International Monetary Fund. Asia and Pacific Dept
The coronavirus disease (COVID-19) pandemic is still unfolding around the globe. In Asia, as elsewhere, the virus has ebbed in some countries but surged in others. The global economy is beginning to recover after a sharp contraction in the second quarter of 2020, as nationwide lockdowns are lifted and replaced with more targeted containment measures.
International Monetary Fund. Middle East and Central Asia Dept.
Countries in the Middle East, North Africa, Afghanistan, and Pakistan (MENAP) region and those in the Caucasus and Central Asia (CCA) responded to the COVID-19 pandemic with swift and stringent measures to mitigate its spread and impact but continue to face an uncertain and difficult environment. Oil exporters were particularly hard hit by a “double-whammy” of the economic impact of lockdowns and the resulting sharp decline in oil demand and prices. Containing the health crisis, cushioning income losses, and expanding social spending remain immediate priorities. However, governments must also begin to lay the groundwork for recovery and rebuilding stronger, including by addressing legacies from the crisis and strengthening inclusion.
We find that countries which are able to borrow at spreads that seem low given fundamentals (for example because investors take a bullish view on a country's future), are more likely to develop economic difficulties later on. We obtain this result through a two-stage procedure, where a first regression links sovereign spreads to fundamentals, after which residuals from this regression are deployed in a second stage to assess their impact on future outcomes (real GDP growth and the occurrence of fiscal crises). We confirm the relevance of past sovereign debt mispricing in several out-of-sample exercises, where they reduce the RMSE of real GDP growth forecasts by as much as 15 percent. This provides strong support for theories of sentiment affecting the business cycle. Our findings also suggest that countries shouldn't solely rely on spread levels when determining their fiscal strategy; underlying fundamentals should inform policy as well, since historical relationships between spreads and fundamentals often continue to apply in the medium-to-long run.
The widespread availability of internet search data is a new source of high-frequency information that can potentially improve the precision of macroeconomic forecasting, especially in areas with data constraints. This paper investigates whether travel-related online search queries enhance accuracy in the forecasting of tourist arrivals to The Bahamas from the U.S. The results indicate that the forecast model incorporating internet search data provides additional information about tourist flows over a univariate approach using the traditional autoregressive integrated moving average (ARIMA) model and multivariate models with macroeconomic indicators. The Google Trends-augmented model improves predictability of tourist arrivals by about 30 percent compared to the benchmark ARIMA model and more than 20 percent compared to the model extended only with income and relative prices.