Several part-time research assistants (30% and 50%) for our Research Centre - Empirical Microeconomics
Location: Frankfurt am Main Position: Part-time, temporary position (2 years) Job ID: 2026_0541_02 Valuable work: your role with us Your role will be to support the academic work of the Research Centre in the field of empirical microeconomics. You will be involved in the Research Centre’s survey projects, in particular. You will be responsible for preparing and analysing microdata, especially on the behaviour and expectations of firms. As part of an international team, your work will centre on fundamental issues, with the resulting insights intended to provide a sound academic footing for the Deutsche Bundesbank’s decisions. You will have access to excellent IT facilities and first-class data resources, and will have the opportunity to interact with leading international researchers. Unique assets: your skills and qualifications Master’s degree or equivalent qualification in a degree programme with a quantitative focus (e.g. economics or statistics) Soon to be enrolled in or already pursuing a PhD programme in economics, business administration or statistics Very good command of English In addition, desirable: Working towards a specialisation in empirical microeconomics Good knowledge of mathematical/statistical applications, especially Stata (or R) Applied knowledge in using microdata, preferably survey data Strong analytical skills Organisational skills as well as the ability to work both independently and as part of a team Good communication skills Knowledge of German Valuable work, generously rewarded Remuneration that corresponds to pay grade E 13 of the wage agreement for the public sector (Tarifvertrag für den öffentlichen Dienst – TVöD) plus a bank allowance, international working environment, varied tasks, extensive training opportunities, support for your PhD/doctorate degree. New work Extensive options for working from home within Germany (generally up to 60% of total working hours), friendly and respectful working environment, flexible and predictable working hours, work-life balance. Additional benefits Free Deutschlandticket as a JobTicket, good transport links (bus and train), central location, workplace health management scheme, staff canteen. In your application, please state whether you have already started a doctoral project or which specific plans exist in this regard. Interested in enriching our team? Then we look forward to receiving your application. If you still have questions that you would like answered before you apply, simply get in touch with the contact person(s) listed below. For questions about the application process Ms Sandra Johanning, +49 (0)69 9566 38302 jobs@bundesbank.de For questions about the role Dr Pawel Smietanka, +49 (0)69 9566 11445 Pawel.Smietanka@bundesbank.de Dr Tobias Schmidt, +49 (0)69 9566 33730 Tobias.Schmidt@bundesbank.de Please use job ID 2026_0541_02 to apply by 07 September 2026 using our online application tool. Apply now Submission end: 07.09.2026 Diversity and equal opportunities are important to us. Where candidates are equally qualified for the position, preference will be given to applicants with a disability. The Bundesbank also promotes gender equality in the workplace, especially when filling leadership positions. We therefore particularly welcome applications from women. Application tips Please apply as early as possible and do not wait until the end of the application period. This shortens the processing time after the application deadline and simplifies technical processing. Make sure that your documents are complete (cover letter, CV and certificates). Attach proof of all internships and courses mentioned in your CV. Make sure that scanned documents are clearly legible. Name attached files so that they can be clearly assigned to your application (e.g. Mustermann_Zeugnis2024).
The Deutsche Bundesbank is a special type of bank. Together with the ECB and the other euro area central banks, we ensure a stable euro. To achieve this, as well as other central bank tasks, we need a diverse range of specialists in a wide array of areas in order for the institution to function. Join us and become part of a strong team of reliable and responsible individuals. Several part-time research assistants (30% and 50%) for our Research Centre
You will work on health economics research projects with a methodological focus on causal identification. You will independently carry out the preparation, validation and analysis of (large) datasets and support, where applicable, the planning, implementation and evaluation of economic (field) experiments. You will present the results at national and international conferences and prepare them for publication in academic journals. You will work closely with colleagues within collaborative research projects and support the communication of research findings to the public. Furthermore, teaching students (e.g., giving tutorials, thesis supervision, seminar organization) is a central component of the position. The possibility of pursuing a doctorate is given and this is expressly encouraged. Please see the job description for details. We look forward to your application!
🎓 Join a dynamic health economics research team! The Institute of Health Economics (IHE) at Leibniz University Hannover (www.ihe.uni-hannover.de) welcomes applications for the following position, starting on 01 January 2027: 👉 PhD Student in health economics 📊 75% | salary scale 13 TV-L | initially limited to two years
Visiting Assistant Professor of Economics
Description Located in the vibrant community of Walla Walla, WA, Whitman College is home to an intellectually diverse, dynamic, and supportive community of some 500 staff and faculty serving roughly 1,500 students from the local region and across the globe. With exceptional students, accomplished faculty and staff, and engaged alumni, Whitman College continues to build on its national reputation for academic excellence as one of the top undergraduate, liberal arts colleges in the country. The Economics Department at Whitman College is seeking candidates for a one-semester position with expertise in microeconomics, at the rank of Visiting Assistant Professor beginning January 2027. A Ph.D. is preferred upon starting the position. ABD candidates will be considered. The teaching load will be 3 courses in the Spring semester, including Principles of Microeconomics, and Applied Microeconomics in areas of the candidate’s specialty. Renewal of the position for a subsequent year is possible, pending funding and positive evaluation of teaching. Whitman College is committed to fostering an inclusive learning community that values diverse identities, experiences, and perspectives. In the cover letter, candidates should describe their interest in teaching undergraduates, majors as well as non-majors, at all levels of instruction. In doing so, candidates should address how their classroom and scholarly practices will advance equity and inclusion in the learning environment. To apply, go to https://apply.interfolio.com/192018. The online application will prompt you to upload all of the required materials: a letter of application; curriculum vitae; statement of teaching philosophy; and evidence of demonstrated or potential excellence in undergraduate instruction. The committee will solicit three letters of recommendation from applicants who reach the interview stage. Review of applications will begin September 21 and continue until the position is filled. Salary Range: $35,000 - $37,000 Whitman College offers a competitive benefits package that is designed to attract qualified candidates and retain talented employees. Full-time employees enjoy the following benefits: Medical/Dental/Vision Insurances; basic life, accidental death and dismemberment and long term disability insurances with the capability to elect additional voluntary coverage; 403(b) Defined Contribution Retirement Plan with a matching contribution after eligibility requirements are met; Tuition Remission – Dependent Children, after eligibility requirements; employee tuition waiver for two Whitman courses per semester; and an Employee Assistance Program. All FTE benefit eligibility can be found here. New faculty receive a relocation stipend for moving expenses based on the distance of relocation. Benefit offerings and eligibility described reflect current offerings and may be subject to change in accordance with College policies and plan documents. Application Process This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge. Equal Employment Opportunity Statement Whitman College is cultivating a community built on inclusion and belonging. We recognize the value of those who can offer historically underrepresented perspectives and encourage applications from those whose background, knowledge, and insights from lived experience can add to the college’s working and learning environment. Whitman College is an EEO employer. The college shall abide by the requirements of 41 CFR §§ 60-1.4(a), 60-300.5(a) and 60-741.5(a). These regulations prohibit discrimination against qualified individuals based on their status as protected veterans or individuals with disabilities, and prohibit discrimination against all individuals based on their race, color, religion, sex, or national origin.
Whitman College is seeking candidates for a one-semester position with expertise in microeconomics, at the rank of Visiting Assistant Professor beginning January 2027.
