Tesi etd-11092023-101835
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Tipo di tesi
Dottorato
Autore
GUZZARDI, DEMETRIO
URN
etd-11092023-101835
Titolo
warming unequal: income distribution, fiscal system, and the impact of climate change in italy
Settore scientifico disciplinare
SECS-P/02
Corso di studi
Istituto di Economia - PHD IN ECONOMICS
Commissione
Relatore Prof. ROVENTINI, ANDREA
Parole chiave
- climate change
- extreme events
- income inequality
- National Accounts
- tax data
- tax progressivity
- top income
Data inizio appello
08/03/2024;
Disponibilità
parziale
Riassunto analitico
This thesis has a twofold aim: to deepen our understanding of income inequality in Italy by generating new and more precise estimates of the income distribution through diverse methodologies and to study the intricate mechanisms influencing this disparity. To achieve the latter goal, this study follows two paths. It examines the progressivity of the Italian fiscal system and delves into the impact of climate change on income distribution within the country. By interlinking these factors, this research aims to provide a comprehensive analysis of the multifaceted nature of inequality in Italy.
This thesis is thus divided into four chapters.
After a brief Introduction section, Chapter 1 reconstructs a novel series on income distribution in Italy combining survey data, tax data and National Accounts both at the national and regional levels, and it analyzes the overall progressivity of the tax system. Following the Distributional National Accounts methodology the presented estimates correct the misreporting of capital income in surveys, provide more accurate estimates of consumption, and better account for the role of informal economy. These estimates show that the share of national income of the richest top top 1% and top 0.1% has been steadily increasing after the 2008 crisis. We also shed further light on the multifaceted nature of inequality in Italy: youngest individuals, women and inhabitants of Southern regions have been increasingly exposed to growing levels of inequality. Finally, this chapter shows that the Italian tax system is only slightly progressive up to the 95th percentile of the income distribution, and regressive for the top 5% of the income distribution.
Chapter 2 transitions from the Distributional National Accounts methodology to a more established approach focusing on top income shares. This approach, while limited to certain income sources within the National Accounts, enables the estimation of top income shares in great detail, extending down to the municipal level. By integrating income tax tabulations and National Accounts data, it is possible to calculate top income shares from 1976 to 2021 at the national level and from 2000 to 2021 at both regional and municipal levels. Leveraging the diverse and abundant geographical data from income tax records, the analysis extends beyond the traditional geographic divisions of South, Center, and North. The official geographical classification of the Italian National Strategy, known as "Inner areas" (Aree Interne), is utilized. This classification helps identify fragile and marginalized territories that lack essential public services. Additionally, the chapter presents growth incidence curves across the income distribution, allowing the relative position of each geographical unit within the national income distribution to be pinpointed based on its mean income level.
Chapter 3 investigates the influence of extreme climate events on income distribution at the municipality level in Italy, utilizing the rich dataset on income distribution constructed in Chapter 2. To assess the occurrence of climate events, climate data at the grid level from the Copernicus datastore are utilized, providing daily precipitation and temperature data across Europe at a 5.5km x 5.5km grid resolution. Additionally, information on disaster events from the European Severe Weather Database is included, offering geo-referenced details about catastrophic events, including their date and type. To establish the relationship between extreme climate events and income distribution, various climate indexes at the grid level are constructed. These indexes, along with data on catastrophic events, temperature, and precipitation, are then spatially matched to the corresponding municipality where they occurred. Econometric techniques are employed to estimate the impact of extreme events on the reduction of average income growth for different income groups in the local income distribution.
Preliminary estimates indicate that extreme climate events lead to decreased income growth for the lower-income group within each municipality, while having no impact on the top income earners. By shedding light on the socioeconomic consequences of extreme climate events, this research contributes to a better understanding of the complex relationship between climate change and income inequality, offering valuable insights for policymakers in devising targeted mitigation and adaptation policies.
Finally, Chapter 4 provides some concluding remarks.
This thesis is thus divided into four chapters.
After a brief Introduction section, Chapter 1 reconstructs a novel series on income distribution in Italy combining survey data, tax data and National Accounts both at the national and regional levels, and it analyzes the overall progressivity of the tax system. Following the Distributional National Accounts methodology the presented estimates correct the misreporting of capital income in surveys, provide more accurate estimates of consumption, and better account for the role of informal economy. These estimates show that the share of national income of the richest top top 1% and top 0.1% has been steadily increasing after the 2008 crisis. We also shed further light on the multifaceted nature of inequality in Italy: youngest individuals, women and inhabitants of Southern regions have been increasingly exposed to growing levels of inequality. Finally, this chapter shows that the Italian tax system is only slightly progressive up to the 95th percentile of the income distribution, and regressive for the top 5% of the income distribution.
Chapter 2 transitions from the Distributional National Accounts methodology to a more established approach focusing on top income shares. This approach, while limited to certain income sources within the National Accounts, enables the estimation of top income shares in great detail, extending down to the municipal level. By integrating income tax tabulations and National Accounts data, it is possible to calculate top income shares from 1976 to 2021 at the national level and from 2000 to 2021 at both regional and municipal levels. Leveraging the diverse and abundant geographical data from income tax records, the analysis extends beyond the traditional geographic divisions of South, Center, and North. The official geographical classification of the Italian National Strategy, known as "Inner areas" (Aree Interne), is utilized. This classification helps identify fragile and marginalized territories that lack essential public services. Additionally, the chapter presents growth incidence curves across the income distribution, allowing the relative position of each geographical unit within the national income distribution to be pinpointed based on its mean income level.
Chapter 3 investigates the influence of extreme climate events on income distribution at the municipality level in Italy, utilizing the rich dataset on income distribution constructed in Chapter 2. To assess the occurrence of climate events, climate data at the grid level from the Copernicus datastore are utilized, providing daily precipitation and temperature data across Europe at a 5.5km x 5.5km grid resolution. Additionally, information on disaster events from the European Severe Weather Database is included, offering geo-referenced details about catastrophic events, including their date and type. To establish the relationship between extreme climate events and income distribution, various climate indexes at the grid level are constructed. These indexes, along with data on catastrophic events, temperature, and precipitation, are then spatially matched to the corresponding municipality where they occurred. Econometric techniques are employed to estimate the impact of extreme events on the reduction of average income growth for different income groups in the local income distribution.
Preliminary estimates indicate that extreme climate events lead to decreased income growth for the lower-income group within each municipality, while having no impact on the top income earners. By shedding light on the socioeconomic consequences of extreme climate events, this research contributes to a better understanding of the complex relationship between climate change and income inequality, offering valuable insights for policymakers in devising targeted mitigation and adaptation policies.
Finally, Chapter 4 provides some concluding remarks.
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