【正文】 ure stationarity. Firstdifferencing eliminates a lot of information in the time series. Is there no better way to analyse gold and silver prices.Long before the development of multivariate time series econometrics, people realised that gold and silver seem to have a mon movement around a longterm equilibrium (goldsilver price ratio). Moreover, the idea of equilibrium conditions in economics and the availability of macroeconomic time series led to the development of cointegration analysis. The idea is very simple. Even if two (or more) time series are nonstationary and hence have stochastic trends, they might be still driven by the same underlying factors that lead to their stochastic behaviour. Therefore, we analyse the time series in levels and see whether we can find a longterm equilibrium – a socalled cointegrating vector. Before we explore the Johansen procedure, let’s look at the goldsilver ratio over time shown in Figure 3.Figure 3: The goldsilver ratio, 19002010The ratio looks like a meanreverting process。A). There is evidence that multinationals outperform local peers due to the benefits of operating in many countries. At the same time, we know that highperforming panies are more likely to enter foreign markets due to their ownership specific advantages. This argument is based on the Resourcebased View and the OLS framework developed by Dunning and Rugman (Reading School of International Business). The VAR model allows you to incorporate both effects: in fact you can test whether performance drives internationalisation or internationalisation drives performance.Before you start using a VAR model, you have to make sure that the time series are stationary. So the first step is to check whether the time series is stationary using DickeyFuller tests and KPSS tests. The second step is to specify the optimal lag length (p) of the model. This is done by paring different model specifications using information criteria. Apart from using Akaike (AIC) and Bayesian Schwarz (BIC), the HannanQuinn (HQIC) is monly used. Most applied econometricians favour the HannanQuinn (HQIC) criterion. STATA will help you to make a good choice. After specifying your model, you need to check stability conditions. The coefficient matrix of the reduced form VAR has to ensure that the iteration sequence converges to a longterm value. STATA will help you in checking stability.To be precise, you need to show that the eigenvalues of the coefficient matrix lie within the unit circle. The reason behind it can be only understood when you understand the method of diagonalizing a matrix. VAR models offer another nice feature: impulse response functions. VAR models capture the dynamics of two (or more) stationary time series。Let’s look at a standard AR(p) process for two variables (yt and xt).(1) yt=α1+i=1pβ1iyti+ε1t(2) xt=α2+i=1pβ2ixti+ε2tThe next step is to allow that lagged values of xt can affect yt and vice versa. This means that we obtain a system of equations for two dependent variables (yt and xt). Bo