Socrative – a nice way to present quizzes and measure student performance. Can be teacher paced so that you ensure all students have answered before moving on to the next question
Typeform – a way to generate longer forms that are tailored to student responses
Qualtrics and Survey Monkey are great for running a survey, and purport to allow you to create a quiz, but in my experience lack the functionality required to be used in a classroom setting. I am very keen to find an intuitive quiz builder that allows students to see their score, and allows instructors to batch grade open ended questions and then export the results. So far it seems that Google Forms are the best option.
Here’s a list of some resources that have been recommended to me, but I don’t currently use:
Nearpod– allows interaction and student participation
Mentimeter— presentation software to encourage fun workshops
Participants should select one of the countries under study and identify a potentially internationally competitive cluster. Using the format provided in the lecture, and the East Belarus mechanical engineering article as a guide, participants will submit a written report. The report should contain diamond analysis and cluster mapping.
If an economics instructor requires students to submit work using PowerPoint, they can reasonably expect that those students will either possess the skillset required to do so, or recognise the need to develop it. And student’s wouldn’t feel that the choice of format is a source of disadvantage. In a few years time the same will apply to the creation of a video. We all need to become capable of producing videos with ease. I see 4 options to create simple content:
Video – the most obvious route is to use the video feature on a standard smartphone. Here’s an example. This can be done in a single shot without any additional resources. Here are some tips. This is the simplest way to record yourself, but I find it a little awkward when done as a lecture. If it’s more informal it’s more engaging, but slightly more complicated to plan. Using a light board is possibly the best way to do this. Social media platforms now have great video functionality. I like TikTok (here’s an example).
Powerpoint with voiceover – this is probably the simplest, and I have several examples. There’s also products such as Adobe Spark that perform the same function but slightly slicker. Do be careful about whether to put the slides online as well, since this can reduce the likelihood of students watching the video. I use Camtasia to narrate over a PowerPoint screen record. Here’s an example. It also allows relatively easy editing but it’s not cheap and I’m sure there’s plenty of other options. Here’s some instructions for screen recording on a Mac. Quicktime has a very simple audio + screen capture device and it’s baked into Mac OS. See Tom’s Guide for some more.
Dual video and slides – this is a great way to convey detailed content but in a personalised way (e.g. Andy Field). I’m keen to find simple software that allows a presentation recording, webcam footage, and note space. In other words I want to know what these guys use. But here are some different options:
Loom – best for people who want a free solution that is intuitive and easy to use
ManyCam – best for people with a license, and willing to learn how to use it
OBS Studio – best for people who want a free, open source option that is slightly more complicated to use but allows a lot more functionality (here’s a tutorial)
Zoom – best for people that are used to using Zoom
Interactive powerpoint – for my EMIB course we had an interactive green screen. This puts the presenter inside the screen and permits interaction (e.g. drawing directly on the screen). It’s basically reading the weather. It’s harder to plan but the final result can be quite effective. For lecturing, I don’t think that a green screen adds much value over a plain background. A virtual set though, may be worth investing in!
Finally, it’s not always necessary to reinvent the wheel. I think there’s value added in giving students content that you’ve created, since it generates a student-teacher bond. But I also utilise high quality videos created by others.
I am an Affiliate Faculty Member of the Microeconomics of Competitiveness program at Harvard Business School, and a big fan of Michael Porter – his work consistently reminds me of the importance of bringing clarity to management practice.
I also like his inclination for frameworks rather than models. If your goal is to interpret and assess, as opposed to measure and predict, a framework is a critical analytical tool. One that I especially like is his explanation for what determines competitiveness. For example, consider the following slide (which I believe originates from here).
I’ve given this framework a lot of thought, but I don’t think it fits as neatly into the Diamond model as is often claimed. For example in this NBER paper Porter (and co-authors) present an enlarged version:
This clearly shows that the Diamond model is intended to be a more detailed view of the “Quality of the National Business Environment” segment. But consider something like nutrient rich soil, or a large natural harbour. One might think that constitutes an endowment. But it is also a relevant “Factor input condition”. Indeed what’s the difference between the “Supporting and Related industries” and “State of Cluster Development”? I suspect this is why Figure 3 above has dropped endowments and clusters, and renamed it a “Foundational Competitiveness Index”. I think this is a shame, because the “What Determines Competitiveness” slide is clearer, and more coherent, than the FCI.
