Society by Numbers : Studies on Model-Based Explanations in the Social Sciences

The aim of this dissertation is to provide conceptual tools for the social scientist for clarifying, evaluating and comparing explanations of social phenomena based on formal mathematical models. The focus is on relatively simple theoretical models and simulations, not statistical models. These studies apply a theory of explanation according to which explanation is about tracing objective relations of dependence, knowledge of which enables answers to contrastive why and how-questions. This theory is developed further by delineating criteria for evaluating competing explanations and by applying the theory to social scientific modelling practices and to the key concepts of equilibrium and mechanism. The dissertation is comprised of an introductory essay and six published original research articles. The main theses about model-based explanations in the social sciences argued for in the articles are the following. 1) The concept of explanatory power, often used to argue for the superiority of one explanation over another, compasses five dimensions which are partially independent and involve some systematic trade-offs. 2) All equilibrium explanations do not causally explain the obtaining of the end equilibrium state with the multiple possible initial states. Instead, they often constitutively explain the macro property of the system with the micro properties of the parts (together with their organization). 3) There is an important ambivalence in the concept mechanism used in many model-based explanations and this difference corresponds to a difference between two alternative research heuristics. 4) Whether unrealistic assumptions in a model (such as a rational choice model) are detrimental to an explanation provided by the model depends on whether the representation of the explanatory dependency in the model is itself dependent on the particular unrealistic assumptions. Thus evaluating whether a literally false assumption in a model is problematic requires specifying exactly what is supposed to be explained and by what. 5) The question of whether an explanatory relationship depends on particular false assumptions can be explored with the process of derivational robustness analysis and the importance of robustness analysis accounts for some of the puzzling features of the tradition of model-building in economics. 6) The fact that economists have been relatively reluctant to use true agent-based simulations to formulate explanations can partially be explained by the specific ideal of scientific understanding implicit in the practise of orthodox economics.

Topological Quantum Computation - An Analysis of an Anyon Model Based on Quantum Double Symmetries

There exists various suggestions for building a functional and a fault-tolerant large-scale quantum computer. Topological quantum computation is a more exotic suggestion, which makes use of the properties of quasiparticles manifest only in certain two-dimensional systems. These so called anyons exhibit topological degrees of freedom, which, in principle, can be used to execute quantum computation with intrinsic fault-tolerance. This feature is the main incentive to study topological quantum computation. The objective of this thesis is to provide an accessible introduction to the theory. In this thesis one has considered the theory of anyons arising in two-dimensional quantum mechanical systems, which are described by gauge theories based on so called quantum double symmetries. The quasiparticles are shown to exhibit interactions and carry quantum numbers, which are both of topological nature. Particularly, it is found that the addition of the quantum numbers is not unique, but that the fusion of the quasiparticles is described by a non-trivial fusion algebra. It is discussed how this property can be used to encode quantum information in a manner which is intrinsically protected from decoherence and how one could, in principle, perform quantum computation by braiding the quasiparticles. As an example of the presented general discussion, the particle spectrum and the fusion algebra of an anyon model based on the gauge group S_3 are explicitly derived. The fusion algebra is found to branch into multiple proper subalgebras and the simplest one of them is chosen as a model for an illustrative demonstration. The different steps of a topological quantum computation are outlined and the computational power of the model is assessed. It turns out that the chosen model is not universal for quantum computation. However, because the objective was a demonstration of the theory with explicit calculations, none of the other more complicated fusion subalgebras were considered. Studying their applicability for quantum computation could be a topic of further research.

Aspiration-based utility functions in a planning model for timber flow management.

