estimated impact of domestic uncertainty (as measured by the EPU) on domestic investment is highly significant.

**C. Spillovers from the United States, the Euro Area, and China** . In order to quantify spillovers from an output slowdown in the United States and the Euro Area, a Bayesian structural vector autoregression is estimated for 1998Q1–2016Q2, using weighted average data for 18 EMDEs. The sample includes Brazil, Bulgaria, Chile, Costa Rica, Hungary, India, Indonesia, Malaysia, Mexico, Paraguay, Peru, Philippines, Poland, Romania, Russia, South Africa, Thailand and Turkey. The regression includes, in this Cholesky ordering: weighted average output growth in major advanced economies and China (excluding either the United States or the Euro Area), U.S. or Euro Area output growth, proxies for global financial conditions (U.S. 10‐year sovereign bond yield and JP Morgan’s EMBI index), and aggregate output growth or investment growth in EMDEs (excluding China). To conserve degrees of freedom, oil price growth is included as an exogenous regressor in the model. A similar estimation is applied to estimate the impact of a slowdown in China’s output or investment growth on EMDE output growth. The regression includes, in this Cholesky ordering: weighted average output growth in major advanced economies, proxies for global financial conditions (U.S. 10‐year sovereign bond yield and JP Morgan’s EMBI index), China’s output growth or China’s non‐investment growth and China’s investment growth, and output growth in EMDEs (excluding China). The oil price is again included as exogenous regressor.

**D. Crowding‐in of private investment by public investment** . A vector autoregression is conducted to estimate crowding‐in of private investment by public investment for eight EMDEs with available data for 1998Q1‐2016Q2. A decomposition of investment into private and public investment is only available for a restricted sample of EMDEs. The sample includes Bulgaria, Czech Republic, Hungary, Mexico, Poland, Romania, Slovak Republic, and Turkey. These countries are highly open and rank above the EMDE average in the World Bank Doing Business indicators. Variables included are, in this ordering: real government investment, real GDP, real private investment, current account balance, and the real effective exchange rate. The results are statistically significant within the usual 16‐84 percent confidence bands.

**E. Investment growth and reforms** . Values in columns of Figure 19 are based on a panel data regression in which the dependent variable is real investment growth. A spurt (setback) is defined as a two‐year increase (decrease) by two standard deviations in one or more of the following four measures of the Worldwide Governance Index (WGI): regulatory quality, government effectiveness, rule of law, and control of corruption. The WGI indicators are principal components of a wide range of survey based and other indicators. For each index, the standard deviation is measured as the average of the standard errors of the WGI Index in the beginning and at the end of each two‐year interval. Episodes in which there were improvements in one measure and simultaneous setbacks in another are excluded. The sample spans 97 EMDEs over 1996 ‐ 2015, and excludes EMDEs with populations less than 3 million.

Let t denote the end of a two‐year spurt or setback. The coefficients are dummy variables for spurts and setbacks over the [t‐3, t+2] window around these episodes. In Figure 19, “Reform” denotes the t=[‐1,0] window (i.e., around the two years of improvement/deterioration). All coefficients show the investment growth differential of economies during an episode compared to those that experienced neither improvements nor setbacks. All estimates include time‐fixed effects to control for global common shocks ‐ ‐ and country‐fixed effects to control for time invariant heterogeneity at the country level. Robust standard error estimates during the reform spurt window are jointly significant at the ten percent level (Annex Table 2.1).

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