Carbon Abatement Leaders and Laggards Non Parametric Analyses of Policy Oriented Kuznets Curves

We study the eventual structural differences of climate change leading ‘actors’ such as Northern EU countries, and ‘lagging actors’ - southern EU countries and the ‘Umbrella group’ - with regard to long run (1960-2001) carbon-income relationships. Parametric and semi parametric panel models show that the groups of countries that were in the Kyoto arena less in favour of stringent climate policy, have yet to experience a turning point, though they at least show relative delinking in their monotonic carbon-income relationship. Northern EU instead robustly shows bell shapes across models, which seem to depend on time related (policy) events. Time related effects are more relevant than income effects in explaining the occurrence of robust Kuznets curves. The reaction of northern EU to exogenous policy events such as the 1992 climate change convention that gave earth to the Kyoto era, and even the second oil shock that preceded it in the 80’s are among the causes of the observed structural differences.Carbon Kuznets Curves, Kyoto, Long Run Dynamics, Policy Events, Heterogeneous Panels, Cross-Section Correlation, Semi Parametric Models, Common Time Trends

Water Consumption and Long-Run Urban Development: The Case of Milan

Analyses of long run consumption series are rare in literature. We study the evolution of water consumption in Milan in the twentieth century. The objective is twofold: on one side, the univariate analysis tries both to assess the impact of relevant socio-economic and environmental changes on water consumption in Milan and verify if consumers have deeply rooted consumption habits. On the other side, the multivariate analysis is used to identify the socio-economic factors that are relevant in explaining consumption evolution. Results indicate both that water users have well entrenched consumption habits and that population, climate and economic structure behave more similarly, in Euclidean terms, to water consumption than to other economic and social variables.Urban consumption, Long-run, Development, Environmental changes

Income and time related effects in EKC

This paper documents the structural differences between climate change leading `actors' as Northern EU countries, and `lagging actors' - southern EU countries and the `Umbrella group' - with regard to their long run carbon-income relationships. We show that such categorization gives relevant policy and methodological insights. We investigate the issue of cross-country heterogeneity and the heterogeneity biases associated to standard panel data estimates but also disentangle time related and income effects. Parametric and semi parametric panel models allowing for time invariant unobserved heterogeneity robustly show that the groups of countries that were in the `Kyoto arena' less in favour of stringent climate policy, have yet to experience a turning point. Northern EU instead shows bell shapes. The key result is however obtained by estimating a semi-parametric random growth model. Country specific time related factors - that may represent latent innovation and policy features of countries - have been relatively more relevant than income effects in explaining the occurrence of such Kuznets curves. Overall, the countries differ more on their carbon-time relation than on the carbon-income relation which is in almost all cases monotonic positive. Just a few Nordic countries show a bell curve in both income and time related factors.Carbon Kuznets Curves; heterogeneous panels; semi parametric models; random growth; income effect; time related effect

Carbon Kuznets Curves: Long-run Structural Dynamics and Policy Events

We study the structural differences among climate change leading ‘factors’ - Northern EU members -, and lagging actors - southern EU countries and the ‘Umbrella group’ - with regard to long run carbon-income relationships. Homogeneous and heterogeneous panel models show that the groups of countries less in favour of stringent climate policy have yet to experience a Kuznets curve, though they show relative delinking. Northern EU instead robustly shows bell shapes. Exogenous policy events such as the 1992 climate change convention appear to be relevant in shaping the EKC of Northern EU. In addition, other events such as the second oil price shock appear to have also impacted in shaping the long run emission/GDP dynamics.Carbon Kuznets Curve, Panel Cointegration, Heterogeneous Panels, Cross-Section Correlation, Kyoto Framework, Bayesian Models, Policy Events, Long Run Dynamics

A Bayesian Approach to the Estimation of Environmental Kuznets Curves for CO2 Emissions

This paper investigates the EKC curves for CO2 emissions in a panel of 109 countries during the period 1959-2001. The length of the series makes the application of a heterogeneous estimator suitable from an econometric point of view. The results, based on the hierarchical Bayes estimator, show that different EKC dynamics are associated with the different sub samples of countries considered. On average, more industrialized countries show an EKC evidence in quadratic specifications, which are nevertheless probably evolving into an N shape, emerging from cubic specifications. Less developed countries consistently show that CO2 emissions still rise positively with income, though some signals of an EKC path arise.Environmental Kuznets Curve, CO2 Emissions, Bayesian Approach, Heterogeneous Panels