The study presents a theory of utility models based on aspiration levels, as well as the application of this theory to the planning of timber flow economics. The first part of the study comprises a derivation of the utility-theoretic basis for the application of aspiration levels. Two basic models are dealt with: the additive and the multiplicative. Applied here solely for partial utility functions, aspiration and reservation levels are interpreted as defining piecewisely linear functions. The standpoint of the choices of the decision-maker is emphasized by the use of indifference curves. The second part of the study introduces a model for the management of timber flows. The model is based on the assumption that the decision-maker is willing to specify a shape of income flow which is different from that of the capital-theoretic optimum. The utility model comprises four aspiration-based compound utility functions. The theory and the flow model are tested numerically by computations covering three forest holdings. The results show that the additive model is sensitive even to slight changes in relative importances and aspiration levels. This applies particularly to nearly linear production possibility boundaries of monetary variables. The multiplicative model, on the other hand, is stable because it generates strictly convex indifference curves. Due to a higher marginal rate of substitution, the multiplicative model implies a stronger dependence on forest management than the additive function. For income trajectory optimization, a method utilizing an income trajectory index is more efficient than one based on the use of aspiration levels per management period. Smooth trajectories can be attained by squaring the deviations of the feasible trajectories from the desired one.

Detecting Earnings Management Using Neural Networks

Detecting Earnings Management Using Neural Networks. Trying to balance between relevant and reliable accounting data, generally accepted accounting principles (GAAP) allow, to some extent, the company management to use their judgment and to make subjective assessments when preparing financial statements. The opportunistic use of the discretion in financial reporting is called earnings management. There have been a considerable number of suggestions of methods for detecting accrual based earnings management. A majority of these methods are based on linear regression. The problem with using linear regression is that a linear relationship between the dependent variable and the independent variables must be assumed. However, previous research has shown that the relationship between accruals and some of the explanatory variables, such as company performance, is non-linear. An alternative to linear regression, which can handle non-linear relationships, is neural networks. The type of neural network used in this study is the feed-forward back-propagation neural network. Three neural network-based models are compared with four commonly used linear regression-based earnings management detection models. All seven models are based on the earnings management detection model presented by Jones (1991). The performance of the models is assessed in three steps. First, a random data set of companies is used. Second, the discretionary accruals from the random data set are ranked according to six different variables. The discretionary accruals in the highest and lowest quartiles for these six variables are then compared. Third, a data set containing simulated earnings management is used. Both expense and revenue manipulation ranging between -5% and 5% of lagged total assets is simulated. Furthermore, two neural network-based models and two linear regression-based models are used with a data set containing financial statement data from 110 failed companies. Overall, the results show that the linear regression-based models, except for the model using a piecewise linear approach, produce biased estimates of discretionary accruals. The neural network-based model with the original Jones model variables and the neural network-based model augmented with ROA as an independent variable, however, perform well in all three steps. Especially in the second step, where the highest and lowest quartiles of ranked discretionary accruals are examined, the neural network-based model augmented with ROA as an independent variable outperforms the other models.

Stand growth and management scenarios for Paraserianthes falcataria smallholder plantations in Indonesia

Paraserianthes falcataria is a very fast growing, light wood tree species, that has recently gained wide interest in Indonesia for industrial wood processing. At the moment the P. falcataria plantations managed by smallholders are lacking predefined management programmes for commercial wood production. The general objective of this study was to model the growth and yield of Paraserianthes falcataria stands managed by smallholders in Ciamis, West Java, Indonesia and to develop management scenarios for different production objectives. In total 106 circular sample plots with over 2300 P. falcataria trees were assessed on smallholder plantation inventory. In addition, information on market prices of P. falcataria wood was collected through rapid appraisals among industries. A tree growth model based on Chapman-Richards function was developed on three different site qualities and the stand management scenarios were developed under three management objectives: (1) low initial stand density with low intensity stand management, (2) high initial stand density with medium intensity of intervention, (3) high initial stand density and strong intensity of silvicultural interventions, repeated more than once. In general, the 9 recommended scenarios have rotation ages varying from 4 to 12 years, planting densities from 4x4 meters (625 trees ha-1) to 3x2 meters (1666 trees ha-1) and thinnings at intensities of removing 30 to 60 % of the standing trees. The highest annual income would be generated on high-quality with a scenario with initial planting density 3x2 m (1666 trees ha-1) one thinning at intensity of removing 55 % of the standing trees at the age of 2 years and clear cut at the age of 4 years.

