population of non-agricultural firms within each country.<sup>4</sup> The BEEPSs contain both qualitative and quantitative information about the firms and the business environment where they operate. We exploit the sections of the surveys that focus on the business perceptions about the most relevant obstacles to investment, the relative importance of different constraints to boosting employment and productivity, and the effects of the country-specific environment on firms’ international competitiveness.

To ensure comparability across countries and over time, we convert in US dollar at constant prices the values of the variables of interest from the BEEPS expressed in local currencies. The WDI and GDF provide exchange rate time series and estimates of the GDP deflator used to convert the nominal time series in real terms. The use of the GDP deflator implies that the inflation rate has been constant across sectors in a given country and during a specific year. The use of sectorspecific price indexes for each ISIC sector would be preferable but these series are not available for the countries we study. We account for country-specific factors such as general economic conditions with GDP (constant 2000 US$), likelihood to obtain credit with the number of commercial bank branches (per 100,000 adults), domestic credit provided by banking sector (% of GDP), and the extra-cost of borrowing (lending rate minus deposit rate, %).

The United Nations Statistics Division (UNSD) manages the National Accounts Estimates of Main Aggregates that report the gross value added at constant prices (in USD) by country and sector for all the years and countries in the BEEPS. The TPIS data set reports bilateral export volumes and we can then estimate the demand shocks based on the strategy proposed by Coulibaly, Sapriza, and Zlate (2012). The authors construct an index of demand as a function of the firms’ exports-to-sales ratio, the sector-specific exposure to various foreign destinations, and real GDP growth across destinations as a proxy for the change in demand. We provide details regarding the construction of these indices in Section 3.1.

# **3 Empirical Analysis**

Firms in our sample constitute a representative sample of non-agricultural firms in 27 ECA countries. On average, they have been operative for 15 years and are middle-sized with less than 100 employees (Table 1). They tend to be liquidity constrained based on both the subjective and objective measures, and operate in a relatively volatile macroeconomic environment as indicated by the fact that domestic GDP fluctuates from _−_ 4 _._ 5% up to +25%. Only 26% of the firms in the sample export to foreign markets, and they tend to make relatively small shares of their total sales abroad (11%).

The panel nature of the data also provides important insights from the cross-country and time variations. For example, in Kazakhstan firms’ exports amount to only 3% of total sales, while in

> tia, Czech Republic, Estonia, Former Yugoslavian Republic of Macedonia (FYRM), Georgia, Hungary, Kazakhstan, Kyrgyz Republic, Latvia, Moldova, Montenegro, Poland, Romania, Russian Federation, Serbia, Slovak Republic, Turkey and Ukraine.

> 4In the 2002 and 2005, the sample is self-weighted, while in 2009 and 2013 firms are sampled randomly with replacement according to sector of activity, firm size, and geographical location strata.

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