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)
Econometrics, Statistics and Quantitative Methods (JEL C)
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)
Ulrich Bindseil Joins Frankfurt School as Professor of Practice in Financial Infrastructure
Frankfurt School of Finance & Management has appointed Ulrich Bindseil as a Professor of Practice in Financial Infrastructure, effective 1 September 2026. Bindseil, a distinguished figure in central banking and financial market infrastructure, is transitioning from the Technische Universität Berlin to strengthen the Economics & Law Department at Frankfurt School. His expertise encompasses payment infrastructures, cross-border transactions, and innovations in currency forms—including stablecoins and central bank digital currencies. This appointment is set to enhance both research and teaching initiatives in the Centre for Digital Economics (C4DE) and the Centre for Central Banking. Markus Reisinger, Head of the Economics & Law Department, expressed enthusiasm about Bindseil’s arrival, underscoring his extensive background in the digital economy and financial technologies. "He is a perfect fit for our department and the Frankfurt School at large," Reisinger stated. Co-Pierre Georg, Director of the Centre for Digital Economics, remarked on the timely nature of Bindseil's expertise, noting it aligns with the ongoing transformation of financial market infrastructures driven by new technologies. Recognized for his international leadership in monetary policy and regulatory frameworks, Bindseil previously served in key positions at the European Central Bank (ECB) and is also a respected author in the field. "I am delighted to join Frankfurt School, where I can help bridge central banking with digital innovations," said Bindseil, highlighting the school’s unique positioning during this pivotal growth phase in financial technologies. Read the full press-release: frankfurt-school.de
Frankfurt School of Finance & Management welcomes Professor Ulrich Bindseil from Technische Universität Berlin to bolster its Centres for Digital Economics and Central Banking from September 1, 2026. Bindseil, an expert in central banking and financial infrastructures, will enhance research and education, focusing on payments and monetary innovations like stablecoins and digital currencies.
Frankfurt School of Finance and Management
2026 Top-Up Fanno & Foscolo Fellowships Target: Students and researchers Category: Research support Date: 20 July 2026 - 30 October 2026 This initiative aims to attract and retain outstanding PhD graduates in Economics or Finance by enabling academic institutions to offer internationally competitive compensation packages, consistently with UniCredit Foundation mission to invest in talent and promote academic excellence in Europe. Fellowship Details UniCredit Foundation will award 7 Top-Up fellowships (2 Marco Fanno and 5 Ugo Foscolo), intended for university departments or research institutes in Economics or Finance located in countries where the UniCredit Group operates. The fellowships consist in salary top-ups aimed at supporting and recognizing outstanding researchers. Total value: €150,000 for each fellowship Duration: 3 years Eligibility Criteria To be eligible, applicants must meet the following criteria: Be departments or research institutes in Economics, Finance, or related fields Be located in one of the Countries where UniCredit Group operates Recruit outstanding job market candidates through internationally recognized selection processes, including participation in global PhD job markets such as the US job market or equivalent European placement processes Apply rigorous and transparent evaluation methods aimed at appointing exceptional early-career scholars to post-doctoral or tenure-track positions. Key Dates Application deadline: 30 October 2026 Announcement of winners: by 11 December 2026 This initiative reflects UniCredit Foundation’s commitment to investing in young talent, supporting academic excellence, and fostering the next generation of economists and researchers. Download the announcement Apply Eligibility Who can apply? Applications can be submitted by departments or research institutes active in Economics, Finance, or related fields. Can individual candidates apply for a fellowship? No. The fellowship is awarded to the institution which subsequently appoints the selected recipient through its own recruitment process. Can research institute (rather than a university department) apply? Yes, both university departments and research institutes in eligible countries may apply, provided they operate in Economics, Finance, or related fields and satisfy the eligibility requirements. Which countries are eligible for Fellowships? Eligible institutions must be in the countries where UniCredit operates: Austria; Bosnia and Herzegovina; Bulgaria; Croatia; Czech Republic; Germany; Hungary; Italy; Poland; Romania; Serbia; Slovakia; Slovenia. Is the United Kingdom eligible? No. The United Kingdom is not included among the eligible countries. Can institutions that received a fellowship in previous years apply again? The applicants have not been awarded either the Fanno Top-up or the Foscolo Top-up fellowship in the previous year (i.e. 2025). Contact Information For further information email: info@unicreditfoundation.org
UniCredit Foundation announces the opening of the Top-Up Fanno & Foscolo fellowships competition for students and researchers in Economics and Finance.
Postdoctoral Research Associate, PIIRS Postdoctoral Fellowship Program
Appointments will be made at the rank of Postdoctoral Research Associate and are for one year (12 months) with the possibility of renewal pending satisfactory performance and continued funding. Postdoctoral Research Associates are expected to be in residence at Princeton or the local vicinity for the entire academic year or demonstrate to the program’s satisfaction the ability to be on campus on a daily basis and on short notice in order to fulfill responsibilities relating to in-person participation. The position requires Postdoctoral Research Associates to be on campus at least four days per week. Leveraging Princeton's scholarly resources, fellows will focus on research, expand their intellectual horizons, and prepare work for publication. They will have biweekly meetings with the faculty director to share their work, and monthly meetings with faculty fellows from various social sciences to present their work and learn from others. Fellows are also encouraged to engage with colleagues and attend departmental seminars. Applicants must demonstrate outstanding scholarly achievement and promise. To be eligible, applicants generally cannot have more than two years of postdoctoral experience prior to the start of the appointment, at the beginning of the academic year on September 1, 2027. The postdoctoral selection will be made based on the strength of the candidates' scholarly record; the promise of the proposed research; and the ability to contribute to the intellectual life of the postdoctoral program (with interest in connecting with other PIIRS and Princeton departments on campus). In addition to a competitive salary and benefits, the program will provide the Fellow with the opportunity to host a small, pre-publication, book workshop; and a research fund of $4,000 per year. The program will also provide shared office space, and a laptop computer. Please apply at: https://apply.interfolio.com/189215. Further information can be found at https://piirs.princeton.edu/funding-fellowships/piirs-postdoctoral-fellows. This position is subject to the University's background check policy. The work location for this position is in-person on campus at Princeton University. Position is not eligible for sponsorship of an H-1B visa requiring consular processing; other visa sponsorships (including H-1B visas not requiring consular processing) may be available, as appropriate. Application Instructions Applications are due by September 15, 2026 (11:59 p.m. EST). The following application items should be uploaded by the applicant: *Cover letter *Curriculum vitae *Transcripts *Research Proposal indicating plans for two-year postdoc (maximum 5 pages double-spaced) *Dissertation abstract (including Table of Contents) *Writing sample: one chapter of the dissertation or one published article related to dissertation topic. *Document confirming either that you have completed all requirements for the PhD degree or a letter signed by your dissertation advisor indicating that you will complete the PhD by the start date of the fellowship. *The names and email addresses of three referees, who will be contacted automatically by the online application system with an invitation to upload their letter of recommendation to the system by the application deadline. (**Please note: all letters of reference should be submitted by your referees before September 15, 2026. deadline. **) Equal Employment Opportunity Statement Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law.
The Princeton Institute for International and Regional Studies (PIIRS) at Princeton University is pleased to announce the call for applications to the PIIRS Postdoctoral Fellowship Program for the 2027-28 academic year. As a leading global institution in interdisciplinary research on international issues, PIIRS is dedicated to advancing innovative scholarship that addresses the world's most pressing challenges. The PIIRS Postdoctoral Fellows Program is integral to that mission. We will award up to four postdoctoral fellowships to our 2027-28 cohort. PIIRS seeks recent PhDs in the Social Sciences who have demonstrated exceptional scholarship, congruent with the Institute's intellectual focus, that simultaneously advances theoretical debates in their disciplinary field; creatively speaks to and engages with a multidisciplinary audience; and deepens substantive regional knowledge of specific places.
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.
Public Economics & Economic Policy (JEL H)
Economic Development, Innovation and Growth (JEL O)
Agricultural and Environmental Economics (JEL Q)
ICF is one of the UK's leading public policy consultancies, supporting government departments, regulators and public bodies to develop evidence-based policy and make better decisions. Our economists work alongside policy researchers, evaluators and subject matter experts to provide robust economic analysis that informs policy development, appraisal, evaluation and investment decisions. Our economics team delivers economic evaluation, value for money (VfM) analysis, cost-benefit analysis, impact assessment, economic appraisal, business case development and bespoke economic analysis. We work on issues at the top of today’s policy agenda, including economic growth, energy, telecoms, security, the impact of new technologies, and better regulation. Economic analysis in support of assignments for one or more of DESNZ, BIST (DBT), DCMS and Defra will be a particular focus of your work, alongside ICF's wider public sector portfolio. About the role The Lead Consultant (Economist) role is required to strengthen ICF's senior economic leadership and technical delivery capability in response to sustained demand for economic analysis across evaluation and advisory projects. The role will help ensure that economics expertise is embedded across evaluations and wider analytical work. What you'll do From day one, you will have the opportunity to help win, manage and deliver a diverse range of economic analyses for UK public sector clients. You will be a core member of our growing and collegiate team and work in an international environment in which more than 30 nationalities are represented. You will be contributing innovative ideas and practices to the business, helping achieve excellent, cutting-edge economic analysis and expanding ICF’s work into new areas. You will have the chance to develop your knowledge and skills through excellent training and development opportunities, including via ICF’s peer-to-peer communities of practice. Your main responsibilities will be to: Lead complex economic evaluation and advisory projects. Provide technical quality assurance. Lead bids and strategic client relationships. Develop new economics opportunities. Mentor economists and grow capability. What you'll need to succeed You will thrive in a fast-paced environment. You will have a wide range of interests and be able to develop a nuanced understanding of complex economic issues. You will have a proven track record in leading consulting assignments, economic/VfM evaluations, and/or other economic analysis projects. You will be self-motivated and able to manage a varied workload to deadlines without compromising quality. Your experience could have been gained in consulting, government, a regulatory agency, academia, or the private sector. You will have: Degree in economics or quantitative discipline. At least ten years' relevant experience. Recognised technical leadership. Strong business development and people management experience. Desirable experience Economic evaluation, value for money analysis, appraisal or cost-benefit analysis. HM Treasury Green Book, Magenta Book and Aqua Book. Economic modelling and quantitative analysis. Experience in one or more of DESNZ, DBT. About us: Working at ICF means applying a passion for meaningful work with intellectual rigor to help solve the leading issues of our day. Smart, compassionate, innovative, committed, ICF employees tackle unprecedented challenges to benefit people, businesses, and governments around the globe. We believe in collaboration, mutual respect, open communication, and opportunity for growth. We can only solve the world's toughest challenges by building an inclusive workplace that allows everyone to thrive. We are committed to creating a culture where we embrace our differences in ideas and identities. Together, our employees are empowered to share their expertise and collaborate with others to achieve personal and professional goals. The benefits of joining ICF: Our people at ICF are our most important asset, so we invest in them from the moment they arrive. When you join our team, you’ll have access to a vast array of benefits to help you live your life well. We offer a hybrid working policy, which will provide you with the flexibility to collaborate in the office, as well as in the comfort of your own home, ensuring you are able to successfully deliver the requirements of your role. To support you, our employee wellbeing hub is designed to provide highly personalised support across a comprehensive range of wellbeing issues, such as mind, body, finances, community, career programs and HR support. We enjoy celebrating success, which is why we have a competitive recognition program called ‘You Matter’, which awards points as a ‘thank you’ for your work achievements. These can be spent on a large variety of high-quality items, as well as online or high-street vouchers, all with zero tax payable by the employee. ICF also offers a range of competitive benefits, which include: Single Private Medical Insurance cover with no restrictions on existing conditions. Dental insurance and an online GP service. 25 days annual leave, plus UK bank holidays (annual leave increases with years of service). Pension scheme with 5% of salary employer contribution. Life assurance paying 4x annual salary and Group Income Protection paying 66% of salary for up to 5 years if you are off work on long-term sick. Enhanced parental leave policies, enhanced maternity, paternity, adoption, and shared parental pay. Candidate AI Usage Policy At ICF, we are committed to ensuring a fair and equitable interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate or assist with responses during interviews (whether in-person or virtual) is not permitted. This policy is in place to maintain the integrity and authenticity of the interview process. However, we understand that some candidates may require accommodations that involve the use of AI. If such an accommodation is needed, candidates are instructed to contact us in advance at candidateaccommodation@icf.com. We are dedicated to providing the necessary support to ensure that all candidates have an equal opportunity to succeed.
We are looking for a Lead Consultant (Economist) to join ICF's growing economics function within our UK Policy Research, Evaluation and Strategy (PRES) team.We are looking for a Lead Consultant (Economist) to join ICF's growing economics function within our UK Policy Research, Evaluation and Strategy (PRES) team.
Doctoral Researcher in Economic Theory, Empirical Microeconomics, International, Experimental or Behavioural Economics
Main Tasks Research and teaching in the area of Economic Theory, Empirical Microeconomics, Econometrics, Industrial Organisation, Behavioural/ Experimental Economics, or International Economics Your Profile A completed scientific university education (M.Sc. / M.A. / Diploma / Magister) in Economics or in a related quantitative-mathematical discipline with outstanding grades Talented and motivated applicants with a strong interest in Economic Theory and Policy, Industrial Organization, Behavioural Economics, International Economics, Empirical Economics or Econometrics Very good knowledge of theoretical and empirical economic methods An excellent command of the English language Our Offer The pay scale grouping will be, depending on the personal qualification of the applicant, up to pay grade 13 TV-L. Heinrich Heine University Düsseldorf aims at increasing the percentage of female employees. Applications from women will therefore be given preference in cases of equal aptitude, ability and professional achievements, unless there are exceptional reasons for choosing another applicant. Applications from suitably qualified severely disabled persons or disabled persons regarded as being of equal status according to Book IX of the German Social Code (SGB – Soziales Gesetzbuch) are encouraged. The employment is initially limited to a period of 2 years with an option for prolongation by two additional years if the applicant reaches the targets agreed upon with his/her supervisor during the hiring process. It is a qualification position in the sense of the Act on Fixed-Term Employment Contracts in Academia (Wissenschaftszeitvertragsgesetz-WissZeitVG), which is to promote the scientific qualification of the employee. The qualification target of this position is a PhD. The DGSE’s specific focus on Competition Economics and Regulatory Issues in research and teaching and the close links of DICE to competition policy practice provide an excellent platform for the education of doctoral students. Besides Competition Economics and Policy, we supervise other research topics in Applied Microeconomics, such as Behavioural Economics, Experimental Economics, International Economics and Econometrics. Doctoral students participate in courses and seminars which focus on the topics of the graduate programme. Our Benefits Company pension grant Good transport connection Free parking Flexitime Working from home International work Union rates Payment of capital-forming benefits About us Detailed information about DGSE and DICE is available at https://www.dice.hhu.de/phd-programme. Your contact person in case of questions regarding the position is Prof. Dr. Hans-Theo Normann; email: normann@dice.hhu.de. Please send your application by 16 September 2026. Heinrich Heine University upholds the principle of "Excellence through Diversity". It has signed the "Diversity Charter" and successfully participated in the Stifterverband's audit "Shaping Diversity". It is certified as a family-friendly university and has set itself the goal of promoting diversity among its staff. Applications from people of all genders are expressly welcome. Applications from women will be given preferential consideration in accordance with the State Equal Opportunities Act. The application of severely disabled persons and persons with equivalent disabilities is also welcome. In order for a severe disability or equality to be taken into account, please provide evidence of this with suitable documents. Contact Prof. Dr. Hans-Theo Normann Email: normann@dice.hhu.de
The Düsseldorf Graduate School of Economics (DGSE) and the Düsseldorf Institute for Competition Economics (DICE) are inviting applications for a position as Doctoral Researcher in Doctoral Researcher in Economic Theory, Empirical Microeconomics, International, Experimental or Behavioural Economics (m/f/d) (75% TV-L EG13).
Düsseldorf Institute for Competition Economics (DICE) - University of Düsseldorf
Two Tenure-Track Assistant Professor Positions in Econometrics or Statistics/Economic Statistics - University of Verona
The positions offer a gross annual salary of approximately €50,000. National tax benefits may be available to researchers moving to Italy from academic positions abroad. Research funds covering expenses such as travel, conference fees and submission fees are allocated annually on the basis of research performance, including publications and research projects. The positions offer a tenure-track pathway to Associate Professor: researchers who meet the scientific qualification and productivity requirements established by Italian law and receive a positive evaluation by the University are appointed as Associate Professors. The positions come with a teaching load of up to 60 hours per year during the first three years and up to 120 hours per year from the fourth year onwards. The Department offers courses taught in both Italian and English at all academic levels. Candidates are expected to have a strong research track record and the ability to attract competitive research funding at both national and international levels. Interested applicants are requested to submit their expression of interest to hiring@dse.univr.it, including a complete curriculum vitae and a selection of three representative publications. The deadline for submissions is September 30, 2026. Recognized by the Italian Ministry of University and Research as one of the “Departments of Excellence” for the period 2023-2027, the Department of Economics offers a vibrant research environment at the Santa Marta campus in Verona. The Department has a young faculty with a good gender balance and pursues an active recruitment policy aimed at attracting talented scholars from Italy and abroad, further strengthening its dynamic and inclusive academic environment. Please note that this expression of interest does not constitute a formal job vacancy announcement.
