Time Series Modelling and Forecasting using Stata
COURSE DESCRIPTION Time Series data is today available for a wide range of several phenomena in Business, Finance, Economics, Public Health, the Political and Social Sciences. The aim of TStat Training’s Times Series Modelling and Forecasting Course is therefore, to provide researchers and professionals with the standard tool kit required for the analysis of time series data in Stata. As such the program has been developed to offer an overview of the most commonly used methods for analysing, modelling and forecasting the dynamic behaviour of time series data, offering practical examples of empirical modelling using real-world data. The course begins with an introduction to Stata’s basic time series commands, before moving onto the analysis of time series features and to univariate time series models. Sessions 3 and 4 instead focus on the estimation of both multivariate time series models with stationary and nonstationary data and univariate models of volatility. In common with TStat’s training philosophy, throughout the course theory and methods are illustrated in an intuitive way and are complemented by practical exercises undertaken in Stata, during which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. Particular attention is also given to both the interpretation and presentation of empirical results. In this manner, the course leader is able to bridge the “often difficult” gap between theory and practice of time series modelling and forecasting. Upon completion, it is expected that participants are able to autonomously implement the statistical methods discussed during the course to their own data, customizing when necessary, the Stata do-file routines specifically developed for the course. TARGET AUDIENCE Researchers and professionals working in financial institutions, policy institutions, research departments of utilities, governments, corporations, Ph.D and Master students in biostatistics, economics, finance, engineering, psychology, social and political sciences needing to implement time series data analysis methods. PREREQUISITES Participants are required to have a good working knowledge of: • Linear regression model definition and assumptions • Ordinary Least Squares (OLS) estimation. Properties ofOLS • Inference in the linear regression model: confidenceintervals, t-test, F-test • Violation of the linear regression model assumptions:heteroscedasticity, serial correlation, functional formmisspecification, non-Normality. Consequences ofviolations and remedies • Diagnostic analysis of regression: tests forheteroscedasticity, test for serial correlation, Normalitytest, Ramsey’s RESET • Regression with time series data. Concepts of laggedvariable and differenced variable • Dynamic models Those needing to refresh these concepts are referred to: • Hill, R.C., Griffiths, W.E., and G.C. Lim (2018). Principlesof Econometrics, 5th Edition. Wiley • Stock, J.H., and Watson, M.W. (2019). Introduction toEconometrics, 4th edition, Pearson • Wooldridge, J.M. (2020). Introductory Econometrics: AModern Approach, 7th Edition, Cengage Learning PROGRAM SESSION I: WORKING WITH TIME SERIES IN STATA 1. A quick introduction to Stata for time series data: • Creating and formatting date variables using date and time functions and time-series declaration • Using Stata time-series operators to create lags, leads, differences, seasonal differences, percentage changes 2. Graphical analysis of time series: • Creating and examining line plots to understand the behaviour of series over time • Creating and examining correlograms to assess dependence in time series • Creating and examining histograms to evaluate Normality 3. Descriptive statistics analysis of time series: • Unit root test: Augmented Dickey Fuller Test and DFGLS test • White Noise test • Normality test SESSION II: UNIVARIATE TIME SERIES MODELS 1. Univariate Time Series Models: theoretical elements • Autoregressive model (AR) • Moving Average model (MA) • Autoregressive Moving Average Model (ARMA) • Autoregressive Integrated Moving Average Model (ARIMA) • Seasonal ARIMA models (SARIMA) 2. ARIMA modelling in practice: using the Box-Jenkins approach to model real-world economic time series • Examining the sample autocorrelation function and the sample partial autocorrelation function • Estimation of ARIMA models • Model diagnostic analysis and model selection using information criteria 3. Forecasting with ARIMA models 4. An introduction to Markov-Switching Models • Markov-switching dynamic regression • Markov-switching autoregression SESSION III: MULTIVARIATE TIME SERIES MODELS 1. Multivariate Time Series Models – Vector Autoregression (VAR): theoretical elements 2. VAR modelling in practice: • Lag order selection • Estimation • Diagnostic checking: autocorrelation, stationarity and normality 3. Granger causality and impulse response function analysis 4. Forecasting with VAR models 5. Nonstationary time series: spurious regressions versus cointegration • Concepts of long-run equilibrium relationships and short-run relationships • Vector Error Correction Model (VECM) • Testing for cointegration in regressions: a residuals-based test 6. Engle and Granger two-step method 7. Testing for cointegration and estimating cointegrating relationships with the Johansen’s approach SESSION IV: MODELLING AND FORECASTING VOLATILITY IN TIME SERIES MODELS 1. Time-varying volatility: • Visual inspection of time-varying volatility (i.e. volatility clustering) and leptokurtosis with line plots and histograms • ARCH test 2. Modelling volatility of financial time series: • ARCH model: estimation and diagnostic checking • Extension to the ARCH model: GARCH model, estimation and diagnostic checking • ARCH-in-Mean model • Modelling the asymmetric impact of news on volatility: Asymmetric GARCH models (EGARCH, GJR-GARCH, TGARCH, APARCH) • Model selection 3. Forecasting volatility with GARCH models SUGGESTED READING (PRE – AND POST-COURSE) Becketti, S. (2020). Introduction to Time Series Using Stata. Stata Press Publication. Boffelli, S. and Urga G. (2016). Financial Econometrics Using Stata. Stata Press Publication. DATE AND LOCATION The 2026 edition of this training course will be offered ONLINE on a part-time basis on the 1st-2nd, 8th-9th of October. To this end, programme includes a series of sessions based on 4 modules from 10:00 am to 1:30 pm Central European Summer Time (CEST). COURSE LEADERS Dr Elisabetta PELLINI, Centre for Econometric Analysis, Bayes Business School (formerly Cass), London (UK). REGISTRATION FEE AND REGISTRATION FORM Students*: € 470.00 Ph.D Students: € 610.00 University: € 1110.00 Commercial: € 1480.00 *To be eligible for full-time student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters, access to our student registration rates. Part-time master and doctoral students on the other hand, who are also currently employed will however, be assigned the standard academic registration fee. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: teaching materials (handouts, Stata do-files, program templates and datasets to use during the course), a temporary course licence of StataNow™ valid for 30 days from the beginning of the course. Individuals interested in attending the training course, must return their completed registration forms to TStat by the 20th of September 2026. To request further information or the registration form, please fill in the following form or send an email to training@tstat.eu
The course has been developed to offer an overview of the most commonly used methods for analysing, modelling and forecasting the dynamic behaviour of time series data, offering practical examples of empirical modelling using real-world data. TStat Training’s live online training courses are offered interactively via Zoom with a qualified trainer in real-time. All materials (slides, datasets and Stata routines specifically developed for the course) are made available for download before the start of the course. The 2026 edition of this training course will be offered ONLINE on a part-time basis on the 1st-2nd of October and 8th-9th of October.
