Im Projekt t+20 des Statistischen Bundesamtes wurden Methoden untersucht, um Konjunkturindikatoren für das Verarbeitende Gewerbe beschleunigt bereitzustellen. Der Einsatz mikrodatenbasierter Modelle, darunter Imputationsmethoden und Maschinelles Lernen, sowie eines makrodatenbasierten...

Im Projekt t+20 des Statistischen Bundesamtes wurden Methoden untersucht, um Konjunkturindikatoren für das Verarbeitende Gewerbe beschleunigt bereitzustellen. Der Einsatz mikrodatenbasierter Modelle, darunter Imputationsmethoden und Maschinelles Lernen, sowie eines makrodatenbasierten...

Timely updates of business cycle fluctuations-commonly represented by movements in the output gap-help policymakers make informed decisions on the appropriate course of action. Unfortunately, business cycle assessments often suffer from lags in actual gross domestic product data releases. This...

This paper explores the application of machine learning (ML) techniques to nowcast the monthly year-over-year growth rate of both total and non-primary GDP in Peru. Using a comprehensive dataset that includes over 170 domestic and international predictors, we assess the predictive performance of...

This paper focuses on identifying useful indicators for nowcasting GDP in Sweden. We analyze 35 monthly indicators spanning the period from 1993 to 2023. Additionally, we evaluate the group-wise performance of these indicators. The analysis is conducted using mixed-data sampling (MIDAS) and...

We analyse the accuracy of an econometric model for nowcasting GDP growth in a true real-time setting. The analysis is based on a unique sample of nowcasts that were produced in real time and stored. Our results support the use of econometric models for nowcasting because the accuracy of these...

This paper examines online search activity's ability to capture consumers' intentions and enhance short-term forecasting of key economic outcomes. Economic decisions such as consumption and investment are typically preceded by intentions, which, while difficult to observe directly, often...

We analyse the accuracy of an econometric model for nowcasting GDP growth in a true real-time setting. The analysis is based on a unique sample of nowcasts that were produced in real time and stored. Our results support the use of econometric models for nowcasting because the accuracy of these...

This paper examines online search activity's ability to capture consumers' intentions and enhance short-term forecasting of key economic outcomes. Economic decisions such as consumption and investment are typically preceded by intentions, which, while difficult to observe directly, often...

Timely updates of business cycle fluctuations-commonly represented by movements in the output gap-help policymakers make informed decisions on the appropriate course of action. Unfortunately, business cycle assessments often suffer from lags in actual gross domestic product data releases. This...

This paper explores the application of machine learning (ML) techniques to nowcast the monthly year-over-year growth rate of both total and non-primary GDP in Peru. Using a comprehensive dataset that includes over 170 domestic and international predictors, we assess the predictive performance of...

This paper focuses on identifying useful indicators for nowcasting GDP in Sweden. We analyze 35 monthly indicators spanning the period from 1993 to 2023. Additionally, we evaluate the group-wise performance of these indicators. The analysis is conducted using mixed-data sampling (MIDAS) and...

This paper introduces the Trade Policy Activity (TPA) Index, a novel indicator measuring evolving global trade policy dynamics since the Global Financial Crisis. Using a Dynamic Factor Model on comprehensive trade policy data covering 197 countries and territories, we document a structural shift...

This paper provides a detailed assessment of the real‐time forecast accuracy of a wide range of vector autoregressive models that allow for both structural change and indicators sampled at different frequencies. We extend the literature by evaluating a mixed‐frequency time‐varying...

Large language models have expanded their application from traditional tasks in natural language processing to several domains of science, technology, engineering, and mathematics. This research studies the potential of these models for financial "nowcasting"-real-time forecasting (of the recent...

Die Armutsgefährdungsquote, ein zentraler Indikator zur Analyse der Einkommensverteilung, gewinnt im Kontext wirtschaftlicher Prognosen zunehmend an Bedeutung. Die jüngsten Krisen, darunter die COVID-19-Pandemie und der Ukraine-Krieg, sowie staatliche Hilfsmaßnahmen haben die...

This paper introduces a novel monthly consumption indicator: the IZA/Fable Swipe consumption index for Germany. It is based on credit card transactions data collected and anonymised by Fable Data from 2017 onwards. We study some of the properties of the data and use a so-called "one year look...

This paper introduces a novel monthly consumption indicator: the IZA/Fable Swipe consumption index for Germany. It is based on credit card transactions data collected and anonymised by Fable Data from 2017 onwards. We study some of the properties of the data and use a so-called 'one year look...

The paper compares two forecasts of Slovak GDP, the first with high-frequency data and the second without them. We utilize the last observation from the economic activity index acting as a short-term GDP forecast. We use data from 2000 to 2024 in weekly frequencies and have 27 variables related...

This paper introduces the Trade Policy Activity (TPA) Index, a novel indicator measuring evolving global trade policy dynamics since the Global Financial Crisis. Using a Dynamic Factor Model on comprehensive trade policy data covering 197 countries and territories, we document a structural shift...

This paper investigates the feasibility of using earlier provisional data to improve the now- and forecasting accuracy of final and official statistics. We propose the use of a multivariate structural time series model which includes common trends and seasonal components to combine official...

The European Commission's growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a...

This paper introduces a novel monthly consumption indicator: the IZA / Fable Data consumption indicator for Germany. It is based on credit card transactions data collected and anonymised by Fable Data from 2017 onwards. We study some of the properties of the data and use a so-called ”one year...

This paper introduces a novel monthly consumption indicator: the IZA / Fable Data consumption indicator for Germany. It is based on credit card transactions data collected and anonymised by Fable Data from 2017 onwards. We study some of the properties of the data and use a so-called "one year...

In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...

Der Außenhandel der österreichischen Volkswirtschaft zählt zu jenen Wirtschaftsbereichen, in denen die Öffentlichkeit und die Wirtschaftspolitik von zusätzlichen zeitnahen Indikatoren profitieren. Die monatlichen Daten der offiziellen Außenhandelsstatistik zu den Warenexporten und...

Survey data can offer timely information on the current state of the economy and its short-term outlook. In this paper, we propose a "Swiss Economic Confidence Index" (SEC). This is a monthly indicator based on aggregating a selection of individual survey indicators, which we show to have...

Economic indicators provide important information for the evaluation of the state of the economy of a country and they are used for business cycle analysis. Timeliness of the indicators is of fundamental interest for analysts of government authorities, national banks, politicians or economic...

In this study, we analyzed the forecasting and nowcasting performance of a generalized regression neural network (GRNN). We provide evidence from Monte Carlo simulations for the relative forecast performance of GRNN depending on the data-generating process. We show that GRNN outperforms an...

The European Commission’s growth forecasts play a crucial role in shaping policies and provide a benchmark for many (national) forecasters. The annual forecasts are built on quarterly estimates, which do not receive much attention and are hardly known. Therefore, this paper provides a...

This research introduces an innovative GDP nowcasting strategy tailored for developing countries, specifically addressing challenges related to limited data timeliness. The study centers on Bolivia, where the official monthly indicator of economic growth is released with a substantial delay of...