The Department of Economics at the University of Verona (Italy) invites expressions of interest for two six-year tenure-track Assistant Professor (RTT) positions in Econometrics and Statistics/Economic Statistics.
Department of Economics, University of Verona
Doctoral Researcher (Deep Learning for High-Frequency Financial Data Modeling)
Tampere University and Tampere University of Applied Sciences create a unique environment for multidisciplinary, inspirational and high-impact research and education. Our university community has its competitive edges in technology, health and society. www.tuni.fi/en. We are looking for a Doctoral Researcher to work on deep learning methodologies for high-frequency financial data modeling. The selected applicant will be member of the Computational Intelligence group led by Professor Alexandros Iosifidis, and closely collaborate with the Financial Data Science group led by Professor Juho Kanniainen, at the Unit of Computing Sciences of Tampere University. The position is full-time and will be filled as soon as possible for a fixed-term period of four years. The workplace is located at Hervanta Campus of Tampere University, Finland. JOB DESCRIPTION The Doctoral Researcher will conduct research on designing, implementing, and proposing new Machine/Deep Learning methods and models for Financial Markets. Topics of interest include generative models for financial data synthesis and/or forecasting, trustworthy financial data predictions, world models for financial markets, system-II predictive models, and multi-model multi-asset routing mechanisms for financial predictions. The project combines real-world financial data analysis with hands-on design and development of Machine Learning models that push the state-of-the-art, with room to shape the direction of research based on the researcher’s interests. Writing high-level scientific publications is an essential part of the research. In addition to the research towards the doctoral dissertation, the duties of the researcher may include some teaching tasks (5-10%) or other small faculty tasks that support the studies. REQUIREMENTS A completed master's degree in computer science, computer engineering, or another related field. Strong knowledge of Machine Learning theory and methods, and related Deep Learning approaches, with emphasis on fundamental concepts and techniques. Ability to conduct systematic scientific research related to the design of Deep Learning methods and models. A curious mind and solid skills in critical thinking and problem solving. Knowledge and experience of Generative AI focusing on the methodologies and their applications in different types of data. Knowledge of financial data analysis, especially Limit Order Book data, is considered an advantage. Excellent communication skills in English, and ability to collaborate in multidisciplinary teams. Ability to write research papers in high-quality peer-reviewed journals or conferences in the field of Machine Learning and/or Finance. You need to have completed a relevant Master’s degree before the starting date of employment. The selected person will need to apply for and be granted a study right for a doctoral degree in the doctoral programme of Computing and Electrical Engineering at Tampere University. Please visit the admission web page of the doctoral programme of Computing and Electrical Engineering for more information on eligibility requirements of the doctoral programme. Please note that if you have not completed a university degree in Finland, an official English language certificate will also be required for the admission to the doctoral programme. The accepted English language certificates and their minimum requirements, as well as exemptions regarding the certificates, are available here. WE OFFER The full-time position will be filled for a fixed-term period of four years. The planned starting date is December 1st, 2026 or as mutually agreed by both parties. A trial period of six (6) months applies to all our new employees. The salary will be based on both the job requirements and the employee’s personal performance in accordance with the Finnish University Salary System. According to the criteria applied to teaching and research staff, the position of a Doctoral Researcher is placed on level 2-4 of the job requirements scale. A typical starting salary for a Doctoral Researcher is approximately 2770-2900 EUR/month. The salary increases based on experience and the progress of doctoral studies. We are inviting you to be a part of a vibrant, active and truly international research community. Our Data Science Research Centre is formed by experts actively contributing to different aspects of Artificial Intelligence, especially in Fundamental and Applied Machine Learning. Moreover, both Professor Alexandros Iosifidis and Professor Juho Kanniainen are Associated Faculty of the newly established ELLIS Institute Finland which is a world-class research hub in AI and machine learning. We value interdisciplinarity, as it allows new perspectives and ideas to solve research problems and pursue novel research findings in human-centered interactive technologies. We are strongly committed to the highest level of scientific research and the provision of high-quality doctoral education. As a member of staff at Tampere University, you will enjoy a range of competitive benefits, such as occupational health care services, flexible work schedule, versatile research infrastructure, modern teaching facilities and a safe and inviting campus area as well as a personal fund to spend on sports and cultural activities in your free time. Please read more about working at Tampere University. You can also find more information about us and working and living Tampere by watching our video: Tampere Higher Education Community - our academic playground. Tampere is one of the major academic hubs in the Nordic countries and offers a dynamic living environment. Tampere region is one of Finland´s three most rapidly growing urban areas and home to a vibrant knowledge-intensive entrepreneurial community. The city is an industrial powerhouse that enjoys a rich cultural scene and a reputation as a centre of Finland’s information society. HOW TO APPLY Please submit your application through our online recruitment system. The closing date for applications is Monday, October 5th, 2026 (23:59:00 EEST / UTC +3). Please write your application and all the accompanying documentation in English and attach them in PDF format. Please attach only the following documents to your application: Curriculum vitae. Free-form application letter including 1) a brief statement of how you meet the criteria for this position, and 2) description of your research interests in the scope of the Doctoral Researcher position described above. This letter should be max. 3 pages long, font 12. PDF copies of your Master’s and Bachelor’s degree certificates, including transcripts of all university records (in Finnish or English). Other relevant documents that support your application, e.g. your Master’s thesis, the most relevant publications regarding the call (max. 2), and a list of referees. For more information, please contact: Professor Alexandros Iosifidis, alexandros.iosifidis@tuni.fi Professor Juho Kanniainen, juho.kanniainen@tuni.fi
Join Tampere University as a Doctoral Researcher focusing on deep learning methodologies for financial data modeling. This full-time position has a starting date of December 1st, 2026.
Postdoctoral Researcher in Economic Theory, Empirical Microeconomics, or in Behavioural/ Experimental Economics
Main tasks research in the area of Economic Theory, Empirical Microeconomics or Behavioural/ Experimental Economics teaching in the Economics programmes of the faculty Your Profile a completed scientific university education (M.Sc./ M.A./ Diploma/ Magister) in the field of Economics or a related discipline with outstanding grades PhD in the relevant field very good knowledge of theoretical and empirical economic methods excellent command of the English language Our Offer The pay scale grouping will be, depending on the personal qualification of the applicant, up to pay grade 13 TV-L. In principle, the employment can also take place part-time, if no compelling official reasons are opposed in an individual case. The employment is limited to a period of three years, starting on January 1st, 2027. It is a qualification position in the sense of the Act on Fixed-Term Employment Contracts in Academia (Wissenschaftszeitvertragsgesetz-WissZeitVG), which is to promote the scientific qualification of the employee. Our Benefits Company pension grant Good transport connection Free parking Flexitime Working from home International work Union rates Part-time possible Payment of capital-forming benefits About us Heinrich Heine University Düsseldorf aims at increasing the percentage of employed women. Applications from women will therefore be given preference in cases of equal aptitude, ability and professional achievements unless there are exceptional reasons for choosing another applicant. Heinrich Heine University strongly supports the principle of excellence through diversity. Heinrich Heine University signed the “Diversity Charter” and successfully participated in the Stifterverband‘s “Shaping Diversity” audit. It is certified as a family-friendly university and has set itself the goal of promoting the diversity of its employees. Applications from suitably qualified severely disabled persons or disabled persons regarded as being of equal status according to Book IX of the German Social Code (SGB – Soziales Gesetzbuch) are encouraged. Detailed information about DICE is available at https://www.dice.hhu.de. Your contact person in case of questions regarding the position is Prof. Dr. Joel Stiebale; email: stiebale@dice.hhu.de. Interviews may also be conducted virtually via Cisco WebEx. Please send your application by September 23th, 2026. Heinrich Heine University upholds the principle of "Excellence through Diversity". It has signed the "Diversity Charter" and successfully participated in the Stifterverband's audit "Shaping Diversity". It is certified as a family-friendly university and has set itself the goal of promoting diversity among its staff. Applications from people of all genders are expressly welcome. Applications from women will be given preferential consideration in accordance with the State Equal Opportunities Act. The application of severely disabled persons and persons with equivalent disabilities is also welcome. In order for a severe disability or equality to be taken into account, please provide evidence of this with suitable documents. Contact Prof. Dr. Joel Stiebale stiebale@dice.hhu.de
The Faculty of Business Administration and Economics of Heinrich Heine University Düsseldorf and the Düsseldorf Institute for Competition Economics (DICE) are inviting applications for a position as Postdoctoral Researcher in Economic Theory, or in Empirical Microeconomics, or in Behavioural/ Experimental Economics (m/f/d).
