This page provides access to data used or produced in my research. Please ask me for any data that is not on this website.
Data and Stata code used in our paper about short-run dynamics of carbon dioxide emissions:
Burke, P. J., M. Shahiduzzaman, and D. I. Stern (2015) Carbon dioxide emissions in the short run: The rate and sources of economic growth matter, Global Environmental Change 33, 109-121.
This is a 1MB zip file hosted on Dropbox:
Data used in my paper about predicting citations in the social sciences:
Stern D. I. (2014) High-ranked social science journal articles can be identified from early citation information, PLoS ONE.
This is a 14MB Excel workbook hosted on the ANU Data Repository:
Data used in my paper about standard errors for economics journal impact factors:
Stern D. I. (2013) Uncertainty measures for economics journal impact factors, Journal of Economic Literature 51(1), 173-189.
This is an 8MB Excel workbook hosted on Figshare:
Data as used in our recent paper on Granger testing for the causes of climate change. The paper has details of sources and calculations:
Stern D. I. and R. K. Kaufmann (2014) Anthropogenic and natural causes of climate change, Climatic Change 122, 257-269.
The main worksheet is in the correct format for RATS.
This data is described in:
Stern D. I. (2012) Modeling international trends in energy efficiency, Energy Economics 34, 2200-2208.
The paper presents graphs of the time series of the distances for some countries. Data for all countries is in the file linked below. The methods are explained in the paper. A distance of one (or log of zero) implies that a country is just on the frontier as estimated using averaged data for the entire 1971-2007 period. Countries can have time series values below zero (or a distance of less than one) because they may reach levels of energy efficiency greater than the the average best practice for the whole period. This is especially the case in the later years. The file also gives income per capita in PPP terms from the Penn World Table.
This data (pdf format) was prepared for Ma and Stern, 2006 but not published. It is briefly discussed on my blog.
Ecological Economics data:
Follow the link below to download a copy of the classic Berndt and Wood data set I used in my research on elasticities of substitution and complementarity.
Also available is the RATS program I used to estimate and compute the results in MPRA Paper 12414:
Also available is the RATS program I used to estimate and compute the results in MPRA Paper 12454:
Follow the link below to download a copy of Stern and Kaufmann's estimates of anthropogenic methane emissions from 1860 to 1994. The file is in text format spaced by tabs. It is an updated version (October 1998) of Table 1 in Stern D. I. and R. K. Kaufmann (1996) Estimates of global anthropogenic methane emissions 1860-1993, Chemosphere 33, 159-176.
These data are also now available from CDIAC's Trends Online.
This data set combines the ASL data and GDP per capita from the Penn World Table for the period 1960-1990. This is the dataset used in Stern D. I. and M. S. Common (2001) [Is there an environmental Kuznets curve for sulfur? Journal of Environmental Economics and Management. 41, 162-178] and in EEP Working Paper 9804. Countries are indicated by code numbers.
This data set is described in the two papers Global Sulfur Emissions from 1850 to 2000 and Reversal in the Trend of Global Sulfur Emissions. Please cite one of these two papers if you use the data in a research paper or other publication. It provides continuous time series from 1850 to 2000, 2001, 2002 (Most OECD countries), or 2003 (China, Mexico, and USA) using a combination of published and reported estimates and my own estimates. The files are in Microsoft Excel format. The data was completely updated in November 2005 when I resubmitted my paper to Global Environmental Change. The data are available on a country by country basis organized into eight global regions:
Mid-East and North Africa
Emissions are measured in thousands of metric tonnes of sulfur (i.e. Gg). This file presents estimates aggregated for the eight regions, shipping, the northern and southern hemispheres, and the World as a whole: