Impacto del entorno institucional en la financiación público-privada de infraestructuras de transporte

Actualmente el sector privado posee un papel relevante en la provisión y gestión de infraestructuras de transporte en los países de ingreso medio‐bajo, principalmente a través de los proyectos de participación público‐privada (PPPs). Muchos países han impulsado este tipo de proyectos con el fin de hacer frente a la gran demanda de infraestructuras de transporte existente, debido a la escasez de recursos públicos y a la falta de eficiencia en la provisión de los servicios públicos. Como resultado, las PPPs han experimentado un crecimiento importante en las últimas dos décadas a nivel mundial. A pesar de esta tendencia creciente, muchos países no han sido capaces de atraer la participación del sector privado para la provisión de sus infraestructuras o no han logrado el nivel de participación privada que habrían requerido para alcanzar sus objetivos. Según numerosos autores, el desarrollo y el éxito de los proyectos PPP de infraestructuras de transporte de cualquier país está condicionado por una diversidad de factores, siendo uno de ellos la calidad de su entorno institucional. La presente tesis tiene como objetivo principal analizar la influencia del entorno institucional en el volumen de inversión en proyectos de participación público‐privada de infraestructuras de transporte en los países de ingreso medio‐bajo. Para acometer dicho objetivo se ha realizado un análisis empírico de 81 países distribuidos en seis regiones del mundo, durante el periodo 1996‐2013. En el análisis se han desarrollado dos modelos empíricos aplicando principalmente dos metodologías: el contraste de hipótesis y los modelos de datos de panel Tobit. El desarrollo de estos modelos ha permitido analizar de una forma exhaustiva el tema de estudio. Los resultados obtenidos aportan evidencia de que la calidad del entorno institucional posee una influencia significativa en el volumen de inversión en los proyectos PPP de transporte. En general, en esta tesis se muestran evidencias empíricas de que el sector privado ha tendido a invertir en mayor medida en países con entornos institucionales fuertes, es decir, en aquellos países en los que ha existido un mayor nivel de Estado de derecho, estabilidad política y regulatoria, efectividad del gobierno, así como un mayor control de la corrupción. Además, aquellos países donde se ha registrado una mejora en el nivel de su calidad institucional también han experimentado un incremento en el volumen de inversión en PPP de transporte. The private sector has an important role in the provision and management of transport infrastructure in countries of medium‐low income, primarily through projects of public‐private partnerships (PPPs). Many countries have developed PPP projects to meet the high demand of transport infrastructure, due to the scarcity of public resources and the lack of efficiency in the provision of public services. As a result, PPPs have experienced a significant growth, worldwide, in the past two decades. Despite this growing trend, many countries have not been able to attract private sector participation in the provision of infrastructure or have not accomplished the level of private participation that would have required to achieve its objectives. According to various authors, the development of PPP projects for transport infrastructure is determined by a number of factors, one of them being the quality of the institutional environment. The main objective of this dissertation is to analyze the influence of the institutional environment on the volume of investment, in projects of public‐private partnerships for transport infrastructure in countries of medium‐low income. In order to meet this objective, we conducted an empirical analysis of 81 countries, in six regions of the world, during the period of 1996‐2013. The analysis used two empirical models, implementing different methodologies and various statistical techniques: hypothesis testing, and Tobit model using panel data. The development of these models allowed to carry out a more comprehensive analysis. The results show that the quality of the institutional environment has a significant influence on the volume of investment in PPP projects of transport. Overall, this dissertation shows that the private sector tends to invest more in countries with stronger institutional environments, i.e. countries where there has been a higher level of Rule of Law, political and regulatory stability, and an effective control of corruption. In addition, those that have improved the level of institutional quality have also experienced an increase in the volume of investment in PPP of transport.

The observed global warming record: What does it tell us?

Global, near-surface temperature data sets and their derivations are discussed, and differences between the Jones and Intergovernmental Panel on Climate Change data sets are explained. Global-mean temperature changes are then interpreted in terms of anthropogenic forcing influences and natural variability. The inclusion of aerosol forcing improves the fit between modeled and observed changes but does not improve the agreement between the implied climate sensitivity value and the standard model-based range of 1.5–4.5°C equilibrium warming for a CO2 doubling. The implied sensitivity goes from below the model-based range of estimates to substantially above this range. The addition of a solar forcing effect further improves the fit and brings the best-fit sensitivity into the middle of the model-based range. Consistency is further improved when internally generated changes are considered. This consistency, however, hides many uncertainties that surround observed data/model comparisons. These uncertainties make it impossible currently to use observed global-scale temperature changes to narrow the uncertainty range in the climate sensitivity below that estimated directly from climate models.