Junior Professorship (W1) with Tenure Track to W2 ”Management of Bio-based Value Chains“
Martin Luther University Halle-Wittenberg's aim in offering the junior professorship with tenure track is to enable young academics with excellent prospects to become independent at an early stage of their career and to offer them long-term career prospects. The junior professorship with tenure track is aimed at academics in the early career phase. At the Faculty of Natural Sciences III, Institute of Agricultural and Nutritional Sciences (IAEW) at Martin Luther University Halle-Wittenberg, the following position is to be filled: Junior Professorship (W1) with Tenure Track to W2 ”Management of Bio-based Value Chains“ We are seeking a candidate with in-depth knowledge and an outstanding doctorate in agricultural economics or related disciplines. The candidate should be involved in research and teaching in the field of demand-oriented management of bio-based value chains and after completing the tenure track, will represent the entire broad spectrum of the subject area in research and teaching. Bio-based value chains form the basis of modern sustainable agriculture. Appropriate management of bio-based value chains should reduce negative social externalities and promote positive economic, ecological and social development, at the same time being subject to dynamic change. On the one hand, there are technological innovations, e.g. in the substitution of fossil raw materials in the bioeconomy, the cascade use of plant and animal products, and the efficient use of resources through circular economy. On the other hand, change arises from organisational innovations within value chains, for example through digitised and automated business processes, as well as digital and platform-based transactions between stakeholders. The junior professor therefore will focus on examining the impact of innovations on businesses, end consumers and the agri-environmental system across the value chain – always from a business management and strategic planning perspective. Relevant areas of research include but are not limited to: new customer-centric business models, risk management and corporate resilience in the face of increasingly volatile environmental factors, relationship marketing, cross-functional quality management, corporate social responsibility, consumer and societal acceptance of business models and the promotion of positive externalities. Methodologically, one can employ both quantitative and qualitative methods of business analysis and planning, agricultural economic modelling as well as life-cycle assessment and sustainability metrics for estimating environmental impacts. The research focus of the professor offers a wide range of opportunities for cooperation with other professorships at the IAEW and the Faculty. Examples are joint research on new concepts for coupled plant and animal production to replace fossil raw materials and energy sources or to assess environmental impacts. Links are also available to existing and future interdisciplinary joint projects (e.g. DiP – https://www.dip-sachsen-anhalt.de and JTC – https://jtc.uni-halle.de) focusing on innovation and the design of socioeconomic agricultural systems. Research should be compatible with the university's profile areas, in particular ‘transformation’ and ‘sustainability’. Networking is highly desired with the natural and nutritional sciences within the university and with socio-economic institutions, such as the Leibniz Institute for Agricultural Development in Transition Economies (IAMO). A willingness to cooperate in related fields is expected with the aim of contributing to the research output and third-party funding of the IAEW. Experience in independent scientific publishing must be demonstrated through relevant international publications. Experience in acquiring third-party funding is an advantage. The focus of the teaching offered by the professor should be on management in the bachelor's and master's programmes at the IAEW, e.g. on the management of value-chains, marketing, and corporate social responsibility. Experience in teaching and supervising academic theses is expected. The willingness and ability to teach in German and English is a prerequisite. The faculty places great emphasis on committed and innovative teaching. Applicants are expected to demonstrate a commitment to delivering attractive teaching through innovative ideas. Experience in the development and design of degree programs is desirable. In addition, a cooperative, team-oriented approach to work and strong communication skills are desirable. Participation is also required in academic self-administration and a willingness to take on leadership responsibilities at Martin Luther University Halle-Wittenberg and to improve personal development. Further duties are specified in Section 34 of the Saxony-Anhalt Higher Education Act. Applicants must fulfil the requirements of being appointed according to Section 40 of the Saxony-Anhalt State Law of Universities. In particular, the prerequisites for employment are a completed university degree, pedagogical ability and a particular aptitude for scientific work, which is usually demonstrated by the outstanding quality of a doctorate. As a rule, the time period between the final doctoral degree examination and the application for this junior professorship should not exceed six years (family-related reductions in working hours are taken into account appropriately when assessing the academic age). Junior professorships are filled on the basis of a temporary civil service contract, initially for a period of three years. The position shall be renewed for a further three years conditional upon a positive mid-term evaluation. Upon a positive tenure evaluation, and without a new vacancy announcement, there is a transition to a permanent W2 professorship. If the general legal requirements are met, this transition includes appointment through a lifelong civil servant relationship, or alternatively, transfer to an indefinite private-law employment relationship. The Martin Luther University Halle-Wittenberg is committed to diversity and aims to create an inclusive environment where our staff and students feel valued and inspired. In particular, we aim to increase the proportion of women appointed as permanent staff; therefore, appropriately qualified female candidates are strongly encouraged to apply for this position. The Martin Luther University Halle-Wittenberg strives to provide an environment compatible with work-life balance and has been certified as a family-friendly university since 2009. Applications from candidates with disabilities are particularly welcome, and will be given preference in the event of equivalent qualification. Applications are accepted only electronically via the Appointment Portal of Martin Luther University Halle-Wittenberg at: https://berufungsportal.uni-halle.de/ before 18.10.2026. With the application the following information must be submitted: a cover letter, a detailed curriculum vitae should be uploaded including the candidate’s scientific career and qualifications, academic certificates, a list of publications and successful third-party funding as well as a teaching record including evaluations. Please include a statement outlining future research plans, with a brief description of your research project for the next six years of the junior professorship in relation to MLU as a research institution (maximum 2 pages), as well as a teaching plan (1–2 pages). For further subject-related information, please contact Prof. Dr. Jan-Henning Feil (Tel.: +49 345 55 22361, e-mail: jan-henning.feil@landw.uni-halle.de). Please note: Applications to his email address will not be considered. If there are any questions about the appointment portal, please contact the Dean of the Faculty of Natural Sciences III and Chair of the Appointments Committee, Prof. Dr. Matthias Müller-Hannemann, (e-mail: dekanat@natfak3.uni-halle.de). The call for applications is subject to possible budgetary restrictions. Please note that the University is unfortunately unable to reimburse costs associated with the application.
We are seeking a candidate with in-depth knowledge and an outstanding doctorate in agricultural economics or related disciplines.
