Quantifying macroeconomic uncertainty in Norway

This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the uncertainty forecasts. This approach helps provide deeper insights into the macroeconomic uncertainty surrounding forecasts than more traditional time-series models, where uncertainty is usually symmetric and with limited time-variation. Formal tests, such as the log score and the Continuous Ranked Probability Score (CRPS), show that using informative indicators tend to improve density forecasts, particularity in the medium run.publishedVersio

A SMARTer way to forecast

In this paper we describe the newly developed System for Model Analysis in Real Time (SMART) used for forecasting and model analysis in Norges Bank. While the long-term goal is to include all empirical models used in forecasting in Norges Bank, the emphasis in this paper will be on the empirical model systems for inflation and GDP. SMART builds on Norges Bank’s previous System for Averaging short-term Models (SAM), but with greater flexibility and a richer set of models. In addition, SMART contains a real-time database with a wide-ranging set of historical data, forecasts from empirical models, Norges Bank’s forecasts from Monetary Policy Reports (MPR) and forecasts from other institutions (e.g. Statistics Norway). Overall, SMART seems to provide good forecasts and will be a useful tool in the monetary policy process.publishedVersio

A high-frequency financial conditions index for Norway

We have constructed a financial conditions index for Norway (FCIN). The FCIN offers a daily update on Norwegian financial conditions based on data from January 2003 on bank lending rates, bond spreads, the foreign exchange market, the stock market and the housing market. The index is constructed by the use of principal component analysis and has an average value of zero and a standard deviation of one. A positive value indicates that financial conditions are tighter than the historical average, while a negative value suggests that financial conditions are looser than the historical average. The FCIN is constructed to provide real time insight into financial conditions for the Norwegian economy beyond what is already included in the policy rate and market policy rate expectations. Here we depart from other studies which typically aim at assessing financial conditions more broadly. The index is meant to complement monetary policy analyses and improve our assessments of economic activity.publishedVersio

Quantifying macroeconomic uncertainty in Norway

This paper presents a framework for quantifying uncertainty around point forecasts for GDP, inflation and house prices in Norway. The framework combines quantile regressions using a broad set of uncertainty indicators with a skewed t-distribution, allowing for time-variation and asymmetry in the uncertainty forecasts. This approach helps provide deeper insights into the macroeconomic uncertainty surrounding forecasts than more traditional time-series models, where uncertainty is usually symmetric and with limited time-variation. Formal tests, such as the log score and the Continuous Ranked Probability Score (CRPS), show that using informative indicators tend to improve density forecasts, particularity in the medium run

A SMARTer way to forecast

In this paper we describe the newly developed System for Model Analysis in Real Time (SMART) used for forecasting and model analysis in Norges Bank. While the long-term goal is to include all empirical models used in forecasting in Norges Bank, the emphasis in this paper will be on the empirical model systems for inflation and GDP. SMART builds on Norges Bank's previous System for Averaging short-term Models (SAM), but with greater flexibility and a richer set of models. In addition, SMART contains a real-time database with a wide-ranging set of historical data, forecasts from empirical models, Norges Bank's forecasts from Monetary Policy Reports (MPR) and forecasts from other institutions (e.g. Statistics Norway). Overall, SMART seems to provide good forecasts and will be a useful tool in the monetary policy process