Using choice experiments to value the social benefits from reduced pesticide usage in the United Kingdom

In this thesis, a Choice Experiment (CE) approach was used to estimate public 'willingness-to-pay' (WTR) for pesticide reduction in the UK. The need to determine WTP for pesticide reductions is driven by policy pressures to reduce the associated negative externalities of pesticide use. Two surveys were undertaken 19 examine different aspects ofthis policy concern. The first survey used a CE to value the public's WTP fot,pesticide- free food. This survey was large in scale but relatively simple in design. The second sun\ey employed two related but separate CEs to value WTP for reductions in insecticides, herbicides and 'fungicides in the UK. In particular, it was designed to examine WTP with respect to 'environmental s~:ty' ..', . and 'food safety'issues.' ,; The first survey was part ofa large survey conducted 'in-home' byMORl for DEFRA. Though access too8 MaRl survey yielded a large number of respondents, the simplicity of the CE is a reflection of the space constraint faced. WTP for pesticide reduction was estimated by employing a 'standard; conditional logit (CL) model. An important component ofthis research is the use ofa novel statistical approach to generaqse the CL to allow and measure respondents' tendency to mis-report their 'true' preferences. To facilitatp estimation, Bayesian methods were used. The motivation for employing the generalised CL lies iR.. ~re considerable concern expressed in the WTP literature regarding upwardly biased WTP estimates. Bayefi Factors were used to assess model specification and indicate a strong preference for the generalised CL. AS anticipated, many respondents (41%) reported 'false' preferences, most of which (79%) reported in favo~r of 'No Pesticides; food. By accounting for bias in responses, WTP estimates were downwardly revised by 35% relative to the standard CL. However, adjusting for mis-reporting reduced WTP from 149010 to only 97% for 'No Pesticides' food. The second survey was mail-delivered and included two CEs. Though a smaller sample than the first survey was obtained, both of these CEs were much more sophisticated. These CEs differentiate~ environmental and health concerns, by associating each with a particular commodity: bread, and a basket of .fruit and vegetables, respectively. Both CEs were designed to estimate marginal WTP for insecticide, herbicide and fungicide reductions. Using Classical statistical methods, the CL specifications revealed that being female, environment- or food safety-sensitive, living as a couple, caring for dependents, and regularly purchasing organic food are factors that increase WTP for reduced-pesticide food. Howevh, 'higherincome, age and education seem to reduce WTP. In ordertoa~ountfor heterogeneity,a latent:cl~ model (LCM) was. estimated. Segments with positive payment parameters were initially observed. 111(& instance of yea-saying was resolved by discarding respondents who only chose 'No Pesticides'. The LCM revealed a significant segmentation of the population in both CEs. Moreover, the LCMs yielded higher WTP estimates than CLs..WTP, expressed as percentage or the baseline price, was higher in the 'environmental safety' CE (102% and 83% for LCM and CL respectively) than in the 'food safety' ~E (69% and 40% for LCM and CL respectively). ! . Overall, the results pr~sentedin this thesis indicate that the public is willing to pay a considerable'prem.i~m for food produ~ed usmg less or no pesticides. Our results are .reasonably similar for the two survey.s con~uc~ed and the variation in econometric methods employed. Furthermore, the results are in keeping with the lImited results- avaHable in the literature todate.Imperial Users onl

Economics of controlling a spreading environmental weed

Weeds can cause significant problems to natural ecosystems. Although there have been numerous studies on the economics of weed control, relatively few of these studies have focused on natural ecosystems. This paper addresses this gap in the literature by assessing the cost-effectiveness of a comprehensive range of control strategies for blackberry (Rubus anglocandicans) in natural environments in Australia. We developed a stochastic dynamic simulation model and a deterministic dynamic optimisation model. The stochastic model calculates the expected net present value (NPV) of a range of control strategies, including any combination of treatment options. The optimisation model identifies the treatment combination that maximises NPV. Both models represent the costs and efficacies of control options over 25 years. The results indicate that using rust (Phragmidium violaceum) as a biological control agent only marginally increases NPV and excluding rust does not affect the optimal choice of other control options. The results also show for a wide range of parameter values that a strategy which combines the herbicide grazon (Triclopyre and picloram) and mowing is optimal. If chemical efficacy decreases by 20 percent it becomes optimal to include grazing blackberry by goats in the control strategy.environment, economics, weed, stochastic, optimisation, management, Environmental Economics and Policy,