Martin-Luther-Universität Halle-Wittenberg
Two Tenure-Track Assistant Professorships (2 x 100%) - Specialisation: Empirical Management Research
The two professorships are in empirical management research, with a particular interest in the opportunities and challenges associated with digital transformation, data-driven decision-making, and the increasing use of artificial intelligence in organisations and the wider economy. Relevant research areas include decision research, human resource management, managerial accounting, innovation and digitisation, industrial organisation, information systems, data science for business, and related areas of empirical management research. Methodologically, the research profiles should be grounded in quantitative empirical approaches, including field or laboratory experiments and/or the analysis of organisational, personnel, or other data sources using modern quantitative methods. Successful candidates fit well with the faculty’s existing research cluster in applied microeconomics and econometrics and contribute to collaboration and exchange across research groups. Ideal candidates therefore also build on perspectives from microeconomics and address topics of societal relevance related to the existing research cluster. Your responsibilities Conducting methodologically rigorous and societally relevant empirical management research, guided by open science practices. Publishing regularly in high-quality scientific journals in the field. Actively participating in relevant national and international workshops and conferences. Supervising Bachelor’s, Master’s, and doctoral theses. Acquiring competitive third-party funding from institutions such as the Swiss National Science Foundation and other Swiss or international funding bodies. Establishing research and teaching cooperations with other universities and with other faculties at UniDistance Suisse. Teaching in the faculty’s Bachelor programmes (in German, French, and/or English) and/or in the Master’s and Doctoral programmes (in English). Developing and implementing innovative teaching methods, with a particular focus on e-learning and digital education. Actively supporting the further development of the faculty, the faculty’s study programmes, and the range of courses offered by the faculty. Contributing to and further developing continuing education courses and the faculty’s services targeted at a broader public. Your profile Doctoral degree and research experience in a relevant field. Expertise in the application of quantitative empirical research approaches, including field or laboratory experiments and/or the analysis of organisational, personnel, or other data sources using modern quantitative methods. A promising research agenda in empirical management research, with a specialisation that complements the faculty’s existing research cluster and demonstrates integration into an international research network. A promising research and publication pipeline, ideally including first publications in high-quality journals in the field. Experience in acquiring, or strong potential to acquire, competitive third-party research funding. Willingness and ability to develop effective online teaching modules in areas related to the candidate’s specialisation; teaching experience, particularly in blended learning, is an advantage. Proficiency in English and active knowledge of either German or French is required, together with passive knowledge of the other language, as well as the ability and willingness to teach in German or French within one year. We offer Tenure-track assistant professor positions, with the possibility of promotion to a permanent position, subject to a positive tenure evaluation. Support and dedicated funding to establish and develop a research and teaching team. A dynamic academic environment within a research-intensive institution, characterised by strong scientific expertise, interdisciplinary collaboration, and a growing international profile. A high degree of autonomy and responsibility, offering substantial scope for initiative, ownership, and professional development within a dynamic and evolving institutional context. The opportunity to contribute to and shape innovative approaches to online teaching and distance education, supported by comprehensive training and technical pedagogical support. An inspiring working environment at our campus in Brig, located close to the historic town centre and the Swiss Federal Railways (SBB) station, with excellent rail connections across Switzerland and Europe as well as into the surrounding mountain region, offering a high quality of life. Attractive employment conditions, including modern working arrangements, competitive social benefits, and access to a wide range of continuing education and professional development opportunities. A strong institutional commitment to equity, diversity, inclusion, and accessibility. We particularly encourage applications from individuals who are underrepresented in academia and from candidates with diverse backgrounds, experiences, and career paths. How to apply We look forward to receiving your full application in one PDF document no later than 13 September 2026 at the following email address: jobs@unidistance.ch. Your application should include the following elements: Letter of motivation, CV (including a list of publications, working papers, and/or current research projects), teaching experience, teaching evaluations (if available), list of third-party funds (if applicable), research statement (maximum 2 pages), teaching statement (maximum 2 pages), and the names and contacts of two to four references who are ready to supply a reference letter upon request. For administrative questions regarding the procedure, please contact Mr Patrick Constantin, Head of Human Resources (patrick.constantin@unidistance.ch). For academic questions, please contact Prof. Manuel Grieder, Dean of the Faculty (manuel.grieder@unidistance.ch).
UniDistance Suisse offers fully online university degree programmes and is accredited under the Swiss Higher Education Act (HEdA). It combines flexible, location-independent, part-time distance learning with an active, interdisciplinary research culture on its campus in Brig. Across five faculties – Law, Psychology, Business & Economics, History, and Mathematics & Computer Science – we have been shaping modern teaching, learning, and research for more than 30 years. Today, UniDistance Suisse has over 2,700 students and around 550 staff members. To further support the growth and development of UniDistance Suisse, the Faculty of Business & Economics invites applications for two Tenure-Track Assistant Professorships (2 x 100%), Specialisation: Empirical Management Research Place of work: Brig | Start of work: 1 February 2027 or upon agreement
Understanding bias Bias means that an estimator we’re using to learn about a real-world phenomenon is not accurate. It’s not hard to see that this is a bad thing! On the flip side, if an estimator is unbiased, it’s (usually) accurate and thus we can trust it without doing any further work. The linguistic definition of bias varies and can be misleading, but the mathematical definition is precise. We’ll use it to explore the concept of bias further. It states: \begin{equation*} \mathbb{E}(\hat{\beta}) - \beta = 0 \end{equation*} Or, equivalently, \begin{equation*} \mathbb{E}(\hat{\beta}) = \beta \end{equation*} This equation says “the expectation of our estimator of beta minus the true value of beta is zero”, or equivalently, “the expectation of our estimator of beta equals the true value of beta”. Beta is simply a Greek letter that’s most often used to denote a regression coefficient; here, it symbolizes the effect we’re interested in studying. The expectation symbol (the fancy “E”) is a very important part of this definition: it gives the expected value, or mean, of the quantity inside it. (If you need touching up on mathematical symbols, we’ve got you covered.) Let’s dig deeper into how this works. The expectation of a constant is trivial, since constants don’t vary and the mean of a constant is itself. So for example, the expectation of 4 is just 4. Not very exciting. But when it comes to random variables that can take on many different values — like “the number of heads in 5 coin flips” — the expectation is suddenly very useful. It tells us what our “best bet” is: the average (or most likely) outcome. Of course, in 5 coin flips, the expected number of heads is 2.5, and it’s impossible to get 2.5 heads out of 5 flips. But, this is still an intuitive way to think about it. Therefore, the expectation of our estimator \hat{\beta} tells us its expected value, or in other words, what we’d guess it would be if we ran an experiment to measure it. When we’re using this estimator \(\hat{\beta}\) to study, say, the effect of car sales on carbon dioxide emissions, we want its expected value to be the true effect that selling a car has on emissions. If our estimator is wrong on average — say, it oversells the true effect and makes selling cars look worse than it actually is (or vice versa) — then it is biased. In other words, if the estimator’s expectation is not equal to the true, real-world effect (represented by \(\beta\) ), it is biased! Meanwhile, estimators that satisfy this criteria are unbiased, which is great news! Unbiased estimators are usually preferred over biased ones, all else equal. Examples of bias in economics Sadly, in economics and many sciences, naturally-occurring unbiased estimators are few and far between. This is often the case because of how complicated and interconnected economic factors are. When one factor affects another in economics, we usually need to work hard to disentangle the effects of everything else in the economy on those two things. If we can do so, we will be able to study them in “isolation”. This will lead us to getting an unbiased estimator, but it can be devilishly tricky. For example, we can’t simply throw investment and GDP into a regression and expect to get an unbiased estimate for “how much investment increases GDP”. This is a classic endogeneity problem, because investment increases GDP, but a higher GDP means an economy will have more funds to invest! And even besides this issue, there are many factors that increase both investment and GDP at the same time: a fall in interest rates, for example, can spur investment and increase GDP. Therefore we must account for interest rates when considering this relationship. In fact, once you learn how to think about bias in economics, it becomes difficult to find an estimator that isn’t biased. The effects of education on income are biased because of people’s innate ability — those with more ability tend to get more schooling, and those with more schooling tend to earn higher wages. An estimate of how city parks affect people’s life satisfaction would be biased, too — wealthier neighborhoods can afford more parks, but also likely have higher life satisfaction than poorer neighborhoods because they’re wealthier (not because of the parks). The effects of policing on crime can be biased because high-crime areas attract more police attention. Analyzing these biased scenarios improperly can lead to erroneous results — with this last example, a simple regression might suggest that more police cause more crime! There are nearly infinite examples of how an estimator could be biased in economics. It seems important, then, that we understand what the effects of bias on our analysis are. Bias causes inference to be inaccurate As we discussed above, the mathematical definition of bias tells us that if an estimator is biased, it’s inaccurate. Let’s expand on this idea further. The regression coefficient \(\hat{\beta}\) is supposed to give an idea of the effect