Journal of Environmental Economics and Management

The files contain the replication data and replication instructions (as STATA files) that replicate the results presented in the article: Brunnschweiler, Christa and Steven Poelhekke (2021), Pushing One's Luck: Petroleum ownership and discoveries, Journal of Environmental Economics and Management 109: 102506. doi: 10.1016/j.jeem.2021.102506 The files also allow replication of the results in the Online Appendix linked to this paper.

Readme file describing all data sources and analysis files used in "Superfund Cleanups and Children’s Lead Exposure"

This is the data and do file for the first round of review. We will gladly provide updated data and code if the journal accepts our article. The data and code will also be posted on the Colorado State University website.

This zip file contains a technical appendix ("Trade_and_Enviro_Numerical_Appendix.pdf") that describes the parameter values and system of equations contained in the included Matlab files. The zip file also contains all of the Matlab files used to solve and simulate the combined framework in "THE ENVIRONMENTAL EFFECTS OF TRADE WITHIN AND ACROSS SECTORS." All of the data used to generate the figures and tables in the paper were generated using these files and the included Excel sheets..

This data package contains all raw data and codes used for the research paper. It contains six files, including an excel file, a Stata do-file, and 4 .dta data files. Readers need to have Stata and MS Excel to reproduce the analysis. See the do-file for more details.

Lab experiment data and analysis in Stata for paper published in JEEM

My data set pools different sources of information: information on plant-level TRI emissions, newspapers location, newspapers content, and demographics measured in 2-km rings around the TRI plants. Please find details about each source in Section III of the paper. The different sources are pooled together in the dataset named ``dataset press and leaks.dta" The dataset named ``articles distance.dta" contains information on plants that have at least one newspaper within 90 km from their location, observed between 1996 and 2009. It reports their respective distance from each of these newspapers. The dataset also records whether the plant's TRI emissions are covered or not in each of these newspapers every year. See Section III in the paper for more details. This dataset is needed to reproduce Figure 1. Do-files that reproduce all the Figures and Tables in the paper are included in the folder. If you have any questions do not hesitate to contact me.

Four files are attached : - OptimalThreshold_JEEM_R1_data.Rdata (Rdata format) contains the simulation results (emissions, gross margin, agricultural area, livestock units) at the representative farm level (see Section 4) for an emission tax varying from 0 to 200 EUR/tCO2eq, as well as the data retrieved from Bellassen et al (2015) about MRV costs; - OptimalThreshold_JEEM_R1_data.r contains the R code necessary for the design of the various scenarios explored in the paper (emission tax level, magnitude and distribution of MRV costs, choice of the criterion) and determine the respective optimal coverage; - OptimalThreshold_JEEM_R1_tables.r contains the R code for the tables presented in the paper; - OptimalThreshold_JEEM_R1_graphes.r contains the R code used to construct the figures presented in the paper.

The zip folder contains the model codes and data used to reproduce the results for Section 4 in the paper.

We develop a model of optimal taxation and redistribution under an ambitious climate target. We take into account vertical income differences, but also explicitly capture horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon and labor taxes, transfers and energy subsidies, we investigate analytically how vertical and horizontal inequality is considered in the welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal and show that redistribution of carbon tax revenues via household-specific transfers is the first-best policy. Under plausible assumptions on inequality aversion, transfers to energy-intensive households should be about five times higher than transfers to energy-efficient households. Equal per-capita transfers do not require to observe households' efficiency type, but increase mitigation costs by around 5 percent compared to the first-best. Mitigation costs increase by less, if the government can implement a uniform clean energy subsidy or household-specific tax-subsidy schemes on energy consumption and labor income that target heterogeneous energy efficiencies. Horizontal equity concerns may therefore constitute a new second-best rationale for clean energy policies or differentiated energy taxes.