We explore how trading networks among commercial real estate brokerage firms are formed, and the effects of network structure on centrality, assortativity and power in the six largest commercial real estate markets in the United State. Fitting the dynamic network formation model developed by Jackson and Rogers American Economic Review, 97(3), 890-915, (2007) to U.S. commercial real estate transaction data (2003–2016), we calculate the importance of network search relative to random search for commercial real estate brokerage firms. We observe that in general approximately 67% of trades of commercial properties are made through network searches. Network search is more important during the global financial crisis (2008–2010). The trading networks also show geographic heterogeneity as network search is most important in Chicago (79.7%), but relatively less important in Boston and Los Angeles (56.2% and 58.2%). Finally, brokerage firms with many trading partners are more likely to trade with those with fewer partners (negative assortativity) creating conditions for power asymmetry between firms.

我们探讨了如何在商业房地产经纪公司之间形成交易网络，以及网络结构对美国六个最大的商业房地产市场的集中度，分类性和实力的影响。拟合由杰克逊和罗杰斯（Jackson and Rogers）开发的动态网络形成模型，《美国经济评论》，97年（3），890-915，（2007）对美国商业房地产交易数据（2003-2016）的计算，相对于商业房地产经纪公司的随机搜索，我们计算了网络搜索的重要性。我们观察到，一般而言，大约67％的商业地产交易是通过网络搜索进行的。在全球金融危机期间（2008-2010年），网络搜索更为重要。交易网络还显示出地理异质性，因为网络搜索在芝加哥最为重要（79.7％），而在波士顿和洛杉矶则相对不那么重要（56.2％和58.2％）。最后，拥有许多贸易伙伴的经纪公司更有可能与拥有较少贸易伙伴的经纪公司进行交易（负分类），从而为公司之间的权力不对称创造了条件。