Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN)

Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.

Predicting microbial pollution concentrations in UK rivers in response to land use change

The Water Framework Directive has caused a paradigm shift towards the integrated management of recreational water quality through the development of drainage basin-wide programmes of measures. This has increased the need for a cost-effective diagnostic tool capable of accurately predicting riverine faecal indicator organism (FIO) concentrations. This paper outlines the application of models developed to fulfil this need, which represent the first transferrable generic FIO models to be developed for the UK to incorporate direct measures of key FIO sources (namely human and livestock population data) as predictor variables. We apply a recently developed transfer methodology, which enables the quantification of geometric mean presumptive faecal coliforms and presumptive intestinal enterococci concentrations for base- and high-flow during the summer bathing season in unmonitored UK watercourses, to predict FIO concentrations in the Humber river basin district. Because the FIO models incorporate explanatory variables which allow the effects of policy measures which influence livestock stocking rates to be assessed, we carry out empirical analysis of the differential effects of seven land use management and policy instruments (fiscal constraint, production constraint, cost intervention, area intervention, demand-side constraint, input constraint, and micro-level land use management) all of which can be used to reduce riverine FIO concentrations. This research provides insights into FIO source apportionment, explores a selection of pollution remediation strategies and the spatial differentiation of land use policies which could be implemented to deliver river quality improvements. All of the policy tools we model reduce FIO concentrations in rivers but our research suggests that the installation of streamside fencing in intensive milk producing areas may be the single most effective land management strategy to reduce riverine microbial pollution.

Forecast encompassing tests and probability forecasts

We consider tests of forecast encompassing for probability forecasts, for both quadratic and logarithmic scoring rules. We propose test statistics for the null of forecast encompassing, present the limiting distributions of the test statistics, and investigate the impact of estimating the forecasting models' parameters on these distributions. The small-sample performance is investigated, in terms of small numbers of forecasts and model estimation sample sizes. We show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables, and for evaluating survey-based probability forecasts.

The dependent variable problem in quantitative studies of Active Labour Market Programmes: uncovering hidden dynamics?

The question of what explains variation in expenditures on Active Labour Market Programs (ALMPs) has attracted significant scholarship in recent years. Significant insights have been gained with respect to the role of employers, unions and dual labour markets, openness, and partisanship. However, there remain significant disagreements with respects to key explanatory variables such the role of unions or the impact of partisanship. Qualitative studies have shown that there are both good conceptual reasons as well as historical evidence that different ALMPs are driven by different dynamics. There is little reason to believe that vastly different programs such as training and employment subsidies are driven by similar structural, interest group or indeed partisan dynamics. The question is therefore whether different ALMPs have the same correlation with different key explanatory variables identified in the literature? Using regression analysis, this paper shows that the explanatory variables identified by the literature have different relation to distinct ALMPs. This refinement adds significant analytical value and shows that disagreements are at least partly due to a dependent variable problem of ‘over-aggregation’.

Ant larval demand reduces aphid colony growth rates in an ant-aphid interaction

Ants often form mutualistic interactions with aphids, soliciting honeydew in return for protective services. Under certain circumstances, however, ants will prey upon aphids. In addition, in the presence of ants aphids may increase the quantity or quality of honeydew produced, which is costly. Through these mechanisms, ant attendance can reduce aphid colony growth rates. However, it is unknown whether demand from within the ant colony can affect the ant-aphid interaction. In a factorial experiment, we tested whether the presence of larvae in Lasius niger ant colonies affected the growth rate of Aphis fabae colonies. Other explanatory variables tested were the origin of ant colonies (two separate colonies were used) and previous diet (sugar only or sugar and protein). We found that the presence of larvae in the ant colony significantly reduced the growth rate of aphid colonies. Previous diet and colony origin did not affect aphid colony growth rates. Our results suggest that ant colonies balance the flow of two separate resources from aphid colonies- renewable sugars or a protein-rich meal, depending on demand from ant larvae within the nest. Aphid payoffs from the ant-aphid interaction may change on a seasonal basis, as the demand from larvae within the ant colony waxes and wanes.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

Influence of multi-scale landscape structure on the occurrence of carnivorous mammals in a human-modified savanna, Brazil

