I have felt like this before. Check out XKCD for more of this.
It may be time to pull out the old Milo Optimisation Post. It was trivial 5 years ago and it’s still intended as funny rather than serious, but the sad, sad thing is that the lesson still hasn’t been learnt in our airports and probably a range of other entities.
The security check point is a bottleneck. More specifically, the number of scanners open at certain rush times isn’t enough to cope with the arrival rate of passengers at the check point.
The bottleneck is the small number of open scanners. The bottleneck could be fixed and throughout increased by having more scanners. No amount of hurrying up the process to inspect tickets will change the bottleneck. No amount of directing people to stand in queues at each scanner will change the rate at which people go through the scanners (as long as there is always a queue at each of them). None of this changes the throughput of the sytem.
But it does mean that there are extra people employed to inspect tickets and extra handlers directing people to queues – these employees could presumably operate an extra scanner and massively increase throughput. This might in turn create a bottleneck somewhere else, but if that happens it shows that throughput has already been increased. It also presents an opportunity for the next stage of optimisation.
Should South Africa import Chinese television sets? Your answer to this question depends probably on your education.
If you were university educated in South Africa, you are likely to be in the market at various times in your life for a large LED backlit LCD panel with a high refresh rate and more HDMI inputs than you will ever need. You will also quite likely have a market-oriented, Anglo-Saxon view of government’s role in industrial policy and international trade. Thus you would probably say “yes, import cheap TVs from China so I can buy a cheap TV and not pay for inefficient local firms to manufacturer expensive, inferior TVs.”
If you are a TV snob, you will still want free imports of Chinese TVs to keep the prices down of competing, but fancier Sony and LG models from Japan and Korea.
If you are a little cynical, you might say South Africa could never have the manufacturing capability and scale to produce all the components and assemble them into a modern LCD TV. That’s not actually the debate I ant to pursue now, so in that case let’s say the alternative would be to locally assemble sets made with significant local components, even if the LCD panel itself were imported. Of course, the reason South Africa doesn’t have the scale to produce the panels themselves at the moment is a function of industrial policy decisions decades go. There is no absolute reason we couldn’t have that capability. But, that debate is related but separate post. Continue reading
Any model is a simplification of reality. If it isn’t, then it isn’t a model as rather is the reality.
A MODEL ISN’T REALITY
Any simplified model I can imagine will also therefore not match reality exactly. The closer the model gets to the real world in more scenarios, the better it is.
Not all model parameters are created equal
Part of the approach to getting a model to match reality as closely as possible is calibration. Models will typically have a range of parameters. Some will be well-established and can be set confidently without much debate. Others will have a range of reasonable or possible values based on empirical research or theory. Yet others will be relatively arbitrary or unobservable.
We don’t have to guess these values, even for the unobservable parameters. Through the process of calibration, the outputs of our model can be matched as closely as possible to actual historical values by changing the input parameters. The more certain we are of the parameters a priori the less we vary the parameters to calibrate the model. The parameters with most uncertainty are free to move as much as possible to fit the desired outputs.
During this process, the more structure or relationships that can be specified the better. The danger is that with relatively few data points (typically) and relatively many parameters (again typically) there will be multiple parameter sets that fit the data with possibly only very limited difference in “goodness of fit” for the results. The more information we add to the calibration process (additional raw data, more narrowly constrained parameters based on other research, tighter relationships between parameters) the more likely we are to derive a useful, sensible model that not only fits out calibration data well but also will be useful for predictions of the future or different decisions.
How not to calibrate a model
Scientific American has a naive article outlining “why economic models are always wrong”. I have two major problems with the story: Continue reading
Stand aside Freakonomics, here is a very real, very current, very practical application of economics, incentives and game theory to a universal city development problem. Provide fewer parking spaces to help manage the car and parking problem in congested downtown areas.
Bit by bit, for the past 40 years, the city of Copenhagen has done something revolutionary: The Danish capital has reduced its parking supply. Cutting the total number of parking spaces by a small percentage each year stands in stark contrast to the more common pattern of cities adding more and more parking to accommodate private cars.
It’s a longish article, but definitely worth reading. Hat-tip to Samora Adams of @CapeChat fame for the link.
South Africa’s unemployment is a different creature from that in the US and in the developed world’s papers at the moment. We don’t have a cyclical lack of demand (although demand isn’t as robust as I’d like). We have massive, unmanaged structural unemployment in large sectors of the economy.
I say “in large sectors of the economy” because it isn’t true to say that we have universal unemployment. In fact, a feature of structural unemployment is that it usually is not uniform throughout the economy (like cyclical unemployment often is). I don’t know any actuaries or engineers who are unemployed for more than a brief period between jobs, and usually the jobs start and end back to back. There will be other examples too.
Unemployment is driven by education
Interesting that 75% of our unemployed are “unskilled”. (I heard this on the radio, so I don’t know that the number is correct or it’s source, but it does map to my previous analysis based on census showing unemployment by education level attained.
- The unemployment rate for those with less than “matric with university exemption” is between 30% and 40%.
- Matric with university exemption unemployment is 23%
- The unemployment rate for this with better than “matric with university exemption” is on average below 10%.
Economic growth isn’t the only solution to unemployment; in fact it’s not even necessarily a solution. Prior periods of strong economic growth added jobs only very slowly. We have massive, structural unemployment in this country. We are making some of the right noises with our government’s new jobs plan and jobs fund.
Education in South Africa is not performing as needed
Found these views on teamwork interesting, and largely in line with my own experiences. In particular, I’ve gone from thinking videoconferencing is all we need to the realisation that in-person interaction is important. I’d add to the point about stable, long-standing teams performing better by suggesting this is at least partly through better understanding each other’s strengths and weaknesses.