Econometrics, Statistics and Quantitative Methods (JEL C)
Call for Expressions of Interest Tenure-Track Assistant Professor (RTT) in Economics, Management, and Statistics
The IMT School for Advanced Studies Lucca invites expressions of interest from outstanding candidates for a prospective tenure-track Assistant Professor (RTT) position in Economics, Management, and Statistics, and related fields. The purpose of the scouting procedure is to collect expressions of interest in sectors deemed strategic for the development of the School’s research areas and doctoral programs in order to evaluate the opportunity to open call (“concorsi”) as expected according to the Italian law. The call for expressions of interest is open to candidates working in any field of economics, management, statistics, and related fields. We particularly welcome applicants whose research combines strong theoretical, empirical, experimental, or computational foundations with the analysis of economically and socially relevant questions. The ideal candidate will have a solid research profile and the potential to develop an internationally visible and independent research agenda. Applications are encouraged from scholars using a broad range of methodologies, including business analytics, economic theory, econometric methods, causal inference, experimental methods, survey methods, psychometric methods, mathematical and statistical methods, optimization, game theory, and machine learning. Research interests may include, but are not limited to, microeconomics, macroeconomics, econometrics, applied mathematics, statistics, operations research, management science, strategy, planning and control, business model and innovation, behavioral economics, political economy, computational economics, labor economics, public economics, health economics, environmental economics, international economics, industrial organization, economics of innovation, and economic networks. The successful candidate is expected to actively contribute to the research environment at the IMT School and, in particular, to the activities of the AXES – Laboratory for the Analysis of Complex Economic Systems. The candidate should be willing to collaborate with researchers from economics, management, statistics, and related disciplines and to participate in interdisciplinary research projects. Expected activities include: carrying out high-quality research; publishing in leading peer-reviewed international journals; contributing to national and international research projects and funding applications; teaching economics, management, mathematics, statistics, econometrics and quantitative methods, primarily at the doctoral level; supervising and mentoring PhD students; participating in seminars, workshops, and the scientific life of the School; contributing to the PhD Programs in Economics, Analytics and Decision Sciences (EADS), Social Sciences for Sustainability and Wellbeing (S3W), and Intelligence Systems for Business Administration (ISBA); and to other relevant educational and research initiatives. Applicants should hold a PhD in Economics, Management, Statistics or a closely related discipline and demonstrate excellent research potential. A strong command of English is required. International research experience, experience in doctoral teaching or supervision, experience in research grant writing, funding acquisition (including university performance awards) and technology transfer, and the ability to work in interdisciplinary research teams will be considered valuable assets. IMT School offers a highly international and interdisciplinary research environment, with strong interactions among economics, statistics, management, data science, computer science, engineering, neuroscience, and the social sciences.
The IMT School for Advanced Studies Lucca invites expressions of interest from outstanding candidates for a prospective tenure-track Assistant Professor (RTT) position. ON LINE APPLICATION FORM
Visualizing Geospatial Data In Stata: Spatial Maps In Stata - Live Online Course
The creation of spatial maps has become a valuable tool for researchers interested in both the spatial data visualization and the identification of geographical patterns in the data. This interactive course therefore, offers an introduction to the mapping techniques currently available in Stata for visualization of geospatial data. The workshop opens with an overview of the peculiar characteristics of geospatial data, the implications of such for the analysis of such data and an overview of the special terminology used in this field, before moving on to discuss the concept of spatial proximity and its relevance to the visualization of spatial data analysis. The remainder of the workshop is dedicated to the principle mapping techniques, using a combination of both official Stata commands and a series of user written commands, currently adopted to visualize geospatial data in Stata. Participants will learn how to import geospatial data shapefiles in Stata and merge them with their existing Stata databases in order to create, compare and customize different mapping techniques. At the end of the course, participants will be able to autonomously implement (with the help of the Stata routine templates specifically developed for the workshop) the appropriate mapping methods, given both the nature of their spatial data and the analysis in hand, within their own research. TARGET AUDIENCE This online course is of particular interest for criminologists, social psychologists, sociologists, economists, epidemiologists and political scientists seeking to acquire the requisite tools required for the exploration and visualisation of spatial data in Stata. PREREQUISITES A knowledge of basic statistics (distributions of variables, position indices, dispersion indices) and the statistical software Stata is recommended. PROGRAM SESSION I: SPATIAL DATA 1. General characteristics of spatial data 2. Types of spatial objects 3. Spatial coordinate systems 4. Maps and shapefiles 5. The transformation of spatial databases SESSION II: SPATIAL PROXIMITY 1. Spatial distance 2. Spatial proximity matrices 3. Spatial lags 4. Spatial autocorrelation SESSION III: VISUAL ANALYSIS OF SPATIAL DATA 1. Visual analytics and data science 2. Thematic maps 3. Dot maps 4. Graduated symbol maps 5. Diagram maps 6. Choropleth Maps 7. Isarithmic Maps 8. Multivariate Maps SUGGESTED READING Anthamatten, P. (2021). How to Make Maps: An Introduction to Theory and Practice of Cartography. Abingdon: Routledge. Lambert, N. & Zanin, C. (2020). Practical Handbook of Thematic Cartography: Principles, Methods, and Applications. Boca Raton, FL: CRC Press. DATE AND LOCATION The next edition of this training course will be offered online on a part-time basis on the 30th of September from 9:00 am to 1:30 pm CET. COURSE LEADERS Professor Maurizio Pisati, University of Milano-Bicocca, Department of Sociology and Social Research, Milan (IT). REGISTRATION FEE AND REGISTRATION FORM Full-time Students*: € 155 Ph.D. Students: € 205 Academic: € 370 Commercial: € 495 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. Register Here The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 20th of September 2026.
This interactive online course offers an introduction to the mapping techniques currently available in Stata for visualization of geospatial data. The next edition of this training course will be offered online on a part-time basis on the 30th of September.
Urban, Rural and Transportation Economics (JEL R)
Part-time Faculty, Economics – Lariccia School of Accounting & Finance – Online Courses
Description Teach undergraduate online courses in economics and personal financial literacy. Position Information Plans, organizes, teaches, and provides feedback to promote and direct student success. Responds to students in a timely manner. Communicates with students, departments, and university officials via university provided tools and resources. An Institution of Opportunity: YSU inspires individuals, enhances futures, and enriches lives. As a student-centered university, Youngstown State University’s mission is to provide innovative lifelong learning opportunities that will inspire individuals, enhance futures, and enrich lives. YSU inspires individuals by cultivating a curiosity for life-long learning; enhances the futures of our students by empowering them to discover, disseminate and apply their knowledge; and enriches the region by fostering collaboration and the advancement of civic, scientific, and technological development. YSU’s culture of enrichment flourishes in our intellectually diverse, accessible, and quality education. Work Schedule: Typically, Monday through Friday. Teaching assignments will be courses online. Qualifications and Competencies Required Certifications, Training, and/or Licensures: None. Sponsorship and/or Work Authorization Status: Must be currently authorized to work in the United States on a full-time basis. Minimum Qualifications: At least an earned master’s degree in economics or a related field; at least three years of professional field experience in economics; must be currently authorized to work in the United States on a full-time basis. Preferred Qualifications: Professional certification(s) in economics or finance. Prior teaching experience. Physical Requirements: In accordance with the U.S. Department of Labor physical demands strength ratings, this position will perform sedentary work. Sedentary: work involves exerting up to 10 pounds of force occasionally or a negligible amount of force frequently to lift, carry, push, pull, or otherwise move objects, including the human body. Sedentary work involves sitting most of the time but may involve walking or standing for brief periods of time. Jobs may be defined as Sedentary when walking and standing are required only occasionally, and all other Sedentary criteria are met. Supplemental Information Please upload all transcripts as one PDF file. At time of hire, all candidates must provide official transcripts. Official transcripts must be provided in an unopened, sealed envelope and must bear the embossed or raised college seal, date and Registrar’s signature. Employer Youngstown State University (OH) Address: 1 Tressel Way, Youngstown, Ohio, 44555 Phone: 330-941-1508 Website: http://www.ysu.edu
Teach undergraduate online courses in economics and personal financial literacy at Youngstown State University.
