Assessing poverty with survey data. Uni-dimensional, multidimensional and resilience poverty analysis in Kenya

Traditionally Poverty has been measured by a unique indicator, income, assuming this was the most relevant dimension of poverty. Sen’s approach has dramatically changed this idea shedding light over the existence of many more dimensions and over the multifaceted nature of poverty; poverty cannot be represented by a unique indicator that only can evaluate a specific aspect of poverty. This thesis tracks an ideal path along with the evolution of the poverty analysis. Starting from the unidimensional analysis based on income and consumptions, this research enter the world of multidimensional analysis. After reviewing the principal approaches, the Foster and Alkire method is critically analyzed and implemented over data from Kenya. A step further is moved in the third part of the thesis, introducing a new approach to multidimensional poverty assessment: the resilience analysis.

A Semantic-based Framework for Digital Survey of Architectural Heritage

The research aims at developing a framework for semantic-based digital survey of architectural heritage. Rooted in knowledge-based modeling which extracts mathematical constraints of geometry from architectural treatises, as-built information of architecture obtained from image-based modeling is integrated with the ideal model in BIM platform. The knowledge-based modeling transforms the geometry and parametric relation of architectural components from 2D printings to 3D digital models, and create large amount variations based on shape grammar in real time thanks to parametric modeling. It also provides prior knowledge for semantically segmenting unorganized survey data. The emergence of SfM (Structure from Motion) provides access to reconstruct large complex architectural scenes with high flexibility, low cost and full automation, but low reliability of metric accuracy. We solve this problem by combing photogrammetric approaches which consists of camera configuration, image enhancement, and bundle adjustment, etc. Experiments show the accuracy of image-based modeling following our workflow is comparable to that from range-based modeling. We also demonstrate positive results of our optimized approach in digital reconstruction of portico where low-texture-vault and dramatical transition of illumination bring huge difficulties in the workflow without optimization. Once the as-built model is obtained, it is integrated with the ideal model in BIM platform which allows multiple data enrichment. In spite of its promising prospect in AEC industry, BIM is developed with limited consideration of reverse-engineering from survey data. Besides representing the architectural heritage in parallel ways (ideal model and as-built model) and comparing their difference, we concern how to create as-built model in BIM software which is still an open area to be addressed. The research is supposed to be fundamental for research of architectural history, documentation and conservation of architectural heritage, and renovation of existing buildings.

El Niño southern oscillation and its effect on fog oases along the Peruvian and Chilean coastal deserts

Fog oases, locally named Lomas, are distributed in a fragmented way along the western coast of Chile and Peru (South America) between ~6°S and 30°S following an altitudinal gradient determined by a fog layer. This fragmentation has been attributed to the hyper aridity of the desert. However, periodically climatic events influence the ‘normal seasonality’ of this ecosystem through a higher than average water input that triggers plant responses (e.g. primary productivity and phenology). The impact of the climatic oscillation may vary according to the season (wet/dry). This thesis evaluates the potential effect of climate oscillations, such as El Niño Southern Oscillation (ENSO), through the analysis of vegetation of this ecosystem following different approaches: Chapters two and three show the analysis of fog oasis along the Peruvian and Chilean deserts. The objectives are: 1) to explain the floristic connection of fog oases analysing their taxa composition differences and the phylogenetic affinities among them, 2) to explore the climate variables related to ENSO which likely affect fog production, and the responses of Lomas vegetation (composition, productivity, distribution) to climate patterns during ENSO events. Chapters four and five describe a fog-oasis in southern Peru during the 2008-2010 period. The objectives are: 3) to describe and create a new vegetation map of the Lomas vegetation using remote sensing analysis supported by field survey data, and 4) to identify the vegetation change during the dry season. The first part of our results show that: 1) there are three significantly different groups of Lomas (Northern Peru, Southern Peru, and Chile) with a significant phylogenetic divergence among them. The species composition reveals a latitudinal gradient of plant assemblages. The species origin, growth-forms typologies, and geographic position also reinforce the differences among groups. 2) Contradictory results have emerged from studies of low-cloud anomalies and the fog-collection during El Niño (EN). EN increases water availability in fog oases when fog should be less frequent due to the reduction of low-clouds amount and stratocumulus. Because a minor role of fog during EN is expected, it is likely that measurements of fog-water collection during EN are considering drizzle and fog at the same time. Although recent studies on fog oases have shown some relationship with the ENSO, responses of vegetation have been largely based on descriptive data, the absence of large temporal records limit the establishment of a direct relationship with climatic oscillations. The second part of the results show that: 3) five different classes of different spectral values correspond to the main land cover of Lomas using a Vegetation Index (VI). The study case is characterised by shrubs and trees with variable cover (dense, semi-dense and open). A secondary area is covered by small shrubs where the dominant tree species is not present. The cacti area and the old terraces with open vegetation were not identified with the VI. Agriculture is present in the area. Finally, 4) contrary to the dry season of 2008 and 2009 years, a higher VI was obtained during the dry season of 2010. The VI increased up to three times their average value, showing a clear spectral signal change, which coincided with the ENSO event of that period.

