Y Yedid-Levi, S Haller, and D Fitzgerald (2017) (How Exporters Grow)

The authors of this paper use confidential Irish data to document 4 novel facts about the lifecycle of exporting firms and then combine two existing modeling pieces to builds a partial equilibrium model that can reconcile the reported facts.

Data

The authors use two confidential micro data sets from Ireland:

1. The Irish census of industrial production
2. Irish custom records

They are able to link the datasets to build a panel dataset at the firm-product-destination market level.

Empirics

The main empirical exercise is to determine how one of log revenue, log quantity, or log price varies with both the firm-product duration in a particular market and the length of a firm-product-market export spell. The export spell is defined as the number of consecutive periods a firm exports a particular product to a particular market. Note that in the regressions this is a constant number for the entire spell, while the export tenure rises from 1 to the duration of the spell.

The authors also control for destination market fixed effects and firm-product-year fixed effects.

There are 4 key results from the estimation:

1. Quantities grow dramatically in the first five years of successful export spells, defined as spells that last at least seven years. This growth is statistically significant up to a horizon of four years and is not driven purely by part-year effects in the first year (i.e. there is economically and statistically significant growth between years 2 and 4).
2. Within successful export spells, there are no statistically or economically significant dynamics in prices.
3. Higher initial quantities predict longer export spells: for spells lasting between one and four years, all pairwise comparisons of initial quantities are statistically different.
4. Initial prices do not predict export spell length.

The authors do a number of robustness checks and report that the results are qualitatively unchanged when the data is cut differently or other controls are used.

Model

I now turn to the model. The use of the model is not as interesting or enlightening as the components themselves, so I will focus my discussion on why they made the assumptions they did.

The authors make a quick note that common supply-side tricks for generating revenue and size dynamics (productivity shocks, capital adjustment costs, capacity or financial constraints, market-specific cost shocks, etc.) have a difficult time generating the observed dynamics in quantity without introducing dynamics in prices. For this reason they choose to focus on demand-side features that can generate dynamics.

They choose two of the more common demand side bells and whistles to include in their model:

1. Learning about unobserved idiosyncratic shocks.
2. Consumer capital: firms build up a consumer base that deprecates over time and add consumers by direct investment in marketing or other costly acquisition methods.

After estimating the model with simulated method of moments (targeting moments about revenues and quantities over export spells), the authors show that the model can match all 4 of the key facts.

They also show that both learning and consumer capital are necessary in their framework. To do this they remove one at a time, re-estimate the model, and show that the model generates price dynamics.