Master of Agribusiness / Department of Agricultural Economics / Allen M. Featherstone / During the past 10 years, ethanol production in the United States has grown exponentially. From 2000 to 2009 U.S. ethanol production increased from 1.6 billion gallons annually to 10.8 billion gallons annually. In 2010, U.S ethanol production increased by 23 percent from 2009 to 13.23 billion gallons. The increase in ethanol production was due to lawmakers reacting to skyrocketing oil prices by implementing a Renewable Fuels Standard (RFS) in 2005 and expanding the RFS in 2007. The RFS requires the use of specified amounts of biofuels, such as ethanol, through the year 2022. The creation of the RFS represented a step beyond lawmakers’ usual policy of using the tax code to promote ethanol production. There is a long history of encouraging ethanol production by using the tax code, but the implementation of a biofuels mandate is new and therefore there is not a great deal of research on the effects of such a policy. This study analyzes U.S. oil, unleaded gasoline, corn and ethanol prices dating back to 1985 to determine the impact that the RFS has had on corn prices. The key question answered is whether the creation and expansion of the RFS has brought the instability of the oil market into the corn market. The prices that an ethanol plant in western Kansas paid for the grain it used to produce ethanol and the price that the plant received for the ethanol that it produced are also analyzed. The plant began operation in January 2004, so it is possible to analyze the grain and ethanol prices both before and after the implementation and expansion of the RFS. To study the impact of the RFS creation and expansion, the prices were analyzed to see if there was an increase in the correlation after the creation and expansion of the RFS. Regression analysis of the national corn prices and the prices that Western Plains Energy paid for the grain that it used to produce ethanol; and regression analysis of the national price of ethanol and the price that Western Plains Energy sold its ethanol for were also used to study the impact of the RFS. Finally, the vector autoregression (VAR) model is used to analyze the dynamic relationships between the variables in the system: corn price, oil price, ethanol price and unleaded gasoline price. The analysis of the correlation reveals that both at the national and plant level grain and oil prices track much more closely together after the creation and then expansion of the RFS. The VAR reveals that there is some relationship between corn and oil prices contemporaneously. The correlation matrix of residuals reveals that there is not a strong correlation between national corn and oil prices. The results suggest the need for greater research in this area. The creation and expansion of the RFS represented a step into uncharted territory and the consequences are still not known.

The "global" financial crisis (GFC) emerged during 2008 and it was mainly triggered by the sub-prime mortgage crisis (SMC) in the United States of America. The main aims of this thesis is to conduct an econometric analysis of the financial crisis and household savings in South Africa and also to provide a rationale that will facilitate a policy attention on Domestic Resource Mobilisation (DRM) through household savings. The study uses quarterly time series data for the period 199401 to 201102 obtained on-line from the South African Reserve Bank (SARB). The research is based on the Keynesian saving function, which is a complement of the consumption function. The model will be estimated by using a cointegrating vector autoregressive (CVAR) framework, which allows for endogeneity of the regressors. To check robustness on the cointegration results, the study employs the second empirical technique based on Generalized Impulse Response Function (GIRF) analysis and Variance Decomposition. The regression equation of household savings is expressed as a function of household disposable income, household debt to disposable income, real GOP, interest rate, inflation rate and foreign savings. The variables are tested for the presence of a unit root by the application of the Augmented Dickey-Fuller (AOF), Phillips-Perron (PP) Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The findings of the study are that all variables have unit roots. The cointegration model emphasises the presence of a long run equilibrium relationship between dependent and independent variables. The CVAR reveals the short run of the dynamic household savings model. Taking this into consideration, the study concludes that household debt has a huge influence on the level of household savings. The econometric analysis also revealed that household savings in South Africa actually improved during the period associated with the GFC. It could be postulated that South African households responded to their deteriorating financial situations by reducing their average spending and increasing their savings. Variance decomposition analysis revealed that 'own shocks' constitute the predominant source of variations in household saving therefore household savings can be explained by the disturbances in macroeconomic variables in the study. The study recommends the promotion of household savings and economic growth in order to reduce the dependence of South Africa on foreign savings. DRM is therefore enhanced by a higher level of household savings, which can facilitate higher levels of investment and economic growth. / Thesis (PhD (Economics) North-West University, Mafikeng Campus, 2012

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).

<p>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.</p><p>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.</p>

We analyze the interaction between monetary policy in the US and the global economy proposing a new class of Bayesian global vector autoregressive models that accounts for time-varying parameters and stochastic volatility (TVP-SV-GVAR). Our results suggest that US monetary policy responds to shocks to the global economy, in particular to global aggregate demand and monetary policy shocks. On the other hand, US-based contractionary monetary policy shocks lead to persistent international output contractions and a drop in global inflation rates, coupled with rising interest rates in advanced economies and a real depreciation of currencies with respect to the US dollar. We find considerable evidence for heterogeneity in the spillovers across countries, as well for changes in the transmission of monetary policy shocks over time. (authors' abstract) / Series: Department of Economics Working Paper Series

This article assesses the empirical relationship between per capita income growth fluctuations and the age-structured human capital variations across four groups of geographically clustered developed and developing countries from spatial perspective. We estimate a spatial Vector Autoregressive (VAR) model of income dynamics where the distance between countries is defined on relational space based on their similarity in appropriation tendency of human capital in the production processes. These distances are computed using a newly developed human capital data set which fully characterizes the demographic structure of human capital, and thus underlines the joint relevance of demography and human capital in economic growth. Spatial effects on growth interdependence and complementarity are then explored with respect to the proposed distance metrics. Our results imply that significant cross-country growth interdependence based on human capital distances exists among defined country groups suggesting the need for a cooperative policy programme among them. We also find that the relationship between economic growth and human capital is highly nonlinear as a function of the proposed human capital distance.

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%.

This study constructs a financial stress index with a specific focus on the case of the Czech Republic. The advantage of the index is primarily its ability to measure the current level of stress in the financial system incorporating information from various sectors of the economy and expressing it in a single-value statistic. Our index successfully recorded and evaluated critical periods of elevated financial stress especially during the recent financial crisis. Furthermore, we examine a systematic interaction between financial stress and the macroeconomics using vector autoregression analysis along with method of impulse responses. Based on our results we observe a significant and positive response of unemployment due to the shock in financial stress. Conversely, a negative effect was examined on inflation and interest rates. JEL Classification G17, G32 Keywords financial stress index, vector autoregression, impulse responses

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’inflation. / Inflation 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.

This work combines discrete and continuous methods while modeling connect- edness of financial tick data. As discrete method we are using vector autore- gression. For continuous domain Hawkes process is used, which is special case of point process. We found out that financial assets are connected in non- symmetrical fashion. By using two methodologies we were able to model bet- ter how are the series connected. We confirmed existence of price leader in our three stock portfolio and modeled connectedness of jumps between stocks. As conclusion we state that both methods yields important results about price nature on the market and should be used together or at least with awareness of second approach. JEL Classification C32, G11, G14 Keywords Vector Autoregression, Hawkes process, High- frequency analysis, Connectedness Author's e-mail petr.petras@email.cz Supervisor's e-mail krehlik@utia.cas.cz