Identifying the role of natural resources in knowledge-based strategies of development

Knowledge has adopted a preferential role in the explanation of development while the evidence about the effect of natural resources in countries’ performance is more controversial in the economic literature. This paper tries to demonstrate that natural resources may positively affect growth in countries with a strong natural resources specialization pattern although the magnitude of these effects depend on the type of resources and on other aspects related to the production and innovation systems. The positive trajectory described by a set of national economies mainly specialized in natural resources and low-tech industries invites us to analyze what is the combination of factors that serves as engine for a sustainable development process. With panel data for the period 1996-2008 we estimate an applied growth model where both traditional factors and other more related to innovation and absorptive capabilities are taken into account. Our empirical findings show that according to the postulates of a knowledge-based approach, a framework that combines physical and intangible factors is more suitable for the definition of development strategies in those prosperous economies dominated by natural resources and connected activities, while the internationalization process of activities and technologies become also a very relevant aspect.

Determinants of Farm Labour Use: A Comparison between Ireland and Italy. Factor Markets Working Documents No. 60, August 2013

This paper examines the effect of the decoupling of farm direct payments upon the off-farm labour supply decisions of farmers in both Ireland and Italy, using panel data from the Farm Business Survey (REA) and FADN database covering the period from 2002 to 2009 to model these decisions. Drawing from the conceptual agricultural household model, the authors hypothesise that the decoupling of direct payments led to an increase in off-farm labour activity despite some competing factors. This hypothesis rests largely upon the argument that the effects of changes in relative wages have dominated other factors. At a micro level, the decoupling-induced decline in the farm wage relative to the non-farm wage ought to have provoked a greater incentive for off-farm labour supply. The main known competing argument is that decoupling introduced a new source of non-labour income i.e. a wealth effect. This may in turn have suppressed or eliminated the likelihood of increased off-farm labour supply for some farmers. For the purposes of comparative analysis, the Italian model utilises the data from the REA database instead of the FADN as the latter has a less than satisfactory coverage of labour issues. Both models are developed at a national level. The paper draws from the literature on female labour supply and uses a sample selection corrected ordinary least squares model to examine both the decisions of off-farm work participation and the decisions regarding the amount of time spent working off-farm. The preliminary results indicate that decoupling has not had a significant impact on off-farm labour supply in the case of Ireland but there appears to be a significantly negative relationship in the Italian case. It still remains the case in both countries that the wealth of the farmer is negatively correlated with the likelihood of off-farm employment.

Essays on Fiscal Policy, Monetary Policy and Currency Unions: Exploring the Role of Informality and Labor Mobility

Thesis (Ph.D.)--University of Washington, 2016-06

How cost efficient are Australia's mining industries?

This paper uses a stochastic translog cost frontier model and a panel data of five key mining industries in Australia over 1968-1969 to 1994-1995 to investigate the sources of output growth and the effects of cost inefficiency on total factor productivity (TFP) growth. The results indicate that mining output growth was largely input-driven rather than productivity-driven. Although there were some gains from technological progress and economics of scale in production, cost inefficiency which barely exceeded 1.1% since the mid-1970s in the mining industries was the main factor causing low TFP growth. (C) 2002 Elsevier Science B.V. All rights reserved.

Trade liberalisation and technical efficiency: Evidence from Bangladesh manufacturing industries

The paper investigates the effects of trade liberalisation on the technical efficiency of the Bangladesh manufacturing sector by estimating a combined stochastic frontier-inefficiency model using panel data for the period 197894 for 25 three-digit level industries. The results show that the overall technical efficiency of the manufacturing sector as well as the technical efficiencies of the majority of the individual industries has increased over time. The findings also clearly suggest that trade liberalisation, proxied by export orientation and capital deepening, has had significant impact on the reduction of the overall technical inefficiency. Similarly, the scale of operation and the proportion of non-production labour in total employment appear as important determinants of technical inefficiency. The evidence also indicates that both export-promoting and import-substituting industries have experienced rises in technical efficiencies over time. Besides, the results are suggestive of neutral technical change, although (at the 5 per cent level of significance) the empirical results indicate that there was no technical change in the manufacturing industries. Finally, the joint test based on the likelihood ratio (LR) test rejects the Cobb-Douglas production technology as description of the database given the specification of the translog production technology.

A metafrontier production function for estimation of technical efficiencies and technology gaps for firms operating under different technologies

This paper presents a metafrontier production function model for firms in different groups having different technologies. The metafrontier model enables the calculation of comparable technical efficiencies for firms operating under different technologies. The model also enables the technology gaps to be estimated for firms under different technologies relative to the potential technology available to the industry as a whole. The metafrontier model is applied in the analysis of panel data on garment firms in five different regions of Indonesia, assuming that the regional stochastic frontier production function models have technical inefficiency effects with the time-varying structure proposed by Battese and Coelli ( 1992).

Industry-specific human capital, knowledge labour, and industry wage structure in Taiwan

This paper investigates the role of industry-specific human capital (ISHC) in determining industry wage structure. The model presented in this paper distinguishes between knowledge labour and physical labour. Knowledge labour is physical labour embodied with ISHC. It is postulated that more ISHC-intensive industries, such as high-tech industries, pay higher wages and the wage premiums increase with workers' experience. The hypothesis is tested using a merged sample of 1997 - 1999 manpower utilization survey data from a newly industrialized economy - Taiwan. The findings show support for the effect of ISHC.