EcoMod ONLINE - Introduction to General Equilibrium Modeling using GAMS
Date: January 1, 2026 - December 31, 2026 EcoMod ONLINE expands the EcoMod School’s offerings to a flexible, accessible learning environment designed for professionals worldwide. Our online programs cover the major economic policy challenges facing governments, central banks, international organizations, and research institutions. Key topics include sustainability, energy, climate change, monetary and fiscal policy, taxation, labor markets, development, pensions, health, social protection, gender, agriculture, tourism, water, and regional economic issues. Through EcoMod ONLINE, participants learn how to design, develop, and apply quantitative economic models for scenario analysis, impact assessment, forecasting, and policy simulations. All courses are asynchronous—allowing you to study at your own pace and from any location—while maintaining the rigor, structure, and practical orientation that define EcoMod training. Instruction is delivered by senior experts with extensive hands-on experience as heads of modeling units and research divisions in major institutions. Course Open - EcoMod ONLINE - Introduction to General Equilibrium Modeling using GAMS This immersive online course enables participants to master Computable General Equilibrium (CGE) modeling using GAMS, following the successful EcoMod framework—an internationally recognized standard in applied economic modeling. Participants will build models from the ground up, developing practical skills in partial and general equilibrium analysis, household behavior, production technologies, macro‐economic policy, government interventions, labor markets, savings-investment dynamics, and international trade. Advantages of EcoMod ONLINE Learn from anywhere, at any time, with full flexibility for professional schedules Progress at your own pace through structured, high-quality modules Access the same level of expert instruction as our in-person schools Apply learning immediately through real datasets, models, and hands-on exercises Join a global network of peers and experts across institutions and regions EcoMod Legacy and Expertise EcoMod ONLINE builds on the EcoMod Network’s 25-year legacy as the global leader in training on CGE, macroeconometric, financial, and environmental modeling. The EcoMod School of Modeling and Data Science is recognized worldwide for its step-by-step, practice-oriented teaching methodology, enabling participants to construct and work with operational models under expert guidance. Our ONLINE courses preserve this proven learning approach through carefully designed modules, practical exercises, and real-world model applications. EcoMod also maintains the largest alumni network in the world in this specialized field, with participants from more than 2,000 institutions in 180 countries. By joining EcoMod ONLINE, you become part of this global community of policymakers, economists, and analysts who rely on EcoMod’s training to support evidence-based decision making. Header Image Credit: Unsplash / Additional Image Credits: Ecomod
Join a Global Community of Modeling Professionals through the EcoMod ONLINE program.
Public Economics & Economic Policy (JEL H)
CIMS Online Summer Schools: Foundations and Advanced of DSGE Macro Modelling
This is a Virtual Summer school (online) this year. Registration is now open for the CIMS summer school 2026. Register Here This year's Summer school will feature: Foundations of DSGE Macro Modelling The five-day course in Foundations of DSGE Modelling will run from 07-11 September 2026. The five days will consist of foundations courses aimed at early researchers with some knowledge of Real Business Cycle (RBC) or Dynamic Stochastic General Equilibrium (DSGE) macroeconomic models, but little or no experience of Dynare. This course assumes a basic knowledge of Matlab and will begin with the basics of Dynare and proceed to the construction, in stages, of a closed economy New Keynesian (NK) DSGE model. It will then progress to the estimation by Bayesian methods, the study of optimal monetary policy and finish with an extension to the open economy NK DSGE model. The course is aimed at MSc, MRes and PhD students, early researchers, and research staff from central banks, ministries and the private sector, all with some prior experience of macroeconomic modelling and a basic knowledge of Matlab. No prior knowledge of Dynare is necessary. Please note that all participants need to have their own copy of Matlab (https://www.mathworks.com/products/matlab.html) for the course on Foundations of DSGE Macro Modelling. There is a short-term license available for students which is worth checking: https://www.mathworks.com/campaigns/products/trials.html Advanced Macro-Modelling with Applications to Numerical Methods and Heterogeneous Agents The five-day course in Advanced Modelling will run from 14-18 September 2026. The advanced course is aimed at people who are already fluent in Dynare and Matlab, but are finding that their ambition currently exceeds what they are able to do with these tools. We will cover advanced numerical and computational methods to enable people to tackle non-standard models. This course will be useful to anyone who is engaged in practical macroeconomic modelling work, especially if they are interested in working with models that are either computationally expensive to simulate, nonlinear, or infinite dimensional thanks to heterogeneous agents, monetary policy, or optimal taxation and inequality. The course is aimed at MSc, MRes and PhD students, early researchers, and research staff from central banks, ministries and the private sector, all with some prior experience of macroeconomic modelling and a basic knowledge of Matlab. Please note that all participants need to have their own copy of Matlab (https://www.mathworks.com/products/matlab.html) for the course on Advanced Macro Modelling. There is a short-term license available for students which is worth checking: https://www.mathworks.com/campaigns/products/trials.html Online delivery method: The course will be conducted using the Microsoft Teams platform. The university and the lecturers are used to do online teaching and have state-of-the-art systems to do so and are able to deliver highly interactive experiences. Though we will do our best to record all sessions, we are expecting participants to attend them live to enable interactions between participants and lectures. Any and all questions are welcome. There will be opportunities to discuss the projects and research ideas of the participants. This will occur both informally as well as formally during the lecture or break time. After the summer school, lecturers will be available to answer questions and discuss the projects of the participants. Participants will be sent computer codes, lecture notes, and slides ahead of time. Participants will also receive direct assistance before the summer school starts in order to set up all the systems ahead of the online events. The summer school covers the theoretical aspects of the techniques. In addition, the summer school is very hands-on and participants will have carefully implemented exercises where they need to modify parts of the codes. This will be done in the lectures, both in groups and with the help of the instructors. The participants will receive solutions to all exercises and will be provided with computer codes that may then use in their own research..
Following highly successful Summer Schools in previous years, the Centre for International Macroeconomic Studies (CIMS) in the School of Economics, University of Surrey will hold two online summer schools on the Macroeconomics/DSGE School (Foundation and Advanced), from September 7 to 18, 2026. Foundations of DSGE Macro Modelling will consist of a five-day course running from 7 September to 11 September 2026. Advanced Macro-Modelling with Topics including Numerical Methods and Heterogeneous Agents will consist of a five-day course running from 14 September to 18 September 2026.