Economics of controlling a spreading environmental weed

Weeds can cause significant problems to natural ecosystems. Although there have been numerous studies on the economics of weed control, relatively few of these studies have focused on natural ecosystems. This paper addresses this gap in the literature by assessing the cost-effectiveness of a comprehensive range of control strategies for blackberry (Rubus anglocandicans) in natural environments in Australia. We developed a stochastic dynamic simulation model and a deterministic dynamic optimisation model. The stochastic model calculates the expected net present value (NPV) of a range of control strategies, including any combination of treatment options. The optimisation model identifies the treatment combination that maximises NPV. Both models represent the costs and efficacies of control options over 25 years. The results indicate that using rust (Phragmidium violaceum) as a biological control agent only marginally increases NPV and excluding rust does not affect the optimal choice of other control options. The results also show for a wide range of parameter values that a strategy which combines the herbicide grazon (Triclopyre and picloram) and mowing is optimal. If chemical efficacy decreases by 20 percent it becomes optimal to include grazing blackberry by goats in the control strategy.Environment, Economics, Weed, Stochastic, Optimisation, Management, Environmental Economics and Policy,

Estimating average marginal effects in nonseparable structural systems

We provide nonparametric estimators of derivative ratio-based average marginal effects of an endogenous cause, X, on a response of interest, Y , for a system of recursive structural equations. The system need not exhibit linearity, separability, or monotonicity. Our estimators are local indirect least squares estimators analogous to those of Heckman and Vytlacil (1999, 2001) who treat a latent index model involving a binary X. We treat the traditional case of an observed exogenous instrument (OXI)and the case where one observes error-laden proxies for an unobserved exogenous instrument (PXI). For PXI, we develop and apply new results for estimating densities and expectations conditional on mismeasured variables. For both OXI and PXI, we use infnite order flat-top kernels to obtain uniformly convergent and asymptotically normal nonparametric estimators of instrument-conditioned effects, as well as root-n consistent and asymptotically normal estimators of average effects.

Economics of controlling invasive species: a stochastic optimisation model for a spatial-dynamic process

Invasive species are significant threats to biodiversity, natural ecosystems and agriculture leading to large worldwide economic and environmental damage. Spread and control of invasive species are stochastic processes with important spatial dimensions. Most economic studies of invasive species control ignore spatial and stochastic aspects. This paper covers this gap in the previous studies by analysing a spatially explicit dynamic process of controlling invasive species in a stochastic setting. We show how stochasticity, spatial location of infestation and control can influence the spread, control efficiency and optimal control strategies. The main aim of this paper is to analyse the relationship between economic parameters and stochastic spatial characteristics of infestation and control. In the model used, there are two ways to control infestation: border control, under which the spread of invasive species from any of its infested neighbouring cell is prevented, and cell control, which removes the infestation from the existing cell. An integer optimisation model is applied to find the optimal strategies to deal with invasive species. Results show that it is optimal to eradicate or contain for a larger range of border control and cell control costs when the invasion is in the corner or on the edge as compared to the case where the initial infestation is in the middle of the landscape. Decrease in the probability of successful border control makes containment an unfavourable control option even for low border control costs. We show that decrease in the rate of spread can result in switching optimal strategies from containment to abandonment of control, or from eradication to containment. We also showed when the probability of successful cell control decreases, a lower eradication cost is required for eradication to remain the optimal strategy. In summary, this paper shows that in order to avoid providing misleading recommendations to environmental managers, it is important to include uncertainty in the spatial dynamic analysis of invasive species control.Spatial, Dynamics, Invasive, Economics, Stochastic, Optimisation, Environmental Economics and Policy,

Economics of Controlling Invasive Species: A Stochastic Optimisation Model for a Spatial-Dynamic Process

Invasive species are significant threats to biodiversity, natural ecosystems and agriculture leading to large worldwide economic and environmental damage. Spread and control of invasive species are stochastic processes with important spatial dimensions. Most economic studies of invasive species control ignore spatial and stochastic aspects. This paper covers this gap in the previous studies by analysing a spatially explicit dynamic process of controlling invasive species in a stochastic setting. We show how stochasticity, spatial location of infestation and control can influence the spread, control efficiency and optimal control strategies. The main aim of this paper is to analyse the relationship between economic parameters and stochastic spatial characteristics of infestation and control. In the model used, there are two ways to control infestation: border control, under which the spread of invasive species from any of its infested neighbouring cell is prevented, and cell control, which removes the infestation from the existing cell. An integer optimisation model is applied to find the optimal strategies to deal with invasive species. Results show that it is optimal to eradicate or contain for a larger range of border control and cell control costs when the invasion is in the corner or on the edge as compared to the case where the initial infestation is in the middle of the landscape. Decrease in the probability of successful border control makes containment an unfavourable control option even for low border control costs. We show that decrease in the rate of spread can result in switching optimal strategies from containment to abandonment of control, or from eradication to containment. We also showed when the probability of successful cell control decreases, a lower eradication cost is required for eradication to remain the optimal strategy. In summary, this paper shows that in order to avoid providing misleading recommendations to environmental managers, it is important to include uncertainty in the spatial dynamic analysis of invasive species control.Environmental Economics and Policy, Land Economics/Use,

Economics of controlling invasive species: the case of Californian thistle in New Zealand

