Modeling the spatial dynamics of economic models

The advances that have been characterizing spatial econometrics in recent years are mostly theoretical and have not found an extensive empirical application yet. In this work we aim at supplying a review of the main tools of spatial econometrics and to show an empirical application for one of the most recently introduced estimators. Despite the numerous alternatives that the econometric theory provides for the treatment of spatial (and spatiotemporal) data, empirical analyses are still limited by the lack of availability of the correspondent routines in statistical and econometric software. Spatiotemporal modeling represents one of the most recent developments in spatial econometric theory and the finite sample properties of the estimators that have been proposed are currently being tested in the literature. We provide a comparison between some estimators (a quasi-maximum likelihood, QML, estimator and some GMM-type estimators) for a fixed effects dynamic panel data model under certain conditions, by means of a Monte Carlo simulation analysis. We focus on different settings, which are characterized either by fully stable or quasi-unit root series. We also investigate the extent of the bias that is caused by a non-spatial estimation of a model when the data are characterized by different degrees of spatial dependence. Finally, we provide an empirical application of a QML estimator for a time-space dynamic model which includes a temporal, a spatial and a spatiotemporal lag of the dependent variable. This is done by choosing a relevant and prolific field of analysis, in which spatial econometrics has only found limited space so far, in order to explore the value-added of considering the spatial dimension of the data. In particular, we study the determinants of cropland value in Midwestern U.S.A. in the years 1971-2009, by taking the present value model (PVM) as the theoretical framework of analysis.

Intangible resources and organization capital: measurement and economic evaluation

Intangible resources have raised the interests of scholars from different research areas due to their importance as crucial factors for firm performance; yet, contributions to this field still lack a theoretical framework. This research analyses the state-of-the-art results reached in the literature concerning intangibles, their main features and evaluation problems and models. In search for a possible theoretical framework, the research draws a kind of indirect analysis of intangibles through the theories of the firm, their critic and developments. The heterodox approaches of the evolutionary theory and resource-based view are indicated as possible frameworks. Based on this theoretical analysis, organization capital (OC) is identified, for its features, as the most important intangible for firm performance. Empirical studies on the relationship intangibles-firm performance have been sporadic and have failed to reach firm conclusions with respect to OC; in the attempt to fill this gap, the effect of OC is tested on a large sample of European firms using the Compustat Global database. OC is proxied by capitalizing an income statement item (Selling, General and Administrative expenses) that includes expenses linked to information technology, business process design, reputation enhancement and employee training. This measure of OC is employed in a cross-sectional estimation of a firm level production function - modeled with different functional specifications (Cobb-Douglas and Translog) - that measures OC contribution to firm output and profitability. Results are robust and confirm the importance of OC for firm performance.

Performance evaluation of low environmental impact asphalt concretes using the mechanistic empirical design method based on laboratory fatigue and permanent deformation models

