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...

Starting with the year of 2020 pandemic, the world has entered a testing period for the economy (Nicola et al., 2020). It has been three years since the Covid-19 began, and the misalignment of the timing of the pandemic and its spread (Kuckertz et al., 2020), combined with the misalignment of...

Medium-term budgetary frameworks are institutional arrangements at national level intended to improve official forecasts in EU member states. The influence of those frameworks on official forecasts of output growth and the budget balance ratio in 24 EU member states over the years 2008 to 2019...

The mainstream analytical methods of modern economics, such as the Solow model, impose a limitation on the historical interpretation of sources and the future projection of economic growth potential in a transitional country like China, as the model assumes scenarios that are inconsistent with...

For about three decades, the Japanese economy suffered a prolonged phase of economic stagnation but may have started, in late 2019, to emerge from this state with the implementation of Abenomics in late 2012 or early 2013. Abenomics consisted of “three arrows”, namely aggressive monetary...

Probabilistic forecasts such as quantiles are essential inputs to decision-making under uncertainty. The most common type of forecasts often comes in the form of point forecasts, and it is therefore necessary for the decision maker to construct uncertainty measures around the obtained point...

This paper provides a bibliometric account of the International Journal of Forecasting across the Journal’s first 35 years. We identify publication patterns, namely the volume of published research, co-authorship, internationalization, prolific authors, institutions, and countries. We also...

We evaluate the performance of the penalized vector autoregression (VAR), diffusion index (DI), and regression tree-based ensemble learning models to forecast Singapore's macroeconomy using high-dimensional data. Our dataset consists of 220 monthly time series that capture the economy of...

I evaluate whether incorporating sub-national trends improves macroeconomic fore-casting accuracy in a deep machine learning framework. Specifically, I adopt a computer vision setting by transforming U.S. economic data into a ‘video’ series of geographic ‘images’ and utilizing a...

We propose two types of equal predictive ability (EPA) tests with panels to compare the predictions made by two forecasters. The first type, namely S-statistics, focuses on the overall EPA hypothesis which states that the EPA holds on average over all panel units and over time. The second,...

The paper describes the "Halle Institute for Economic Research (IWH) Forecasting Dashboard (ForDas)". This tool aims at providing, on a non-commercial basis, historical and actual macroeconomic forecast data for the Germany economy to researchers and interested audiences. The database renders it...

We have studied the relationship between Receiver Operating Characteristics (ROC) and Precision-Recall Curve (PRC) both analytically and using a real-life empirical example of yield spread as a predictor of recessions. We show that false alarm rate in ROC and inverted precision in PRC are...

The recovery of the global economy from the Covid crisis came to an end in 2022 amid high energy prices and great uncertainty. While the energy crisis is easing, the effects of monetary policy, which was tightened rather late but then very quickly, are now increasingly weighing on growth. World...

After the US dollar replaced gold, the US debt became the attention worldwide, thus the demand for the US dollar continued, furthermore the extremely low interest of the dollar. This helped the US government to borrow great amounts of debt as well as kept the creditors pleased. Due to the...

This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1–2019Q4. The adaptive learning...

We develop an agent-based model for the euro area that fulfils widely recommended requirements for next-generation macroeconomic models by i) incorporating financial frictions, ii) relaxing the requirement of rational expectations, and iii) including heterogeneous agents. Using macroeconomic and...

Stock prices declined abruptly in the wake of the Covid-19, reflecting both the deterioration of investors’ expectations of economic activity as well as the surge in risk aversion. In the following months, however, economic activity remained sluggish while equity markets bounced back. This...

We apply functional data analysis to survey expectations data, and show that functional principal component analysis combined with functional regression analysis is a fruitful way of capturing the effects of others' forecasts on a respondent's inflation forecasts. We estimate forward-looking...

This study tries to predict as accurately as possible CDS risk premia for BRICS countries by utilizing state-of-the-art recurrent neural network architectures. These are ELMAN, NARX, GRU, and LSTM RNNs in the time series setting, taking into account both local and global features. The predictive...

The Chinese economy upheld a frail recovery in 2022 under the triple superposition of contraction of demand, disruption in supply, and weakening expectations, aggravated by unanticipated adverse shocks in the midst of global turmoil. Over the year, rising income uncertainty set off by the...

Nordrhein-Westfalen ist wie Gesamtdeutschland in einer wirtschaftlichen Krisensituation. Schon im ersten Halbjahr 2022 war das Wirtschaftswachstum leicht unter dem Bundestrend, ähnlich zur Situation der anderen großen Flächenländer. Die Einschätzungen der Unternehmen sind für das Jahr 2023...

In der vorliegenden Studie werden zunächst die weltweiten konjunkturellen Aussichten für das Ende des Jahres 2022 und für die Jahre 2023 bis 2027 dargestellt. Dabei wird folgender Länderkreis betrachtet: Deutschland, Frankreich, Griechenland, Großbritannien, Irland, Italien, Niederlande,...

This paper examines the role of a country's data transparency in explaining gross domestic product growth forecast errors. It reports four sets of results that have not been previously reported in the existing literature. First, forecast errors-the difference between forecasted and realized...

Commodity windfalls and private consumption have sustained Indonesia's growth despite a difficult global environment, but signs of normalizing domestic demand are emerging. Inflation is easing at a faster pace than markets anticipated. Indonesia's external vulnerabilities remain moderate. The...

Against a backdrop of debt ratio targets being central to recent proposed changes to the EU fiscal rules, we examine errors in official forecasts of the General Government debt ratios and their determinants in 26 member states from 2012 to 2019 when the "six pack" rules applied. We find debt...

I use Bayesian VARs to forecast global temperatures anomalies until the end of the XXI century by exploiting their cointegration with the Joint Radiative Forcing (JRF) of the drivers of climate change. Under a ‘no change’ scenario, the most favorable median forecast predicts the land...

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...

VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We extend the VAR framework by modeling interest rates as censored observations of a latent shadow-rate process,...