Macroeconomics and Monetary Economics (JEL E)
Up and Running in Stata - Live Online Training
TStat live online training courses are offered interactively via Zoom with a qualified trainer in real-time. All materials (slides, datasets and Stata routines specifically developed for the course) are made available for download before the start of the course. COURSE DESCRIPTION Up and Running in Stata provides participants with the necessary introductory toolset to enable them to carry out efficient data analysis and data management in Stata in a reproducible manner. The interactive course covers everything from the very basics, in order to get one up and running in Stata, to an overview of the available Stata commands for preliminary data analysis, data management, importing and exporting data formats, merging of databases and the creation of graphs in Stata. In common with TStat’s training philosophy, Up and Running in Stata is by its very nature to be considered very much a hands on approach to learning Stata course. Each individual session is composed of both a theoretical component and an applied segment, during which participants have the opportunity to implement the techniques illustrated under the watchful eye of the course tutor. COURSE ID: D-IN10-OL LANGUAGE: English TARGET AUDIENCE This interactive online course is invaluable to both professionals and researchers (working in Epidemiology, Business Studies, Marketing and Management, Biostatistics, Economics, Epidemiology, Medicine, Public Health, Social and Political Sciences and Statistics), wishing to use Stata for applied statistical analysis, data management or data visualization. PREREQUISITES Familiarity with PCs and a working knowledge of English. PROGRAM SESSION I: GETTING STARTED SESSION II: STATA FUNDAMENTALS SESSION III: CREATING SIMPLE STATA ROUTINES: DO FILES SESSION IV: IMPORTING DATA FROM SPREADSHEETS SESSION V: MERGING DATA BASES SESSION VI: GRAPHICS – AN INTRODUCTION SUGGESTED READINGS - Acock, A. (2023). A Gentle Introduction to Stata. Revised Sixth Edition. Stata Press Publication. - Kohler, U. & Kreuter, F. (2012). Data Analysis Using Stata. Third Edition. Stata Press Publication. - Mitchell, M. N. (2020). Data Management Using Stata: A Practical Handbook. Second Edition. Stata Press Publication. DATE AND LOCATION The next 2026 edition of this training course will be offered online on a part-time basis on the 19th-20th, 22nd-23rd of October from 9:30 am to 1:30 pm CET. REGISTRATION FEE AND REGISTRATION FORM Full-Time Students*: € 545.00 Ph.D. Students: € 710.00 Academic: € 1295.00 Commercial: € 1505.00 *To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year. Our standard policy is to provide all full-time students, be they Undergraduates or Masters students, access to student participation rates. Part-time master and doctoral students who are also currently employed will however, be allocated academic status. Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number. The number of participants is limited to 8. Places will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled. Course fees cover: I) teaching materials – copies of lecture slides, databases and Stata programs specifically developed for the course; ii) a temporary licence of StataNow™ valid for 30 days from the day before the course commences. Individuals interested in attending this course must return their completed registration forms by e-mail to TStat by the 9th of October 2026. To request further information or the registration form, please fill in the form on our website or send an email to training@tstat.eu
Up and Running in Stata provides participants with the necessary introductory toolset to enable them to carry out efficient data analysis and data management in Stata in a reproducible manner. The next 2026 edition of this training course will be offered online on a part-time basis on the 19th-20th, 22nd-23rd of October from 9:30 am to 1:30 pm CEST.
GTAPinR Course "Running the GTAP Model using R packages HARr and tabloToR" General Information Dates: Open enrollment Learners can enroll in this course at any time. Once payment has been received and access to the learning management system has been granted, learners will have 56 days to complete the course before access ends. Since the course is self-paced, instructor assistance is not available during or after the course. No feedback or grading beyond automated assessments will be provided. Location GTAPinR is delivered fully online. There is no onsite component to this course. Offered by Center for Global Trade Analysis, Purdue University Enrollment Fees $625 Professional (Developed Country) $470 Professional (Developing Country) $315 Student (Developed Country) $160 Student (Developing Country) Why You Should Enroll Enhance your GTAP skills with open-source R tools designed to streamline simulation and analysis! Execute the GTAP Model directly in R - Learn how to run GTAP simulations end-to-end within the R environment using the open-source HARr and tabloToR packages Streamline data handling and model workflows - Gain practical skills in reading and writing GTAP data, solution files, and header arrays directly in R, enabling more efficient experiment setup and result processing Build practical skills for GTAP workflows - Build hands-on skills in GTAP workflows – setting closures, applying shocks, solving the model, and extracting results all in R environment Strengthen policy analysis with advanced visualization - Turn outputs into insight with R visualization workflows, improving interpretation, communication, and presentation of simulation results Flexible, self-paced learning for busy schedules - With open enrollment and a 56-day completion window, the course is designed to fit into busy schedules while providing structured modules, practical exercises and assessments Course Content This course aims to empower GTAP users with practical tools in R statistical software to enhance simulation analysis for policy making through improved processing of economic model outputs. The specific objective of this course is to introduce the R packages "HARr" and "tabloToR" which are open-source programs specifically designed to interface with the GTAP Model, as well as its outputs and inputs. The "HARr" package serves as a bridge between the GTAP Data Bases and the R environment by enabling the reading and writing of the header array (.har) file format adopted in the GEMPACK suite. The "tabloToR" package facilitates GTAP simulations by interpreting the model in GEMPACK-style TABLO (.tab) files and solves it within the R environment after the model inputs are defined. This course covers topics such as basic installation of the R packages, utilizing its features, as well as data visualization emphasizing practical, hands-on experience. This course is geared towards current users of the GTAP Model who are interested in running the model and processing its inputs and outputs within the R environment. Course Structure The course is delivered fully online and includes reading materials, codes, audio-visual lectures, hands-on exercises, and weekly assessments, all designed to enhance learning. As a self-paced online course, participants will work through the weekly plan of study outlined in the learning management system. Since the course is self-paced, instructor assistance is not available during or after the course. No feedback or grading beyond automated assessments will be provided. Learners will have 56 days from the date access to the learning management system was granted, to complete the course before access ends. Content Overview Module 1 - Getting Started with GTAPinR Module 2 - Reading and Writing Databases with HARr Module 3 - Solving the Model with tabloToR Module 4 - Wrap-Up and Evaluation Time Commitment Participants should expect to spend approximately 2-6 hours per module on this course. Prerequisites Participants are expected to know how to run the GTAP Model and be familiar with the inputs used in running the model. Participants are also expected to know how to use R statistical software. Enrollment Individuals interested in enrolling in this course must register on the GTAP website, after which they will be provided details for making payment by bank transfer or credit card. Once payment has been received and access to the learning management system has been granted, learners will have 56 days to complete the course before access ends.
Enroll in the GTAPinR Course to enhance your GTAP skills with practical tools in R statistical software for policy making.
