stock and will thus prefer to wait or even attempt to disinvest from their existing stock. Therefore, exporters, and particularly those focusing on sales of goods that are hard to resell, should expect a further reduction in trade if the importer uncertainty is accompanied with a major hit to the real economy.

To summarize, based on guidance from previous literature we expect the following parameters to matter for the aggregate response of trade in the downturn and in the recovery. First, importer uncertainty should matter more for exporters than domestic uncertainty. Second, the size of the shock should also matter, with a potentially non-linear effect. Third, liquidity constraints and large adjustments in wealth, that tend to accompany major uncertainty shocks, will be aggravating the contraction of expenditures. Finally, the adjustment costs should also matter. We expect that countries specialized in goods entailing high adjustment costs (such as durables or investment goods) should experience an heightened impact of uncertainty on exports. Exports of non-durables on the other hand could potentially be boosted due to the fact that consumers have a higher disposable income that they can devote to these goods, due to the savings on durable goods.

# **3 Producer and consumer uncertainty: VAR analysis**

As a preliminary test of the hypotheses outlined above we focus on US data and conduct a vector autoregression (VAR) analysis analogous to that of Bloom (2009). He estimates a standard VAR model that includes stock market volatility used as a proxy for uncertainty and the following additional variables: the S&P500 stock market index, federal funds rate, average hourly earnings, consumer price index, hours in manufacturing, employment in manufacturing and industrial production. His sample covers the period June 1962 to June 2008 which comprises seventeen uncertainty shocks that are depicted in Figure 1. For reasons discussed in Section 4.2 of this paper he works with a stock market volatility based measure of uncertainty. Rather than working with stock market volatility explicitly he chooses to only work with periods of exceptional uncertainty during which the measured volatility exceeded the mean by at least 1.65 times the standard deviation. The identification of the uncertainty shock is achieved through a standard Cholesky decomposition with the uncertainty shocks ordered after the stock market index so that the effect of the stock market is already accounted for when looking at the effect of the uncertainty shocks.

In order to extend Bloom’s analysis, which only focuses on the impact of uncertainty of production, we augment this baseline VAR in several ways. To assess the impact of uncertainty shocks on consumption we add consumption expenditures in the model. To further disentangle the effects of consumer uncertainty, we split the consumption expenditures into a durable and non-durable component. Finally, as the focus of this paper is on international trade, we augment the VAR with monthly import and export levels. Given that many uncertainty periods occur at times of major financial constraints and stock market crashes we also take a brief look at the impact of these effects on our variables of interest. We use the same dataset as in Bloom (2009). Additional variables, not included in Bloom’s dataset, are taken from the Federal Reserve Economic Data (FRED) of the St. Louis Fed.

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