The Unassuming Economist

The FT cites my new working paper with Zidong An and Joao Jalles:

“Recessions are not rare,” echoed Prakash Loungani, a macro-economist at the IMF. “What is rare is a recession that is forecast in advance.” Despite an increased amount of economic data being available, “the ability to predict downturns remains dismal”, he told the FT.”

[…]

The fact that forecasts are “typically over-optimistic for horizons beyond the current year” is not necessarily the result of economist optimism. They “fail to forecast strong booms, just as they fail to predict recessions,” said Mr Loungani, suggesting that economic forecasts “are too rooted in thinking that things stay close to normal or will revert to normal soon”.

[…]

“The IMF’s April outlook is often more accurate. This is because it is easier to get a forecast right for the current year than the following year. The April report is better able to signal a recession for the current year than the October publication, “but one that is much milder than what transpires”, says Mr Loungani, author of several studies.”

Continue reading here.

R package for M4 Forecasting Competition – Hyndsight (Rob Hyndman’s Blog)

2018 & 2019 Economic Outlook for the Top Oil Producing Countries – Focus Economics

Big Data and Economic Nowcasting – No Hesitations (Frank Diebold’s Blog)

The Poorest Countries in the World – Focus Economics

STILL MORE on NN’s and ML – No Hesitations (Frank Diebold’s Blog)

Use and misuse of information in supply chain forecasting of promotion effects – IIF Blog

ML, Forecasting, and Market Design – No Hesitations (Frank Diebold’s Blog)

Emerging Markets 2018 Economic Outlook – Focus Economics

Averaging for Prediction in Econometrics and ML – No Hesitations (Frank Diebold’s Blog)

Economic Goodness-of-Fit – Dave Giles’ Blog

Forecasting global economic growth in 2018 – Brookings

Comparing Interval Forecasts – No Hesitations (Frank Diebold’s Blog)

How do you forecast? Practitioners’ insights needed – IIF Blog

From an interview article by Damian Carrington:

“Ashattering collapse of civilisation is a “near certainty” in the next few decades due to humanity’s continuing destruction of the natural world that sustains all life on Earth, according to biologist Prof Paul Ehrlich.

In May, it will be 50 years since the eminent biologist published his most famous and controversial book, the Population Bomb. But Ehrlich remains as outspoken as ever.

The world’s optimum population is less than two billion people – 5.6 billion fewer than on the planet today, he argues, and there is an increasing toxification of the entire planet by synthetic chemicals that may be more dangerous to people and wildlife than climate change.

Ehrlich also says an unprecedented redistribution of wealth is needed to end the over-consumption of resources, but “the rich who now run the global system – that hold the annual ‘world destroyer’ meetings in Davos – are unlikely to let it happen”.

[…]

More of Paul and Anne Ehrlich’s reflections on their book are published in The Population Bomb Revisited.”

From a new post by Aakash Mankodi and Tim Pike:

“Tetlock and Gardner’s acclaimed work on Superforecasting provides a compelling case for seeing forecasting as a skill that can be improved, and one that is related to the behavioural traits of the forecaster. These so-called Superforecasters have in recent years been pitted against experts ranging from U.S intelligence analysts to participants in the World Economic Forum, and have performed on par or better by accurately predicting the outcomes of a broad range of questions. Sounds like music to a central banker’s ears? In this post, we examine the traits of these individuals, compare them with economic forecasting and draw some related lessons. We conclude that considering the principles and applications of Superforecasting can enhance the work of central bank forecasting.

[…]

With continuous forecasting challenges on the horizon in coming years, perhaps it is an opportune time to incorporate these ideas in the central banking sphere. Economic forecasting will always be an imperfect science. So while it is unlikely that a major shock such as the global financial crisis would have been averted by improving the accuracy of forecasting efforts in these ways, we believe the lessons learnt through the experiment of Superforecasting have a lot to offer to take forecasting a step forward in that direction.  Potentially over time, we might be able to create a next generation of central bank Superforecasters.”

From a new IMF working paper:

“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.”