Confidence bounds for the extremum determined by a quadratic regression

A quadratic function is frequently used in regression to infer the existence of an extremum in a relationship. Examples abound in fields such as economics, epidemiology and environmental science. However, most applications provide no formal test of the extremum. Here we compare the Delta method and the Fieller method in typical applications and perform a Monte Carlo study of the coverage of these confidence bounds. We find that unless the parameter on the squared term is estimated with great precision, the Fieller confidence interval may posses dramatically better coverage than the Delta methodTurning Point, Fieller interval, U-shaped

DETERMINANTS OF TECHNICAL EFFICIENCY IN AGRICULTURE AND CATTLE RANCHING: A SPATIAL ANALYSIS FOR THE BRAZILIAN AMAZON

The determinants of technical efficiency in agriculture and cattle ranching are closely related with the debate involving the conservation-development trade-off in the Brazilian Amazon. Concerned with balancing development and environmental conservation, policy makers and academics have emphasized the importance of choosing ways of selecting areas where land use restrictions would be established. In order to understand the relationship between spatial patterns of deforestation and the associated distribution and characteristics of economic activity, issues regarding technical efficiency are clearly important. This paper aims to identify the socio-economic and environmental determinants of technical efficiency in agriculture and cattle ranching in the Brazilian Amazon emphasizing their relationship with spatial processes of deforestation and development. The study is structured in two parts. The first part is concerned with measuring technical efficiency for agriculture and cattle ranching in each geographical unit focusing on the production relationship between inputs and outputs. The second one focuses on the variation in the efficiency measure explained by exogenous factors and includes the spatial analysis. We adopt the model proposed by Battese and Coelli (1995) where the production function and the exogenous effects influencing technical efficiency are estimated simultaneously.

Incorporation of Socio-Economic Data into the Analysis of Remotely-Sensed Images: Basic Quantitative Strategy to Explore Functional Forms of Deforestation

2015年度第2回研究集会[2015年6月25日(木)]報告要

Test of Convergence in Agricultural Factor Productivity: A Semiparametric Approach

We tested for club convergence in U.S. agricultural total factory productivity using a sigma convergence test. We used the same club of states as used by McCunn and Huffman as well as different states within 10 clubs identified by the cluster analysis. Results showed convergence was evident only in a few club groups. Clusters group identified using a statistical method identified only converging clubs. Variables affecting total factor productivity among states were identified using parametric, semiparametric and nonparametric methods. Semiparametric and nonparametric methods gave a better fit than a parametric method as indicated by the specification test. Our results indicated that health care expenditure, public research and extension investment, and private expenditure are important variables impacting total factor productivity differences across states.Clubs, sigma convergence, cluster analysis, semiparametric and nonparametric methods, Productivity Analysis, Research Methods/ Statistical Methods,

Temporal and spatial homogeneity in air pollutants panel EKC estimations: Two nonparametric tests applied to Spanish provinces

Although panel data have been used intensively by a wealth of studies investigating the GDP-pollution relationship, the poolability assumption used to model these data is almost never addressed. This paper applies a strategy to test the poolability assumption with methods robust to functional misspecification. Nonparametric poolability tests are performed to check the temporal and spatial homogeneity of the panel and their results are compared with the conventional F-tests for a balanced panel of 48 Spanish provinces on four air pollutant emissions (CH4, CO, CO2 and NMVOC) over the 1990-2002 period. We show that temporal homogeneity may allow the pooling of the data and drive to well-defined nonparametric and parametric cross-sectional U-inverted shapes for all air pollutants. However, the presence of spatial heterogeneity makes this shape compatible with different timeseries patterns in every province - mainly increasing or decreasing depending on the pollutant. These results highlight the extreme sensitivity of the income-pollution relationship to region- or country-specific factors.Environmental Kuznets Curve; Air pollutants; Non/Semiparametric estimations; Poolability tests

Rule of law and the Environmental Kuznets Curve: evidence for carbon emissions

In response to recently growing literature investigating the relationship between environment and institutions, this study investigates how rule of law influences the level of income at the turning point of the Environmental Kuznets Curve (EKC). Using an alternative specification of EKC that avoids nonlinear transformation of potentially nonstationary regressors, investigated by Bradford et al. (2005) and Leitao (2010), we find the evidence for the EKC in European countries for carbon emissions. Our results find a negative relationship between pollution and rule of law, demonstrating that when rule of law is strong, the turning point of the EKC occurs at a lower level of income per capita, thus, decreasing emissions. In terms of policy implication, our study suggests that institutional reinforcement should deserve close attention in designing and enforcing policies that limit environmental degradation.Environmental Kuznets Curve, Rule of law, Panel data, Turning point

