![]() ![]() ![]() When requesting a correction, please mention this item's handle: RePEc:taf:jnlbes:v:40:y:2022:i:3:p:1390-1402. You can help correct errors and omissions. " Autoregressions in small samples, priors about observables and initial conditions,"Īll material on this site has been provided by the respective publishers and authors. Marcet, Albert & Jarociński, Marek, 2010." The Local to Unity Dynamic Tobit Model," " Distribution of the Least Squares Estimator in a First-Order Autoregressive Model,"ĩ610004, University Library of Munich, Germany. " Modeling and forecasting realized volatility with the fractional Ornstein–Uhlenbeck process," Wang, Xiaohu & Xiao, Weilin & Yu, Jun, 2023." Structural Break Detection in Quantile Predictive Regression Models with Persistent Covariates," " Asymptotic theory for near integrated processes driven by tempered linear processes," Sabzikar, Farzad & Wang, Qiying & Phillips, Peter C.B., 2020." Distribution Of The Least Squares Estimator In A First-Order Autoregressive Model,"Įconometric Reviews, Taylor & Francis Journals, vol. " Asymptotics for LS, GLS, and Feasible GLS Statistics in an AR(1) Model with Conditional Heteroskedaticity,"ġ665R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2010.ġ665R2, Cowles Foundation for Research in Economics, Yale University, revised Feb 2012.ġ665, Cowles Foundation for Research in Economics, Yale University. ![]() " Time Series Regression with a Unit Root,"Įconometrica, Econometric Society, vol. " Folklore Theorems, Implicit Maps, and Indirect Inference,"Įconometrica, Econometric Society, vol. " Asymptotic theory for linear diffusions under alternative sampling schemes,"Įconomics Letters, Elsevier, vol. " Approximations to Some Finite Sample Distributions Associated with a First-Order Stochastic Difference Equation,"Įconometrica, Econometric Society, vol. Taken together, the five papers offer diversified perspectives for both understanding and critically assessing emergent forms of datafied living." Adaptive Estimation of Autoregressive Models with Time-Varying Variances,"ġ585, Cowles Foundation for Research in Economics, Yale University.ġ585R, Cowles Foundation for Research in Economics, Yale University, revised Nov 2006. Finally, Nick Couldry, Andreas Hepp and Jun Yu (LSE, UK, and University of Bremen, Germany) reflect the different imaginations of datafied living: on the one hand, the active imagination of pioneer communities (the Maker and Quantifed Self movements) and on the other hand, the repressed imagination of the facts of data collection in public ‘big data’ discourse. Andrew Iliadis (Temple University, USA) investigates ‘data forging’ to provide a critical assessment of ‘datasmith’ ontologies, ontologists, and ontology-making practices. Examining the Chinese Sesame Credit – one of the most prominent prototypes of its sort – Alison Hearn (University of Western Ontario, Canada) discusses the potential effects of living with credit scoring. The second paper presented by Göran Bolin (Södertörn University, Sweden) reflects on how the deeper penetration of algorithmically generated metrics into our life-worlds produces a new environment in which we live. In the first paper, Joseph Turow (University of Pennsylvania, USA) analyzes how the multifaceted retailing activities are reshaping the ways companies construct shoppers, and creating a new environment of discrimination through which shoppers will be purchasing products. ![]() More specifically, we will discuss five different dimensions of datafied living: shopping, the metricated mindset, credit scoring, data forging and imaginations of datafied living in times of deep mediatization. Referring to such examples, the panel will reflect on datafied living from multiple perspectives that each take a critical point of view, so as to get a sense of this transformation’s complexity. There are already many examples for this in everyday life. Therefore, datafied living means that everyday practices are related to data in a constitutive way. In times of deep mediatization (Couldry / Hepp 2017), ‘living’ is deeply entangled with digital media and their infrastructures, which continuously produce, assess and communicate data back and forth. Investigating ‘living’ entails not focusing on a single practice of media use but rather researching the range of everyday practices overall. This becomes possible as more and more media and media business models rely on algorithmic processing of data extracted from everyday life Besides ‘tools’ of communication, digital devices and platforms also become generators of data. Datafication means the representation of social life through computerized data (Schäfer & van Es, 2017 van Dijck, 2014). Remove from Personal Schedule Datafied Living: The Everyday of Datafication Sun, May 27, 15:30 to 16:45, Hilton Old Town, Floor: M, Mozart Iĭatafied living is an emerging new ‘way of life’ (Williams, 1971) that is based on datafication. ![]()
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