Economic Development, Innovation and Growth (JEL O)
Agricultural and Environmental Economics (JEL Q)
Non-resident full-time faculty position: Assistant, Associate, or Full Professor in Sustainability and Green Economy
Hamdan Bin Mohammed Smart University (HBMSU), located in Dubai, UAE, the first accredited smart learning university in the region, is seeking exceptional scholars who are passionate about advancing innovative online education. To complement the existing faculty of the School of Sustainability and Green Economy, this non-resident appointment specifically targets scholars whose primary expertise is in sustainable finance, ESG, carbon management, climate policy, or environmental economics. Successful candidates will join a dynamic, learner-centric institution dedicated to excellence in smart learning. Faculty are expected to teach undergraduate and graduate courses in a fully online environment, contribute to the development of engaging digital course content, and maintain an active record of research and scholarly contributions in their specific field. The ideal candidates will demonstrate a commitment to research output including high-quality publications, innovative online pedagogy, and meaningful service to the academic community. Non-resident faculty appointments are full-time roles that allow candidates to teach, conduct research, and engage in service remotely from outside the UAE while fully participating in HBMSU’s online learning environment, contributing to academic service, and mentoring students. These faculty members reside outside the UAE and contribute to our mission entirely through digital platforms. Teaching is delivered fully online, whether asynchronous or synchronous; allowing them to engage with learners across borders. Non-resident faculty actively participate in faculty meetings, committees, and training sessions virtually, ensuring strong collaboration despite the distance. They are expected to produce impactful research in their specific areas, mentor students, and contribute to academic service, with all responsibilities carried out remotely. Community involvement is fostered through regular virtual participation in campus events and initiatives, enabling them to remain an integral part of HBMSU’s vibrant academic network while working from abroad. Applicants must be familiar with online teaching platforms and methodologies and be dedicated to supporting HBMSU’s mission of transforming learning through technology and innovation. Candidates must hold a completed terminal degree at the time of application; conferral letters or equivalent official verification are required. Highlights: Non-resident full-time position Competitive, tax-free salary in the UAE Teach in a dynamic, fully online program accredited by the Commission for Academic Accreditation (CAA), UAE Opportunity to shape the future of digital learning and contribute to the UAE Net Zero 2050 strategy, the UAE Green Agenda 2030, and post-COP28 sustainability priorities in the region Main roles & responsibilities The successful candidate will play a vital role within the School of Sustainability and Green Economy, complementing the school’s existing expertise in environmental management, waste and water sustainability, energy transitions, and circular-economy/data-driven innovation by leading teaching and research in sustainability finance, ESG, carbon management, and climate policy. Responsibilities include: Teaching: Deliver online courses that foster expertise in sustainable finance, ESG and sustainability reporting (GRI, IFRS S1/S2, TCFD, SASB), carbon management and accounting (GHG Protocol, ISO 14064), climate finance, environmental and ecological economics, climate policy and governance, green entrepreneurship, and sustainable business models. Engage learners in developing analytical skills to evaluate the financial, environmental, social, and governance impacts of corporate and policy decisions, and promote entrepreneurial approaches to sustainability solutions. Use interdisciplinary teaching methods and cutting-edge online platforms to equip students with the knowledge and leadership skills needed to tackle global sustainability challenges, climate change, and the low-carbon economy transition. Curriculum Development: Design instructional materials and e-content tailored to sustainable finance, ESG, carbon management, and climate policy, and develop and implement innovative curricula that integrate industry best practices, international sustainability standards and disclosure frameworks, and emerging technologies such as AI and machine learning applied to ESG analytics and climate-risk modelling. Research: Enhance the academic landscape by publishing research findings in high-quality, peer-reviewed Scopus/Web-of-Science indexed journals. Conduct impactful research in areas such as sustainable finance, ESG investing, climate finance, carbon markets and pricing, net-zero pathways, sustainability disclosure and reporting, climate-risk assessment, and the economics of the energy transition. Develop proposals and pursue funding opportunities for research. Mentorship: Guide, advise, and mentor learners throughout their academic journeys, including supervising MSc and (where applicable) PhD theses in sustainable finance, ESG, and carbon management. Professional Development: Create and facilitate professional short courses and workshops aimed at specific target groups and professional communities, including ESG officers, sustainability/CSR managers, and corporate finance professionals in the UAE and the wider GCC region. Service: Undertake necessary responsibilities to support academic programs and their accreditations, conduct feasibility studies, perform business analytics, and carry out benchmarking analyses. Required qualification & skills Qualifications: Candidates should possess the following qualifications and skills: A PhD in Sustainable Finance, Environmental Economics, Climate Policy, Carbon Management, ESG/Sustainability Accounting, or a closely related field from an accredited university, preferably top ranked universities. Demonstrated expertise in at least one of the following areas: (i) sustainable finance, ESG investing, or climate finance; (ii) carbon management, carbon accounting, or net-zero/decarbonisation pathways; (iii) sustainability reporting and disclosure (GRI, IFRS S1/S2, TCFD, SASB, CSRD); or (iv) climate policy, environmental economics, or natural-capital valuation. Expertise in sustainability, sustainability finance and policy instruments, and their application to complex environmental, social, governance, and economic challenges. Ability to evaluate the sustainability of corporate strategies, investment portfolios, policies, and projects, with a focus on innovative finance- and policy-driven solutions for the low-carbon, green economy. Proven capability in fostering interdisciplinary approaches, entrepreneurship, and leadership in global sustainability issues, including climate change mitigation and adaptation, ESG integration, and sustainable finance. The candidate should be capable of teaching at undergraduate and graduate levels in sustainability and green economy. Preference will be given to those willing to teach sustainable finance and ESG, carbon management, climate policy and economics, and sustainability reporting standards. A demonstrated record of successful teaching experience at an accredited university. Ability to integrate industry insights into curriculum development and classroom instruction, ideally with prior consulting, regulatory, financial-sector, or corporate sustainability experience. Demonstrated strong scholarly preparation with the ability to teach and publish effectively in English. Proven capability in developing and delivering professional workshops. Proven teaching experience in online learning environments. Ability to teach and engage learners effectively in online undergraduate and graduate programs. Must meet the academic qualification requirements of the School of Sustainability and Green Economy, the University, the UAE Ministry of Higher Education and Scientific Research (MOHESR), and relevant accreditation bodies (CAA-UAE). Application process Submit the following: cover letter, CV (including a clear terminal degree, publications, and references), a one-page statement outlining how the applicant complements rather than overlaps with the existing faculty, and a Google Scholar profile link with current h-index and citation count. Applications must be submitted through the HBMSU designated application portal (link provided in the posting). Review of applications begins immediately and continues until the position is filled. Location Dubai Academic City P.O.Box 71400. Dubai. UAE Toll Free (UAE) 800 333 000 Telephone (International): 009714 424 1111 Email learn@hbmsu.ac.ae
Hamdan Bin Mohammed Smart University (HBMSU) seeks exceptional scholars for the School of Sustainability and Green Economy.
