To explore whether exogenous risks reduce growth, or whether the direction of causality runs the other way with recessions increasing uncertainty, Baker and Bloom (2012) examine the impact on GDP growth of over 1,000 unanticipated exogenous shocks for 60 countries, both developed and developing, since 1970. Their identifying assumption is that some shocks, like natural disasters, lead primarily to a change in stock-market levels so are more first-moment shocks, while other shocks like political coups lead more to changes in stock-market volatility, implying they are more second-moment shocks. They find a significant causal impact of both first and second moment shocks on growth: in the quarter following a shock, they estimate that a one standard deviation reduction in stock-market levels and a one standard deviation increase in stock-market volatility each lead to a 1.9% reduction in GDP; and in the year following the shock, they estimate larger effects, with the same changes leading to falls in annual GDP growth of 2.8% and 6.3%, respectively. So both first and second moment shocks have a significant negative impact on growth, with second moment effects having equal or higher impact. To explore the extent to which these results differ across countries, they first include interactions with being a “rich” country, defined as being above the sample-average GDP per capita of $25,000, and find no significant effect – suggesting that shocks have the same impact on rich and poor countries alike. However, the higher frequency of disaster shocks in developing countries implies that the greater uncertainty there has more negative effects on growth and other variables. In addition, they find that less financially developed countries and those with stricter labor regulations<sup>7</sup> have a significantly larger negative impact of uncertainty shocks (with no difference in response to first-moment shocks) – suggesting that incompleteness of financial markets and rigidities in labor markets are two important channels for the impact of risk on firms.

An important part of the plant-specific risks faced by firms, at least in the US, appears to be due to the greater degree of innovations and creative destruction in some industries relative to others. To develop a better understanding of the cross-industry variation of plant-level idiosyncratic shocks, Castro, Clementi and Lee (2011) examine annual US manufacturing data over the 25 year period 1972-97.<sup>8</sup> They find considerable variation in idiosyncratic risk across industries: plants in the most volatile industries are subject to at least 3 times as much risk as plants in the least volatile.<sup>9</sup> To explore why certain industries have so much greater variation in the growth of productivity, they propose that the heterogeneity in idiosyncratic risk is driven by the differential extent to which creative destruction shapes competition risks/illness of the workforce, resource risks, geopolitical risk and social unrest/strikes, infrastructure risks, other economic, financial, and regulatory risks, and changing trends over time in technology and tastes. Bloom (2009) highlights the importance to policymakers of distinguishing between the more persistent first-moment effects and the more temporary second-moment effects of major shocks (with the increased volatility of “uncertainty shocks” typically generating a rapid and costly slowdown followed by a bounce-back in enterprise investment, hiring and productivity growth). Endogenous risks are _voluntary_ resource reallocation and innovation investments firms take in the pursuit of opportunities for better expected rates of return.

7 Their measure of financial development is generated by the World Economic Forum (ranking countries according to the strength of their financial markets and the depth and breadth of access to capital and financial services), while the labor regulation measure is the World Bank’s Doing Business indicator of the strictness of hiring, firing and contract change regulations.

8 Their data are comprised of 50-70,000 plants per year distributed over 140 three-digit industries 9 Their proxy for risk is the volatility of the portion of Total Factor Productivity (TFP) growth which cannot be forecast by means of factors, either known or unknown to the econometrician, that are systematically related to plant dynamics(which is not explained by either industry- or economy-wide factors, or by plants’ characteristics systematically associated with changes in TFP itself): the volatility of TFP growth due to idiosyncratic shocks ranges from 4% for producers of fur goods to 12.4% for manufacturers of computer equipment.

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