Metropolitan Barcelona 2001–06, or how people’s spatial–temporal behaviour shapes urban structures

This is an Accepted Manuscript of an article published by Taylor & Francis in Regional Studies on 03 April 2019, available online:http://www.tandfonline.com/10.1080/00343404.2019.1583326Traditionally, urban structure has been analyzed using employment density or commuting. The main contribution of this paper is the use of a new source of information which includes other daily activities and that can be integrated into existing subcentre-identification methods. Thus, subcentres are identified using a time-density indicator departing from origin–destination surveys. Results suggest that changes in urban structure during the period under review have taken place in parallel to economic growth and that urban sprawl has increased in all activities except for healthcare and work, where the timeshare lost by the central business district has been redistributed to subcentres and peripheries.Peer ReviewedPostprint (author's final draft

The use of the city in space and time as a new social approach for the prioritising transport corridors in the metropolitan area of Barcelona (Spain)

Postprint (published version

Social parameters in the spatial and temporal use of the city

The developed urban models explain the location considering, among others, a variable of general accessibility, which definition and understanding are divergent and ambiguous. In this way we develop a first stage of investigation that raises a new dimension of accessibility (functional probability), that it is constructed with the population pattern of mobility (how the people move in the city). This dimension was compared with traditional measures of accessibility (distance, time), in its capacity to explain the spatial pattern of residential densities, in the metropolitan area of Santiago (Chile) and Barcelona (Spain). The functional probability (“disposition to travel”), in both cities, shows a statistical similarity in the purposes journey to shop and to study, but a dissimilarity in the journey to work purpose. These results are interesting in the sense that Barcelona and Santiago are structurally different. In this context, we develop a second stage of the investigation, based on the new paradigm of understanding the integration of the mobility (transport) in the social territorial system. The newness of the investigation is the way (quantitative) to characterize and to visualize space-time operation of social systems in the city, understanding them not only by the mobility, but also by the space-time behavior of the stay of people in the different zones of the city, with different purposes. The study applies a trip chain analysis (like the activity-based transportation model) over trip surveys for the metropolitan area of Barcelona (2001, 2006), and for Santiago (1991, 2001). The results are analyzed in a probabilistic dimension (aggregate) in space and time. The first result of this second stage of the investigation is the dynamic density (variation in space and time) of the use of the city and the transport network, for different purposes, for the metropolitan area of Barcelona 2001. The functional probability (mobility and activity) approach can be used as a measure of social equity in the use of time in the city.Peer ReviewedPostprint (author’s final draft

Initialization Methods for Multiple Seasonal Holt-Winters Forecasting Models

[EN] The Holt-Winters models are one of the most popular forecasting algorithms. As well-known, these models are recursive and thus, an initialization value is needed to feed the model, being that a proper initialization of the Holt-Winters models is crucial for obtaining a good accuracy of the predictions. Moreover, the introduction of multiple seasonal Holt-Winters models requires a new development of methods for seed initialization and obtaining initial values. This work proposes new initialization methods based on the adaptation of the traditional methods developed for a single seasonality in order to include multiple seasonalities. Thus, new methods to initialize the level, trend, and seasonality in multiple seasonal Holt-Winters models are presented. These new methods are tested with an application for electricity demand in Spain and analyzed for their impact on the accuracy of forecasts. As a consequence of the analysis carried out, which initialization method to use for the level, trend, and seasonality in multiple seasonal Holt-Winters models with an additive and multiplicative trend is provided.Trull, O.; García-Díaz, JC.; Troncoso, A. (2020). Initialization Methods for Multiple Seasonal Holt-Winters Forecasting Models. Mathematics. 8(2):1-17. https://doi.org/10.3390/math8020268S11782Weron, R. (2014). Electricity price forecasting: A review of the state-of-the-art with a look into the future. International Journal of Forecasting, 30(4), 1030-1081. doi:10.1016/j.ijforecast.2014.08.008Taylor, J. W. (2003). Short-term electricity demand forecasting using double seasonal exponential smoothing. Journal of the Operational Research Society, 54(8), 799-805. doi:10.1057/palgrave.jors.2601589Taylor, J. W. (2010). Triple seasonal methods for short-term electricity demand forecasting. European Journal of Operational Research, 204(1), 139-152. doi:10.1016/j.ejor.2009.10.003Holt, C. C. (2004). Forecasting seasonals and trends by exponentially weighted moving averages. International Journal of Forecasting, 20(1), 5-10. doi:10.1016/j.ijforecast.2003.09.015Bowerman, B. L., Koehler, A., & Pack, D. J. (1990). Forecasting time series with increasing seasonal variation. Journal of Forecasting, 9(5), 419-436. doi:10.1002/for.3980090502Initializing the Holt–Winters Methodhttps://robjhyndman.com/hyndsight/hw-initialization/Rasmussen, R. (2004). On time series data and optimal parameters. Omega, 32(2), 111-120. doi:10.1016/j.omega.2003.09.013Trull, Ó., García-Díaz, J., & Troncoso, A. (2019). Application of Discrete-Interval Moving Seasonalities to Spanish Electricity Demand Forecasting during Easter. Energies, 12(6), 1083. doi:10.3390/en12061083Segura, J. V., & Vercher, E. (2001). A spreadsheet modeling approach to the Holt–Winters optimal forecasting. European Journal of Operational Research, 131(2), 375-388. doi:10.1016/s0377-2217(00)00062-xMakridakis, S., & Hibon, M. (1991). Exponential smoothing: The effect of initial values and loss functions on post-sample forecasting accuracy. International Journal of Forecasting, 7(3), 317-330. doi:10.1016/0169-2070(91)90005-gWilliams, D. W., & Miller, D. (1999). Level-adjusted exponential smoothing for modeling planned discontinuities. International Journal of Forecasting, 15(3), 273-289. doi:10.1016/s0169-2070(98)00083-

