Fang, Li <br/><br/>
Agglomeration and innovation:  Selection or true effect?/ 

 -  Sage,   2020. 
 - Vol. 52, Issue 2, 2020 ( 423–448 p.) 
<br/><br/> This paper separates two mechanisms through which agglomeration increases average firm innovation: selection (less innovative firms being forced out of agglomerations) and true agglomeration (firms become more innovative). I apply a quantile regression to estimate the distribution of firm innovation and separate these two mechanisms. Linking a unique establishment-level dataset with the patent dataset in the state of Maryland for the period 2004–2013, I find that a 1-mile radius area with above-median employment concentration significantly encourages firm innovation. An average establishment that files for at least one patent during the study period increases citation-weighted patent applications by 31.2% to 31.5% in such employment centers. I also find evidence of selection: non-innovators are 1.3% less likely to survive in agglomerations. The coexistence of agglomeration and selection causes the result of an ordinary least squares regression to be upwardly biased. By eliminating the selection effect, this study more precisely estimates the agglomeration effect, which can be applied to cost–benefit and cost-effectiveness analyses of urban and industrial policies.