Modelli non lineari statici e dinamici su dati microeconomici: analisi delle condizioni finanziarie delle famiglie italiane

The thesis studies the economic and financial conditions of Italian households, by using microeconomic data of the Survey on Household Income and Wealth (SHIW) over the period 1998-2006. It develops along two lines of enquiry. First it studies the determinants of households holdings of assets and liabilities and estimates their correlation degree. After a review of the literature, it estimates two non-linear multivariate models on the interactions between assets and liabilities with repeated cross-sections. Second, it analyses households financial difficulties. It defines a quantitative measure of financial distress and tests, by means of non-linear dynamic probit models, whether the probability of experiencing financial difficulties is persistent over time. Chapter 1 provides a critical review of the theoretical and empirical literature on the estimation of assets and liabilities holdings, on their interactions and on households net wealth. The review stresses the fact that a large part of the literature explain households debt holdings as a function, among others, of net wealth, an assumption that runs into possible endogeneity problems. Chapter 2 defines two non-linear multivariate models to study the interactions between assets and liabilities held by Italian households. Estimation refers to a pooling of cross-sections of SHIW. The first model is a bivariate tobit that estimates factors affecting assets and liabilities and their degree of correlation with results coherent with theoretical expectations. To tackle the presence of non normality and heteroskedasticity in the error term, generating non consistent tobit estimators, semi-parametric estimates are provided that confirm the results of the tobit model. The second model is a quadrivariate probit on three different assets (safe, risky and real) and total liabilities; the results show the expected patterns of interdependence suggested by theoretical considerations. Chapter 3 reviews the methodologies for estimating non-linear dynamic panel data models, drawing attention to the problems to be dealt with to obtain consistent estimators. Specific attention is given to the initial condition problem raised by the inclusion of the lagged dependent variable in the set of explanatory variables. The advantage of using dynamic panel data models lies in the fact that they allow to simultaneously account for true state dependence, via the lagged variable, and unobserved heterogeneity via individual effects specification. Chapter 4 applies the models reviewed in Chapter 3 to analyse financial difficulties of Italian households, by using information on net wealth as provided in the panel component of the SHIW. The aim is to test whether households persistently experience financial difficulties over time. A thorough discussion is provided of the alternative approaches proposed by the literature (subjective/qualitative indicators versus quantitative indexes) to identify households in financial distress. Households in financial difficulties are identified as those holding amounts of net wealth lower than the value corresponding to the first quartile of net wealth distribution. Estimation is conducted via four different methods: the pooled probit model, the random effects probit model with exogenous initial conditions, the Heckman model and the recently developed Wooldridge model. Results obtained from all estimators accept the null hypothesis of true state dependence and show that, according with the literature, less sophisticated models, namely the pooled and exogenous models, over-estimate such persistence.

Quantitative evaluation of household nutrition patterns: an econometric assessment of the UK 5-a-day impact on fruit and vegetable consumption

The present work provides an ex-post assessment of the UK 5-a-day information campaign where the positive effects of information on consumption levels are disentangled from the potentially conflicting price dynamics. A model-based estimate of the counterfactual (no-intervention) scenario is computed using data from the Expenditure and Food Survey between 2002 and 2006. For this purpose fruit and vegetable demand is modelled employing Quadratic Almost Ideal Demand System (QUAIDS) specification with demographic effects and controlling for potential endogeneity of prices and total food expenditure.

