endogeneity and missing variables that would better capture demand effects, a correct identification of causality between dependent and independent variables and supply versus demand effects is no simple matter. Thus, the supply side perspective often fails to sufficiently account for the growth implications of the recurrent macro and trade shocks and large demand fluctuations (both domestic and external) that have dominated LA’s growth history.<sup>6</sup> Similarly, at the firm level, the Hsieh and Klenow (2009) conclusion that differences between firms in revenue-based TFP measures reflect resource misallocations is critically dependent on the strong assumption that firms face iso-elastic demand functions. As shown by Restuccia and Rogerson (2017) and Haltiwanger, Kulick and Syverson (2018), and as illustrated in the model of Appendix I, it is only under this assumption that differences in revenue between firms using similar factors of production can be uniquely associated with resource misallocations. Moreover, the research inspired in the Hsieh and Klenow approach typically assumes that firms within the same industry do not compete based on different mark-ups associated with product quality differences. As a result, the higher revenues of a firm with the same factor usage as another are attributed solely to higher productive efficiency. But under less restrictive assumptions, firms with similar factors could have different revenues not only because of differences in efficiency but also because of differences in demand leading to differences in mark-ups (hence in prices) due to differences in quality and product appeal (see Appendix I for a simple overview; and Cusolito and Maloney, 2018, for a deeper discussion based on a comprehensive survey of the literature).<sup>7</sup> As a result, the supply side perspective tends to understate the growth relevance of “what” is produced, that is, of differences in the broad categories of goods being produced—tradable and nontradable, commodities, manufactures or services—as well as in the quality of individual goods produced within these categories.<sup>8</sup> Yet quality changes or lags in quality improvements can quickly translate into major shifts in demand that deeply affect firm growth but are hard to measure.<sup>9</sup> 6 While there is an important literature on the growth impairment effects of macro-financial volatility in Latin America—see, for instance, IDB (1995), Calvo (1998), and Mendoza (2010)—this literature has few direct linkages with the growth literature. For its part, the growth literature’s lack of connections with potentially key explanatory demand factors leads to puzzling enigma such as the difficulty in explaining Mexico’s lack of growth when only supply side factors are considered and China’s impact on the demand for Mexican exports is ignored.

7 For example, Canales and Garcia Marin (2018) find that 80 percent of the growth of high performing firms in Chile reflects increased demand rather than efficiency gains.

8 By focusing on economic complexity and the capabilities that support it, Hausmann et al (2007) provide one of the most visible and well-known cases in favor of the growth relevance of “what” is produced.

9 Lederman and Maloney (2012) argue that “how” goods are produced matters more than “what” is produced. However, their conceptual understanding of the “how” is congenial with our “what” and associated emphasis on the role of demand. Lederman and Maloney’s “how” not only captures efficiency and creativity in the use and combination of resources (including knowledge) within suitable production technologies, but also managerial and technological innovations geared at responding to demand, for instance, by upgrading product design with a view to raise quality and appeal as needed to seize and develop market niches with auspicious demands. Importantly, Lederman and Maloney recognize that moving from concept to empirics is not a simple matter, not least because of the difficulty in adequately measuring quality (the “what”) based on the 3- to 6-digit classifications available in trade statistics.

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