I think Porter’s attempt to force fit the Diamond model into the Competitiveness index creates an opportunity to take the “What Determines Competitiveness” slide in a new direction. Indeed I think it complements nicely the “Growth is Like an iPhone” analogy:
In my attempts to merge the three level analogy with a template that my students can use in class, and with all appropriate nods to Prof. Porter, this is the “Country Competitiveness Dashboard“:
Rather than viewing the Diamond model as a subset of the “Business environment”, I see it more as a strategic tool that cuts across the whole Country Competitiveness Dashboard. In other words step 1 is to populate the dashboard, and ensure that you are covering all bases. Step 2 is to conduct a Diamond analysis – which is better suited at the cluster level than the national level anyway.
I think it’s important to understand competitiveness but it looks toward the supply side of the economy, which is much more important for long term growth than either monetary or fiscal policy. Two recent articles on the rise of new supply side thinking include:
Finally, it is well worth reading Paul Krugman’s, Competitiveness – a dangerous obsession (Foreign Affairs, March/April 1994). When treated as a mercantilist trade “strategy”, or the conflation of corporate planning with national level decision making, attention to competitiveness can lead us down the wrong path. But when competitiveness is wedded to our understanding of economic growth, and the conditions required for entrepreneurship to flourish, the competitiveness framework is immensely beneficial.
The covid-19 pandemic has prompted a mass transition from in class tuition to virtual learning. It’s an incredible pedagogical experiment, and I’m intrigued as to how it will play out. ESCP Business School was an early mover – our Turin campus made a complete switch online on February 23rd. I’m the Teaching & Learning coordinator for our London campus, and we have been anticipating and managing as smooth a transition as possible since then. We went fully online on March 16th [the day after I wrote the first draft of this article].
This crisis situation has prompted an immediate action, but it reflects a deeper trend away from the classroom. I feel well placed to react because I’ve made online learning a key part of my professional strategy. In 2016 I launched an online Managerial Economics course as part of ESCP’s “Executive Master in International Business” (EMIB). Since then I’d added a new online course every year, such that in 2019/20 my online teaching exceeded my in class instruction. I am a digitally minded person, and have loved the opportunity to develop such courses to be able to recognise more clearly the value of being physically present. For me at least, those two forms of teaching are complementary and teasing out how they interact has been satisfying.
This article isn’t intended to be updated in real time, and maybe it will become quickly outdated. But to start off with here are some key resources I’ve used recently:
It’s not obvious that teachers have the right skillset to create online courses.
The key skillset for a lecturer:
Knowledge of the content
Ability to grade exams
The key skillset for an online instructor:
Ability to curate content
Aptitude with alternative technologies
Choice of assessment
So instructors should think carefully before attempting to move online. It takes preparation and experience, and may be detrimental to in class instruction.
I see four basic models for online learning:
Model 1: Your own pace
These type of courses remove students from the dreaded (and stupid) syllabus and allows us to package a course into a simple process:
Listen to this
The platforms that I use and recommend are Coursera and Udemy. I’ve built a course on Teachable, but it’s expensive. I’ve also trialled Canvas, which looks good. Another option is Versal. (In the stampede prompted by the coronavirus I simply used the existing learning management system (our school uses Blackboard) because it integrates with grading and students already have password protected access. But if I were reaching out to non enrolled students I’d use something else.)
When built well, student led classes can be very effective. But they can be a challenge to ensure consistent student engagement. It’s no surprise therefore that for many traditional courses that are having to transfer online, the prevailing course structure is important. The need to retain a timetable, and get students to interact, more closely replicates their previous experience. Don’t forget, one reason people pay for gym membership is the discipline of going to the gym. If students wanted a DIY alternative they’d already have chosen that, and would have saved a large amount of money in doing so. So how do you keep the class together?
