U Midas
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Applied Economic Forecasting Using Time Series Methods
| Author | : Eric Ghysels |
| Publisher | : Oxford University Press |
| Total Pages | : 617 |
| Release | : 2018 |
| Genre | : Business & Economics |
| ISBN | : 0190622016 |
Economic forecasting is a key ingredient of decision making in the public and private sectors. This book provides the necessary tools to solve real-world forecasting problems using time-series methods. It targets undergraduate and graduate students as well as researchers in public and private institutions interested in applied economic forecasting.
Identifying Optimal Indicators and Lag Terms for Nowcasting Models
| Author | : Jing Xie |
| Publisher | : International Monetary Fund |
| Total Pages | : 38 |
| Release | : 2023-03-03 |
| Genre | : Business & Economics |
| ISBN | : |
Many central banks and government agencies use nowcasting techniques to obtain policy relevant information about the business cycle. Existing nowcasting methods, however, have two critical shortcomings for this purpose. First, in contrast to machine-learning models, they do not provide much if any guidance on selecting the best explantory variables (both high- and low-frequency indicators) from the (typically) larger set of variables available to the nowcaster. Second, in addition to the selection of explanatory variables, the order of the autoregression and moving average terms to use in the baseline nowcasting regression is often set arbitrarily. This paper proposes a simple procedure that simultaneously selects the optimal indicators and ARIMA(p,q) terms for the baseline nowcasting regression. The proposed AS-ARIMAX (Adjusted Stepwise Autoregressive Moving Average methods with exogenous variables) approach significantly reduces out-of-sample root mean square error for nowcasts of real GDP of six countries, including India, Argentina, Australia, South Africa, the United Kingdom, and the United States.
Robustness in Econometrics
| Author | : Vladik Kreinovich |
| Publisher | : Springer |
| Total Pages | : 693 |
| Release | : 2017-02-11 |
| Genre | : Technology & Engineering |
| ISBN | : 3319507427 |
This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
Theory and Applications of Time Series Analysis
| Author | : Olga Valenzuela |
| Publisher | : Springer Nature |
| Total Pages | : 236 |
| Release | : 2023-12-11 |
| Genre | : Mathematics |
| ISBN | : 303140209X |
This book presents the latest developments in the theory and applications of time series analysis and forecasting. Comprising a selection of refereed papers, it is divided into several parts that address modern theoretical aspects of time series analysis, forecasting and prediction, with applications to various disciplines, including econometrics and energy research. The broad range of topics discussed, including matters of particular relevance for sustainable development, will give readers a modern perspective on the subject. The included contributions were originally presented at the 8th International Conference on Time Series and Forecasting, ITISE 2022, held in Gran Canaria, Spain, June 27-30, 2022. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.
20 kratkih priča na esperantu za početnike
| Author | : lingoXpress |
| Publisher | : lingoXpress |
| Total Pages | : 62 |
| Release | : |
| Genre | : Foreign Language Study |
| ISBN | : |
Unaprijedite svoje jezične vještine i uživajte u ovoj zbirci kratkih priča za početnike! Čitanje može biti moćan alat u učenju jezika, nudeći mnoštvo prednosti koje poboljšavaju razumijevanje i uživanje u novom jeziku. Evo nekih od glavnih prednosti: Širenje vokabulara: Čitanje vas izlaže novim riječima u kontekstu, što je ključno za izgradnju vokabulara. Učenje novih riječi kroz priče može biti učinkovitije od učenja napamet jer ćete vidjeti kako se one koriste u rečenicama. Razumijevanje konteksta: Priče pružaju kontekst za jezik, olakšavajući razumijevanje kako se riječi i izrazi koriste u situacijama stvarnog života. Ovo kontekstualno učenje pomaže u razumijevanju i zadržavanju. Vježbanje gramatike: čitanje vam omogućuje da vidite gramatiku na djelu. Promatrajući kako su rečenice strukturirane i kako su glagoli konjugirani unutar pripovijesti, možete prirodno poboljšati svoje razumijevanje gramatike. Kulturološki uvidi: Priče često sadrže kulturne nijanse, idiome i izraze specifične za jezik. Razumijevanje ovih elemenata može poboljšati vašu kulturnu kompetenciju i učiniti vašu upotrebu jezika autentičnijom. Poboljšane vještine čitanja: Redovita praksa čitanja poboljšava vašu tečnost i razumijevanje pročitanog na