So Paulo is the most developed state in Brazil and contains few fragments of native ecosystems, generally surrounded by intensive agriculture lands. Despite this, some areas still shelter large native animals. We aimed at understanding how medium and large carnivores use a mosaic landscape of forest/savanna and agroecosystems, and how the species respond to different landscape parameters (percentage of landcover and edge density), in a multi-scale perspective. The response variables were: species richness, carnivore frequency and frequency for the three most recorded species (Puma concolor, Chrysocyon brachyurus and Leopardus pardalis). We compared 11 competing models using Akaike`s information criterion (AIC) and assessed model support using weight of AIC. Concurrent models were combinations of landcover types (native vegetation, ""cerrado"" formations, ""cerrado"" and eucalypt plantation), landscape feature (percentage of landcover and edge density) and spatial scale. Herein, spatial scale refers to the radius around a sampling point defining a circular landscape. The scales analyzed were 250 (fine), 1,000 (medium) and 2,000 m (coarse). The shape of curves for response variables (linear, exponential and power) was also assessed. Our results indicate that species with high mobility, P. concolor and C. brachyurus, were best explained by edge density of the native vegetation at a coarse scale (2,000 m). The relationship between P. concolor and C. brachyurus frequency had a negative power-shaped response to explanatory variables. This general trend was also observed for species richness and carnivore frequency. Species richness and P. concolor frequency were also well explained by a second concurrent model: edge density of cerrado at the fine (250 m) scale. A different response was recorded for L. pardalis, as the frequency was best explained for the amount of cerrado at the fine (250 m) scale. The curve of response was linearly positive. The contrasting results (P. concolor and C. brachyurus vs L. pardalis) may be due to the much higher mobility of the two first species, in comparison with the third. Still, L. pardalis requires habitat with higher quality when compared with other two species. This study highlights the importance of considering multiple spatial scales when evaluating species responses to different habitats. An important and new finding was the prevalence of edge density over the habitat extension to explain overall carnivore distribution, a key information for planning and management of protected areas.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

Growth, migration and unemployment across Swedish municipalities

Fundamental questions in economics are why some regions are richer than others, why their economic growth rates vary, whether their growth tends to converge and the key factors that contribute to the variations. These questions have not yet been fully addressed, but changes in the local tax base are clearly influenced by the average income growth rate, net migration rate, and changes in unemployment rates. Thus, the main aim of this paper is to explore in depth the interactive effects of these factors (and local policy variables) in Swedish municipalities, by estimating a proposed three-equation system. Our main finding is that increases in local public expenditures and income taxes have negative effects on subsequent local income growth. In addition, our results support the conditional convergence hypothesis, i.e. that average income tends to grow more rapidly in relatively poor local jurisdictions than in initially “richer” jurisdictions, conditional on the other explanatory variables.

Growth and Inequality : A study of Swedish municipalities

This paper explores the relationship between the growth rate of the average income and income inequality using data at the municipal level in Sweden for the period 1992-2007. We estimate a fixed effects panel data growth model where the within-municipality income inequality is one of the explanatory variables. Different inequality measures (Gini coefficient, top income shares, and measures of inequality in the lower and upper ends of the income distribution) are also examined. We find a positive and significant relationship between income growth and income inequality, measured as the Gini coefficient and top income shares, respectively. In addition, while inequality at the upper end of the income distribution is positively associated with the income growth rate, inequality at the lower end of the income distribution seems to be negatively related to the growth rate. Our findings also suggest that increased income inequality enhances growth more in municipalities with a high level of average income than in those with a low level of average income.

Essays on growth and environment

This thesis consists of a summary and four self-contained papers. Paper [I] Following the 1987 report by The World Commission on Environment and Development, the genuine saving has come to play a key role in the context of sustainable development, and the World Bank regularly publishes numbers for genuine saving on a national basis. However, these numbers are typically calculated as if the tax system is non-distortionary. This paper presents an analogue to genuine saving in a second best economy, where the government raises revenue by means of distortionary taxation. We show how the social cost of public debt, which depends on the marginal excess burden, ought to be reflected in the genuine saving. We also illustrate by presenting calculations for Greece, Japan, Portugal, U.K., U.S. and OECD average, showing that the numbers published by the World Bank are likely to be biased and may even give incorrect information as to whether the economy is locally sustainable. Paper [II] This paper examines the relationships among per capita CO2 emissions, per capita GDP and international trade based on panel data spanning the period 1960-2008 for 150 countries. A distinction is also made between OECD and Non-OECD countries to capture the differences of this relationship between developed and developing economies. We apply panel unit root and cointegration tests, and estimate a panel error correction model. The results from the error correction model suggest that there are long-term relationships between the variables for the whole sample and for Non-OECD countries. Finally, Granger causality tests show that there is bi-directional short-term causality between per capita GDP and international trade for the whole sample and between per capita GDP and CO2 emissions for OECD countries. Paper [III] Fundamental questions in economics are why some regions are richer than others, why their growth rates differ, whether their growth rates tend to converge, and what key factors contribute to explain economic growth. This paper deals with the average income growth, net migration, and changes in unemployment rates at the municipal level in Sweden. The aim is to explore in depth the effects of possible underlying determinants with a particular focus on local policy variables. The analysis is based on a three-equation model. Our results show, among other things, that increases in the local public expenditure and income taxe rate have negative effects on subsequent income income growth. In addition, the results show conditional convergence, i.e. that the average income among the municipal residents tends to grow more rapidly in relatively poor local jurisdictions than in initially “richer” jurisdictions, conditional on the other explanatory variables. Paper [IV] This paper explores the relationship between income growth and income inequality using data at the municipal level in Sweden for the period 1992-2007. We estimate a fixed effects panel data growth model, where the within-municipality income inequality is one of the explanatory variables. Different inequality measures (Gini coefficient, top income shares, and measures of inequality in the lower and upper part of the income distribution) are examined. We find a positive and significant relationship between income growth and income inequality measured as the Gini coefficient and top income shares, respectively. In addition, while inequality in the upper part of the income distribution is positively associated with the income growth rate, inequality in the lower part of the income distribution seems to be negatively related to the income growth. Our findings also suggest that increased income inequality enhances growth more in municipalities with a high level of average income than in municipalities with a low level of average income.

