probably also endogenous, but we do not take explicit measures with them because their returns lie beyond our research questions. Time and individual fixed effects, however, tackle issues of omitted variables for all independent variables, decreasing bias of all estimated coefficients.

Given that firms construct their knowledge stock by investing in innovation activities, these decisions are very likely endogenous to firms’ productivity, and exogeneity of regressors cannot be assumed. Unobservable omitted variables such as know-how the firms’ workers possess, or the quality of managerial capabilities could affect both firms’ decisions regarding innovation and firms’ productivity. In addition, while larger knowledge stocks may increase firm productivity, more productive firms are more likely to be exposed to and aware of innovation opportunities. Hence, these firms may be more prone to investing in innovation and increasing their knowledge stock than less productive firms, causing reverse causality issues.

We tackle time-invariant omitted variables—both observable and unobservable—by exploiting the panel structure of our data with the inclusion of firm and time fixed effects, as has been done in other papers using ENDEI survey databases (see, for example, Brambilla and Tortarolo (2018)). We also explore an instrumental variable (IV) approach to estimate the returns of R&D over productivity. Claiming exogeneity of variables coming from our own ENDEI database is questionable and the restrictions to merge other potential instruments from external sources at the firm level due to ENDEI’s confidentiality issues limits our analysis. However, it is important to try to minimize potential biases due to the endogeneity. Next, we describe the IV strategy and present the best IV candidates. As we shall see, the instruments proposed are statistically strong and exogenous, but the results of the IV estimation differ sharply from those of our panel data estimation, which raises questions about the accuracy of the point estimates.

Our first IV candidate is a dummy variable on firm’s _knowledge_ about the existence of public support programs for innovation activities offered by the Ministry of Science and Technology (Ministerio de Ciencia y Tecnología). This variable has been implemented in previous empirical studies that use information from innovation surveys in Argentina (see, for example, Brambilla and Tortarolo (2018), de Elejalde, Giuliodori, and Stucchi (2011). The condition of relevance is expected to be fulfilled because firms that know about public programs are candidates to use it, and therefore have a higher investment in innovation activities. The exclusion condition is justified considering that this dummy variable measures _knowledge_ about the program rather than firms’ participation. The latter can be correlated with other variables that may affect firm ́s productivity, given that the provision of public funds is sometimes based on firm performance. On the other hand, knowledge of the program greatly depends on public and private publicity for the program, which we can assume is random and uncorrelated with other firm characteristics.

Our second IV candidate exploits a pseudo-panel built by merging the two waves of the ENDEI survey. Although we cannot match firms across waves, we proceeded to match them at the sector-region-size level.<sup>20</sup> An essential reason for choosing this IV candidate is that there was a change in government in Argentina in December 2015.During the ENDEI 1 period (2010– 12) and the first two years of the ENDEI 2 period (2014–15), the leading political party differed

> 20 This is possible given that samples were constructed to be representative of the Argentinean manufacturing sectors (by industry-size). However, because ENDEI 1 was not constructed to be representative at the regional level, we could not divide the sample into the same regions as ENDEI 2. We therefore made an ad hoc split of the sample considering that cases were relatively balanced: “Region” is taken as a dichotomous variable signaling whether the firm belongs to the Gran Buenos Aires region (comprising Ciudad de Buenos Aires and the main adjacent districts in Buenos Aires Province) or to the rest of the country.

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