# 1. Introduction

Does innovation spur productivity? Griliches (1986) famously argued that innovation accounts for a sizeable portion of productivity growth, as changes in capital and labor alone can explain only half of it. By introducing new products, processes, or managerial practices, innovation would lead to improved uses of capital and labor, enabling firms to enter new markets and grow. Indeed, Porter and Millar (1985) argue that information and communication technology (ICT) may improve the accuracy and efficiency of production and help upgrade operational and production processes. Yet not everyone agrees with this view. Robert Solow coined the term “productivity paradox” in reference to the lack of apparent productivity gains when ICT technologies were largely adopted in the 1970s and 1980s.<sup>2</sup> These apparent contradictions are reconciled by Cirera and Maloney (2017). They document that the “innovation paradox” can be explained by the fact that complementary physical and human capital factors, chiefly firm managerial capabilities, are critical to reap the returns to innovation investments. This empirical evidence echoes insights from Acemoglu et al. (2006): limited firms’ capabilities and distance from the technological frontier can explain low incentives to adopt innovation and weak productivity growth.

Also, timing issues may affect the ability to uncover the positive impact of innovation on productivity. There may be a delay between the introduction of new technologies and the realization of productivity improvements. From a within-firm perspective, Brynjolfsson et al. (2019) argue that adapting pre-existing production processes to new technologies is not necessarily smooth and quick. Technology adoption in developing countries may require substantial reorganization of production, hence it is slow and its contribution to productivity requires time to realize (Juhász et al.,2020). From an economy-wide perspective, Gort and Klepper (1982) postulate that rapid product innovation yields a surge in entry, a period of significant experimentation followed by a shakeout period when unsuccessful enterprises wither and exit while successful developers and firms grow. Pioneering a new methodology, Foster et al. (2018) provide some empirical support to this hypothesis for the U.S.<sup>3</sup> 2 In a 1987 interview by the New York Times, Solow is quoted saying: “[...] what everyone feels to have been a technological revolution, a drastic change in our productive lives, has been accompanied everywhere, including Japan, by a slowing-down of productivity growth, not by a step up. You can see the computer age everywhere but in the productivity statistics.” (New York Times, July 12, 1987, p. 36)

> 3 The authors use low-frequency firm-level data for the entire U.S. private sector and infer whether innovation took place by looking at firms’ entry dynamics. Building on Gort and Klepper (1982), spikes in entry could be interpreted as proxy of innovation in the previous period. Foster et al. (2018) document that a surge in productivity in high-tech sectors in the late 1990s is a strong contributor of the increased within-industry covariance between market share and productivity (i.e., firms whose productivity has grown in previous period gain market share). This surge in productivity is associated with higher entry and within-industry productivity dispersion, and high productivity growth in high-tech sectors, all elements that could be reconciled with an increase in innovation. In line with the Gort and Klepper (1982) hypothesis, they also find that the post-2000s period has seen a decline in entry and a high-tech productivity slowdown driven by lower within-firm productivity growth and smaller covariance between market share and productivity. In contrast with Gort and Klepper (1982), they also find increased within-industry productivity dispersion, which is even greater for young (instead of mature) firms.

2