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.

Modelling the nitrogen-driven trade-off between nitrogen utilisation efficiency and water use efficiency of wheat in eastern Australia.

The nitrogen-driven trade-off between nitrogen utilisation efficiency (yield per unit nitrogen uptake) and water use efficiency (yield per unit evapotranspiration) is widespread and results from well established, multiple effects of nitrogen availability on the water, carbon and nitrogen economy of crops. Here we used a crop model (APSIM) to simulate the yield, evapotranspiration, soil evaporation and nitrogen uptake of wheat, and analysed yield responses to water, nitrogen and climate using a framework analogous to the rate-duration model of determinate growth. The relationship between modelled grain yield (Y) and evapotranspiration (ET) was fitted to a linear-plateau function to derive three parameters: maximum yield (Ymax), the ET break-point when yield reaches its maximum (ET#), and the rate of yield response in the linear phase ([Delta]Y/[Delta]ET). Against this framework, we tested the hypothesis that nitrogen deficit reduces maximum yield by reducing both the rate ([Delta]Y/[Delta]ET) and the range of yield response to evapotranspiration, i.e. ET# - Es, where Es is modelled median soil evaporation. Modelled data reproduced the nitrogen-driven trade-off between nitrogen utilisation efficiency and water use efficiency in a transect from Horsham (36°S) to Emerald (23°S) in eastern Australia. Increasing nitrogen supply from 50 to 250 kg N ha-1 reduced yield per unit nitrogen uptake from 29 to 12 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 15 kg grain ha-1 mm-1 at Emerald. The same increment in nitrogen supply reduced yield per unit nitrogen uptake from 30 to 25 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 25 kg grain ha-1 mm-1 at Horsham. Maximum yield ranged from 0.9 to 6.4 t ha-1. Consistent with our working hypothesis, reductions in maximum yield with nitrogen deficit were associated with both reduction in the rate of yield response to ET and compression of the range of yield response to ET. Against the notion of managing crops to maximise water use efficiency in low rainfall environments, we emphasise the trade-off between water use efficiency and nitrogen utilisation efficiency, particularly under conditions of high nitrogen-to-grain price ratio. The rate-range framework to characterise the relationship between yield and evapotranspiration is useful to capture this trade-off as the parameters were responsive to both nitrogen supply and climatic factors.

Analysis-By-Synthesis Based Switched Transform Domain Split Vq Using Gaussian Mixture Model

Using analysis-by-synthesis (AbS) approach, we develop a soft decision based switched vector quantization (VQ) method for high quality and low complexity coding of wideband speech line spectral frequency (LSF) parameters. For each switching region, a low complexity transform domain split VQ (TrSVQ) is designed. The overall rate-distortion (R/D) performance optimality of new switched quantizer is addressed in the Gaussian mixture model (GMM) based parametric framework. In the AbS approach, the reduction of quantization complexity is achieved through the use of nearest neighbor (NN) TrSVQs and splitting the transform domain vector into higher number of subvectors. Compared to the current LSF quantization methods, the new method is shown to provide competitive or better trade-off between R/D performance and complexity.

The UNCITRAL Model Law on Cross-border Insolvency and its Potential Role in Upholding the Rule of Law

The rule of law is understood to be a core aspect in achieving a stable economy and an ordered society. Without the elements that are inherent in this principle the possibilities of anarchy, unfairness and uncertainty are amplified, which in turn can result in an economy with dramatic fluctuations. In this regard, commentators do not always agree that the rule of law is strictly adhered to in the international legal context. Therefore, this paper will explore one aspect of international regulation and consider whether the UNCITRAL Model Law on Cross-border Insolvency (1997) (‘Model Law’) and its associated Guide to Enactment and Interpretation (2013) contribute to the promotion of the key elements of the rule of law.

The transfer problem and the intertemporal terms of trade

In this paper the effects of a transfer on the intertemporal terms of trade are examined in the context of a simple two-country, two-period model. When intertemporal trade occurs because the two economies have different rates of time preference, a transfer improves the terms of trade of the paying country. Alternatively, when trade occurs owing to international differences in the endowments of goods over the two periods, the effect of a transfer depends on (a) the relationship between the interest rate and the rates of time preference of the two countries and (b) the relationship between their elasticities of intertemporal consumption substitution.

