We explore the determinants of export survival for a panel of Georgian firms between 2006 and 2012. The data set contains detailed information on firms’ balance sheets matched with Customs data on exports disaggregated at the six-digit HS level. The key feature of our matched firm-export data is that we can look at the role of product and sector characteristics while simultaneously control for firm heterogeneity, by incorporating important elements such as total factor productivity, size and ownership. We analyze how different firm, product, sectors and country characteristics influence export survival.

We analyze survival at the firm-product-destination level. A product-destination export spell is defined as a period when a firm continuously exports a given product to a particular destination country. Products are defined at the HS six-digit level. An important choice relates to the exact period of time used to classify an export spell. In this paper we use a three-year period, following Gorg et al. (2012). A spell is considered completed only if the firm did not export that product for three consecutive years before starting again. An alternative option would have been to use a one year definition, considering a spell as completed if the firm stops exporting the product for at least one year. However, short breaks of one year in the export flow can be caused by different factors not necessarily indicating the end of the trade relationship. Moreover, our firm-level data set is characterized by a high degree of firms’ entry and exit implying that a less restrictive spell definition is desirable.

For spells starting in 2006 we do not know the exact starting year of the transaction, they are leftcensored. Left-censoring can potentially bias the results so we exclude left-censored spells from the estimation. A second form of censoring concerns spells that in 2010 are still active. These spells are right-censored as we cannot determine when they will eventually end. Right censoring does not represent a problem for the estimation and such spells can be included in the analysis.

The problem of censoring is amplified by the unbalanced nature of the panel in which firms enter and exit at different times and sometimes have gaps between the first and last appearance in the panel. In cases where gaps in the panel for a given firm are exactly the year before (after) the beginning (end) of a spell we are again unable to observe the exact duration of the spell. We treat these spells as either left or right censored dropping from the analysis only the left censored.

We use a discrete survival model for the main estimation. Discrete survival models have been indicated as the best solution available to analyze trade dynamics given the nature of trade data (Brenton et al. 2010; Hess and Persson 2010). In particular, trade data is recorded at yearly intervals and this violates one of the main assumptions of continuous time survival models. They also partly relax the quite stringent assumption of proportional hazard, which characterizes continuous time survival models.

Discrete survival models describe the probability that an export spell terminates given that it has not terminated before as a function of time and other covariates. If _T_ is the discrete random variable indicating the time period _j_ when the export spell terminates for a randomly selected firm we can define the discrete time hazard as the conditional probability that the firm stops exporting 12