Temporal and spatial homogeneity in air pollutants panel EKC estimations: Two nonparametric tests applied to Spanish provinces

Although panel data have been used intensively by a wealth of studies investigating the GDP-pollution relationship, the poolability assumption used to model these data is almost never addressed. This paper applies a strategy to test the poolability assumption with methods robust to functional misspecification. Nonparametric poolability tests are performed to check the temporal and spatial homogeneity of the panel and their results are compared with the conventional F-tests for a balanced panel of 48 Spanish provinces on four air pollutant emissions (CH4, CO, CO2 and NMVOC) over the 1990-2002 period. We show that temporal homogeneity may allow the pooling of the data and drive to well-defined nonparametric and parametric cross-sectional U-inverted shapes for all air pollutants. However, the presence of spatial heterogeneity makes this shape compatible with different timeseries patterns in every province - mainly increasing or decreasing depending on the pollutant. These results highlight the extreme sensitivity of the income-pollution relationship to region- or country-specific factors.Environmental Kuznets Curve, Air pollutants, Non/Semiparametric estimations, Poolability tests

Quality of Institutions, Technological Progress, and Pollution Havens in Latin America. An Analysis of the Environmental Kuznets Curve Hypothesis

A set of 17-year panel data (1996–2013) across a representative sample from eighteen Latin American countries is used to respond four research questions: Did Latin American Greenhouse Gas (GHG) emissions prove the Environmental Kuznets Curve (EKC) hypothesis? Did the quality of institutions play a compensating role for income on environmental stress? Did technological progress help decouple income from environmental stress? Has the Pollution Haven Hypothesis (PHH) been proven? In order to answer the research questions, the paper expands the traditional EKC approach by including an exclusive quality analysis of institutions, technological progress, and PHH as part of the model. This innovation is developed considering the most recent literature about EKC as a starting point. Major findings show that the relationship between income and GHG emissions is adjusted to the traditional EKC hypothesis for the analyzed period. They also show that the quality of institutions and technological progress improve environmental sustainability. However, the variables, Foreign Direct Investment and International Trade, provide a negative answer to the fourth question. The main methodological contribution of this paper is to use a threefold extended classic EKC model to conduct the feasible generalized least squares method. The paper also contributes to the growing body of PHH literature.Junta de Andalucía proyecto SEJ-132Cátedra de Economía de la Energía y del MedioUniversidad Autónoma de Chil

Road development in the Brazilian Amazon and its ecological implications

Roads are a distinctive feature in any landscape, with many countries giving 1-2% of their land surface over to roads and roadsides (Forman 1998). However, the ecological effects of roads spread beyond the physical footprint of the network and may impact 15-20% of the land or more (Forman & Alexander 1998). The Brazilian Amazon contains approximately one third of the world’s remaining rainforest, covering an area of 4.1 million km2. The region is highly biodiverse with 10-20 percent of the planet’s known species, it is also one of the three most bioculturally diverse areas in the world (Loh & Harmon 2005), and it provides many valuable ecosystem services. However, the Brazilian Amazon is rapidly undergoing extensive development with widespread land-use conversion. Road development is often perceived as the initial stage of development, opening access to remote areas for colonisation, agriculture development, resource extraction, and linked with these; deforestation (Chomitz & Gray 1996, Laurance et al. 2001, Perz et al. 2007, Laurance et al. 2009, Caldas et al. 2010). As such roads are a key spatial determinant of land use conversion in the Amazon region, dictating the spatial pattern of deforestation and biodiversity loss (Fearnside 2005, Kirby et al. 2006, Perz et al. 2008). Given that roads are a key spatial determinant of land use conversion and that they have extensive impacts on rates and patterns of habitat loss, it is important that we know how much, how fast and where road networks are developing in this globally important ecosystem. In this thesis, I aim to construct models of road network development to help better understand and predict the impacts of economic development in the Brazilian Amazon.Open Acces