The "sustainability" concept relates to the prolonging of human economic systems with as little detrimental impact on ecological systems as possible. Construction that exhibits good environmental stewardship and practices that conserve resources in a manner that allow growth and development to be sustained for the long-term without degrading the environment are indispensable in a developed society. Past, current and future advancements in asphalt as an environmentally sustainable paving material are especially important because the quantities of asphalt used annually in Europe as well as in the U.S. are large. The asphalt industry is still developing technological improvements that will reduce the environmental impact without affecting the final mechanical performance. Warm mix asphalt (WMA) is a type of asphalt mix requiring lower production temperatures compared to hot mix asphalt (HMA), while aiming to maintain the desired post construction properties of traditional HMA. Lowering the production temperature reduce the fuel usage and the production of emissions therefore and that improve conditions for workers and supports the sustainable development. Even the crumb-rubber modifier (CRM), with shredded automobile tires and used in the United States since the mid 1980s, has proven to be an environmentally friendly alternative to conventional asphalt pavement. Furthermore, the use of waste tires is not only relevant in an environmental aspect but also for the engineering properties of asphalt [Pennisi E., 1992]. This research project is aimed to demonstrate the dual value of these Asphalt Mixes in regards to the environmental and mechanical performance and to suggest a low environmental impact design procedure. In fact, the use of eco-friendly materials is the first phase towards an eco-compatible design but it cannot be the only step. The eco-compatible approach should be extended also to the design method and material characterization because only with these phases is it possible to exploit the maximum potential properties of the used materials. Appropriate asphalt concrete characterization is essential and vital for realistic performance prediction of asphalt concrete pavements. Volumetric (Mix design) and mechanical (Permanent deformation and Fatigue performance) properties are important factors to consider. Moreover, an advanced and efficient design method is necessary in order to correctly use the material. A design method such as a Mechanistic-Empirical approach, consisting of a structural model capable of predicting the state of stresses and strains within the pavement structure under the different traffic and environmental conditions, was the application of choice. In particular this study focus on the CalME and its Incremental-Recursive (I-R) procedure, based on damage models for fatigue and permanent shear strain related to the surface cracking and to the rutting respectively. It works in increments of time and, using the output from one increment, recursively, as input to the next increment, predicts the pavement conditions in terms of layer moduli, fatigue cracking, rutting and roughness. This software procedure was adopted in order to verify the mechanical properties of the study mixes and the reciprocal relationship between surface layer and pavement structure in terms of fatigue and permanent deformation with defined traffic and environmental conditions. The asphalt mixes studied were used in a pavement structure as surface layer of 60 mm thickness. The performance of the pavement was compared to the performance of the same pavement structure where different kinds of asphalt concrete were used as surface layer. In comparison to a conventional asphalt concrete, three eco-friendly materials, two warm mix asphalt and a rubberized asphalt concrete, were analyzed. The First Two Chapters summarize the necessary steps aimed to satisfy the sustainable pavement design procedure. In Chapter I the problem of asphalt pavement eco-compatible design was introduced. The low environmental impact materials such as the Warm Mix Asphalt and the Rubberized Asphalt Concrete were described in detail. In addition the value of a rational asphalt pavement design method was discussed. Chapter II underlines the importance of a deep laboratory characterization based on appropriate materials selection and performance evaluation. In Chapter III, CalME is introduced trough a specific explanation of the different equipped design approaches and specifically explaining the I-R procedure. In Chapter IV, the experimental program is presented with a explanation of test laboratory devices adopted. The Fatigue and Rutting performances of the study mixes are shown respectively in Chapter V and VI. Through these laboratory test data the CalME I-R models parameters for Master Curve, fatigue damage and permanent shear strain were evaluated. Lastly, in Chapter VII, the results of the asphalt pavement structures simulations with different surface layers were reported. For each pavement structure, the total surface cracking, the total rutting, the fatigue damage and the rutting depth in each bound layer were analyzed.

Econometric models of financial risks

The goal of this dissertation is to use statistical tools to analyze specific financial risks that have played dominant roles in the US financial crisis of 2008-2009. The first risk relates to the level of aggregate stress in the financial markets. I estimate the impact of financial stress on economic activity and monetary policy using structural VAR analysis. The second set of risks concerns the US housing market. There are in fact two prominent risks associated with a US mortgage, as borrowers can both prepay or default on a mortgage. I test the existence of unobservable heterogeneity in the borrower's decision to default or prepay on his mortgage by estimating a multinomial logit model with borrower-specific random coefficients.

Development of parallelizable flood inundation models for large scale analysis

Flood disasters are a major cause of fatalities and economic losses, and several studies indicate that global flood risk is currently increasing. In order to reduce and mitigate the impact of river flood disasters, the current trend is to integrate existing structural defences with non structural measures. This calls for a wider application of advanced hydraulic models for flood hazard and risk mapping, engineering design, and flood forecasting systems. Within this framework, two different hydraulic models for large scale analysis of flood events have been developed. The two models, named CA2D and IFD-GGA, adopt an integrated approach based on the diffusive shallow water equations and a simplified finite volume scheme. The models are also designed for massive code parallelization, which has a key importance in reducing run times in large scale and high-detail applications. The two models were first applied to several numerical cases, to test the reliability and accuracy of different model versions. Then, the most effective versions were applied to different real flood events and flood scenarios. The IFD-GGA model showed serious problems that prevented further applications. On the contrary, the CA2D model proved to be fast and robust, and able to reproduce 1D and 2D flow processes in terms of water depth and velocity. In most applications the accuracy of model results was good and adequate to large scale analysis. Where complex flow processes occurred local errors were observed, due to the model approximations. However, they did not compromise the correct representation of overall flow processes. In conclusion, the CA model can be a valuable tool for the simulation of a wide range of flood event types, including lowland and flash flood events.