Analyzing changes in macro-level drivers of country-specific emissions : The role of consumption, technology and trade

Industrial ecology is an important field of sustainability science. It can be applied to study environmental problems in a policy relevant manner. Industrial ecology uses ecosystem analogy; it aims at closing the loop of materials and substances and at the same time reducing resource consumption and environmental emissions. Emissions from human activities are related to human interference in material cycles. Carbon (C), nitrogen (N) and phosphorus (P) are essential elements for all living organisms, but in excess have negative environmental impacts, such as climate change (CO2, CH4 N2O), acidification (NOx) and eutrophication (N, P). Several indirect macro-level drivers affect emissions change. Population and affluence (GDP/capita) often act as upward drivers for emissions. Technology, as emissions per service used, and consumption, as economic intensity of use, may act as drivers resulting in a reduction in emissions. In addition, the development of country-specific emissions is affected by international trade. The aim of this study was to analyse changes in emissions as affected by macro-level drivers in different European case studies. ImPACT decomposition analysis (IPAT identity) was applied as a method in papers I III. The macro-level perspective was applied to evaluate CO2 emission reduction targets (paper II) and the sharing of greenhouse gas emission reduction targets (paper IV) in the European Union (EU27) up to the year 2020. Data for the study were mainly gathered from official statistics. In all cases, the results were discussed from an environmental policy perspective. The development of nitrogen oxide (NOx) emissions was analysed in the Finnish energy sector during a long time period, 1950 2003 (paper I). Finnish emissions of NOx began to decrease in the 1980s as the progress in technology in terms of NOx/energy curbed the impact of the growth in affluence and population. Carbon dioxide (CO2) emissions related to energy use during 1993 2004 (paper II) were analysed by country and region within the European Union. Considering energy-based CO2 emissions in the European Union, dematerialization and decarbonisation did occur, but not sufficiently to offset population growth and the rapidly increasing affluence during 1993 2004. The development of nitrogen and phosphorus load from aquaculture in relation to salmonid consumption in Finland during 1980 2007 was examined, including international trade in the analysis (paper III). A regional environmental issue, eutrophication of the Baltic Sea, and a marginal, yet locally important source of nutrients was used as a case. Nutrient emissions from Finnish aquaculture decreased from the 1990s onwards: although population, affluence and salmonid consumption steadily increased, aquaculture technology improved and the relative share of imported salmonids increased. According to the sustainability challenge in industrial ecology, the environmental impact of the growing population size and affluence should be compensated by improvements in technology (emissions/service used) and with dematerialisation. In the studied cases, the emission intensity of energy production could be lowered for NOx by cleaning the exhaust gases. Reorganization of the structure of energy production as well as technological innovations will be essential in lowering the emissions of both CO2 and NOx. Regarding the intensity of energy use, making the combustion of fuels more efficient and reducing energy use are essential. In reducing nutrient emissions from Finnish aquaculture to the Baltic Sea (paper III) through technology, limits of biological and physical properties of cultured fish, among others, will eventually be faced. Regarding consumption, salmonids are preferred to many other protein sources. Regarding trade, increasing the proportion of imports will outsource the impacts. Besides improving technology and dematerialization, other viewpoints may also be needed. Reducing the total amount of nutrients cycling in energy systems and eventually contributing to NOx emissions needs to be emphasized. Considering aquaculture emissions, nutrient cycles can be partly closed through using local fish as feed replacing imported feed. In particular, the reduction of CO2 emissions in the future is a very challenging task when considering the necessary rates of dematerialisation and decarbonisation (paper II). Climate change mitigation may have to focus on other greenhouse gases than CO2 and on the potential role of biomass as a carbon sink, among others. The global population is growing and scaling up the environmental impact. Population issues and growing affluence must be considered when discussing emission reductions. Climate policy has only very recently had an influence on emissions, and strong actions are now called for climate change mitigation. Environmental policies in general must cover all the regions related to production and impacts in order to avoid outsourcing of emissions and leakage effects. The macro-level drivers affecting changes in emissions can be identified with the ImPACT framework. Statistics for generally known macro-indicators are currently relatively well available for different countries, and the method is transparent. In the papers included in this study, a similar method was successfully applied in different types of case studies. Using transparent macro-level figures and a simple top-down approach are also appropriate in evaluating and setting international emission reduction targets, as demonstrated in papers II and IV. The projected rates of population and affluence growth are especially worth consideration in setting targets. However, sensitivities in calculations must be carefully acknowledged. In the basic form of the ImPACT model, the economic intensity of consumption and emission intensity of use are included. In seeking to examine consumption but also international trade in more detail, imports were included in paper III. This example demonstrates well how outsourcing of production influences domestic emissions. Country-specific production-based emissions have often been used in similar decomposition analyses. Nevertheless, trade-related issues must not be ignored.

