Financial crises pose unique challenges for forecast accuracy. Using the IMF’s Monitoring of Fund Arrangement (MONA) database, we conduct the most comprehensive evaluation of IMF forecasts to date for countries in times of crises. We examine 29 macroeconomic variables in terms of bias, efficiency, and information content to find that IMF forecasts add substantial informational value as they consistently outperform naive forecast approaches. However, we also document that there is room for improvement: two thirds of the key macroeconomic variables that we examine are forecast inefficiently and 6 variables (growth of nominal GDP, public investment, private investment, the current account, net transfers, and government expenditures) exhibit significant forecast bias. Forecasts for low-income countries are the main drivers of forecast bias and inefficiency, reflecting perhaps larger shocks and lower data quality. When we decompose the forecast errors into their sources, we find that forecast errors for private consumption growth are the key contributor to GDP growth forecast errors. Similarly, forecast errors for non-interest expenditure growth and tax revenue growth are crucial determinants of the forecast errors in the growth of fiscal budgets. Forecast errors for balance of payments growth are significantly influenced by forecast errors in goods import growth. The results highlight which macroeconomic aggregates require further attention in future forecast models for countries in crises.

We document information rigidity in forecasts for real GDP growth in 46 countries over the past two decades. We investigate: (i) if rigidities are lower around turning points in the economy, such as in times of recessions and crises; (ii) if rigidities differ across countries, particularly between advanced countries and emerging markets; and (iii) how quickly forecasters incorporate news about growth in other countries into their growth forecasts, with a focus on how advanced countries‘ growth forecasts incorporate news about emerging market growth and vice versa.

We consider simple methods to improve the growth nowcasts and forecasts obtained by mixed frequency MIDAS and UMIDAS models with a variety of indicators during the Covid-19 crisis and recovery period, such as combining forecasts across various specifications for the same model and/or across different models, extending the model specification by adding MA terms, enhancing the estimation method by taking a similarity approach, and adjusting the forecasts to put them back on track by a specific form of intercept correction. Among all these methods, adjusting the original nowcasts and forecasts by an amount similar to the nowcast and forecast errors made during the financial crisis and following recovery seems to produce the best results for the US, notwithstanding the different source and characteristics of the financial crisis. In particular, the adjusted growth nowcasts for 2020Q1 get closer to the actual value, and the adjusted forecasts based on alternative indicators become much more similar, all unfortunately indicating a much slower recovery than without adjustment and very persistent negative effects on trend growth. Similar findings emerge also for the other G7 countries.

In this paper, I take a talk show in which Coen Teulings, then Director of the official Dutch Bureau for Economic Forecasting and Policy Analysis (CPB) was interviewed about its economic forecasts in the immediate aftermath of the financial crisis of 2008 as point of entry into an examination into how personal experience and judgment enter, and are essential for, the production and presentation of economic forecasts. During the interview it transpired that CPB did not rely on its macroeconomic models, but on personal experience encapsulated in “hand-made” monitors, to observe the unfolding crisis; monitors that were, in Teulings' words, used to “feel the pulse” of the Dutch economy. I will take this metaphor as a cue to present several historical episodes in which models, numbers, and a certain feel for economic phenomena aimed to make CPB economists' research more precise. These episodes are linked with a story about vain attempts by CPB director Teulings to drive out the personal from economic forecasting. The crisis forced him to recognize that personal experience was more important in increasing the precision of economic forecasts than theoretical deepening. The crisis thus both challenged the belief in the supremacy of theory driven, computer-based forecasting, and helped foster the view that precision is inevitably linked to judgment, experience and observation, and not seated in increased attention to high theory; scientifically sound knowledge proved less useful than the technically unqualified experiential knowledge of quacks.