International Agricultural Trade under Regulatory Asymmetry: An Economic Analysis of SME Export Behavior

Over the last three decades, international agricultural trade has grown significantly. Technological advances in transportation logistics and storage have created opportunities to ship anything almost anywhere. Bilateral and multilateral trade agreements have also opened new pathways to an increasingly global market place. Yet, international agricultural trade is often constrained by differences in regulatory regimes. The impact of “regulatory asymmetry” is particularly acute for small and medium sized enterprises (SMEs) that lack resources and expertise to successfully operate in markets that have substantially different regulatory structures. As governments seek to encourage the development of SMEs, policy makers often confront the critical question of what ultimately motivates SME export behavior. Specifically, there is considerable interest in understanding how SMEs confront the challenges of regulatory asymmetry. Neoclassical models of the firm generally emphasize expected profit maximization under uncertainty, however these approaches do not adequately explain the entrepreneurial decision under regulatory asymmetry. Behavioral theories of the firm offer a far richer understanding of decision making by taking into account aspirations and adaptive performance in risky environments. This paper develops an analytical framework for decision making of a single agent. Considering risk, uncertainty and opportunity cost, the analysis focuses on the export behavior response of an SME in a situation of regulatory asymmetry. Drawing on the experience of fruit processor in Muzaffarpur, India, who must consider different regulatory environments when shipping fruit treated with sulfur dioxide, the study dissects the firm-level decision using @Risk, a Monte Carlo computational tool.

Reproduction and maternal health care among young women in Kenya: geographic and socio-economic determinants

Many factors influence the propensity of young women to seek appropriate maternal healthcare, and they need to be considered when analyzing these women’s reproductive behavior. This study aimed to contribute to the analysis concerning Kenyan young women’s determinants on maternal healthcare-seeking behavior for the 5 years preceding the 2008/9 Kenya Demographic and Health Survey. The specific objectives were to: investigate the individual and contextual variables that may explain maternal healthcare habits; measure the individual, household and community effect on maternal healthcare attitudes in young women; assess the link between young women’s characteristics and the use of facilities for maternal healthcare; find a relationship between young women’s behavior and the community where they live; examine how the role of the local presence of healthcare facilities influences reproductive behavior, and if the specificity of services offered by healthcare facilities affects their inclination to use healthcare facilities, and measure the geographic differences that influence the propensity to seek appropriate maternal healthcare. The analysis of factors associated with maternal healthcare-seeking behavior for young women in Kenya was investigated using multilevel models. We performed three major analyses, which concerned the individual and contextual determinants influencing antenatal care (discussed in Part 6), delivery care (Part 7), and postnatal care (Part 8). Our results show that there is a significant variation in antenatal, delivery and postnatal care between communities, even if the majority of variability is explained by individual characteristics. There are differences at the women’s level on the probability of receiving antenatal care and delivering in a healthcare facility instead of at home. Moreover, community factors and availability of healthcare facilities on the territory are also crucial in influencing young women’s behavior. Therefore, policies addressed to youth’s reproductive health should also consider geographic inequalities and different types of barriers in access to healthcare facilities.

Essays on the Empirical Analysis of Economic and Political Development in Sub-Saharan Africa

In Sub-Saharan Africa, non-democratic events, like civil wars and coup d'etat, destroy economic development. This study investigates both domestic and spatial effects on the likelihood of civil wars and coup d'etat. To civil wars, an increase of income growth is one of common research conclusions to stop wars. This study adds a concern on ethnic fractionalization. IV-2SLS is applied to overcome causality problem. The findings document that income growth is significant to reduce number and degree of violence in high ethnic fractionalized countries, otherwise they are trade-off. Income growth reduces amount of wars, but increases its violent level, in the countries with few large ethnic groups. Promoting growth should consider ethnic composition. This study also investigates the clustering and contagion of civil wars using spatial panel data models. Onset, incidence and end of civil conflicts spread across the network of neighboring countries while peace, the end of conflicts, diffuse only with the nearest neighbor. There is an evidence of indirect links from neighboring income growth, without too much inequality, to reduce the likelihood of civil wars. To coup d'etat, this study revisits its diffusion for both all types of coups and only successful ones. The results find an existence of both domestic and spatial determinants in different periods. Domestic income growth plays major role to reduce the likelihood of coup before cold war ends, while spatial effects do negative afterward. Results on probability to succeed coup are similar. After cold war ends, international organisations seriously promote democracy with pressure against coup d'etat, and it seems to be effective. In sum, this study indicates the role of domestic ethnic fractionalization and the spread of neighboring effects to the likelihood of non-democratic events in a country. Policy implementation should concern these factors.