size of x on y. This number is usually calculated with a computer program and reported with supplementary statistics that tell the economist how “significant” the result is. But if the estimator is biased, a significant result might lead us to conclude that the true real-world effect size is close to the biased estimator’s value. By the definition of bias, this is wrong! (Think of our policing example above.) Even worse, our estimate of the sample mean is often used to construct so-called confidence intervals. If we have a biased estimator, the sample mean will also be biased. Confidence intervals are ranges that tell the researcher “with 95% likelihood, the true effect size lies within this range” (or a similar percentage). For example, if we find that 1 additional year of schooling increases future income by $5000, a confidence interval might range from $4300 to $5700. Then, the researcher is led to believe that the true population value lies within that interval with a high probability — it’s at least $4300 or not more than $5700. However, if the estimator was biased this can be completely wrong. We can’t observe innate ability (we can use imperfect measures like IQ scores, but let’s ignore that for now), which increases both the likelihood of getting more education and the likelihood of making a higher income. This means that our simple estimator is biased upwards, since the regression falsely attributes all of “innate ability”’s power for increasing income to “education” instead. Therefore, it’s possible the true effect would be only $3900, which is completely outside of the biased confidence interval that the researcher is now very confident in! Correcting bias If we end up with a biased estimator, not all is lost. There are methods to correct bias. Most of these involve accurately diagnosing the form of the bias and ensuring that appropriate steps are taken to resolve the issue. Let’s return to some of our earlier examples. Suppose we wanted to measure the effect of parks on people’s life satisfaction, and we run a regression to capture this effect. If we don’t have data on wealth included, clearly we have an omitted variable problem and the estimator will be biased. But there’s an easy solution in this case: collect data on wealth of the areas used in the study, and this will ensure the effect of wealth is not captured by our “parks” variable. This can remove the bias. Sometimes, it’s not possible to collect data that we might need to remove the bias. Consider “attenuation bias”, which is caused by measurement error that systematically under- or over-states the true values — if our measurements themselves are biased, clearly we can’t simply fix that by collecting more data. One great example of this is self-reported income: people tend to overstate their income in surveys, which leads to a bias we cannot remove. In cases like these, we can turn to advanced regression and statistical inference methods to help us analyze the data and attempt to recover the truth. Still, it’s better to simply avoid these scenarios if at all possible. Identifying and correcting bias in an economic or data science model is complex and can require years of studying to master. Still, this section should have given a good intuition for how it can be done. We’ve spent quite a while now discussing bias and its effects, and clearly, ceteris paribus, it’s better to have an estimator that is unbiased. And yet… A little bias is often acceptable Bias is sometimes not only okay, but even welcome in an analysis. Of course, this begs a question. Why on earth would we ever want an estimator to be biased?! Has this whole article been a lie? The unfortunate truth is that bias and its cousin, variance, have an interconnected relationship. This forces economists, statisticians, and data scientists to make a choice between how much of either one they’re willing to tolerate. In short, scientists can increase bias to reduce variance, so in cases where variance is too high (creating an “unstable” estimator) we might introduce bias to settle down the variance. In this case, we can reduce the total error of the regression equation, which improves our analysis. Say that increasing bias by 10% reduces variance by 50%; this will lower the overall error of our analysis, and is a worthwhile trade. Still, in general, bias isn’t something to go looking for. Now you should be well equipped to recognize it! Good to Know Small sample sizes are often an issue in regression analysis. Because of this, every economist or data scientist prefers to have more data rather than less in their dataset. To see this, consider a coin flip. When we flip a coin, we expect it to be heads half the time and tails the other half of the time. But, it’s entirely possible that we flip a coin 10 times and get heads 8 times instead of 5. If we were running a regression and used this experiment as our estimate, we’d get an 80% chance of heads. This seems like a problem — if we didn’t already know beforehand that a fair coin has a 50% chance of landing on heads, how could we tell that this estimate is wrong? And, is this a case of bias? This example — and indeed, all of the examples in this article — highlight that theory is very important. When studying bias and analyzing data, it’s imperative that the data scientist understands what the data actually means. This will help them make the right decisions in their analysis, and help them to make correct takeaways. So, if this coin experiment was run and the data scientist had a solid theory about it — like that coins should land on heads 50% of the time — they could make an informed guess that either they’ve observed a slightly unexpected outcome, or the coin could be weighted. Then, they can figure out how to test these hypotheses and learn more. Further Reading Advanced readers might be interested to know that, shockingly, there exist estimators that are biased but provably better than unbiased options — even if variances are comparable! The James-Stein estimator is one such intentionally biased estimator that improves upon the usual “default” results. The classic method for “solving” a regression equation, Ordinary Least Squares (or OLS), minimizes the squared error terms in the regression. This results in coefficient values that can be unbiased (if the researcher used OLS correctly) and that are as close to the true values as we can get, given the variations in the random data we collected. The James-Stein estimator is built on a concept that shocked statisticians when it was initially introduced in 1961. Put simply: we can bias our own estimates downward in order to reduce the sum of squared error even more than OLS can. Then, since we have less error on average, we are closer to discovering the true population value overall, even though we purposefully biased the estimators downwards to understate the effect size! Estimators that are strictly worse in a total-error sense than other estimators in this way are called “inadmissible”. Thus, statisticians proved OLS is inadmissible. And later, they also proved that the James-Stein estimator itself is also inadmissible! This begs many questions, not least of which is why we’d ever use OLS (or other unbiased estimators) if we can purposefully bias our estimators to get “better” results. Alas, this topic goes much beyond the scope of this article, but the answer lies in the bias-variance tradeoff, the specific research question at hand, and the (size of the) dataset used among other factors. Consider taking courses in statistics, data science, or econometrics to learn more!
Nobody wants to be biased! But rather than suggest someone isn’t a fair judge, “bias” in economics has a very specific — and perhaps equally distasteful — meaning. This econometric concept is borrowed straight from the field of statistics, just like its cousin, variance. Both bias and variance have very important roles to play in our analysis of real-world data via regression analysis, and they’re linked together through the bias-variance tradeoff. Regression analysis is an important tool in the modern economists’ toolkit (as well as any other scientist or data analyst!). With it, we have methods to test economic theories and understand how certain processes or variables affect others. In our article on regression analysis, we touched on several factors that can complicate an analysis and lead to incorrect conclusions. Bias is one such factor.
Description: Role Purpose: Support economic and financial analysis of utility networks by evaluating CAPEX, OPEX, lifecycle costs, and investment decisions to improve cost efficiency, resilience, and service performance. Key Responsibilities: Data Assessment: Identify data gaps, assess data quality, and recommend improvements for cost analysis. Benchmarking: Analyze CAPEX, OPEX, and maintenance costs; benchmark against international utilities; identify efficiency gaps. Techno-Economic Analysis: Evaluate Security of Supply Standards (SoSS), resilience, and service levels; assess cost vs reliability trade-offs. Value Engineering: Conduct lifecycle cost analysis; identify cost-saving design and material alternatives. Standards & Specifications: Perform cost-benefit analyses for new technologies and standards; support investment decisions. Digital Tools Support: Develop cost models and support investment prioritization tools. Qualifications: Bachelor’s degree in Finance, Accounting, Economics, or related field. Professional certifications preferred (e.g., CFA, CPA, or FMVA). Advanced degree (MBA / MSc Finance) desirable. Minimum 10 years of work experience. Experience in water, energy or infrastructure sectors preferred. Preferred Specifications: CAPEX/OPEX budgeting, forecasting, and variance analysis. Financial modelling and business case evaluation (ROI, NPV). Strong accounting knowledge (cost allocation, capitalization). Advanced Excel and ERP systems (e.g., SAP) proficiency. Data analysis and reporting (insight generation for decision-making). Stakeholder coordination with finance, engineering, and operations teams. Cost-benefit and investment analysis (NPV, IRR). About Stantec: We’re active members of the communities we serve. That’s why at Stantec we always design with community in mind. We believe growing a great design company happens from the inside out. We look for people who are drawn to use every talent they possess, plus creativity, determination and a drive to do the extraordinary. The Stantec community unites approximately 22,000 employees working in over 400 locations across six continents. We collaborate across disciplines and industries to bring projects to life. Our work as architects, engineers, and consultants from initial project concept and planning through design, construction and commissioning is built on a solid history of success. So, when we take on a project, we see the opportunity to make a lasting connection with the people and places where we live and work. Redefine your personal best. Join us! Work Location(s): United Arab Emirates - Abu Dhabi Employment Type: Full-Time Job Type: Regular Job Category: Consulting APPLY NOW Stantec provides equal employment opportunities to all qualified employees and applicants for future and current employment and prohibit discrimination on the grounds of race, color, religion, sex, national origin, age, marital status, genetic information, disability, protected veteran status, sexual orientation, gender identity or gender expression. We prohibit discrimination in decisions concerning recruitment, hiring, referral, promotion, compensation, fringe benefits, job training, terminations or any other condition of employment. Stantec is in compliance with local, state and federal laws and regulations and ensures equitable opportunities in all aspects of employment.