Um estudo sobre a produtividade total dos fatores em setores de diferentes intensidades tecnólogicas

Este trabalho investigou o problema da determinação da produtividade total dos fatores em diversos setores industriais. Tal determinação se dá por meio de estimação de funções de produção, obtendo-se a produtividade a partir do resíduo destas estimações. A questão que aflora deste procedimento é a existência de correlação entre os resíduos e as variáveis explicativas, implicando em diversos vieses, entre eles o de simultaneidade, de variáveis omitidas e de seleção. Neste trabalho foram abordados diversos métodos de estimação de funções de produção, entre eles os métodos de Olley e Pakes e Levinsohn e Petrin. Todos os métodos foram aplicados a diversos setores da economia. A escolha dos setores se deu com base na intensidade tecnológica de cada um, sendo então escolhidos quatro setores de alta intensidade tecnológica e quatro de baixa intensidade tecnológica. A hipótese básica, fio condutor deste trabalho, é que os diversos métodos de estimação de funções de produção apresentam diferentes resultados quando aplicados a setores de diferentes intensidades tecnológicas. Um dos objetivos deste estudo foi identificar se determinado método seria mais adequado a setores de baixa intensidade tecnológica, enquanto outro seria mais apropriado a setores de alta intensidade tecnológica. Conclui-se que o método de Olley e Pakes é levemente superior ao de Levinsohn e Petrin em ambos os grupos de setores, mas não a ponto de se descartar o segundo método. A sensibilidade dos resultados aos diferentes métodos sugere que todos devem ser consultados. Um resultado adicional deste trabalho é a constatação de que houve queda ou estagnação da produtividade nos setores selecionados para a década de 1996 a 2005.

Aspectos concorrenciais no mercado de leite fluido: um teste empírico no município de São Paulo

O objetivo deste trabalho é caracterizar o padrão de concorrência no mercado de leite fluido (longa vida e pasteurizado) na cidade de São Paulo a partir de evidências sobre os movimentos de preços no varejo e do comportamento das margens de mercado. Utilizou-se o modelo originalmente proposto por Houck (1977) acrescido das observações feitas por Carman e Sexton (2005). Essa abordagem separa as variáveis explicativas entre aumentos e diminuições de preços pagos ao produtor. Além de maior clareza na sua estrutura, essa construção permite comparar a defasagem entre esses dois movimentos e estudar a estratégia de preços dos agentes a partir das margens dos intermediários. O período analisado foi de dezembro de 1999 à dezembro de 2005, com dados de preços ao consumidor da FIPE e dados de preços ao produtor da CEPEA/ USP. Identificou-se que o padrão de concorrência do leite longa vida é bastante diverso do encontrado para o leite pasteurizado. Enquanto para o longa vida o padrão de concorrência é mais próximo do modelo competitivo, para o leite pasteurizado o padrão encontrado foi de pouca concorrência. Para compreender essas diferenças, foi discutido o aspecto locacional do varejo e a importância do mercado relevante geográfico. Os resultados permitem algumas inferências para análises setoriais e de políticas públicas voltadas à produção leiteira. O vertiginoso crescimento das vendas de leite longa vida, absorvendo grande parte do mercado antes abastecido pelo leite pasteurizado, trouxe maior concorrência nos segmentos de indústria e distribuição, assim como maior velocidade de transmissão de preços ao longo da cadeia produtiva. Entretanto, a precificação com markups com percentual fixo, observada no leite longa vida, indica que indústria e distribuição gozam de algum poder de mercado e que variações de custo da matéria-prima são repassadas mais que proporcionalmente, em termos absolutos, ao consumidor final.

Previsão de inflação utilizando modelos de séries temporais

Este trabalho compara modelos de séries temporais para a projeção de curto prazo da inflação brasileira, medida pelo Índice de Preços ao Consumidor Amplo (IPCA). Foram considerados modelos SARIMA de Box e Jenkins e modelos estruturais em espaço de estados, estimados pelo filtro de Kalman. Para a estimação dos modelos, foi utilizada a série do IPCA na base mensal, de março de 2003 a março de 2012. Os modelos SARIMA foram estimados no EVIEWS e os modelos estruturais no STAMP. Para a validação dos modelos para fora da amostra, foram consideradas as previsões 1 passo à frente para o período de abril de 2012 a março de 2013, tomando como base os principais critérios de avaliação de capacidade preditiva propostos na literatura. A conclusão do trabalho é que, embora o modelo estrutural permita, decompor a série em componentes com interpretação direta e estudá-las separadamente, além de incorporar variáveis explicativas de forma simples, o desempenho do modelo SARIMA para prever a inflação brasileira foi superior, no período e horizonte considerados. Outro importante aspecto positivo é que a implementação de um modelo SARIMA é imediata, e previsões a partir dele são obtidas de forma simples e direta.