Bayesian analysis of community dynamics

Elucidating the mechanisms responsible for the patterns of species abundance, diversity, and distribution within and across ecological systems is a fundamental research focus in ecology. Species abundance patterns are shaped in a convoluted way by interplays between inter-/intra-specific interactions, environmental forcing, demographic stochasticity, and dispersal. Comprehensive models and suitable inferential and computational tools for teasing out these different factors are quite limited, even though such tools are critically needed to guide the implementation of management and conservation strategies, the efficacy of which rests on a realistic evaluation of the underlying mechanisms. This is even more so in the prevailing context of concerns over climate change progress and its potential impacts on ecosystems. This thesis utilized the flexible hierarchical Bayesian modelling framework in combination with the computer intensive methods known as Markov chain Monte Carlo, to develop methodologies for identifying and evaluating the factors that control the structure and dynamics of ecological communities. These methodologies were used to analyze data from a range of taxa: macro-moths (Lepidoptera), fish, crustaceans, birds, and rodents. Environmental stochasticity emerged as the most important driver of community dynamics, followed by density dependent regulation; the influence of inter-specific interactions on community-level variances was broadly minor. This thesis contributes to the understanding of the mechanisms underlying the structure and dynamics of ecological communities, by showing directly that environmental fluctuations rather than inter-specific competition dominate the dynamics of several systems. This finding emphasizes the need to better understand how species are affected by the environment and acknowledge species differences in their responses to environmental heterogeneity, if we are to effectively model and predict their dynamics (e.g. for management and conservation purposes). The thesis also proposes a model-based approach to integrating the niche and neutral perspectives on community structure and dynamics, making it possible for the relative importance of each category of factors to be evaluated in light of field data.

Traditionally Protected Forests´ Role within Transforming Natural Resource Management Regimes in Taita Hills, Kenya

In Taita Hills, south-eastern Kenya, remnants of indigenous mountain rainforests play a crucial role as water towers and socio-cultural sites. They are pressurized due to poverty, shortage of cultivable land and the fading of traditional knowledge. This study examines the traditional ecological knowledge of Taitas and the ways it may be applied within transforming natural resource management regimes. I have analyzed some justifications for and hindrances to ethnodevelopment and participatory forest management in light of recently renewed Kenyan forest policies. Mixed methods were applied by combining an ethnographic approach with participatory GIS. I learned about traditionally protected forests and their ecological and cultural status through a seek out the expert method and with remote sensing data and tools. My informants were: 107 household interviewees, 257 focus group participants, 73 key informants and 87 common informants in participatory mapping. Religious leaders and state officials shared their knowledge for this study. I have gained a better understanding of the traditionally protected forests and sites through examining their ecological characteristics and relation to social dynamics, by evaluating their strengths and hindrances as sites for conservation of cultural and biological diversity. My results show that, these sites are important components of a complex socio-ecological system, which has symbolical status and sacred and mystical elements within it, that contributes to the connectivity of remnant forests in the agroforestry dominated landscape. Altogether, 255 plant species and 220 uses were recognized by the tradition experts, whereas 161 species with 108 beneficial uses were listed by farmers. Out of the traditionally protected forests studied 47 % were on private land and 23% on community land, leaving 9% within state forest reserves. A paradigm shift in conservation is needed; the conservation area approach is not functional for private lands or areas trusted upon communities. The role of traditionally protected forests in community-based forest management is, however, paradoxal, since communal approaches suggests equal participation of people, whereas management of these sites has traditionally been the duty of solely accredited experts in the village. As modernization has gathered pace such experts have become fewer. Sacredness clearly contributes but, it does not equal conservation. Various social, political and economic arrangements further affect the integrity of traditionally protected forests and sites, control of witchcraft being one of them. My results suggest that the Taita have a rich traditional ecological knowledge base, which should be more determinately integrated into the natural resource management planning processes.