BFS 2002

Contributed Talk

Matching and the estimated impact of interlisting

Ryan Davies

Using trade and quote data for Toronto Stock Exchange listed securities, this paper employs nonparametric estimation to measure the effect of being interlisted on a US exchange on the percentage bid-ask spread (and other trading properties). Unlike previous studies, I use kernel-based matching estimates in addition to variants of the standard nearest-neighbor approach for constructing matched samples of interlisted stocks and non-interlisted stocks. I explore the sensitivity of results to: (i) using different bandwidth parameters and caliper-matching criteria; (ii) using different matching characteristics; (iii) the exclusion/inclusion of firms. I highlight instances when kernel-based and nearest-neighbor matching estimation techniques produce significantly different results.