Exporter Dynamics, Firm Size and Growth, and Partial Year Effects

Bernard, Andrew B.; Massari, Renzo; Reyes, José-Daniel; Taglioni, Daria

doi:10.1596/1813-9450-6711

Cited by 17 publications

(17 citation statements)

References 29 publications

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“…Existing evidence indicates that a regression of firm growth rates on firm size and age yields statistically and economically significant coefficients on both indicating that growth decreases with firm age (keeping size constant) and size (keeping age constant). The same statistical relationship has been suggested for exporting sales (see Eaton et al (2008) and Albornoz et al (2009)), but recently Bernard et al (2014) has pointed out an important aggregation bias that renders information on the growth of new exporters unreliable. In particular, if exporting sales start late in the calendar year, the recorded growth Note: In all data the outlier observations of growth rates of more than 900% or less than -90% are excluded and entrants are dropped.…”

Section: Density Of Growth Ratessupporting

confidence: 61%

A Unified Theory of Firm Selection and Growth *

Arkolakis

2016

The Quarterly Journal of Economics

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This paper develops an analytical framework to study firm and exporter growth and provides a dynamic foundation for a standard general equilibrium trade model.Firm-level growth is the result of idiosyncratic productivity improvements and there is continuous arrival of new potential producers. A firm enters a market if it is profitable to incur the marginal cost to reach the first consumer and pays an increasing marketing cost to reach additional consumers. I calibrate the model using data on the cross section of firm sales and bilateral trade, as well as the rate of incumbent firm exit. The calibrated model predicts that a firm's growth is inversely related to its initial size and that the distribution of growth rates of small firms is heavily skewed to the right. These predictions are confirmed by looking at the growth of sales of US firms and Brazilian exporters to the US. I use this model to study the impact of cross-firm reallocations on economic activity and measured productivity. JEL codes: F12, L11, M31, D92. * I am grateful to Timothy Kehoe, Samuel Kortum, Cristina Arellano, Jonathan Eaton as well as Giuseppe Moscarini for their insightful comments and discussions on this topic. I am also indebted to Marc Muendler for providing me with moments from the Brazilian data, and Jose Mata for providing me with the estimates for Portuguese firms. For their suggestions and comments, I would also like to thank Andy Atkeson,

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Section: Density Of Growth Ratessupporting

confidence: 61%

A Unified Theory of Firm Selection and Growth *

Arkolakis

2016

The Quarterly Journal of Economics

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“…Over the period, the firmmarket specific beliefs have been characterized by a slightly positive growth. 18 18 Note that the 'calendar year effect' pointed out by Berthou and Vicard (2014) and Bernard et al (2014) is likely to bias upwards the growth rate between the first and second years, because of the potential incompleteness of the first year of export measured over the calendar year. When measuring age by bins as in our estimations, the dummy for year two gets rid of the average bias.…”

Section: Resultsmentioning

confidence: 99%

Demand Learning and Firm Dynamics: Evidence from Exporters

Berman

Rebeyrol

Vicard

2019

The Review of Economics and Statistics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract: This paper provides evidence that learning about demand is an important driver of firms' dynamics. We present a simple model with Bayesian learning in which firms are uncertain about their idiosyncratic demand parameter in each of the markets they serve, and update their beliefs as noisy information arrives in each period. The model predicts that firms update more their beliefs following a new demand shock, the younger they are. To test this learning mechanism, we make use of a specific feature of exporter-level data which contains both the values and the quantities sold by a given firm for the same product in different destination markets. This allows us to derive a methodology that identifies separately the demand shocks faced by the firms and their beliefs about future demand. We find strong support for our main prediction: The updating process appears especially strong in the first years after entry. However, the bulk of accumulated knowledge is lost during short periods of exit. Second, we consider implications of this prediction for firm growth rates and survival. Consistent with the learning model, we find that: (i) the absolute value of the mean growth rate for firms' beliefs decreases with age, as does the variance within cohorts; (ii) exit probability decreases with firms' beliefs and the demand shock the firm faces. Further, demand shocks trigger more exit in younger cohorts. Terms of use: Documents inJEL classification: L11, L25, F12, F14.

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“…As Bernard et al (2013) show a good amount of growth identified between years one and two of an exporting spell may be a statistical anomaly. Since our data are recorded on an annual basis, it is possible that the first year volume is based on shipments during a fraction of the calendar year, while the second year volume is based on a full year's worth of shipments.…”

Section: Calculating Growth Rates Using the Midpoint Formulamentioning

confidence: 93%