of countercyclical measures. The analysis of fiscal police via the Kalman filter seems to be most suitable.
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Chung, Joonho. "Empirical study on the effects of monetary policy on the exchange rates : the role of uncertainty in monetary policy /." free to MU campus, to others for purchase, 1998. http://wwwlib.umi.com/cr/mo/fullcit?p9901229.
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Liu, Guangling. "Forecasting with DSGE models : the case of South Africa." Thesis, University of Pretoria, 2008. http://hdl.handle.net/2263/25396.
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The objective of this thesis is to develop alternative forms of Dynamic Stochastic General Equilibrium (DSGE) models for forecasting the South African economy and, in turn, compare them with the forecasts generated by the Classical and Bayesian variants of the Vector Autoregression Models (VARs). Such a comparative analysis is aimed at developing a small-scale micro-founded framework that will help in forecasting the key macroeconomic variables of the economy. The thesis consists of three independent papers. The first paper develops a small-scale DSGE model based on Hansen's (1985) indivisible labor Real Business Cycle (RBC) model. The results suggest that, compared to the VARs and the Bayesian VARs, the DSGE model produces large out-of-sample forecast errors. In the basic RBC framework, business cycle fluctuations are purely driven by real technology shocks. This one-shock assumption makes the RBC models stochastically singular. In order to overcome the singularity problem in the RBC model developed in the first paper, the second paper develops a hybrid model (DSGE-VAR), in which the theoretical model is augmented with unobservable errors having a VAR representation. The model is estimated via maximum likelihood technique. The results suggest DSGE-VAR model outperforms the Classical VAR, but not the Bayesian VARs. However, it does indicate that the forecast accuracy can be improved alarmingly by using the estimated version of the DSGE model. The third paper develops a micro-founded New-Keynesian DSGE (NKDSGE) model. The model consists of three equations, an expectational IS curve, a forward-looking version of the Phillips curve, and a Taylor-type monetary policy rule. The results indicate that, besides the usual usage for policy analysis, a small-scale NKDSGE model has a future for forecasting. The NKDSGE model outperforms both the Classical and Bayesian variants of the VARs in forecasting inflation, but not for output growth and the nominal short-term interest rate. However, the differences of the forecast errors are minor. The indicated success of the NKDSGE model for predicting inflation is important, especially in the context of South Africa - an economy targeting inflation.Thesis (PhD (Economics))--University of Pretoria, 2008.
Economics
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Karl, Velander, and Callerud Karin. "The development of the financialsystem and economic growth in Sweden : A Granger causality analysis." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-78703.
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Semião, Patrícia Margarida Floro. "Efeitos macroeconómicos do investimento público central e local: uma comparação internacional." Master's thesis, ISEG, 2008. http://hdl.handle.net/10400.5/21971.
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Mestrado em Economia.O investimento público tem sido alvo de interesse por parte das investigações económicas mais recentes, enquanto uma variável que pode fomentar o crescimento económico. Através da observação dos seus impactos na economia, consegue-se compreender se os esforços empreendidos no investimento público são eventualmente produtivos. Este estudo pretende analisar essa produtividade, medindo os efeitos do investimento público no PIB, no investimento privado e no emprego, no longo prazo. A especificidade do exposto neste trabalho consiste numa desagregação diferente do investimento público, ao analisar em separado os efeitos do investimento feito pela administração central, pela administração local e pela administração estadual, quando aplicável. É efectuado para sete países da União Europeia, a saber; Alemanha, Bélgica, Finlândia, França, Holanda, Itália e Portugal, permitindo assim uma comparação a nível internacional. A abordagem metodológica baseia-se em modelos de vectores autoregressivos - modelos VAR. Com base nas funções acumuladas de resposta a um impulso por tipo de investimento público, são calculadas as elasticidades, as produtividades marginais parciais e totais do PIB e do investimento privado, bem como as taxas de rendibilidade parciais e totais do PIB. É ainda calculado o número marginal de empregos criados. Conclui-se que, de modo geral, o investimento público por subsector é produtivo, apresentando efeitos positivos no PIB, no investimento privado e no emprego. Por tipo de investimento público, o investimento local tem sempre efeitos positivos no PIB, apresenta impactos positivos no investimento privado para um maior número de países e, no emprego, embora as elasticidades de longo prazo sejam superiores, os empregos criados são menores do que para o investimento central.
Public investment has been a target of many economical investigations in the recent years, because of its potential to promote economic growth. Through the observation of its impacts in the economy, one can understand if the efforts of public investment are productive. The aim of this study is to analyse that productivity, through the measurement of the public investment effects in the long run in GDP, private investment and employment. The specificity of this work, is the different disaggregation of public investment, that analyse separately the effects of public investment made by the central administration, local administration and state administration, when exists. It is made to seven European Union countries: Germany, Belgium, Finland, France, Netheriands, Italy and Portugal, allowing an intemational comparison. The methodological approach is a model of vector autoregression - a VAR model. With theaccumulated impulse response functions for different t ypes of public investment, elasticities, partial and total marginal productivities and, partial and total rates of retum are calculated for GDP. The number of marginal jobs is also calculated. One can conclude that, generally, public investment is productive, with positive effects in GDP, in private investment and in employment. For a analyse through different types of public investment, the local one hasalways positive effects in GDP, has positive effects in private investment for most countries and, in employment, although the elasticities are greater, the job creation are less than for the central investment.
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