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In order to estimate the VAR, I have firstly to specify the data which will be analysed. As it is my aim to observe the correlations between oil prices and key macroeconomic variables over a period of time, I will use a set of variables which I believe will produce a strong understanding of the effect on the UK macroeconomy. This following subchapter will provide the reasoning behind choosing each variable. The data that will be used is calculated in quarterly periods in order to provide a significantly more accurate result.In cases when data was not ready available in quarterly periods, then the quarterly mean average figure has been calculated from the available data. The sources for all of the following data can be seen in the Data Sources Appendix. This paper will analyse these following variables:
Oil Prices (OIL) - the most obvious variable to analyse. This entire study is structured around the effects that an oil price shock will have on other key indicators, should it be shocked. Therefore it is imperative that this variable is included. The data used is the quarterly mean spot price of Brent Crude Oil, in US dollars. Brent Crude is sourced from the North Sea and it is the most utilised form of oil in the UK. The trend of this data is remarkable; the range of the data is over $100 per barrel, highlighting the volatility in the price of oil.
Q. Describe Supply and demand in macroeconomics? In microeconomics, we are careful to distinguish between demand, supply and observed quantity. The first two are hypothetical c
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Oil price shocks lead to large adverse supply shocks in the macroeconomy, infer Dornbusch et al (2008) who define an adverse supply shock as; ‘one that shifts the aggregate supply
Mathematical Presentation: Consider the utility function U = U(x 1 , x 2 ). Differentiating totally, we get the following: dU = U 1 dx 1 + U 2 dx 2 = 0 (as along the indiffe
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