Positive Science – Economics Best Paper Award 2026: $4,000 Prize Fund for Published Articles
The journal Positive Science – Economics welcomes original research across the broad field of economics, including macroeconomics, microeconomics, finance, development, public economics, labour, education, health, international economics, economic history, environmental economics, digital economy, innovation, and related fields. Positive Science – Economics is open-access, peer-reviewed, and IMRaD-friendly. We welcome theoretical, empirical, applied, policy-oriented, qualitative, quantitative, and interdisciplinary research. Submit your manuscript and, if your article is accepted for publication by December 31, 2026, it will be automatically considered for the award. https://positive-science.com/contest/economics_best_paper_award_2026_75882b7129?utm_source=inomics&utm_medium=announcement&utm_campaign=ps_economics_best_paper_award_2026&utm_content=contest_cta Journal Aims & Scope: https://positive-science.com/journal/human_economics_B1057f9a86?utm_source=inomics&utm_medium=announcement&utm_campaign=ps_economics_best_paper_award_2026&utm_content=journal_scope
🏆 Positive Science is pleased to announce the Positive Science – Economics Best Paper Award 2026, an award recognizing outstanding scholarly contributions published in the peer-reviewed open-access journal Positive Science – Economics. All articles accepted for publication or published in Positive Science – Economics between 1 January and 31 December 2026 are automatically eligible. Authors do not need to submit a separate award application. Total prize fund: US$4,000, distributed across three award categories: 🥇 Best Paper Award: US$2,500 🥈 Runner-up Award: US$1,000 🌱 Special Mention / Emerging Scholar Award: US$500 Results announcement: March 2027
Econometrics with EViews: Time Series, and Panel Data
Econometrics with EViews: Time Series, and Panel Data Created by Dr. Nasir Munir What you'll learn Understanding the concepts of data. Explaining the properties of the OLS. Estimating the different econometric tools used in time series data. Determining the basic economics models and interpreting them. This course includes: 13 hours on-demand video Assignments Access on mobile and TV Certificate of completion Course content 16 sections • 88 lectures • 13h 8m total length Description In this course, you will learn how to collect, import, and structure data (World Bank, IMF, WDI, Panel Data), understand types of data and preparing datasets for analysis, and more. Who Should Enroll? Undergraduate & Graduate Students in Economics, Finance, and Business PhD Scholars & Researchers preparing econometric models for publications Policy Analysts & Data Professionals applying econometrics in real-world decision-making By the End of This Course, you will be able to confidently analyze time series and panel data, detect econometric issues, apply advanced models, and present results like a professional researcher. Course Pricing Current price: €19.99 30-Day Money-Back Guarantee Full Lifetime Access Instructor Dr. Nasir Munir is an Assistant Professor at SZABIST University.
Master Econometrics from Basics to Advanced: OLS, ARDL, VAR, GARCH, Cointegration, Causality & Panel Data Analysis.
Description: The Center for Private Tutoring Policies at the Chung-Ang University Economic Research Institute invites applications for a full-time Postdoctoral Associate position funded by the Korea Research Foundation. We seek candidates with strong training in empirical methods, particularly in labor or public economics, although applicants from all fields of economics are encouraged to apply. The Postdoctoral Associate will collaborate on ongoing empirical research projects with Professors Changhui Kang, Sun Go, and Hoon Choi, and will also contribute to related administrative tasks. The position provides substantial time for independent research and is particularly suitable for recent Ph.D. recipients seeking a research-oriented appointment. There is no teaching requirement; however, optional teaching opportunities may be available with additional compensation. Duration and Compensation: The initial appointment is for one year, beginning in September 2026 or earlier, with the possibility of annual renewal through August 2029. The annual salary is 42 million KRW (inclusive of taxes, social insurance contributions, and retirement benefits). Qualifications: Applicants must have completed a Ph.D. in economics or a closely related field by the start date. While the Center’s primary research areas include labor economics, public economics, and econometrics, candidates from all areas of economics are welcome. Proficiency in Korean is required. Application Requirements: Cover letter Curriculum vitae Job market paper Research statement Academic transcripts Three letters of recommendation Application Deadline: Review of applications will begin immediately and continue on a rolling basis until the position is filled. Additional Information: Shortlisted candidates will be invited for online interviews. Contact Information: For inquiries, please contact: Wonho Song via the CAU CEPT Webpage: https://cept.cau.ac.kr/
Chung-Ang University invites applications for a Postdoctoral Associate position in Economics, specializing in Labor and Public Economics.
Microeconomics: The Power of Markets (Online Course)
Instructor: Rebecca Stein 5 modules Gain insight into a topic and learn the fundamentals. 4.7 (1,638 reviews) 2 weeks to complete at 10 hours a week Flexible schedule; Learn at your own pace 95% Most learners liked this course Skills you'll gain: Resource Allocation, Economics, Market Analysis, Policy Analysis, Supply And Demand, Market Dynamics, Decision Making, Tax, Consumer Behaviour, Cost Benefit Analysis Details to know Shareable certificate Add to your LinkedIn profile Assessments 18 assignments Taught in English 22 languages available Course Modules: The Concept of Scarcity: 2 hours to complete Specialization & Trade: 1 hour to complete Supply and Demand: 3 hours to complete Understanding Markets: Elasticities, Market Surplus, Efficiency, and Equity: 3 hours to complete When Government Intervenes: 3 hours to complete This course is an introduction to the microeconomic theory of markets: why we have them, how they work, what they accomplish. We will start with the concept of scarcity and how specialization according to comparative advantage helps us achieve more than we could alone. Next, we model a market using the tools of Supply and Demand and learn what well-working markets accomplish and what their limits are. We end by exploring the impact of government intervention on perfect markets. Examples are taken from everyday life, from goods and services that we all purchase and use. We will apply the theory to current events and policy debates through weekly exercises, empowering you to be an educated, critical thinker who can understand, analyze, and evaluate market outcomes. Instructor Instructor ratings: 4.8 (313 ratings) Rebecca Stein, University of Pennsylvania 3 Courses • 117,222 learners Offered by University of Pennsylvania Recommended Microeconomics: Foundations and Insights Microeconomics: When Markets Fail Course rating 1,638 reviews 5 stars: 79.42% 4 stars: 17.15% 3 stars: 2.62% 2 stars: 0.42% 1 star: 0.36%
Instructor: Rebecca Stein. Enroll for free.
Overview This graduate-level course provides an introduction into the macroeconomics of business dynamism. Taught by Petr Sedlacek (days 1-4) and Marek Ignaszak (day 5), students will learn about stylized facts and key theoretical concepts related to (i) static factor misallocation, (ii) firm dynamics over the business cycle and (iii) innovation and growth. Throughout the course, emphasis is given on practical knowledge for building, solving and analyzing macroeconomic models of business dynamism and on pointing out typical problems that researchers may run into. In addition, students will learn about available data sources and how to analyze them and how to use them to help discipline their models. Through hands-on computer sessions, participants will walk away with a portfolio of Matlab codes implementing a range of macroeconomic models with heterogeneous firms. Topics include: Static factor misallocation, firm dynamics over the business cycle Innovation and growth Handling (micro-)data, indirect inference and markup estimation
Lectures and Hands-on Computer Labs This summer school runs between August 17-21, 2026 and is virtual only. The course consists of lectures, guided Q&A and coding sessions. Participants can also submit their own work to a dedicated research workshop where up to 6 papers will be selected for presentation. More information: https://sites.google.com/view/firms4macro
Python and Statistics for Financial Analysis
Instructor: Xuhu Wan Course Details 4 modules Flexibility: 1 week at 10 hours a week, learn at your own pace Intermediate level Taught in English, available in 29 languages (AI Translation) Skills You'll Gain Data Visualization Financial Trading Statistical Analysis Data Import/Export Statistical Inference Regression Analysis Financial Data Financial Modeling Jupyter Model Evaluation Course Overview Python is now becoming the number 1 programming language for data science, especially in the financial industry. This course combines both Python coding and statistical concepts and applies them to analyze financial data, such as stock data. Objectives By the end of the course, you can achieve the following using Python: Import, pre-process, save, and visualize financial data into pandas Dataframe. Manipulate financial data by generating new variables using multiple columns. Apply key statistical concepts into financial contexts. Build and evaluate a trading model using linear regression. Course Structure Module 1: Visualizing and Munging Stock Data - 3 hours to complete Module 2: Random Variables and Distribution - 2 hours to complete Module 3: Sampling and Inference - 3 hours to complete Module 4: Linear Regression Models for Financial Analysis - 4 hours to complete Instructor Xuhu Wan from The Hong Kong University of Science and Technology. Additional Information There are 5 assignments included in this course. Enroll now for free!