Trade Liberalization, Heterogeneous Firms and Industrial Dynamics

This master thesis studies how trade liberalization affects the firm-level productivity and industrial evolution. To do so, I built a dynamic model that considers firm-level productivity as endogenous to investigate the influence of trade on firm’s productivity and the market structure. In the framework, heterogeneous firms in the same industry operate differently in equilibrium. Specifically, firms are ex ante identical but heterogeneity arises as an equilibrium outcome. Under the setting of monopolistic competition, this type of model yields an industry that is represented not by a steady-state outcome, but by an evolution that rely on the decisions made by individual firms. I prove that trade liberalization has a general positive impact on technological adoption rates and hence increases the firm-level productivity. Besides, this endogenous technology adoption model also captures the stylized facts: exporting firms are larger and more productive than their non-exporting counterparts in the same sector. I assume that the number of firms is endogenous, since, according to the empirical literature, the industrial evolution shows considerably different patterns across countries; some industries experience large scale of firms’ exit in the period of contracting market shares, while some industries display relative stable number of firms or gradually increase quantities. The special word “shakeout” is used to describe the dramatic decrease in the number of firms. In order to explain the causes of shakeout, I construct a model where forward-looking firms decide to enter and exit the market on the basis of their state of technology. In equilibrium, firms choose different dates to adopt innovation which generate a gradual diffusion process. It is exactly this gradual diffusion process that generates the rapid, large-scale exit phenomenon. Specifically, it demonstrates that there is a positive feedback between firm’s exit and adoption, the reduction in the number of firms increases the incentives for remaining firms to adopt innovation. Therefore, in the setting of complete information, this model not only generates a shakeout but also captures the stability of an industry. However, the solely national view of industrial evolution neglects the importance of international trade in determining the shape of market structure. In particular, I show that the higher trade barriers lead to more fragile markets, encouraging the over-entry in the initial stage of industry life cycle and raising the probability of a shakeout. Therefore, more liberalized trade generates more stable market structure from both national and international viewpoints. The main references are Ederington and McCalman(2008,2009).

Simulation of ENSO-Related Surface Winds in the Tropical Pacific by an Atmospheric General Circulation Model Forced by Observed Sea Surface Temperatures

The authors present the simulation of the tropical Pacific surface wind variability by a low-resolution (R15 horizontal resolution and 18 vertical levels) version of the Center for Ocean-Land-Atmosphere Interactions, Maryland, general circulation model (GCM) when forced by observed global sea surface temperature. The authors have examined the monthly mean surface winds acid precipitation simulated by the model that was integrated from January 1979 to March 1992. Analyses of the climatological annual cycle and interannual variability over the Pacific are presented. The annual means of the simulated zonal and meridional winds agree well with observations. The only appreciable difference is in the region of strong trade winds where the simulated zonal winds are about 15%-20% weaker than observed, The amplitude of the annual harmonics are weaker than observed over the intertropical convergence zone and the South Pacific convergence zone regions. The amplitudes of the interannual variation of the simulated zonal and meridional winds are close to those of the observed variation. The first few dominant empirical orthogonal functions (EOF) of the simulated, as well as the observed, monthly mean winds are found to contain a targe amount of high-frequency intraseasonal variations, While the statistical properties of the high-frequency modes, such as their amplitude and geographical locations, agree with observations, their detailed time evolution does not. When the data are subjected to a 5-month running-mean filter, the first two dominant EOFs of the simulated winds representing the low-frequency EI Nino-Southern Oscillation fluctuations compare quite well with observations. However, the location of the center of the westerly anomalies associated with the warm episodes is simulated about 15 degrees west of the observed locations. The model simulates well the progress of the westerly anomalies toward the eastern Pacific during the evolution of a warm event. The simulated equatorial wind anomalies are comparable in magnitude to the observed anomalies. An intercomparison of the simulation of the interannual variability by a few other GCMs with comparable resolution is also presented. The success in simulation of the large-scale low-frequency part of the tropical surface winds by the atmospheric GCM seems to be related to the model's ability to simulate the large-scale low-frequency part of the precipitation. Good correspondence between the simulated precipitation and the highly reflective cloud anomalies is seen in the first two EOFs of the 5-month running means. Moreover, the strong correlation found between the simulated precipitation and the simulated winds in the first two principal components indicates the primary role of model precipitation in driving the surface winds. The surface winds simulated by a linear model forced by the GCM-simulated precipitation show good resemblance to the GCM-simulated winds in the equatorial region. This result supports the recent findings that the large-scale part of the tropical surface winds is primarily linear.