Exploiting Cellular Data for Disease Containment and Information Campaigns Strategies in Country-Wide Epidemics

Human mobility is one of the key factors at the basis of the spreading of diseases in a population. Containment strategies are usually devised on movement scenarios based on coarse-grained assumptions. Mobility phone data provide a unique opportunity for building models and defining strategies based on very precise information about the movement of people in a region or in a country. Another very important aspect is the underlying social structure of a population, which might play a fundamental role in devising information campaigns to promote vaccination and preventive measures, especially in countries with a strong family (or tribal) structure. In this paper we analyze a large-scale dataset describing the mobility and the call patterns of a large number of individuals in Ivory Coast. We present a model that describes how diseases spread across the country by exploiting mobility patterns of people extracted from the available data. Then, we simulate several epidemics scenarios and we evaluate mechanisms to contain the epidemic spreading of diseases, based on the information about people mobility and social ties, also gathered from the phone call data. More specifically, we find that restricting mobility does not delay the occurrence of an endemic state and that an information campaign based on one-to-one phone conversations among members of social groups might be an effective countermeasure.Comment: 9 pages, 9 figures. Appeared in Proceedings of NetMob 2013. Boston, MA, USA. May 201

Econometric modelling of the regional knowledge production function in Europe

By adopting a semiparametric approach, the ‘traditional’ regional knowledge production function is developed in three complementary directions. First, the model is augmented with region-specific time trends to account for endogeneity due to selection on unobservables. Second, the nonparametric part of the model relaxes the standard assumptions of linearity and additivity regarding the effect of R&D and human capital. Finally, the assumption of homogeneity in the effects of R&D and human capital is also relaxed by explicitly accounting for the differences between developed and lagging regions. The analysis of the genesis of innovation in the regions of the European Union unveils nonlinearities, threshold effects, complex interactions and shado

Coding together at scale:GitHub as a collaborative social network

GitHub is the most popular repository for open source code (Finley 2011). It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities. In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration

You are What you Eat (and Drink): Identifying Cultural Boundaries by Analyzing Food & Drink Habits in Foursquare

Food and drink are two of the most basic needs of human beings. However, as society evolved, food and drink became also a strong cultural aspect, being able to describe strong differences among people. Traditional methods used to analyze cross-cultural differences are mainly based on surveys and, for this reason, they are very difficult to represent a significant statistical sample at a global scale. In this paper, we propose a new methodology to identify cultural boundaries and similarities across populations at different scales based on the analysis of Foursquare check-ins. This approach might be useful not only for economic purposes, but also to support existing and novel marketing and social applications. Our methodology consists of the following steps. First, we map food and drink related check-ins extracted from Foursquare into users' cultural preferences. Second, we identify particular individual preferences, such as the taste for a certain type of food or drink, e.g., pizza or sake, as well as temporal habits, such as the time and day of the week when an individual goes to a restaurant or a bar. Third, we show how to analyze this information to assess the cultural distance between two countries, cities or even areas of a city. Fourth, we apply a simple clustering technique, using this cultural distance measure, to draw cultural boundaries across countries, cities and regions.Comment: 10 pages, 10 figures, 1 table. Proceedings of 8th AAAI Intl. Conf. on Weblogs and Social Media (ICWSM 2014

Is infrastructure capital really productive? Non-parametric modeling and data-driven model selection in a cross-sectionally dependent panel framework

This paper provides a broad replication of Calderón et al. (2015). We address some complex and relevant issues, namely functional form, non-stationary variables and cross-sectional depen- dence. In particular, by adopting the CCE framework, we consider both parametric - static and dynamic - and non-parametric specifications, thus allowing for different degrees of flexibility. Contrary to Calderón et al. (2015), we find a lack of significance of the infrastructure index, with an estimated elasticity very close to zero for all estimates. Moreover, by employing the data-driven model selection procedure proposed by Gioldasis et al. (2021), it is found that non-parametric specifications provide the best predictive performance and that CCE models always overperform with respect to traditional panel data methods that employ cross-sectional demeaning to account for cross-sectional dependence