1992, Taylor, Alan M.

1992-03, Nicolini, Juan Pablo

1997-07, Frankel, Jeffrey A., Schmukler, Sergio L.

1992, Tohmé, Fernando

This paper explores the determinants of rm survival in export markets. Our theoretical framework includes a geometric Brownian motion for rm pro tability, market-speci c sunk and xed exporting costs that are common across rms, and rm- and market-speci c pro tability shifters that are constant over time. We derive the probability of survival upon entry in an export market. We show that this probability increases with the ratio of sunk to xed costs and is insensitive to the pro tability shifters. Also, we show that the survival probability is una ected by xed costs if sunk costs are zero. Combining our theoretical results with observed patterns of survival among Argentine exporters, we infer the impact of distance and experience on the magnitude of sunk and xed costs. In our data set, survival rates upon entry decrease with distance and increase with experience. Hence, we infer that xed costs increase more with distance than sunk cost while xed costs fall with experience su ciently strongly to dominate the fall in sunk costs. These results carry implications on parametrizations of theoretical models of export dynamics and serve as a benchmark to assess structural estimates of xed and sunk costs.

We herein introduce a new method of interpretable clustering that uses unsu- pervised binary trees. It is a three-stage procedure, the rst stage of which entails a series of recursive binary splits to reduce the heterogeneity of the data within the new subsamples. During the second stage (pruning), consideration is given to whether adjacent nodes can be aggregated. Finally, during the third stage (join- ing), similar clusters are joined together, even if they do not share the same parent originally. Consistency results are obtained, and the procedure is used on simulated and real data sets.