Lameness, metabolic and digestive disorders, and technical efficiency in Danish dairy herds: a stochastic frontier production function approach

The relationship between reported treatments of lameness, metabolic disorders (milk fever, ketosis), digestive disorders, and technical efficiency (TE) was investigated using neutral and non-neutral stochastic frontier analysis (SFA). TE is estimated relative to the stochastic frontier production function for a sample of 574 Danish dairy herds collected in 1997. Contrary to most published results, but in line with the expected negative impact of disorders on the average cow milk production, herds reporting higher frequencies of milk fever are less technically efficient. Unexpectedly, however, the opposite results were observed for lameness, ketosis, and digestive disorders. The non-neutral stochastic frontier indicated that the opposite results are due to the relative. high productivities of inputs. The productivity of the cows is also reflected by the direction of impact of herd management variables. Whereas efficient farms replace cows more frequently, enroll heifers in production at an earlier age, and have shorter calving intervals, they also report higher frequency of disorder treatments. The average estimated energy corrected milk loss per cow is 1036, 451 and 242 kg for low, medium and high efficient farms. The study demonstrates the benefit of the stochastic frontier production function involving the estimation of individual technical efficiencies to evaluate farm performance and investigate the source of inefficiency. (C) 2004 Elsevier B.V. All rights reserved.

Relationships of Efficiency to Reproductive Disorders in Danish Milk Production: A Stochastic Frontier Analysis

Relationships of various reproductive disorders and milk production performance of Danish dairy farms were investigated. A stochastic frontier production function was estimated using data collected in 1998 from 514 Danish dairy farms. Measures of farm-level milk production efficiency relative to this production frontier were obtained, and relationships between milk production efficiency and the incidence risk of reproductive disorders were examined. There were moderate positive relationships between milk production efficiency and retained placenta, induction of estrus, uterine infections, ovarian cysts, and induction of birth. Inclusion of reproductive management variables showed that these moderate relationships disappeared, but directions of coefficients for almost all those variables remained the same. Dystocia showed a weak negative correlation with milk production efficiency. Farms that were mainly managed by young farmers had the highest average efficiency scores. The estimated milk losses due to inefficiency averaged 1142, 488, and 256 kg of energy-corrected milk per cow, respectively, for low-, medium-, and high-efficiency herds. It is concluded that the availability of younger cows, which enabled farmers to replace cows with reproductive disorders, contributed to high cow productivity in efficient farms. Thus, a high replacement rate more than compensates for the possible negative effect of reproductive disorders. The use of frontier production and efficiency/ inefficiency functions to analyze herd data may enable dairy advisors to identify inefficient herds and to simulate the effect of alternative management procedures on the individual herd's efficiency.

A Bayesian approach to imposing curvature on distance functions

The estimated parameters of output distance functions frequently violate the monotonicity, quasi-convexity and convexity constraints implied by economic theory, leading to estimated elasticities and shadow prices that are incorrectly signed, and ultimately to perverse conclusions concerning the effects of input and output changes on productivity growth and relative efficiency levels. We show how a Bayesian approach can be used to impose these constraints on the parameters of a translog output distance function. Implementing the approach involves the use of a Gibbs sampler with data augmentation. A Metropolis-Hastings algorithm is also used within the Gibbs to simulate observations from truncated pdfs. Our methods are developed for the case where panel data is available and technical inefficiency effects are assumed to be time-invariant. Two models-a fixed effects model and a random effects model-are developed and applied to panel data on 17 European railways. We observe significant changes in estimated elasticities and shadow price ratios when regularity restrictions are imposed. (c) 2004 Elsevier B.V. All rights reserved.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Data flow and validation in workflow modelling

A complete workflow specification requires careful integration of many different process characteristics. Decisions must be made as to the definitions of individual activities, their scope, the order of execution that maintains the overall business process logic, the rules governing the discipline of work list scheduling to performers, identification of time constraints and more. The goal of this paper is to address an important issue in workflows modelling and specification, which is data flow, its modelling, specification and validation. Researchers have neglected this dimension of process analysis for some time, mainly focussing on structural considerations with limited verification checks. In this paper, we identify and justify the importance of data modelling in overall workflows specification and verification. We illustrate and define several potential data flow problems that, if not detected prior to workflow deployment may prevent the process from correct execution, execute process on inconsistent data or even lead to process suspension. A discussion on essential requirements of the workflow data model in order to support data validation is also given..

Ontological clarity and comprehension in health data models

Conceptual modeling forms an important part of systems analysis. If this is done incorrectly or incompletely, there can be serious implications for the resultant system, specifically in terms of rework and useability. One approach to improving the conceptual modelling process is to evaluate how well the model represents reality. Emergence of the Bunge-Wand-Weber (BWW) ontological model introduced a platform to classify and compare the grammar of conceptual modelling languages. This work applies the BWW theory to a real world example in the health arena. The general practice computing group data model was developed using the Barker Entity Relationship Modelling technique. We describe an experiment, grounded in ontological theory, which evaluates how well the GPCG data model is understood by domain experts. The results show that with the exception of the use of entities to represent events, the raw model is better understood by domain experts