update paper

paper/paper.bib

@@ -155,3 +155,32 @@ @article{tomas2023
 	pages = {113558},
 	file = {ScienceDirect Full Text PDF:C\:\\Users\\eva.alonso\\Zotero\\storage\\8KGU3WAN\\Tomás et al. - 2023 - Ensuring a just energy transition A distributiona.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\eva.alonso\\Zotero\\storage\\SZHDH6X6\\S030142152300143X.html:text/html},
 }
+
+@techreport{eurostat2003,
+	title = {{HOUSEHOLD} {BUDGET} {SURVEYS} {IN} {THE} {EU} — {Methodology} and recommendations for harmonisation – 2003},
+	language = {en},
+	author = {Eurostat},
+	year = {2003},
+	file = {HOUSEHOLD BUDGET SURVEYS IN THE EU — Methodology a.pdf:C\:\\Users\\eva.alonso\\Zotero\\storage\\8AZP2MM5\\HOUSEHOLD BUDGET SURVEYS IN THE EU — Methodology a.pdf:application/pdf},
+}
+
+@article{cazcarro2022,
+  title={Linking multisectoral economic models and consumption surveys for the European Union},
+  author={Cazcarro, Ignacio and Amores, Antonio F and Arto, Inaki and Kratena, Kurt},
+  journal={Economic Systems Research},
+  volume={34},
+  number={1},
+  pages={22--40},
+  year={2022},
+  publisher={Taylor \& Francis}
+}
+
+@article{alonso-epelde2023,
+  title={Transport poverty indicators: A new framework based on the household budget survey},
+  author={Alonso-Epelde, E and Garc{\'\i}a-Muros, X and Gonz{\'a}lez-Eguino, M},
+  journal={Energy Policy},
+  volume={181},
+  pages={113692},
+  year={2023},
+  publisher={Elsevier}
+}

paper/paper.md

@@ -58,7 +58,7 @@ calc_di( year,                     # Base year for the simulation
 
 Addressing critical challenges like climate change requires ambitious policies that promote social justice without worsening existing inequalities, such as income or gender disparities [@alonso-epelde2024]. To ensure this, it is essential to conduct policy impact assessments that not only consider the economy, energy, land, and water systems holistically but also analyze the distributional impacts across different population groups [@bazoli2022; @walker2010]. While Integrated Assessment Models (IAMs) have been invaluable in policy evaluation [@van2020], they often lack the granularity needed to assess socio-economic disparities. Micro-simulation models for distributional analysis fill this gap by providing detailed, heterogeneous results, enabling policymakers to identify vulnerable populations and implement targeted compensatory measures [@tomas2023]. This ensures that policies are equitable and socially just.
 
-`medusa` facilitates distributional impact analyses through an overnight-effect microsimulation model, leveraging microdata from the Household Budget Survey (HBS), a standardized and comprehensive dataset available across EU countries COMMENT: CITA?. The HBS offers detailed insights into household consumption patterns and socioeconomic characteristics at both household and individual levels, allowing for highly granular analysis. This enables the integration of an intersectional approach[^1] considering factors such as class, gender, and race, and provides more robust and nuanced results for assessing policy impacts on diverse population groups.
+`medusa` facilitates distributional impact analyses through an overnight-effect microsimulation model, leveraging microdata from the Household Budget Survey (HBS), a standardized and comprehensive dataset available across EU countries [@eurostat2003]. The HBS offers detailed insights into household consumption patterns and socioeconomic characteristics at both household and individual levels, allowing for highly granular analysis. This enables the integration of an intersectional approach[^1] considering factors such as class, gender, and race, and provides more robust and nuanced results for assessing policy impacts on diverse population groups.
 
 [^1]: Intersectionality refers to the fact that the privileges or oppression of each individual depend on the multiple social categories to which he or she belongs, which are social constructs and can change over time ([@cho2013]; [@crenshaw1994, @davis1983, @djoudi2016, @kaijser2014]). Intersectionality is therefore also a tool for analysing the articulation of different socio-economic categories (e.g. class, gender, race, etc.) rather than considering them as independent forms of power relations (Colombo & Rebughini, 2016).
 
@@ -74,11 +74,11 @@ here $e_{c,h}$ refers to the total spending on each consumption category, $c$, c
 
 The `medusa` package includes several functions that have been classified in 3 main modules. Note that this functions are listed in an [R vignette](https://bc3lc.github.io/medusa/), which includes a [step-by-step tutorial](https://bc3lc.github.io/medusa/articles/Tutorials.html).
 
--   Module 1: Functions to calculate the distributional impacts. The main function for users, `calc_di()`, calculates the distributional impacts for different households according to a wide range of socioeconomic and demographic characteristics. The distributional impacts could be calculated for one or for several intersecting variables COMMENT: several? o solo 2?. When introducing the outputs of a macro model in `medusa`, the microdata in which the microsimulation model is based should be elevated to the National Accounts COMMENT: cita de National Accounts o del pq de la necesidad d este procedimiento?, this can be easily done indicating TRUE in the `elevate` parameter. Furthermore, in order to facilitate the analysis of the results, the package allows the generation of summary dataframes and figures of the distributional impacts either for one or several socioeconomic variables.
+-   Module 1: Functions to calculate the distributional impacts. The main function for users, `calc_di()`, calculates the distributional impacts for different households according to a wide range of socioeconomic and demographic characteristics. The distributional impacts could be calculated for one or more intersecting variables. When introducing the outputs of a macro model in `medusa`, the microdata in which the microsimulation model is based should be elevated to the National Accounts [@cazcarro2022], this can be easily done indicating TRUE in the `elevate` parameter. Furthermore, in order to facilitate the analysis of the results, the package allows the generation of summary dataframes and figures of the distributional impacts either for one or several socioeconomic variables.
 
--   Module 2: Functions to calculate energy poverty indices.The main function for users, `calc_ep()`, calculates the energy poverty index for the selected year/s and the selected indicator. The indicators included in the package are the 10$\%$, 2M, LIHC and VTU. COMMENT: explicar qué son estos indicadores o poner un link a tu página de documentación q lo explique.
+-   Module 2: Functions to calculate energy poverty indices.The main function for users, `calc_ep()`, calculates the energy poverty index for the selected year/s and the selected indicator. The indicators included in the package are the 10$\%$, 2M, LIHC, HEP and HEP_LI. These indicators have been commonly used in the literature to measure energy poverty during the last decades and are explained [here](https://bc3lc.github.io/medusa/articles/EnergyPoverty.html).
 
--   Module 3: Functions to calculate transport poverty indices.The main function for users, `calc_tp()`, calculates the transport poverty index for the selected year/s and the selected indicator. The indicators included in the package are the 10$\%$, 2M, LIHC and VTU. COMMENT: explicar qué son estos indicadores o poner un link a tu página de documentación q lo explique.
+-   Module 3: Functions to calculate transport poverty indices.The main function for users, `calc_tp()`, calculates the transport poverty index for the selected year/s and the selected indicator. The indicators included in the package are the 10$\%$, 2M, LIHC and VTU. These indicators are based on the proposal by Alonso-Epelde et al. [alonso-epelde2023] and are explained [here](https://bc3lc.github.io/medusa/articles/TransportPoverty.html).
 
 The package includes default input files (.Rda), which are required for running the various functions, simplifying the process for users.