Quality assessment of a landslide inventory map and its application to land‐use planning. A case study in the Northern Apennines (Emilia‐Romagna region, Italy)

Landslide hazard and risk are growing as a consequence of climate change and demographic pressure. Land‐use planning represents a powerful tool to manage this socio‐economic problem and build sustainable and landslide resilient communities. Landslide inventory maps are a cornerstone of land‐use planning and, consequently, their quality assessment represents a burning issue. This work aimed to define the quality parameters of a landslide inventory and assess its spatial and temporal accuracy with regard to its possible applications to land‐use planning. In this sense, I proceeded according to a two‐steps approach. An overall assessment of the accuracy of data geographic positioning was performed on four case study sites located in the Italian Northern Apennines. The quantification of the overall spatial and temporal accuracy, instead, focused on the Dorgola Valley (Province of Reggio Emilia). The assessment of spatial accuracy involved a comparison between remotely sensed and field survey data, as well as an innovative fuzzylike analysis of a multi‐temporal landslide inventory map. Conversely, long‐ and short‐term landslide temporal persistence was appraised over a period of 60 years with the aid of 18 remotely sensed image sets. These results were eventually compared with the current Territorial Plan for Provincial Coordination (PTCP) of the Province of Reggio Emilia. The outcome of this work suggested that geomorphologically detected and mapped landslides are a significant approximation of a more complex reality. In order to convey to the end‐users this intrinsic uncertainty, a new form of cartographic representation is needed. In this sense, a fuzzy raster landslide map may be an option. With regard to land‐use planning, landslide inventory maps, if appropriately updated, confirmed to be essential decision‐support tools. This research, however, proved that their spatial and temporal uncertainty discourages any direct use as zoning maps, especially when zoning itself is associated to statutory or advisory regulations.

Cleavage Politics in Changing Times. Political Realignment Processes in Western European Countries

The dissertation fits the political realignment literature and aims to pro-vide further insights into cleavage politics by investigating voting behaviour in the Western European countries’ national elections. In particular, the dis-sertation focuses on the class and value voting patterns and on the change of these patterns in different countries and over the course of time. Peculiar pro-cesses affected all Western European party systems: whilst the «traditional» cleavage theory accounts for National and Industrial revolutions, those pro-cesses assumed to constitute the «societal modernization» determined chang-es in electoral competitions that questioned the relevance of individuals’ so-cial positions to study electoral preferences. Since the associations between social positions and voting behaviour underpin the so-called political cleav-age, the dealignment perspective assumes them to have been eroding since the second half of the XX century. On the other hand, the realignment perspective argues that the cleavage theory still accounts for individuals’ vote choices: of the four «traditional» cleavages, this perspective hypothesizes new class vot-ing patterns and alignments between electoral preferences and a new line of conflict, that is based on values. The dissertation provides a theoretical ac-count of the realignment of the class cleavage and a new conceptualization of value voting. Then, class and value voting patterns are explored. The analyses employ European Social Survey data and detect general and country-specific patterns. The dissertation adopts a mediation perspective and aims to observe how class voting patterns change when controlling for value orientations. The results are provided with a sensitivity analysis, indeed two versions of the measures computed for value orientations are compared. The findings show that social class continues to affect voting behaviour and that value orienta-tions both mediate this effect and affect electoral preferences.

Essays in Empirical Political Economics

This thesis takes two perspectives on political institutions. From the one side, it examines the long-run effects of institutions on cultural values. From the other side, I study strategic communication, and its determinants, of politicians, a pivotal actor inside those institutions. The first chapter provides evidence for the legacy of feudalism - a set of labor coercion and migration restrictions -, on interpersonal distrust. I combining administrative data on the feudal system in the Prussian Empire (1816 – 1849) with the geo-localized survey data from the German Socio-Economic Panel (1980 – 2020). I show that areas with strong historical exposure to feudalism have lower levels of inter-personal trust today, by means of OLS- and mover specifications. The second chapter builds a novel dataset that includes the Twitter handles of 18,000+ politicians and 61+ million tweets from 2008 – 2021 from all levels of government. I find substantial partisan differences in Twitter adoption, Twitter activity and audience engagement. I use established tools to measure ideological polarization to provide evidence that online-polarization follows similar trends to offline-polarization, at comparable magnitude and reaches unprecedented heights in 2018 and 2021. I develop a new tool to demonstrate a marked increase in affective polarization. The third chapter tests whether politicians disseminate distortive messages when exposed to bad news. Specifically, I study the diffusion of misleading communication from pro-gun politicians in the aftermath of mass shootings. I exploit the random timing of mass shootings and analyze half a million tweets between 2010 – 2020 in an event-study design. I develop and apply state-of-the-art text analysis tools to show that pro- gun politicians seek to decrease the salience of the mass shooting through distraction and try to alter voters’ belief formation through misrepresenting the causes of the mass shootings.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.