Related Experiment Video
Updated: Mar 14, 2026

09:34
Implementation of Portable Emissions Measurement Systems PEMS for the Real-driving Emissions RDE Regulation in Europe
Published on: December 4, 2016
29.0K
Data on industrial new orders for the euro area
Gabe J de Bondt1, Heinz C Dieden1, Sona Muzikarova1
1European Central Bank, Frankfurt am Main, Germany.
Data in Brief
|October 5, 2016
Summary
This data article presents euro area industrial new orders time series data. The dataset includes total new orders and breakdowns, utilizing national data and European Central Bank (ECB) estimates.
Area of Science:
- Economics
- Econometrics
- Industrial Economics
Background:
- Euro area industrial new orders data is crucial for economic analysis.
- Previous research has focused on modeling these trends.
- Consistent and reliable time series data is essential for accurate economic forecasting.
Purpose of the Study:
- To provide a comprehensive time series dataset on euro area industrial new orders.
- To support research on economic modeling and analysis of industrial activity.
- To offer a standardized data resource with a fixed base year for comparability.
Main Methods:
- Data compilation from official national sources and European Central Bank (ECB) model estimates.
- Calculation of euro area aggregates using a weighting scheme based on industrial turnover statistics.
- Data presented in index format with a fixed base year (2010) for total new orders and breakdowns.
Main Results:
- A time series dataset of euro area industrial new orders is made available.
- The dataset covers total new orders and various sub-categories.
- Data incorporates both directly collected national statistics and ECB model-based estimates.
Conclusions:
- The provided dataset serves as a valuable resource for researchers and policymakers.
- It enables consistent analysis of industrial new orders across the euro area.
- The data facilitates further investigation into the drivers and implications of industrial new orders.
Related Concept Videos
Econometric Views (EViews)
649
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
649
Orders of Magnitude
27.9K
The order of magnitude of a number is the power of 10 that most closely approximates it. Thus, the order of magnitude estimates the scale (or size) of its value. To find the order of magnitude of a number, take the base-10 logarithm of the number and round it to the nearest integer. Then the order of magnitude of the number is simply the resulting power of 10.
The order of magnitude is simply a way of rounding numbers consistently to the nearest power of 10. This makes doing rough mental math...
The order of magnitude is simply a way of rounding numbers consistently to the nearest power of 10. This makes doing rough mental math...
27.9K
Indicators
61.9K
Certain organic substances change color in dilute solution when the hydronium ion concentration reaches a particular value. For example, phenolphthalein is a colorless substance in any aqueous solution with a hydronium ion concentration greater than 5.0 × 10−9 M (pH < 8.3). In more basic solutions where the hydronium ion concentration is less than 5.0 × 10−9 M (pH > 8.3), it is red or pink. Substances such as phenolphthalein, which can be used to determine the pH of a solution, are...
61.9K
Steel Manufacturing
1.7K
Steel manufacturing is a multi-stage process that begins by smelting iron ore into cast iron in a blast furnace. This initial stage involves layering iron ore with coke, a type of fuel, and crushed limestone within the furnace. The coke is ignited with a high volume of air, leading to the creation of carbon monoxide, which acts to reduce the iron ore to pure iron.
During this smelting process, limestone plays a crucial role by forming slag. Slag captures impurities within the molten iron, such...
During this smelting process, limestone plays a crucial role by forming slag. Slag captures impurities within the molten iron, such...
1.7K
Pie Chart
16.9K
A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
16.9K
Statistical Methods for Analyzing Epidemiological Data
1.1K
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
1.1K