novom jeziku, olakšavajući s vremenom rješavanje složenijih tekstova. Poboljšane vještine slušanja: Kad se nadopuni audioknjigama ili materijalima za čitanje, čitanje priča također može poboljšati vaše vještine slušanja dok učite kako se riječi izgovaraju i kako rečenice teku u jeziku. Motivacija i užitak: Priče mogu biti privlačne i zabavne, čineći učenje jezika ugodnijim i manje zastrašujućim zadatkom. Uvjerljiva pripovijest može motivirati učenike da nastave čitati i istraživati jezik. Kognitivne prednosti: Čitanje na stranom jeziku izaziva vaš mozak, poboljšavajući kognitivne vještine poput fokusa, pamćenja i kritičkog razmišljanja. To je oblik mentalne vježbe koja jača jezične vještine. Poboljšane vještine pisanja: Izlaganje različitim stilovima pisanja i narativima može poboljšati vaše vještine pisanja na novom jeziku, pružajući modele za učinkovito izražavanje ideja. Povećano samopouzdanje: Kako se vaše razumijevanje i vještine poboljšavaju čitanjem, vjerojatno ćete se osjećati sigurnije u korištenju jezika, bilo da govorite, pišete ili razumijete. Uključivanjem priča u svoju rutinu učenja jezika, iskoristit ćete bogat izvor koji ne samo da povećava vaše jezične vještine, već i produbljuje vaše kulturno razumijevanje i čini učenje ugodnijim i korisnijim putovanjem.
Applied Economic Forecasting using Time Series Methods
| Author | : Eric Ghysels |
| Publisher | : Oxford University Press |
| Total Pages | : 617 |
| Release | : 2018-03-23 |
| Genre | : Business & Economics |
| ISBN | : 0190622032 |
Economic forecasting is a key ingredient of decision making both in the public and in the private sector. Because economic outcomes are the result of a vast, complex, dynamic and stochastic system, forecasting is very difficult and forecast errors are unavoidable. Because forecast precision and reliability can be enhanced by the use of proper econometric models and methods, this innovative book provides an overview of both theory and applications. Undergraduate and graduate students learning basic and advanced forecasting techniques will be able to build from strong foundations, and researchers in public and private institutions will have access to the most recent tools and insights. Readers will gain from the frequent examples that enhance understanding of how to apply techniques, first by using stylized settings and then by real data applications--focusing on macroeconomic and financial topics. This is first and foremost a book aimed at applying time series methods to solve real-world forecasting problems. Applied Economic Forecasting using Time Series Methods starts with a brief review of basic regression analysis with a focus on specific regression topics relevant for forecasting, such as model specification errors, dynamic models and their predictive properties as well as forecast evaluation and combination. Several chapters cover univariate time series models, vector autoregressive models, cointegration and error correction models, and Bayesian methods for estimating vector autoregressive models. A collection of special topics chapters study Threshold and Smooth Transition Autoregressive (TAR and STAR) models, Markov switching regime models, state space models and the Kalman filter, mixed frequency data models, nowcasting, forecasting using large datasets and, finally, volatility models. There are plenty of practical applications in the book and both EViews and R code are available online at authors' website.
Nature of Computation and Communication
| Author | : Cong Vinh Phan |
| Publisher | : Springer Nature |
| Total Pages | : 180 |
| Release | : 2023-03-23 |
| Genre | : Computers |
| ISBN | : 3031287908 |
This book constitutes the refereed post-conference proceedings of the 8th EAI International Conference on Nature of Computation and Communication, ICTCC 2022, held in Vinh Long, Vietnam, in October 27-28 2022. The 11 revised full papers presented were carefully selected from 32 submissions. The papers of ICTCC 2022 cover formal methods for self-adaptive systems and discuss natural approaches and techniques for natural computing systems and their applications.
Financial, Macro and Micro Econometrics Using R
| Author | : |
| Publisher | : North Holland |
| Total Pages | : 350 |
| Release | : 2020-01-20 |
| Genre | : Mathematics |
| ISBN | : 0128202505 |
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics.
Predictive Econometrics and Big Data
| Author | : Vladik Kreinovich |
| Publisher | : Springer |
| Total Pages | : 788 |
| Release | : 2017-11-30 |
| Genre | : Technology & Engineering |
| ISBN | : 3319709429 |
This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