Determinants of child undernutrition in India. A micro-case study to operationalize the Capability Approach

The present research aims at shedding light on the demanding puzzle characterizing the issue of child undernutrition in India. Indeed, the so called ‘Indian development paradox’ identifies the phenomenon according to which higher level of income per capita is recorded alongside a lethargic reduction in the proportion of underweight children aged below three years. Thus, in the time period occurring from 2000 to 2005, real Gross Domestic Production per capita has annually grown at 5.4%, whereas the proportion of children who are underweight has declined from 47% to 46%, a mere one point percent. Such trend opens up the space for discussing the traditionally assumed linkage between income-poverty and undernutrition as well as food intervention as the main focus of policies designed to fight child hunger. Also, it unlocks doors for evaluating the role of an alternative economic approach aiming at explaining undernutrition, such as the Capability Approach. The Capability Approach argues for widening the informational basis to account not only for resources, but also for variables related to liberties, opportunities and autonomy in pursuing what individuals value.The econometric analysis highlights the relevance of including behavioral factors when explaining child undernutrition. In particular, the ability of the mother to move freely in the community without the need of asking permission to her husband or mother-in-law is statistically significant when included in the model, which accounts also for confounding traditional variables, such as economic wealth and food security. Also, focusing on agency, results indicates the necessity of measuring autonomy in different domains and the need of improving the measurement scale for agency data, especially with regards the domain of household duties. Finally, future research is required to investigate policy venues for increasing agency in women and in the communities they live in as viable strategy for reducing the plague of child undernutrition in India.

Essays in Household and Demographic Economics

This dissertation consists of three empirical studies that are believed to provide new contributions to the literature exploring the determinants of children/adolescents achievement test scores (Chapter 2), adolescent health risk behaviors (Chapter 3), and children time use patterns (Chapter 4). The second and third studies look at the separate roles of fathers and of mothers in influencing outcomes, wherein parental time is the resource input of interest quantitatively measured and directly derived from time diaries. The last chapter looks at the time allocation of children and how it varies according to child and household characteristics.

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.

Essays in the Economics of Ageing

In the first paper, I assess if financial incentives may be used as an effective device to induce workers to postpone retirement by evaluating the Italian so called “super bonus” reform. The bonus consisted in economic incentives given for a limited period to private sector workers who had reached the requirements for seniority pension. Crucially for this study, public workers were not entitled to the bonus. Using data from the Bank of Italy Survey on Household Income andWealth, and exploiting the DID-Probit strategy proposed by Blundell et al. (JEEA, 2004), I assess the effect of the bonus on the decision to postpone retirement, by comparing private and public workers before and after the reform. Results suggest a reduction of 12ppt in the proportion of private workers who decided to retire among those qualifying for retirement. Results also suggest, not trivially, that most of the effect of the reform is driven by low-income workers. Finally, I propose an estimate of the extensive margin elasticity of Italian older workers. The second study estimates a structural reduced form of the “option value” model developed by Stock and Wise (1990) using Italian data from the Survey of Health, Ageing and Retirement in Europe (SHARE).Exploiting exogenous changes in social security wealth (SSW) results show a significant effect in the expected direction of SSW and of marginal incentives to retire. Results are robust even after controlling for individual heterogeneity and its correlation with financial incentives. Using detailed information on individuals, the results also highlights the importance of individual and job characteristics, which have been very little explored by this literature, as determinants of retirement. This suggests the potential of “tagging” in the design of social security incentives in order to reduce choice distortions and improve the overall efficiency of the system.

Agent-based simulation for renewable energy incentive design

In this thesis, we propose a novel approach to model the diffusion of residential PV systems. For this purpose, we use an agent-based model where agents are the families living in the area of interest. The case study is the Emilia-Romagna Regional Energy plan, which aims to increase the produc- tion of electricity from renewable energy. So, we study the microdata from the Survey on Household Income and Wealth (SHIW) provided by Bank of Italy in order to obtain the characteristics of families living in Emilia-Romagna. These data have allowed us to artificial generate families and reproduce the socio-economic aspects of the region. The families generated by means of a software are placed on the virtual world by associating them with the buildings. These buildings are acquired by analysing the vector data of regional buildings made available by the region. Each year, the model determines the level of diffusion by simulating the installed capacity. The adoption behaviour is influenced by social interactions, household’s economic situation, the environmental benefits arising from the adoption and the payback period of the investment.