Join Stantec as an Economic Analyst in Abu Dhabi to support economic and financial analysis of utility networks.
Researcher | Pre-/Post-Doc - Applied Microeconomics
The position is available from October 2026 for a period of four years, with the option of extension. A part-time arrangement is possible. Our research and teaching focus on the economic behaviour of firms and individuals in the context of globalisation, migration, and structural change. A central element of our research is the empirical analysis of economic phenomena based on large individual-level datasets. Your responsibilities will include: • teaching duties amounting to 4 hours per week during term time (Semesterwochenstunden) • your own research, comprising at least 50 percent of working time, in pursuit of further academic qualification (e.g. PhD or habilitation), publications • supporting the Chair's research activities as well as contributing to academic self-administration Your profile: • Master degree in economics or a related field • interest in and knowledge of applied microeconomics and international economics • interest in, and very good knowledge of, econometrics and the application of empirical methods • very good programming skills in R and/or Stata • very good command of spoken and written English • initiative, creativity, and strong analytical skills • a keen interest in research Desirable selection criteria • experience and expertise in working with individual-level and/or foreign trade data • experience in developing and implementing independent research ideas We offer: • attractive remuneration with financial stability, regular pay adjustments, and an annual special payment • occupational benefits (e.g. retirement provision through VBL, capital-forming benefits, job ticket) • collectively agreed annual leave plus non-working days on 24 and 31 December • flexible working arrangements and family-friendly working conditions • and much more… Please submit your application, quoting the above reference number, as a single PDF file by 20.09.2026 to: bewerbung@europa-uni.de (application data will be deleted without delay once the selection procedure has been completed). Questions regarding the position may be directed by e-mail to: geishecker@europa-uni.de. Interviews are expected to take place on Frankfurt (Oder) in early October 2026. Applications should be submitted digitally in English and include the following documents: a letter of motivation, a detailed curriculum vitae, academic transcripts and references, a list of publications where applicable, a sample publication (PDF), a research proposal outlining the development of a research project (max. 4 pages), and a proposed outline for one MA and one BA seminar related to the subject area of this position (title and a brief description of approx. 10 lines each). The Europa-Universität Viadrina Foundation is actively committed to diversity and equal opportunity among all its staff and pursues the goal of being a non-discriminatory institution that welcomes and protects people in their diversity within the university community. Further information can be found at: www.europa-uni.de/stellenangebote
Europa-Universität Viadrina is an internationally and interdisciplinarily oriented university located in the twin city of Frankfurt (Oder)-Słubice, on the German and Polish banks of the River Oder, where it educates around 4,000 students from all over the world. The university lives the European idea in its everyday practice and promotes European integration through teaching and research. With around 300 academic and 300 non-academic staff, it forms a community for which successful communication and cooperation with Eastern Europe are a particular concern. The Chair of Economics, in particular Applied Microeconomics at the Faculty of Business Administration and Economics invites applications for the position of Researcher | Pre-/Post-Doc Reference number 1201-26-01 (up to pay grade 13 TV-L, 40 hours/week)
The interdisciplinary B.Sc. Hons programme in Economics and Finance will help students to understand the principles of economics and its applications to financial systems and organisations. The department recommends that students complete mathematics in Classes 11 and 12 to be eligible for any economics-related major or minor. For students who have not studied mathematics in Classes 11 and 12 to be eligible for any economics-related major or minor, they need to: a) Take MAT 1000: Calculus (a 1000-level course) offered by the Mathematics department in their first semester and b) Secure at least an A- to be eligible Note, there may be an entry test requirement for MAT 1000 which will be set by the Maths department. Please check the mathematics department website for more details. In addition to quantitative techniques in mathematics and statistics, the curriculum will also include advanced financial techniques such as derivatives pricing, risk management and portfolio management. Finance Courses A sample of courses constituting the Finance electives is the following. Introduction to Finance Financial Markets and Asset Pricing Finance and the Economy Advanced Financial Management Financial Markets and Institutions International Finance Asset Pricing Derivatives and Risk Management Empirical Monetary Policy and Finance The list of economics and finance electives from recent semesters can be found here. Major Requirements Students admitted to Ashoka in 2022 and thereafter fall within the NEP Programs. Credit requirements for interdisciplinary majors are listed below. Four-year Economics and Finance UG degree (BSc Hons. degree) requires 20 major courses, each of 4 credits. The structure of the 20 courses is the following: 9 compulsory courses in Economics: these include — Introduction to Economics, Mathematics for Economics, Microeconomic Theory I, Macroeconomic Theory I, Statistics for Economics, Microeconomic Theory II, Macroeconomic Theory II, Econometrics, and Development Economics. Any 11 economics or finance electives, of which exactly 4 finance electives. In addition to this, one can do a BSc Honours with Research with an additional Dissertation of 12 credits. The exact breakdown of the year-long sequence will be announced after the university discussions by the end of the academic year 2024-25. Three-year Economics and Finance UG degree (BSc degree) comprises of 15 major courses, each of 4 credits. The structure of the 15 courses will be the following. The 9 compulsory Economics major courses include — Introduction to Economics, Mathematics for Economics, Microeconomic Theory I, Macroeconomic Theory I, Statistics for Economics, Microeconomic Theory II, Macroeconomic Theory II, Econometrics, and Development Economics. Any 6 economics or finance electives, of which at least 3 finance electives. Sample Curriculum Structure (For students admitted in 2022 and later) 4-year Economics and Finance major Semester I Semester II Semester III Semester IV Semester V Semester VI Semester VII Semester VIII Introduction to Critical Thinking Foundation Course 4 Foundation Course 6 Foundation Course 7 Foundation Course 8 Economics Elective 2 Economics Elective 4 Economics Elective 7 Foundation Course 1 Foundation Course 5 Statstics for Economics Econometrics Development Economics Economics Elective 3 Economics Elective 5 Finance Elective 4 Foundation Course 2 Introduction To Economics Microeconomics Theory I Microeconomics Theory II Economics Elective 1 Finance Elective 2 Economics Elective 6 Foundation Course 3 Mathematics for Economists Macroeconomics Theory I Macroeconomics Theory II Finance Elective 1 Finance Elective 3 The above table is only a sample curriculum structure. Blank boxes are for non-major courses. There could be other possibilities, e.g. taking the 7th Foundation Course in 6th semester and taking three Economics electives in the 5th semester. Please refer to the UG Handbook for overall degree requirements. 3-year Economics and Finance major Semester I Semester II Semester III Semester IV Semester V Semester VI Introduction to Critical Thinking Foundation Course 4 Foundation Course 6 Foundation Course 7 Foundation Course 8 Economics Elective 2 Foundation Course 1 Foundation Course 5 Statstics for Economics Econometrics Development Economics Economics Elective 3 Foundation Course 2 Introduction To Economics Microeconomics Theory I Microeconomics Theory II Economics Elective 1 Finance Elective 2 Foundation Course 3 Mathematics for Economists Macroeconomics Theory I Macroeconomics Theory II Finance Elective 1 Finance Elective 3
The interdisciplinary B.Sc. Hons programme in Economics and Finance will help students to understand the principles of economics and its applications to financial systems and organisations.