A System-C based Micro architectural Exploration Framework for Latency, Power and Performance Trade-offs of On-Chip Interconnection

We describe a System-C based framework we are developing, to explore the impact of various architectural and microarchitectural level parameters of the on-chip interconnection network elements on its power and performance. The framework enables one to choose from a variety of architectural options like topology, routing policy, etc., as well as allows experimentation with various microarchitectural options for the individual links like length, wire width, pitch, pipelining, supply voltage and frequency. The framework also supports a flexible traffic generation and communication model. We provide preliminary results of using this framework to study the power, latency and throughput of a 4x4 multi-core processing array using mesh, torus and folded torus, for two different communication patterns of dense and sparse linear algebra. The traffic consists of both Request-Response messages (mimicing cache accesses)and One-Way messages. We find that the average latency can be reduced by increasing the pipeline depth, as it enables higher link frequencies. We also find that there exists an optimum degree of pipelining which minimizes energy-delay product.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

A Predictive Perfomance Model for Superscalar Processors

Designing and optimizing high performance microprocessors is an increasingly difficult task due to the size and complexity of the processor design space, high cost of detailed simulation and several constraints that a processor design must satisfy. In this paper, we propose the use of empirical non-linear modeling techniques to assist processor architects in making design decisions and resolving complex trade-offs. We propose a procedure for building accurate non-linear models that consists of the following steps: (i) selection of a small set of representative design points spread across processor design space using latin hypercube sampling, (ii) obtaining performance measures at the selected design points using detailed simulation, (iii) building non-linear models for performance using the function approximation capabilities of radial basis function networks, and (iv) validating the models using an independently and randomly generated set of design points. We evaluate our model building procedure by constructing non-linear performance models for programs from the SPEC CPU2000 benchmark suite with a microarchitectural design space that consists of 9 key parameters. Our results show that the models, built using a relatively small number of simulations, achieve high prediction accuracy (only 2.8% error in CPI estimates on average) across a large processor design space. Our models can potentially replace detailed simulation for common tasks such as the analysis of key microarchitectural trends or searches for optimal processor design points.

Model projections for household energy use in India

Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO(2) emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65-75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9-10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO(2) emissions via increased electricity use. (C) 2011 Elsevier Ltd. All rights reserved.

Trade determination in multi-attribute exchanges

Electronic exchanges are double-sided marketplaces that allow multiple buyers to trade with multiple sellers, with aggregation of demand and supply across the bids to maximize the revenue in the market. Two important issues in the design of exchanges are (1) trade determination (determining the number of goods traded between any buyer-seller pair) and (2) pricing. In this paper we address the trade determination issue for one-shot, multi-attribute exchanges that trade multiple units of the same good. The bids are configurable with separable additive price functions over the attributes and each function is continuous and piecewise linear. We model trade determination as mixed integer programming problems for different possible bid structures and show that even in two-attribute exchanges, trade determination is NP-hard for certain bid structures. We also make some observations on the pricing issues that are closely related to the mixed integer formulations.

The role of the terms of trade in the trade channel of transmission of oil price shocks

This paper highlights the role of the terms of trade in the trade channel of propagation of oil price shocks both empirically and theoretically. Empirically, I show that oil price shocks have a large, persistent and statistically significant impact on the US terms of trade. Theoretically, I add oil in the model by Corsetti and Pesenti (2005) and analyse under what conditions the terms of trade plays a relevant role in the international transmission of oil price shocks. With nominal price rigidities and full exchange rate pass-through positive oil price shocks depreciate the currency of the oil importing country. The subsequent negative wealth effect adds to the recessive effect of the supply channel and may trongly reduce the consumption in the oil importing country economy. Without exchange rate pass-through oil shocks transmit to the economy only through the supply channel. The model suggests that a change in the exchange rate pass-through might contribute to explain the evidence of a weaker impact of oil price shocks on the macroeconomic activity in recent times.