Enroll in this course to gain essential skills in Python and statistics for financial analysis.
Hong Kong University of Science and Technology
MOE START Scheme (Early Career Awards) - Business, Communication and Design
At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in our education, while benefitting them with our talent supply and collaborative research achievements. The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with industry, learners bridge theoretical knowledge with practical application in and out of the classroom. Such active & authentic learning opportunities ensures graduates step into their careers with applicable skills and competence. In research, SIT faculty aims to bridge knowledge creation and utilisation. Our faculty collaborates closely with industry on translational research and innovation with focus on addressing pertinent industry challenges to impact businesses. The Singapore Teaching and Academic Research Talent (START) Scheme is co-funded by the Ministry of Education (MOE) and SIT to encourage and support outstanding young Singaporeans interested in pursuing an academic career at SIT. The Early Career Awards (ECA) are designed to support Singaporeans who have recently completed their postdoctoral training and prepare them for an academic career at SIT. This award aims to enhance the teaching capabilities of the recipient and help build a strong research portfolio. Eligibility and Selection Criteria Singapore Citizen Recently completed postdoctoral training Excellent academic record plus a high degree of proficiency and motivation for a research area that is strongly aligned with SIT’s supported areas Strong passion for teaching, research and an academic career Benefits Awardees may receive research grants to help build a competitive research portfolio. Upon completion of the award, awardees will be considered for Assistant Professorship. Awardees will also be assigned a faculty mentor for the duration of the scheme. Application Process Applications are open throughout the year. Applications received before 15 January 2026 will be considered for intake 2026. Interview by the respective clusters for shortlisted applicants will be conducted throughout the year. Final Interview by Panel for shortlisted applicants will take place from March to April 2026. Awards for intake 2026 will be finalised by July 2026. Supported Areas for START Business, Communication and Design Financial and Sustainability Accounting: The measurement, reporting, and analysis of an organisation's financial performance alongside its environmental, social, and governance (ESG) and carbon footprint. Integrating traditional financial accounting principles with sustainability considerations to provide stakeholders with a more comprehensive view of a company's long-term value creation. Meetings, Incentives, Conferences and Exhibitions (MICE): The planning, management, and execution of business events, corporate gatherings, and large-scale conferences. This field is a key segment of the tourism and hospitality industry, requiring expertise in event management, business tourism, marketing, logistics, and stakeholder engagement.
The Singapore Teaching and Academic Research Talent (START) Scheme is co-funded by the Ministry of Education (MOE) and SIT to encourage and support outstanding young Singaporeans interested in pursuing an academic career at SIT.
Course offered by: Stanford University In the first week we consider the problem of aggregating different agents' preferences, discussing voting rules and the challenges faced in collective decision making. We present some of the most important theoretical results in the area: notably, Arrow's Theorem, which proves that there is no "perfect" voting system, and also the Gibbard-Satterthwaite and Muller-Satterthwaite Theorems. We move on to consider the problem of making collective decisions when agents are self interested and can strategically misreport their preferences. We explain "mechanism design" -- a broad framework for designing interactions between self-interested agents -- and give some key theoretical results. Our third week focuses on the problem of designing mechanisms to maximize aggregate happiness across agents, and presents the powerful family of Vickrey-Clarke-Groves mechanisms. The course wraps up with a fourth week that considers the problem of allocating scarce resources among self-interested agents, and that provides an introduction to auction theory.
Popularized by movies such as "A Beautiful Mind", game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Over four weeks of lectures, this advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective decision making and voting systems), mechanism design, and auctions.
Introduction to Sustainable Finance (Online Course)
We will analyze approaches to sustainable finance, evaluate the correlation between risk and return, and gain insight into the vital features responsible for successfully meeting environmental and social initiatives. We will also explore and evaluate the role of the public sector in sustainable finance, and analyze disruptive trends and the innovations necessary to manage them. At the end of this course, you will complete a case study that outlines how your organization can create your own sustainable finance initiatives and how you can be a key player in meeting those goals. Become a Sustainable Finance expert with a purpose by learning to integrate people, profits, and the planet into the bottom line. Who this course is for: Finance professionals currently in the industry, as well as those seeking to break in, will gain insight into how to best invest capital in order to promote a sustainable future. Instructor: Dominick Mitchell Dominick Mitchell is a leading expert in sustainable finance, with a passion for finance, international development, and sustainability. He has been recognized as the Youth Entrepreneur of the Year and has written a book on the topic, Finance Made Sustainable. In his work, Dominick assists social enterprises with their sustainable finance initiatives, helping them to solve social problems through engagement with the private sector. He also manages WVÉS, a water-focused impact fund that supports investees in achieving both social and financial returns. Dominick's ultimate goal is to mobilize the private sector to become more sustainably conscious and inclusive on a global scale.
Finance is widely seen as an obstacle to a better world. Financial services make up one of the economy's most important and influential sectors globally. Although results vary, most estimates place the financial services sector at around 20-25% of the world economy. Finance fosters growth, promotes entrepreneurship, favors education, alleviates poverty, and reduces inequality. In this online course, you will learn the essential role the financial system plays in reaching the United Nations Sustainable Development Goals and creating a globally sustainable economy. Students will learn how the current financial systems run, the factors that impact them, and the circulation of capital.
