Working Paper: CEPR ID: DP17990
Authors: Thiemo Fetzer; Ludovica Gazz; Menna Bishop
Abstract: Which households are most affected by energy price shocks? What can we learn about the distributional implications of carbon taxes? How do interventions in energy markets affect these patterns? This paper introduces a measurement framework that leverages granular property-level data representing more than 50% of the English and Welsh housing stock. We use this ex-ante measurement framework to investigate these questions and set out an empirical evaluation framework to study the causal effects of the energy crisis more broadly. We find that the energy price shock has a more pronounced effect on relatively more affluent areas highlighting the likely progressive impact of carbon taxation. We document that commonly used untargeted interventions in energy markets significantly weaken market price signals for able-to-pay households. Alternative, more targeted policies are cheaper, easily implementable, and could better align energy saving incentives.
Keywords: climate change; environment; composition of public expenditures
JEL Codes: Q48; C55
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| energy price shock (Q43) | socioeconomic outcomes (I24) |
| energy price shock (Q43) | affluent areas (R20) |
| energy price shock (Q43) | carbon taxation (H23) |
| energy price shock (Q43) | underoccupied homes and elderly residents exposure (R21) |
| untargeted interventions (J68) | market price signals (D41) |
| untargeted interventions (J68) | investments in energy efficiency (Q41) |
| energy price guarantee (EPG) (Q41) | wealthier households benefit (D14) |
| energy price guarantee (EPG) (Q41) | incentives to invest in energy efficiency upgrades (Q48) |
| two-tier tariff (D49) | targeted support (I24) |