on final goods, as defined by the United Nations’ Broad Economic Categories classification system.<sup>10</sup> We also use data on tariff rates by importing country-partner country-HS6 product-year level from WITS-TRAINS. For any given product, we use preferential tariff rates when country pairs are engaged in preferential trade agreements and most-favored nation tariff rates otherwise.<sup>11</sup> For each importing/destination country in Latin America, denoted _d_ , the resulting database includes information about the import value _yodpt_ from each exporting/origin country _o_ of each final good _p_ in each year _t_ , along with the different _NTMdpt_ measures and tariff rates in force in the importing country. Appendix Table A1 provides summary statistics on all key variables based on our final data set.

To understand the role of firm exit and market concentration, we use firm-level customs transaction data sets obtained as part of the expansion of the Exporter Dynamics Database described in Fernandes et al. (2016) covering the universe of firm-level export transactions in each country. We construct four indicators capturing competitive dynamics in each distinct _export market_ that we define to be an exporting country-destination country-HS 6-digit product-year cell: the number of exporters, an indicator for an export monopolist, and the concentration of sales across exporters within that market. The indicator for an export monopolist is equal to one if the market is controlled by a single exporter. Concentration is measured by the Herfindahl–Hirschman Index (HHI) which equals the sum of squared exporter market shares for firms within a market multiplied by 10,000.<sup>12</sup> The export marketbased indicators are constructed for all countries covered by the export customs transaction data in the period 1996-2017 for their exports to the 16 Latin American countries for which we have NTM data.<sup>13</sup> As an example, for Bangladesh, one of the countries with export customs data, we measure the concentration across firms of exports of cotton t-shirts (HS 610910) to Chile and, distinctly, the concentration across firms of exports of cotton t-shirts

> 10We exclude intermediate inputs for two reasons: first, the tradeoff between compliance costs and information benefits—the key mechanism governing the impact of quality regulation—is difficult to model for intermediate inputs; and second, although intermediate inputs account for a larger share of global trade than final goods, they constitute a much smaller share of non-tariff measures.

> 11The assumption used to handle missing WITS-TRAINS tariff data for some importing countries in certain years is to apply the rates from the closest earlier year with available data.

> 12An HHI of 10,000 indicates the product is exported by a monopolist with market share equal to 100 percent of bilateral exports from the exporting country to a given destination country in a year.

> 13The exporting countries are: Albania, Burkina Faso, Bangladesh, Bulgaria, Bolivia, Botswana, Chile, China, Cˆote d’Ivoire, Colombia, Costa Rica, Dominican Republic, Ecuador, Egypt, Ethiopia, Gabon, Georgia, Guinea, Guatemala, Croatia, India, Iran, Jordan, Kenya, Cambodia, Lao, Lebanon, Sri Lanka, Morocco, Madagascar, Mexico, North Macedonia, Myanmar, Mauritius, Malawi, Nicaragua, Nepal, Pakistan, Peru, Paraguay, Senegal, El Salvador, Thailand, Tanzania, Uruguay, South Africa, and Zambia. The time periods of the customs data sets vary across countries. The export customs data is such that for each of the 16 Latin American importing countries, we capture exports by firms from only a _subset_ of exporting countries (those with customs data).

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