(Oxford) Diploma : Macroeconomics/Behavioural Economics
Key details: 48 hours of lectures on macroeconomics Several workbooks on macroeconomics Hundreds of discussions on macroeconomics Regular updates via Educational Announcements Behavioural Economics The Instructor has macroeconomics textbooks on Amazon Five reasons to TAKE THIS COURSE right now: 1. You cannot lose - 30 day refund if you really really don't like the course BUT if you DO like it: a. updated lectures b. case studies based on very very current news items c. detailed responses to messages d. I constantly attempt to have a 'class atmosphere' e.g. throwing questions open to all e. regular Announcements that are not disguised sales ploys f. regular FREE access to numerous other courses offered by me 2. I am a lecturer/teacher in Economics by trade i.e. I teach full-time for a living. I have been Principal, Director of Studies and Head of Economics. (Oxford, UK) I have lectured in University, adult evening classes and also run over 50 seminars in the UK 3. I am/have been an Examiner for FIVE different examination boards 4. I have 100+ books on Amazon - many of them about business/economics 5. The success of my students has been featured on the BBC, Daily Telegraph, The Times and I have been featured on TV in 2 countries. MOTIVATION I make courses on Udemy primarily because I enjoy the process of causing learning. Many of my courses are to improve lives. One of the Economics courses is to raise money for charity. (100% of revenue goes to the charity) Fundamentally this course here, is about helping you. About the course Using ONLY aggregate demand and aggregate supply, this course explains the basics of macro economic policy. The lectures are fully supported by notes - often repeated to ensure learning - that may be copied and used for other studies. If you wish to understand more as to why governments cut/raise taxes, cut/raise government expenditure, how this impacts on inflation, unemployment and growth - then this is the course for you. Topics: Gross Domestic Product (GDP): Measures the total value of all goods and services produced over a specific time period within a nation's borders. Unemployment Rate: Indicates the percentage of the labour force that is jobless and actively seeking employment. Inflation: Describes the rate at which the general level of prices for goods and services is rising, and subsequently, purchasing power is falling. Monetary Policy: Involves the management of a nation's money supply and interest rates by its central bank to control inflation and stabilize currency. Fiscal Policy: Refers to the use of government spending and taxation to influence the economy. Interest Rates: The cost of borrowing money or the return for investing, which are critical in monetary policy and personal finance. Balance of Payments: A record of all economic transactions between residents of a country and the rest of the world in a given period. Exchange Rates: The value of one currency for the purpose of conversion to another, impacting international trade and investments. Economic Growth: The increase in the inflation-adjusted market value of the goods and services produced by an economy over time. Business Cycles: The upward and downward movements of GDP and other economic indicators over time, encompassing periods of expansion and contraction. Supply and Demand: The fundamental economic model of price determination in a market, showing how prices vary based on a balance between product availability and consumer desire. Aggregate Demand and Supply: The total demand for goods and services and total supply of goods and services within an economy at a given overall price level and in a given time period. Budget Deficits and Surplus: A budget deficit occurs when expenses exceed revenue, and a surplus occurs when revenue is higher than expenses. Public Debt: The total amount of money owed by the government to creditors, which can influence a country's fiscal policy and economic health. Trade Policies: Regulations and tariffs that a country applies to its imports and exports, affecting its balance of trade. Labour Markets: The supply and demand for labour, in which employees provide the supply and employers the demand. Capital Markets: Where savings and investments are channelled between suppliers who have capital and those who are in need of capital. Economic Indicators: Statistics that provide information about the overall health of the economy, such as GDP, unemployment rate, and inflation rate. Recessions: A period of temporary economic decline during which trade and industrial activity are reduced, generally identified by a fall in GDP in two successive quarters. Stagflation: A situation in which the inflation rate is high, the economic growth rate slows, and unemployment remains steadily high, presenting a dilemma for economic policy. The course is pitched at a beginner level and thus is IDEAL for anyone just starting an economics course or simply wants to understand macro-economic policy. The initial lectures are short - egg-timer size! - and, if you look at other egg-timer courses, you will know that if you have any questions then they will be answered very quickly. PLUS the course also includes Behavioural Economics. Behavioral economics melds psychology with economics, exploring why people sometimes make irrational decisions, and how their behaviour does not always follow the predictions of economic models. It challenges traditional assumptions of rational choice, investigating heuristics, biases, and framing effects that influence consumption, investment, and other economic activities. Who this course is for: Everyone interested in the world economies Anyone commencing a course in macro-economics 1st year Degree students Anyone who has an interest in understanding the basics of economic policy Non-specialists in Economics Beginners in Economics
Mastering Markets and Minds: An Interactive Journey Through Macroeconomics and Behavioural Economics. By Chris Sivewright / Oxford School of Learning.
Publish A Summary of Your Economics Research on INOMICS
We invite economists who are conducting or have conducted research to write a summary of their research and why it’s important, interesting, or unique in the field, and share that article with other economists via INOMICS. This “research summary” article can function as an extended abstract that will help other economists discover your work and learn more about your area of expertise. The tone can be similar to a relatively casual lunchtime conversation with colleagues who are trained in economics but unfamiliar with your work. Please note: We do not publish academic research. However, an article that describes your research and its importance to an audience of early-career economists and economics students is encouraged. Writing a research summary article on INOMICS can help your research reach a broader economist audience, inspire others’ research, broaden your network by reaching others in related areas, and add to your portfolio of written work. Our Goals for Your Submission: You are able to share your research topic and other factors related to it with economists on INOMICS. Economist readers of INOMICS can find interesting articles about recent or upcoming research in economics on the INOMICS Blog, in addition to what’s already been shared on the Blog. You are able to build your portfolio of written work, and develop your reputation among the thousands of readers who use INOMICS. You add to the library of interesting INOMICS content; readers benefit from learning about the interesting topic area. Less experienced readers additionally benefit from learning about your research, evaluation of economics issues, methodology or challenges overcome while researching, etc. Submission guidelines: Articles must be written in English Articles should be at least 1000 word and no more than 2500 words. Use a conversational but intelligent style - short introduction and conclusion, relatively short sentences, informal but intelligent tone (imagine you are speaking to a junior economist colleague or student at lunch hour). Additionally, please send a description of yourself and your academic and/or career credentials, no longer than 300 words, including a photo and a mention of your affiliated institution or your job title. Again, please note: We do not publish academic research. However, an article that describes your research and its importance to an audience of early-career economists and economics students is encouraged. Submission Process: Please send complete article drafts to: mailto:submissions@inomics.com. Articles that match these submission guidelines will be reviewed by a member of the INOMICS editorial board. If your article is of sufficient quality and adds to our content, we will contact you with initial edits, and begin the editing process with a member of our team. This may entail several rounds of edits. The final draft will be reviewed by another member of our editing team, and any last changes will be communicated with the author. Then, the article will be published on INOMICS, and you will be able to share it across your own channels as long as they are linked to the article’s “home” on INOMICS. Finally, contributors whose articles are published will receive a profile page on INOMICS and will have the opportunity to submit further articles for publication on INOMICS in the future. Contact: INOMICS Team submissions@inomics.com +49 30 2084712 50 Terms of Submission: By sending your submission, you guarantee that the submitted research summary article has not been published in part or in full elsewhere (note that this regards the summary written about the research, NOT the research itself). By sending your article submission you agree that INOMICS may publish your research summary article in-part or in-full, or publish an excerpt of your article in a larger content piece (for example a collection of opinions). If your research summary article is published in-full by INOMICS, you agree that in the event that you share or publish the article elsewhere, you will refer/link to INOMICS as the original location of publication for the research summary article (but NOT the research itself). You guarantee that you are the sole author(s) or that you have permission from your co-authors to publish this summary, and you confirm that you need no further permission from other co-authors, employers or funding bodies in order to grant copyright of the article to INOMICS.
Call for Submissions At INOMICS we aim to support economists, their studies, and their careers.