Noise reduction in coarse bifurcation analysis of stochastic agent-based models: an example of consumer lock-in

We investigate coarse equilibrium states of a fine-scale, stochastic agent-based model of consumer lock-in in a duopolistic market. In the model, agents decide on their next purchase based on a combination of their personal preference and their neighbours' opinions. For agents with independent identically-distributed parameters and all-to-all coupling, we derive an analytic approximate coarse evolution-map for the expected average purchase. We then study the emergence of coarse fronts when spatial segregation is present in the relative perceived quality of products. We develop a novel Newton-Krylov method that is able to compute accurately and efficiently coarse fixed points when the underlying fine-scale dynamics is stochastic. The main novelty of the algorithm is in the elimination of the noise that is generated when estimating Jacobian-vector products using time-integration of perturbed initial conditions. We present numerical results that demonstrate the convergence properties of the numerical method, and use the method to show that macroscopic fronts in this model destabilise at a coarse symmetry-breaking bifurcation.Comment: This version of the manuscript was accepted for publication on SIAD

Noise reduction in coarse bifurcation analysis of stochastic agent-based models: an example of consumer lock-in

We investigate the occurrence of coarse macroscopic states in an agent-based model of consumer lock-in. The system studied here is a modification of an existing model by Garlic and Chli [24] and it serves as a prototypical Ising-type sociological system with binary state variables and spatially-dependent agent parameters. In the regime of globally-coupled agents with independent identically-distributed parameters, we derive an analytic approximate coarse evolution-map for the expectation of the average purchase. Following Barkley et al. [5], we interpret metastable locked-in states as fixed points of this one-dimensional first moment map. We then study the emergence of coarse fronts in the regime of heterogeneous agents with strongly discordant preferences. When agent polarization becomes less pronounced, the front destabilizes and one of the two products prevails, giving rise to inhomogeneous profiles featuring pockets of resistance. Stochastic continuation of the spatially-extended case poses a numerical challenge, as Jacobian-vector products are severely affected by noise. We exploit the non-uniqueness of the lifting step introducing weighted lifting/restriction operators, which result in variance-reduced Jacobian-vector products. We test our numerical strategy and show that weighted operators induce good convergence properties of the Newton-GMRES solver. We then show that macroscopic fronts destabilise at a coarse symmetry-breaking bifurcation

Noise reduction in coarse bifurcation analysis of stochastic agent-based models: an example of consumer lock-in

We investigate coarse equilibrium states of a fine-scale, stochastic agent-based model of consumer lock-in in a duopolistic market. In the model, agents decide on their next purchase based on a combination of their personal preference and their neighbours' opinions. For agents with independent identically-distributed parameters and all-to-all coupling, we derive an analytic approximate coarse evolution-map for the expected average purchase. We then study the emergence of coarse fronts when segregation is present in the relative perceived quality of products. We develop a novel Newton-Krylov method that is able to compute accurately and efficiently coarse fixed points when the underlying fine-scale dynamics is stochastic. The main novelty of the algorithm is in the elimination of the noise that is generated when estimating Jacobian-vector products using time-integration of perturbed initial conditions. We present numerical results that demonstrate the convergence properties of the numerical method, and use the method to show that macroscopic fronts in this model destabilise at a coarse symmetry-breaking bifurcation

Noise reduction in coarse bifurcation analysis of stochastic agent-based models: an example of consumer lock-in

We investigate coarse equilibrium states of a fine-scale, stochastic agent-based model of consumer lock-in in a duopolistic market. In the model, agents decide on their next purchase based on a combination of their personal preference and their neighbours' opinions. For agents with independent identically-distributed parameters and all-to-all coupling, we derive an analytic approximate coarse evolution-map for the expected average purchase. We then study the emergence of coarse fronts when spatial segregation is present in the relative perceived quality of products. We develop a novel Newton-Krylov method that is able to compute accurately and efficiently coarse fixed points when the underlying fine-scale dynamics is stochastic. The main novelty of the algorithm is in the elimination of the noise that is generated when estimating Jacobian-vector products using time-integration of perturbed initial conditions. We present numerical results that demonstrate the convergence properties of the numerical method, and use the method to show that macroscopic fronts in this model destabilise at a coarse symmetry-breaking bifurcation

Essays in applied microeconomics

The four papers in this thesis contribute to four distinct strands of the applied economics literature. Chapter 1 considers whether the level of political competition in a postcode affects the incomes of the people who live there. Unlike previous research, I am able to exploit exogenous variation in electoral boundaries, and as such, exogenous variation in the level of political competition. I do not find a systematic relationship between a change in the political importance of an area - as measured by marginality - and the incomes of the people who live there. Chapter 2 explores whether rents from natural resources affect the sub-components of Political Rights or Civil Liberties, as measured by Freedom House. We find that higher resource rents cause a deterioration in Freedom House's measure of Political Pluralism and Participation, but other sub-components are unaffected. We demonstrate why our results extend upon and differ from those in the existing literature. Chapter 3 uses a random gambling prime to assess the malleability of stated risk and time preferences. The gambling prime causes respondents to self-assess as being more risk-averse, and less patient. These results are remarkably homogeneous across a range of demographic groups. There is also some evidence that, for the small number of respondents whose gambling behaviour may have been problematic in the past, the effect of the prime on risk preferences diminishes as their past gambling behaviour becomes riskier. This could indicate that primes of this nature have limited policy application. Chapter 4 describes, for the first time, the Multi-Agency Data Integration Project dataset. This dataset links medicare service use data to personal income tax and social security data, as well as data from the 2011 census. Of particular interest is the finding that a substantial number of people have stated on the census an income above the tax-free threshold, but do not appear in the personal income tax data. A related finding is that, contrary to our speculation, those with the lowest incomes according to the personal income tax data are the most likely to decline to state an income in the 2011 census

Hidden Citations Obscure True Impact in Science

References, the mechanism scientists rely on to signal previous knowledge, lately have turned into widely used and misused measures of scientific impact. Yet, when a discovery becomes common knowledge, citations suffer from obliteration by incorporation. This leads to the concept of hidden citation, representing a clear textual credit to a discovery without a reference to the publication embodying it. Here, we rely on unsupervised interpretable machine learning applied to the full text of each paper to systematically identify hidden citations. We find that for influential discoveries hidden citations outnumber citation counts, emerging regardless of publishing venue and discipline. We show that the prevalence of hidden citations is not driven by citation counts, but rather by the degree of the discourse on the topic within the text of the manuscripts, indicating that the more discussed is a discovery, the less visible it is to standard bibliometric analysis. Hidden citations indicate that bibliometric measures offer a limited perspective on quantifying the true impact of a discovery, raising the need to extract knowledge from the full text of the scientific corpus

Forecasting: theory and practice

Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The large number of forecasting applications calls for a diverse set of forecasting methods to tackle real-life challenges. This article provides a non-systematic review of the theory and the practice of forecasting. We provide an overview of a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts. We do not claim that this review is an exhaustive list of methods and applications. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of forecasting theory and practice. Given its encyclopedic nature, the intended mode of reading is non-linear. We offer cross-references to allow the readers to navigate through the various topics. We complement the theoretical concepts and applications covered by large lists of free or open-source software implementations and publicly-available databases