Macroeconomic analysis in Lebanon presents a distinct challenge. For example, long delays in the publication of GDP data mean that our analysis often relies on proxy variables, and resembles an extended version of the 'nowcasting' challenge familiar to many central banks. Addressing this...

We examine the role of global and domestic shocks in driving macroeconomic fluctuations for Ghana. We are able to study the impact of exogenous shocks including productivity, credit supply, and commodity price shocks. We identify the shocks with a combination of sign and recursive restrictions...

Over the past two decades, U.S. core PCE goods and services inflation have evolved differently. Against the backdrop of global concerns of low inflation, we use this trend as motivation to develop a bottom-up model of U.S. inflation. We find that domestic forces play a larger role relative to...

We leverage insights from machine learning to optimize the trade off between bias and variance when estimating economic models using pooled datasets. Specifically, we develop a simple algorithm that estimates the similarity of economic structures across countries and selects the optimal pool of...

We develop a framework to nowcast (and forecast) economic variables with machine learning techniques. We explain how machine learning methods can address common shortcomings of traditional OLS-based models and use several machine learning models to predict real output growth with lower forecast...

Forecasting macroeconomic variables is key to developing a view on a country's economic outlook.Most traditional forecasting models rely on fitting data to a pre-specified relationship between inputand output variables, thereby assuming a specific functional and stochastic process underlying...

We produce a social unrest risk index for 125 countries covering a period of 1996 to 2020. The risk of social unrest is based on the probability of unrest in the following year derived from a machine learning model drawing on over 340 indicators covering a wide range of macro-financial,...

This study documents a semi-structural model developed for Sri Lanka. This model, extended with a fiscal sector block, is expected to serve as a core forecasting model in the process of the Central Bank of Sri Lanka's move towards flexible inflation targeting. The model includes a...

This paper presents the Systemic Risk and Interconnectedness (SyRIN) tool. SyRIN allows a comprehensive assessment of systemic risk via quantification of the impact of risk amplification mechanisms, due to interconnectedness structures across banks and other financial intermediaries-insurance,...

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,...