cover only for cartels against which legal is taken, and therefore there are some limitations on the scope of our analytical results. However, we identified characteristics of the structural factors of industries in which cartels are confirmed in Japanese industries.

First, regarding the relationship between the demand factors and cartel formation, we found that the growth rate of value of shipments and its fluctuations had a statistically significant negative effect and that while the former did not support the theoretical hypothesis, the latter support the hypothesis. Next, regarding the relationship between the supply factors and cartel formation, although market concentration does not have a statistically significant effect, contrary to the theoretical hypothesis, it has a negative relationship with cartel formation. The barriers to entry has a significant positive relationship with cartel formation, and this result implies that higher entry barriers result in an environment that made the formation of cartels easier and supports the theoretical hypothesis.

In comparing our results to the results of OFT (2005), it can be said that the fluctuations in the growth rate of value of shipments (demand side factor) and entry barriers (supply side factor) share an equivalent relationship with cartel formation. Conversely, the growth rate of value of shipments (demand side factor) and market concentration (supply side factor) have a reverse effect on cartel formation and our results do not support the theoretical hypothesis. The former is statistically significant, but the latter is not.

In addition to the above mentioned demand and supply factors, following OFT (2005), we analyze the relationship between employment factors and cartel formation. As a result, similar to the results in the OFT, earnings per employee has a significantly positive relationship with cartel formation.

In addition to empirical analysis for the test of theoretical hypotheses of economic theory of collusion, we also predicted several values with these estimation results as the basis for the cartel formation probability of each industry and the number of cartels, and then summarized the 30 industries with the highest probabilities. From the results, seven industries with actually confirmed cartels appear in the top 10 industries. Conversely, due to the inability to use certain data it is possible that there are factors not addressed in this analysis and there were industries with a low cartel formation probability despite the fact that cartels are captured. We also made predictions related to the number of cartels using the same methods but due to the same reasons as with the probability predictions, there were some industries with a significant divergence between the actual number of cases and its predictions.

Next, we would like to discuss the policy implications derived from this analysis. These results can be used as an indicator for the discovery or selection of industries in which it is thought cartels are being formed. Among the various possible industries, when determining toward which industries competition authorities should focus the allocation of resources, it would be more efficient to allocate greater resources toward the monitoring of industries with demadn or supply factors (or both) observed as having a significant relationship to cartel formation. $ ^{11} $