We analyze the causes of the apparent bias towards optimism in growth forecasts underpinning the design of IMF-supported programs, which has been documented in the literature. We find that financial variables observable to forecasters are strong predictors of growth forecast errors. The greater the expansion of the credit-to-GDP gap in the years preceding a program, the greater its over-optimism about growth over the next two years. This result is strongest among forecasts that were most optimistic, where errors are also increasing in the economy’s degree of liability dollarization. We find that the inefficient use of financial information applies to growth forecasts more broadly, including the IMF’s forecasts in the World Economic Outlook and those produced by professional forecasters compiled by Consensus Economics. We conclude that improved macrofinancial analysis represents a promising avenue for reducing over-optimism in growth forecasts.
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.
This 2019 Article IV Consultation with the Republic of Croatia discusses that it experienced its fifth consecutive year of solid economic growth, once again driven largely by private consumption and tourism. Employment gains have been robust, wages have continued to rise, while import prices have helped to keep inflation muted. Increased absorption of European Union funds is likely to raise public investment in the coming years. In conjunction with continued strong consumption, the current account surplus is expected to decline, and turn into a moderate deficit, while economic growth moderates. Both public and external indebtedness are expected to continue their declining trajectories. The pace of fiscal consolidation in 2019 continued to slow, with the budget estimated to be close to balance. Contingent liabilities could also pressure budget balances in the coming years.
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.