Blackboard has a Collaborate tool which allows the sharing of your screen and useful student participation (such as polls and emojis for instant feedback). It also permit breakout rooms so that students can do group work (see here for an instructional video).
Remote classrooms use the technology of the internet to distribute content but don’t fundamentally differ from a distance degree. The key value being provided by the university is therefore the grading of assignments and student feedback. They are paying not for the content per se, but to have a professional instructor grade it for them. Automated quizzes don’t cut it in this context. Examples:
This is when a physical course is delivered as normal but participants receive remote access. This has a bigger emphasis on hardware needs (e.g. high quality cameras and mics throughout the audience) and editing. But it’s an easy way to grant access to those unable to attend physically. Some examples:
I think for all serious online courses (i.e. ones where students pay big money to a reputable institution), the key factors for success:
I see a major advantage for online courses being the opportunity to crowdsource and aggregate grading into quick, responsive, 360 feedback. I like to ensure that students are viewing, and critically engaging in each others submissions.
Finally, I have taken, and recommend, the following online courses:
There are three components to the dynamic AD-AS model.
The first is the Solow curve, which shows the growth rate that would exist (i) if prices were perfectly flexible; (ii) given the existing real factors of production. It can be derived from the Solow growth model and since this treats capacity as being independent of inflation, it is depicted as a vertical line. Improvements in research & development; better infrastructure; increased competitiveness; higher quality education and training; labour market flexibility; or natural events such as more conducive weather would all constitute a positive productivity (or “real” or “supply side”) shock, increase the Solow growth rate, and shift the Solow curve outwards.
The second component is the Aggregate Demand (AD) curve. This can be defined as combinations of inflation and real growth for a specified rate of total spending, and is far more intuitive than the traditional AD curve. This is because instead of being based on other curves (necessitating an explanation of the Pigou effect, for example) it is instead based on a dynamic version of the equation of exchange:
M denotes the growth rate of the money supply, V denotes velocity growth, P denotes inflation and Y denotes real GDP growth. Since the AD curve simply shows how any given amount of (M+V) can be split between P and Y, it will only shift if there is a change in M (i.e. the money supply) or V (confidence).* In terms of what constitutes a velocity shock, we can switch from looking at the left hand side of the equation (our posited increase in total spending) to the right hand side of the equation (how it is being spent). After all an increase in spending must be spent on something. The composition of total spending is household spending, business spending, and government spending (we’re assuming a closed economy).
Potential sources of increased spending are thus fiscal policy (either changes to government spending or changes to taxes) or wealth effects (where “wealth” means the value we place on the assets we own). An important caveat is that generally speaking changes in the growth rate of V tend to be temporary and thus only changes in M can generate sustained inflation.**
If prices were perfectly flexible, the Solow curve and AD curve would suffice. For example, if the Solow growth rate were 3% and the central bank increased M from 5% to 10% this would lead to an equivalent increase in inflation (from 2% to 7%).
However if prices aren’t perfectly flexible, the dynamic AD-AS model shows how the economy can deviate from potential GDP growth. This requires the third component, the Short Run Aggregate Supply curve (SRAS). The SRAS shows the relationship between P and Y for a given expected inflation rate. As with the traditional AD-AS model, the labour market plays a key role in economic adjustments, and so “sticky” wages (i.e. those that don’t adjust quickly to new conditions) are problematic. For example, if revenues are rising at a faster rate than wages (which constitute a large share of the firms costs), firms will appear to be profitable and will expand their output. Similarly, if prices fall quicker than wages, production will appear to be unprofitable, and they will reduce output. It is due to inflation expectations that we might expect wages to lag behind prices – if inflation is higher than expected output will rise. If inflation is lower than expected output will fall. This explains the upward sloping shape of the SRAS curve.
