Koch, N., Naumann, L., Pretis, F. et al. Attributing agnostically detected large reductions in road CO2 emissions to policy mixes. Nat Energy 7, 844–853 (2022)

Objective:

• Introduce an approach to implement and answer the reverse causal question of what reduced CO2 emission ? in the EU road transport sector between 1995 and 2008 by first detecting substantial changes in emissios relative to a control group using machine learning and subsequently attributing them to likely causes such as single or interacting policy interventions

Case:

• EU

Methodology:

• Familiar two-way fixed effects:
  • $log(CO2{it}) = \alpha_i + \phi_t + \sum_j \sum_s \tau{j,s} l_{i=j} + x^{'} \beta +\epsilon_{i,t}$
• Sparse model

Data Source

• Carbon emission in road sector: EDGAR
• GDP and population: World Bank

Findings:

• Ten successful interventions with emissions reductions between 1995 and 2018 and attribute all detected emissions reductions to policy mixes
• Carbon pricing is a critical element of effective policy packages

• The successsful of carbon, fuel or road-use taxes with additional vehicle taxes or subsidies are implemented in Finland, Sweden, Ireland, and Luxembourg

• Emission saving

Coding Reference:

• R