Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2502.07788

Analysis of energy, CO2 emissions and economy of the technological migration for clean cooking in Ecuador

J. Martinez·Jaime Marti-Herrero·S. Villacis·A. J. Riofrio·D. Vaca
View original source ↗Read source document ↗Export metadata ↓

Abstract

The objective of this study is to analyze the CO2 emissions and economic impacts of the implementation of the National Efficient Cooking Program (NECP) in Ecuador, which aims to migrate the population from Liquefied Petroleum Gas (LPG)-based stoves to electric induction stoves. This program is rooted in the current effort to change Ecuador's energy balance, with hydroelectric power expected to generate 83.61% of national electricity by 2022, ending the need for subsidized LPG. For this analysis, the 2014 baseline situation has been compared with two future scenarios for 2022: a business-as-usual scenario and an NECP-success scenario. This study demonstrates the viability of migration from imported fossil fuels to locally-produced renewable energy as the basis for an efficient cooking facility. The new policies scenario would save US$ 1.162 billion in annual government expenditure on cooking subsidies, and reducing CO2 emissions associated to energy for cooking in 1.8 tCO2/y.

Explore related subjects

econ.GNq-fin.EC

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

J. Martinez, Jaime Marti-Herrero, S. Villacis, A. J. Riofrio, D. Vaca. 2025-01-20. Analysis of energy, CO2 emissions and economy of the technological migration for clean cooking in Ecuador. https://doi.org/10.1016/j.enpol.2017.04.033

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Access to Live AI Advice and Behavior Under Risk: An Incentivized Experiment

Generative AI has become an everyday advisor, and the systems people consult are live and interactive, not pre-scripted. We ask whether access to such a system changes behavior under risk. In an incentivized experiment (N = 158), participants made lottery choices with an optional decision aid presented as a conventional pre-written tool, a live one-shot AI, or a live interactive AI they could query, with information format held equivalent across conditions. Risk preferences are elicited via DOSE. We find no evidence that access to a live AI advisor changes risk aversion.

econ.GN↗
arXiv2026

Bricks or Cash? Externalities of Housing Upgrading in High-density Cities

We estimate housing externalities in a high-density city, exploiting the staggered rollout of Singapore's nationwide Main Upgrading Programme for public housing. Controlling for nonrandom neighborhood exposure, we find that upgrading raises treated buildings' prices by 11.5% upon completion and neighboring buildings' resale prices by about 2% within 500 meters, decaying to zero beyond. A model with distance-decaying externalities shows that in dense settings spillovers justify the distortions of in-kind provision; this advantage diminishes and reverses at lower densities. Administrative data on over 2 million residents show that upgrading disproportionately retains older incumbents, suggesting age-specific amenities as an underexplored externality channel.

econ.GN↗
arXiv2026

The Joneses Visit an Economics Lab

Existing literature offers persuasive evidence that individuals care about how their consumption compares to that of peers, and proposes a large variety of explanatory models. The present paper proposes a common framework for many of those models, and compares their ability to predict behavior in a laboratory experiment. We find evidence of Keeping up with the Joneses motivations but also find that conspicuous consumption is enhanced by Veblen motivations arising from peers' ability to observe one's own choice. Among the seven quasi-linear preference models we compare, our data are best explained by a model that contrasts envy and pride (upward vs downward comparisons) using a value function borrowed from Prospect Theory.

econ.GN↗