fluctuations are not coincident.<sup>12</sup> For this very reason, it is important to look at how investment responds to uncertainty at the decision-making level where the relationship is expected to be more robust. Driven by this, there is a simultaneous effort to bring micro data into the analysis. Leahy and Whited (1996) use stock price volatility of US manufacturing firms to measure firm-specific uncertainty and find a weak negative correlation. Going a step further Driver, Yip and Dakhil (1996) bring plant-level data into analysis and document a significant negative association using volatility in market shares. On the other hand, Guiso and Paragi (1999) measure firm-specific uncertainty from firms’ own perceptions and find that investment undertaken by a firm declines when it perceives its demand to be more uncertain. Demir (2009) also uses firm-level data to find a negative relationship for firms in the real sector in Argentina, Mexico and Turkey. More recently, the investigation has tried to highlight the short-term effects of uncertainty on investment which are potentially much larger than long-term effects (Bloom, Bond and Van Reenen (2001, 2007)).

Our investigation is motivated by the deep literature in the investment-uncertainty nexus. We posit that private investment in the FCV economies like Afghanistan remains depressed because of an extreme business environment where numerous risks abound. The main finding of our econometric exercise is that firms that make investment expenditures or participate in the formal financial sector are more likely to realize losses related to crime and corruption, as well as perceive them to be severe obstacle to operation. We interpret this relationship as evidence that returns to investment, as well as reaping benefits of other instruments, are reduced making firms less likely to operate efficiently. Within the theoretical literature this can be seen as persistent weakness in investment rate due to expected returns being lower than the threshold rate (Dixit (1989, 1992)). Rodrik (1991) is an early application of this approach where policy uncertainty has the potential to act as a “hefty tax on investment”, thereby depressing investment. Though we model these _taxes_ on firms’ sales, it is isomorphic to levy them on capital expenditures. We also highlight the systematic variation of these _taxes_ with firm size which we argue is a summary measure of firm productivity based on related research.

In the second part of our analysis, we aim to quantify the aggregate economic impact of business risks and uncertainty in Afghanistan. Our aim is to highlight the losses from the resource misallocation channel which often gets overlooked in quantitative exercises of this nature. There is a growing literature that argues that the distribution of available resources across heterogeneous production technology can have a sizeable impact on aggregate output (Hsieh and Klenow (2009), Restuccia and Rogerson (2008)). Building on this, many papers have documented a positive association between firm size and distortions in various settings.<sup>13</sup> To the best of our knowledge though, Bah and Lang (2015) is the only paper that

> 12 See Bernanke (1983) for a discussion on why microeconomic fluctuations might not cancel at the aggregate.

> 13 For an earlier application see Guner, Ventura and Xu (2008) and Gopinath _et. al._ (2017) for a more recent one. Restuccia and Rogerson (2013) present a survey of this emerging literature.

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