An Illustrated User Guide to the World Input–Output Database: The Case of Global Automotive Production
By M. Timmer, E. Dietzenbacher, B. Los, Robert Stehrer, G. D. de Vries. 2015
2,383 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/28926df0a8402abf19859e3d6c2e236ba171b6e8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
In Environmental Engineering
In Renewable Energy, Sustainability and the Environment
- Zhu Liu
- D. Guan
- Joseph B. Steinberg
- David H. Autor
- A. Salomons
- Michael Pfaffermayr
- Manfred Lenzen
- Jing Meng
Citations in the corpus
- Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030 (2017, background): “The upper bound of its growth rate was 6% in 2010, as the average growth rate of China’s CO2 emissions was approximately 6% from 1995 to 2009 (Timmer et al., 2015).”
- Quantifying the daily economic impact of extreme space weather due to failure in electricity transmission infrastructure (2017, methodology): “To align with the most recent World Input-Output Database (WIOD) statistics [Timmer et al., 2015] used in the next steps of the method, 2011 data are selected for the analysis [World Input-Output Database, 2016].”
- Networks of Value Added Trade (2017, positive): “Timmer et al. (2015) describe in detail the contents of this database and illustrate its potential to examine different aspects of the international fragmentation of production. b. Defining the Networks The construction of a network requires the identification of a set of nodes and a criterion for…”
- The rise of robots and the fall of routine jobs (2020, methodology): “21 This data is obtained from the WIOD 2016 release ( Timmer et al. 2015 ).”
- Gravity models, PPML estimation and the bias of the robust standard errors (2019, methodology): “Using the cross-section data from WIOD (Timmer et al. 2015) 42 economies and estimating a standard gravity model specified as Model 3 in the next section for a random sample of 21 economies (441 country pairs) exhibits a maximum leverage of 0:995 and the minimum leverage amounts to 0:004.”
- To RAS or not to RAS? What is the difference in outcomes in multi-regional input–output models? (2016, methodology): “…www.oecd.org/trade/valueadded © 2016 The International Input–Output Association (Lenzen et al., 2012b, 2013), the model by Nakano et al. (2009), EXIOBASE (Tukker et al., 2009), World Input-Output Database (WIOD) (Timmer et al., 2015) and global resource accounting model (GRAM) (Wiebe et al., 2012).”
- Measuring (2019, neutral): “The variables mentioned above could be classed as situational variables, but there is another category which may be less likely to act via attitude.”