Descrizione del progetto
Scoprire i segreti per il ripristino e la conservazione delle nostre preziose terre
Il degrado del territorio, una sfida di tipo poliedrico che necessità di azione urgente, determina una reazione a catena di conseguenze catastrofiche che aggravano i cambiamenti climatici, la perdita di biodiversità, l’inquinamento delle acque e la diminuzione della produttività agricola globale. Per affrontare questo problema, il progetto SHARE-CTD, finanziato dal CER, ha adottato un approccio olistico che combina misurazioni globali, progettazioni di ricerca econometrica e tecniche innovative di apprendimento automatico allo scopo di fornire preziose informazioni per i soggetti accademici, i politici e il pubblico in generale. In particolare, SHARE-CTD farà luce in merito agli impatti causali generati dalle politiche pubbliche sulle condizioni del territorio raffrontando i loro rapporti tra costi e benefici e identificando i fattori che ne influenzano l’efficacia. In tal modo sarà possibile migliorare le politiche e mitigare gli impatti dannosi esercitati dal degrado del territorio.
Obiettivo
Land degradation is one of the major sustainability challenges of our time. It is a driver of climate change, biodiversity loss, and water pollution, and reduces global agricultural productivity. This requires effective and economically efficient policies.
Here, I outline a project that combines the global measurement and modelling of land degradation trends with econometric research designs to estimate policy effectiveness, their benefit cost ratios, and how design features and contextual factors explain policy performance. This research builds on the unique expertise I have developed over the last 5 years.
The project consists of four work packages. In the first WP, global datasets will be build, including a new database of public policies relevant to land conditions, maps of different land degradation indicators, such as soil productivity trends, vegetation and agricultural yield changes, soil erosion and pollution, and land cover changes, such as cropland expansion and forest loss.
In the second WP, econometric research designs (such as difference-in-differences, difference-in discontinuities, and synthetic control) will be used to estimate the causal effect(s) of public policies on land conditions. The comprehensiveness and global scope of the analysis means that for the first time, we will have the “full picture”, largely free of selection and publication biases, and methodologically unified.
In the third WP, all the policies’ costs and benefits will be compared to each other and we will quantify how much benefit each policy has been generating per its costs.
In the fourth WP, we will use both conventional econometric techniques and novel machine learning approaches to systematically explain when and why some public policies perform better than others.
This research will generate new insights on how to improve public policies to mitigate and reverse land degradation. I expect it will generate high interest among academics, policy makers, and the public.
Campo scientifico
- social sciencespolitical sciencespolitical policiespublic policies
- social scienceseconomics and businesseconomicseconometrics
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- natural sciencesearth and related environmental sciencesenvironmental sciencespollution
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Parole chiave
Programma(i)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Argomento(i)
Meccanismo di finanziamento
HORIZON-ERC - HORIZON ERC GrantsIstituzione ospitante
53113 Bonn
Germania