Underpinning the SRAS is the concept of the signal extraction problem, which implies that in the short run (i.e. whilst prices are adjusting) there may be a positive relationship between inflation and real growth. (This is the conventional argument that money is only neutral once prices have adjusted. One of the nice things about moving away from a “short run” vs. “long run” distinction is that it’s less likely that students fall into the trap of treating these concepts as passages of time. To say that prices are “sticky” is not really to say that it takes time for them to adjust, but that there are costs involved in doing so).
The reason the SRAS curve is flatter below Y* is because wages are especially sticky in a downwards direction. Basic money illusion means that workers tend to be hostile to nominal wage cuts. And the SRAS curve is steeper above Y* because there’s a limit to how fast the economy can grow – it can’t indefinitely exceed the Solow growth rate.*** Given that the SRAS holds for a given rate of inflation expectations, the only thing that can cause it to shift is a change in those inflation expectations. This may appear to underplay the importance of the SRAS curve, but in fact it clarifies the difference between SRAS and the Solow curve. It is tempting to think of the difference in terms of calendar time, for example that a period of bad weather, causing a poor harvest, will primarily affect the SRAS. This is because it is a temporary event that hasn’t altered the underlying production capacity, and if there is nothing to say that bad weather will cause a reduction in supply in the long run, it shouldn’t affect the long run supply curve. However the dynamic AD-AS model makes it a lot clearer to understand why the above reasoning is incorrect. An adverse weather event – even a temporary one – is a real shock, and will therefore impact the Solow curve and not the SRAS. The SRAS shows how the price mechanism facilitates but also can disrupt the adjustments in response to either real (Y*) or nominal (AD) shocks. It can be somewhat complicated (and sometimes arbitrary) to distinguish between SRAS and LRAS shocks in the traditional model. The dynamic model treats all real shocks as Solow shocks and is therefore much easier to use.
* It is tempting to treat M as monetary policy and V as fiscal policy but this wouldn’t be correct. Most central banks use interest rates (specifically a short term risk free rate) as their main policy tool. If the “velocity of circulation” refers to the speed at which money turns over, then this is a function of people’s demand to hold money (relative to their demand to hold goods and services). In other words V is the inverse of the demand for money. If the demand for money is high, people hold onto cash, and velocity is therefore low. Hence central banks can either affect the money supply, or try to influence the demand for money by manipulating the price (i.e. interest rates). This actually helps aid a discussion about quantitative easing. Given that interest rates are very low many central banks have reinstated the quantity of money (through the process of quantitative easing) as a policy tool that can be used in addition to interest rates.
** An increase in C in the dynamic model implies an increase in the growth rate of C, relative to I and G. Indeed this demonstrates a weakness in fiscal stimuli because it is impossible for a permanent increase in the growth rate of G. At some point it is likely that an increase in G that leads to a positive AD shock will at some point reverse itself. Indeed this also implies that when a central bank reduces interest rates this will also be self-reversing. As Cowen and Tabarrok point out (p.257) this reinforces the notion that changes in the growth rate of C, I or G do not change the rate of inflation in the long run. Given that shifts in V will tend to be temporary it is.
*** The above could also be considered a “Lucas” curve, since it follows his islands parable and emphasises the labour market. We might also think of it as a “Hayek” curve if we focus more on the capital market. Entrepreneurs confuse a temporary reduction in real interest rates (due to an increase in the money supply) with a permanent one (or at least one consistent with an increase in real savings) and invest in capital-intensive production plans. The Austrian claim is that this will be self-reversing and bring on a recession. We can incorporate this into the analysis here by stressing that particular increases in AD (i.e. when money supply exceeds the demand to hold it) will – as Cowen and Tabarrok argue happens ordinarily – cause a reverse shift in AD later on, but also end up causing a reduction in Y* through a negative shift in the Solow curve. Monetarists would say an increase in AD ultimately leads to an increase in P. Austrians would say that it increases P and reduces Y*.
This page provides information for students that are interested in me supervising their thesis. It provides some ideas on possible topics and guidance on methodology. I believe that a successful thesis accomplishes four main things:
(1) Choose an insightful research question within an interesting topic
The main difference between a very good thesis and an excellent thesis is whether or not you articulate, and answer, a good research question. In most theses that I see, this isn’t the case. Typically students will identify an interesting topic, and then proceed to investigate it. But the purpose of a thesis isn’t for you to learn about something, it’s about contributing to our collective understanding. I don’t expect students to have a good research question at the beginning of their project, but be wary of reaching the end of it without having one.
