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Informal business activity is ubiquitous around the world, but it is nearly always uncaptured by administrative data, registries, or commercial sources. For this reason, there are rarely adequate sampling frames available for survey implementers wishing to measure the activity and characteristics of the sector. This article applies a well-established sampling method for rare and/or clustered populations, Adaptive Cluster Sampling (ACS), to a novel population of informal businesses. Generally, it shows that efficiency gains through the application of ACS, when compared to Simple Random Sampling (SRS), are large, particularly at higher levels of fieldwork effort. In particular, ACS efficiency gains over SRS remain sizable at higher values of initial starting samples, but with comparatively high expansion thresholds, which can reduce the fieldwork effort. [ABSTRACT FROM AUTHOR]

This paper uses a unique, comparable firm-level dataset covering more than 80 developing middle-income economies to provide a novel set of stylized facts on firms engaging in international trade, focusing on the Middle East and North Africa ( MENA) region. We show that firms in MENA are more likely to export and/or import than their counterparts elsewhere. However, we only find the expected positive and significant productivity premia for exporters outside of MENA. While MENA's larger exporters are indeed more productive than non-exporters, a large share of exporters - the comparatively low-volume ones - are not. We also confirm positive and significant size and productivity premia for manufacturers that import only, with productivity premia in MENA at least double of those in middle-income economies elsewhere. In contrast, we find no size or productivity premia for MENA's manufacturers that export, but do not import. These patterns are consistent with substantial distortions in the relative fixed and variable costs of trading, likely a reflection of selectively applied policies. [ABSTRACT FROM AUTHOR]