Carbon offsets in US cap and trade market: a thorough analysis of its drivers and its effects on allowance prices
Carbon offset credits are claimed to be one of the most cost-effective methods to effectively decrease emissions in carbon markets. As a consequence, the number of offset credits surrendered for compliance within the US has seen a constant increase. The raising interest for offsets among capped entities, however, was not shared between all the US regional cap and trade markets and sectors.
Employing a mixed approach this study discusses the main drivers that influence offsets usage both at the market and sectoral level in California cap and trade and RGGI (Regional Greenhouse Gas Initiative). Moreover, through an ARDL model, it tests whether offset usage and availability have a significant effect on allowances price within the California cap and trade system.
In line with what was expected, several market features influence the use of offsets. Amongst those, the main ones are quantitative limits, allowances prices, cap stringency and qualitative limits. Instead, sectoral characteristics that affect offset use are emissions intensity and the cost of abatement. Finally, offsets supply and offsets in California general account are statically significant in determining allowances price.
This folder include the thesis I discussed to obtain my MSc in Economics.
Briefly, it consists of an analysis of offsets in the US Cap and Trade systems (especially RGGI and california). The goal is to analyze offsets usage main drivers along with understanding what influences their price.
In this repository it can be found (not considering this ReadMe):
1️⃣. a .pdf file that is the complete final dissertation.
2️⃣. a .r file that is the analysis' code.
3️⃣. an in_data folder containing data sources.
4️⃣. an out_data folder containing dataframes coming from the analysis.
5️⃣. an img folder including dissertation images.
ℹ️ Feel free to cite my work if it is useful for your purposes. Just hit my mailbox 📩 to let me know, and we could delve even more into this topic.
💬 Feedbacks, comments and improvements are always well-welcomed.