Keywords Invasive species, Economics, Californian thistle, New Zealand, Stochastic, Dynamic programming, Biological control, Extinction risk, Herbivory, Dispersal, Competition Invasive species are one of the most significant threats to biodiversity and agricultural production systems leading to huge worldwide economic damages. This thesis has two main aims. The first aim is to analyse the control of an invasive plant in an agricultural system, using the case study of the Californian thistle in New Zealand. The second aim is to study the negative externalities that controlling invasion in agriculture can pose to ecosystems. To achieve the first aim, both deterministic and stochastic dynamic programming models are set up to find cost effective methods to tackle the problem of Californian thistle. I make a contribution to the literature by performing a dynamic and stochastic programming analysis in which two different categories of control strategies are considered, each with different dynamics. Models are set up with a discrete decision variable consisting of 62 feasible combinations of integrated control strategies. For the second aim I introduce a novel modelling approach in which two compartments are distinguished: a managed compartment where locally a herbivore is introduced to control a weed, and a natural compartment where the same herbivore species can attack a wild plant species. The main processes are herbivory, competition, dispersal and control. I conclude that bioeconomic modelling is an important tool in analysing optimal management strategies for the control of invasive species and that annual and once and for all choices need to be integrated in the analysis. A stochastic approach is appropriate but does not necessarily lead to different results, depending on the parameter values and the setup of the model. Finally, the method illustrates that an integrated analysis of the economic system and the ecological system is required to assess the risk of extinction of natural plant species. This risk depends on species interactions which in this thesis are competition, dispersal and herbivory. I conclude that a control measure can protect the desirable wild plant species and increase benefits obtained from the ecosystem. For the policy implications, I conclude that there are several strategies to control invasive species, which can be integrated combinations of control options. The optimal strategy depends on the costs and benefits of the control options. In the case study for the Californian thistle I found that the optimal strategy is a combination of methods. For the interaction between agricultural and natural system I conclude that introducing a biological agent to the agricultural system can cause extinction of a desirable plant in the natural system. The main processes are competition, herbivory and dispersal. These processes are important and need to be analysed in detail before introducing the biological agent. I conclude that the optimal strategy to control the introduced biological agent also depends on interaction of species through competition, dispersal and herbivory. <br/

Biological control of invasive plant species: stochastic economic analysis

We analysed to what extent the stochastic effects of two biological control agents (i.e. weevils and mycoherbicides) affect the optimal choice of Californian thistle control. A stochastic, dynamic optimisation model was set up to analyse strategies that maximise the expected net present values. We analysed the cost-effective strategies to control the thistle for deterministic and stochastic cases. Results show that the stochasticity of the efficacy of weevils does not affect the optimal strategy. Compared to the deterministic case, however, mycoherbicides will be introduced at a higher level of weed density if we take the stochastic effect of mycoherbicides into account.Stochastic, Optimisation, Biological control, Californian thistle, Economics.,

The Relationship between Reticence and Personality Types in Iranian University EFL Classrooms

Reticence is regarded as a problematic phenomenon among students in EFL classrooms. The present study was an attempt to explore the issue of reticence in Iranian foreign language classrooms. The study examined the relationship between students’ reticence and their personality types among university EFL learners. For this purpose, the Reticence Scale-12 (RS-12) questionnaire and the 60-item NEO Five-Factor Inventory (NEO-FFI) questionnaire were used. Moreover, interviews with the participants about reticence were employed to find the students’ ideas about reticence in the classroom. The results revealed that the five personality types affected Iranian EFL students’ reticence. In addition, educational, situational, and emotional factors contributed to the students’ reticence in EFL classrooms. It can be concluded that teachers’ awareness of learners’ reticence can help them match their teaching styles with their students’ personality types, and choose more appropriate activities that can enhance EFL learners’ participation. The study can have implications and applications for both teachers and students

Associations between Iranian University-Level EFL Learners’ Perceptions of Their Language Learning Environment and Their Motivation and Self-regulation

The present study attempted to examine Iranian university level EFL students’ perceptions of their language learning environment regarding two fundamental components of language learning engagement and achievement; that is, motivation and self-regulation. The study involved the administration of modified versions of the Engagement in English Language Learning and Self-Regulation (EELLS) questionnaire to assess participants’ motivation and self-regulation in English language learning, and the School, Physical and Campus Environment Survey (SPACES) questionnaire to assess students’ perceptions of their physical language learning environment. Statistical measures of variance, Eigenvalue, alpha Cronbach value, and component correlation matrix ensured the reliability and validity of the two questionnaires. Furthermore, the results of simple and multiple correlation analyses as well as standardized regression analysis revealed a strong and significant association between students’ perceptions of their language learning environment and their motivation and self-regulation. The findings suggest that EFL stakeholders should carefully examine language learning environments that they are creating in terms of architectural, spatial, visual, ambient, and aesthetics features