Stability of Multiple Seasonal Holt-Winters Models Applied to Hourly Electricity Demand in Spain

[EN] Electricity management and production depend heavily on demand forecasts made. Any mismatch between the energy demanded with respect to that produced supposes enormous losses for the consumer. Transmission System Operators use time series-based tools to forecast accurately the future demand and set the production program. One of the most effective and highly used methods are Holt-Winters. Recently, the incorporation of the multiple seasonal Holt-Winters methods has improved the accuracy of the predictions. These forecasts, depend greatly on the parameters with which the model is constructed. The forecasters need to deal with these parameters values when operating the model. In this article, the parameters space of the multiple seasonal Holt-Winters models applied to electricity demand in Spain is analysed and discussed. The parameters stability analysis leads to forecasters better understanding the behaviour of the predictions and managing their exploitation efficiently. The analysis addresses different time windows, depending on the period of the year as well as different training set sizes. The results show the influence of the calendar effect on these parameters and if it is necessary or not to update them in order to obtain a good accuracy over time.The authors would like to thank the Spanish Ministry of Economy and Competitiveness for the support under project TIN2017-8888209C2-1-R.Trull, Ó.; García-Díaz, JC.; Troncoso, A. (2020). Stability of Multiple Seasonal Holt-Winters Models Applied to Hourly Electricity Demand in Spain. Applied Sciences. 10(7):1-16. https://doi.org/10.3390/app10072630S11610

Understanding mobility as the result of the city use, in space and time

Can we reorganize mobility if we don’t know why, when, and where the people move? When we know the different pattern of the use of the city, and more specific of the use of the different activities in the city, then we can evaluate the impact of a transport project, in the sense of the social system that they affect. The pattern of mobility-use the city is important to reorganize the mobility, and not only the efficiency of different transport system. The developed urban models explain the location considering, among others, a variable of general accessibility, which definition and understanding are divergent and ambiguous. Our investigation raises a new dimension of accessibility (functional probability), that it is constructed with the population pattern of mobility (how the people travel in the city).Peer ReviewedPostprint (published version

Optimal dynamic antitrust fines

Standard antitrust optimal fines rely on a microeconomic static model. Motchenkova describes optimal antitrust dynamic sanctions and their application for EU and US methodology. For the EU fine, and based on this methodology, we find an equilibrium point for a high level of offense (2 times normal profits ) and a high detection probability (0.6)

Macroeconomic effects of EU Competition Policy

I estimate the macroeconomic impact of competition policy to deter collusion and merger control in the EU using a dynamic macroeconomic model . The impact was estimated using a traditional Dynamic Stochastic General Equilibrium Model and an upgraded version that includes Central Bank quantitative easing policies. When these are included in the model the macroeconomic effects are higher than previously estimated

Consumer Demand Estimation

In this chapter I will review the main methodologies used in economics for demand estimation, focusing on recent trends such as the structural approach and machine learning techniques. As one can imagine the literature review is extensive so due to space limitations I can only provide a summarized view of each theory. Nevertheless, the interested reader has a comprehensive bibliography at the end of the chapter for extensions and examples. There is also another barrier when explaining any concept in economics. Economics is widely based on Mathematics, Statistics and Econometrics so it is not possible to explain it without its usage. As it is not possible review econometrics and mathematics in this chapter I will refer to specific texts, and an appendix will give the reader a brief summary of the main concepts. Demand is usually the first step in the study of a market. Intuitively, suppliers only start production when they identify consumer interest in a particular good. All models reviewed try to solve the problems that traditionally have embarrassed demand estimation: identification, endogeneity and simultaneity. There is no perfect solution to them, each model has its advantages and limitations and are based on assumptions that are often irreal, so the model in itself is in all cases only an approximation of demand