Generally speaking, business cycle could be discussed as a short-term fluctuation of business cycle and long-term economic growth. In this research, we will confer what impact factors might have affected the business cycle of correlations (BCCs) across countries in a period of short time. Many empirical analysis have pointed out the temporary factors to the business cycle mainly come from the transferred factors of economic aspect. This is called ¡§Transmission Mechanisms.¡¨ What is ¡§Transmission Mechanisms?¡¨ Economists often try to substitute it in good markets, financial markets, and the coordination of monetary policies. However, in this duration of the empirical analysis, using only these proxy variables to explain BCCs between two countries seems too limited. According to this situation, we believe if the BCCs can be explained by using proxy factors of non-economic variable, the result can be utilized by making up the defect. We attempt to find new factors in political approach and combine with the ¡§Transmission Mechanisms¡¨ that we have introduced earlier. After that, we expect to comprehend the BCCs among G7 countries from the inputs of the two completed different variables. To analyze further economic implication in our research, five conclusions have been summarized below: Firstly, increasing bilateral trade has significantly provided positive effect to BCCs among G7 countries from 1980 to 2002. Because the empirical result of Single Country is insignificant, we then use a two-stage method. First, we estimate ¡§Trade¡¨ from endogenous variable to exogenous one. Secondly, we use Panel method to expand its matrix. Finally, we improve the empirical estimators of insignificant statistics before. In other words, the important variables of the correlation of bilateral trade are whether or not the two countries speak the same language; the border problem, and the distance between the two are the same, etc. So, when we talk about the relations between BCCs and good and service markets, we must consider these exogenous factors. Eventually, we will receive more detailed results. Secondly, although to trade in financial markets can increase the BCCs between two countries, the statistic report is insignificant -0.0019 (0.0012). About this empirical result, we can obtain reasonable explanations from the researches (for instance: Imbs, 2004 or Kose et al, 2003), they point out that financial markets are bound excessively by globalization. Therefore, this will aggravatingly make each country to focus on its specialization. Finally, this situation will make the BCCs getting collapsed among these countries. This also explains that the specialization among these countries will reduce the positive effect from the BBCs to financial markets. Thirdly, in this empirical research of Single-Country, we use three proxy estimators of economics to substitute common properties of the monetary policy. At this point, there are no identical correlations of corresponding among other countries except some significantly negative trends shown to the member countries of European Union. According to this situation, we believe it may be the consequence to all the member countries under some ERM restrictions, which is Treaty of Maastricht. Also, because of the rules form this treaty, the monetary policies are getting to be accordant, and the BCCs among the countries will soon appear in obviously positive trend. Fourthly, in the model, the difference of the inflation rate between two countries is not significant with BCCs; therefore, an identical correlation is hardly shown. Moreover, the coefficient symbol is not in our expecting direction, so we think maybe some policies are neglected to the influence of this variable. After all these, we believe if we can control some relative policy effect to inflation rate when discussing the relationship between this variable and the BCCs, we should be able to find out the real effect of this substitutive variable to BCCs Lastly, in the research, the statistics effect of the party variables and business cycle of correlations are very significant. This also indicates the political factor will play an important role for many sources of the fluctuation tread of BCCs. In other words, when we discuss the issue of BCCs if miss the contribution of political factors to the BCCs. Then, this might cause the omitted variable biased, and finally cause the whole computation become inefficient. In addition, we can have further discussion by an input of a factor: to conserve the joint benefit of all the member countries in an economic organization, these countries need to be ruled by the same ideal political party. Otherwise, the institute will never reach its essential result. Combining all the conclusions we have shown above, we can find out the BCCs among G7 countries from 1980-2002. Besides the influence of the ¡§Transmission Mechanisms,¡¨ the result will be varied by the political factors. In conclusion, we need to consider the contribution of the political party variables to the BCCs when talking about this issue, therefore; the original theoretical model can be more persuasive. According to a statistics of IMF, the BCCs among those industrial countries are falling little by little in recent years. Therefore, consolidating trade cooperation is essential for what we believe to improve the BCCs among G7. At the same time, pass through a strong integrate monetary policy can move forward all the incumbent parties from all the countries to agree among themselves, and even reach more substantial effect. From the example like this, we might find evidence from BCCs issues by discussing the integration process in European Monetary Union.