David I. Stern

Data Page

This page provides access to data used or produced in my research. Please ask me for any data that is not on this website.

Jiang, X., and D. I. Stern (in press) Asymmetric business cycle changes in U.S. carbon emissions and oil market shocks, Climatic Change.

Timilsina, G., Stern, D. I., and D. Das (in press) Physical infrastructure and economic growth, Applied Economics.

Kander A. and D. I. Stern (2014) Economic growth and the transition from traditional to modern energy in Sweden, Energy Economics 46, 56-65. .

Stern D. I. (2012) Interfuel substitution: A meta-analysis, Journal of Economic Surveys 26(2), 307-331.

This data are described in a blogpost on Stochastic Trend.

Code for "Directed Technical Change and the British Industrial Revolution"

Data, Figures and Tables for "Research at Public Policy Schools in the Asia-Pacific Region Ranked"

Dressel B. and D. I. Stern (2021) Research at public policy schools in the Asia-Pacific region ranked, Asia and the Pacific Policy Studies 8(1), 151-166.

Data and Code for "Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions"

Bruns S. B., A. Moneta, and D. I. Stern (2021) Estimating the economy-wide rebound effect using empirically identified structural vector autoregressions, Energy Economics 97, 105158.

Data used in "Flying More Efficiently: Joint Impacts of Fuel Prices, Capital Costs and Fleet Size on Airline Fleet Fuel Economy"

Csereklyei Z. and D. I. Stern (2020) Flying more efficiently: Joint impacts of fuel prices, capital costs and fleet size on airline fleet fuel economy, Ecological Economics 175, 106714.

Data Used in "Modeling the Emissions-Income Relationship Using Long-Run Growth Rates"

Data (xls format) and code (RATS rpf format) for our paper on an alternative way to model the emissions-income relationship:

Stern D. I., R. Gerlagh, and P. J. Burke (2017) Modeling the emissions-income relationship using long-run growth rates, Environment and Development Economics 22(6), 699-724.

The RATS code reproduces all results in the tables in the paper with the exception of the growth rate of the global aggregate emissions and GDP. Using the data file you should also be able to reconstruct all the figures in the paper too.

Data and Figures for "A Multicointegration Model of Global Climate Change"

Data (xls format) for our working paper on global climate change modeling:

Bruns, S. B., Z. Csereklyei, and D. I. Stern (2020) A multicointegration model of global climate change, Journal of Econometrics 214(1), 175-197.

The figures and the data underlying them are contained in the following Excel workbook (xlsx format). This includes simulations of ocean heat content before 1940.

Data and Code Used in Csereklyei et al. (2016) Energy Journal

Data (xlsx format) and Stata and RATS code, used for the main results in our paper about substitutability in China:

Csereklyei Z., M. d. M. Rubio Varas, and D. I. Stern (2016) Energy and economic growth: The stylized facts, Energy Journal 37(2), 223-255.

This is a zipped folder containing the various files:

Data and Code Used in Ma and Stern (2016) Resource and Energy Economics

Data (xls format) and RATS code, used for the main results in our paper about substitutability in China:

Ma C. and D. I. Stern (2016) Long-run estimates of interfuel and interfactor elasticities, Resource and Energy Economics 46, 114-130.

This is a zipped folder containing the various files:

Data and Code Used in Kaufmann and Stern (1997) Nature

Data (wks and xls formats), RATS code, used for the main observational results in our paper about Granger causality and climate change:

Kaufmann R. K. and D. I. Stern (1997) Evidence for human influence on climate from hemispheric temperature relations, Nature 388, 39-44.

This is a folder containing the various files including a pdf of the paper:

Data and Code Used in Burke et al. (2015) Global Environmental Change

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 Stern (2014) PLoS ONE

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 Stern (2013) Journal of Economic Literature

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 Used in Stern and Kaufmann (2014) Climatic Change

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.

Energy Efficiency Means and Time Series from Stern (2012) Energy Economics

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.

Most Cited Authors in Ecological Economics and JEEM 1994-2003

This data (pdf format) was prepared for Ma and Stern, 2006 but not published. It is briefly discussed on my blog.

Ecological Economics data:

JEEM data:

Berndt and Wood Data Set

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 in WKS format.

Or in XLS format:

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:

Also available is the RATS program I used to estimate and compute the results in my 2011 Journal of Productivity Analysis paper:

Aggregate Global Methane

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.

Sulfur and GDP per Capita Database

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.

Global Sulfur Emissions by Country 1850-2003

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:

Asia

Mid-East and North Africa

North America

South America

Africa

Oceania

Western Europe

Eastern Europe

Shipping

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:

Global

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Last updated on 12 June 2024 by David Stern