In terms of research topics, I consider the power of economic reasoning to stem from its applicability, and take a broad and eclectic position of what would constitute suitable subject material. For a general management thesis I don’t require students to work on the same research topics that I do. Indeed, there are several topics that I have thoughts and ideas on which I’d be delighted to see students run with. I’ve provided some examples of topics that I find interesting below:
This is crucial because it determines whether the experience is enjoyable or not. The following are necessary (but not sufficient) characteristics you need to have:
Enthusiasm for the research question (and not just the research topic)
Genuine desire to have people read your work
Ability to self-motivate
I will either provide you with detailed feedback on a full draft, or brief feedback on specific questions, but you should not expect me to provide multiple rounds of comments throughout the process. Depending on how many students I supervise in any given year, I intend to provide a similar amount of help to each and will be unable to devote significant time to your project close to the deadline.
When planning the writing of the thesis take a look at:
For more details on the grade ranges that I typically employ see page 7 of my guide for students, however you should adjust the passing grades such that what I deem to be a C grade for a thesis would get a mark of 55-60; a B is 70-80 and an A is 85+. These are only general guidelines and there’ll always be a gap between my judgement and your understanding of my judgment. But just because the grading is subjective does not make it arbitrary.
Professional educators understand the limitations of student evaluations, and yet the culture of external assessment is attempting to incorporate a similar thirst for trivial feedback on our peer-review. As someone who enjoys sharing a classroom with colleagues, and is genuinely keen to share ideas on effective pedagogy, I wanted to outline a possible way to conduct teaching feedback. I will write it from the perspective of the instructor conducting the audit.
Acquire the course outline and read it as closely as you expect students to read your outline.
Meet with your colleague to discuss the audit. Get a good understanding of where the session you will be observing fits into the course as a whole. Make sure you’re aware of any specific areas that they would like feedback on.
Attend the whole class. Arrive early and leave at the end. Alternate roles between being a student and an observer. It might be a good idea to talk to students about any specific questions you have, but even if you think this would be a good idea ensure that the person you are observing is ok with that.
Write a letter to the person you observed, thanking them, and providing your reflections. If there are specific areas of weakness that you believe you’ve identified keep this document private. By all means copy in Programme Management (with prior agreement) but address it to your colleague.
Take your colleague out to lunch, go over the feedback, and give them an opportunity to respond. Agree on what parts you should share with other colleagues, and external examiners. The written feedback it should be tailored to the specific course objectives that you’ve ascertained from step 1 and 2.
This proposed two-day seminar is aimed at junior faculty teaching on general management programs. It shows attendees how to teach using the case method, and provides content for market-focused courses. If satisfactory progress is made attendees will then become licensed to utilise the classroom material in their own courses, and have access to ongoing support and follow up workshops.
Introduction to participant-centred learning
9:00am – 10:30am | Session 1: A negotiation exercise
Malhotra, Deepak, “Hamilton Real Estate”, Harvard Business School Case Nos.9-905-052 and 9-905-053
11:00am – 12:30pm | Session 2: A classroom simulation
Holt, Charles A., and Sherman, R., (1999) “A Market for Lemons”, Journal of Economic Perspectives
The Case Method
2:00pm – 3:30pm | Session 3: Competitiveness
Sölvell, Ö and Porter, M, ”Finland and Nokia”, Harvard Business School case no. 9‐702‐427
4:00pm – 5:30pm | Session 4: Public Finance
“Rovna Dan: The Flat Tax in Slovakia”, Harvard Business School case no. 9-707-043, March 2010
Create your own teaching notes
9:00am – 10:30am | Session 5: Prediction markets
Coles, Peter, Lakhani, Karim and McAfee, Andrew, “Prediction Markets at Google” Harvard Business School Case No. 9-607-088, August 20, 2007