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In order to observe the correlations between each variable, the most effective method to use is Vector Autoregression (VAR). VAR estimation uses a system of simultaneous equations to observe interdependencies throughout multiple time-series data.
The VAR is unrestricted; it will produce a theory-free estimation of economic relationships. It is imperative to understand that the estimation will not test any economic theories, nor will it analyse any government policies such as inflation targeting. The VAR will purely estimate the correlations between the specified macroeconomic variables over the time period. This paper's empirical set-up is largely borrowed from Jiménez-Rodríguez, R. and Sánchez, M. (2004) as their study was very similar to this paper, but focuses onseveral OECD countries, not just the UK. The borrowed methodology is using an unconstrained vector autoregression which is then transformed into its Moving Average Representation form in order to estimate the impulse response functions. The following vector autoregression of order p, where p is the number of lags is estimated;
Where, = GDP, = Oil Prices, = Inflation rate, = Interest Rate, = Unemployment rate and = Real exchange rate. Finally, is the error term for each equation.
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Price/Feeder Quantity Demanded Quantity Supplied $300 500 1800 270 600 1700 240 700 1600 210 800 1500 180 1000 1400 150 1100 1300 120 1200 1200 90 1300 1100 60 1400 1000 30 1500 90
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