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Look at the capability & price of LED lighting over the last 20 years as their production has skyrocketed. As you said, cars have simultaneously become much mo

• dalke 12y ago
  I rather strongly dislike the use of "20-30%" for something as inherently subjective as measuring the differences between a 1950 and 2014 automobile. How many percentage is an airbag? How much better are seat belts? Where is a study which has tried to quantify this? The same holds for LED lighting. We aren't producing the same lights as 20 years, so it's a function of far more than productivity. I believe you are talking about the experience-effect curve, described at http://en.wikipedia.org/wiki/Experience_curve_effects http://en.wikipedia.org/wiki/Experience_curve_effects . "This relationship was probably first quantified in 1936 at Wright-Patterson Air Force Base in the United States,[1] where it was determined that every time total aircraft production doubled, the required labour time decreased by 10 to 15 percent." That curve describes about units in a production run, not aggregated over the industry across multiple types of units. That page links to http://fas.org/news/reference/calc/learn.htm http://fas.org/news/reference/calc/learn.htm , which also talks about identical units. It uses 10-20% reduced costs as a reasonable starting point. Ah! I found a more recent publication, at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0052669 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjourna... which tries to show that it can be extended to a wide range of industries. > all the technologies we study here behave roughly similarly: Information technologies closely follow patterns of improvement originally postulated by Wright for airplanes [3]–[8], and technologies such as beer production or offshore gas pipelines follow Moore's law [9], [10], but with a slower rate of improvement [8], [11]–[15]. The cost reduction in the chemistry industry ranges from 1% to 48% if I read the supporting information correctly. It also covers other industries. Interestingly, it comments that: > One automobile may be faster, while another is less expensive. For this study, we focus on one common measure of performance: the inflation-adjusted cost of one “unit”. This metric is suitable in that it can be used to describe many different technologies. However, the nature of a unit may change over time. ... We nonetheless use the changes in the unit cost as our measure of progress, in order to compare competing models using a sizable dataset. but doesn't actually measure the automobile industry. Then again, according to my estimate, under that unit-based metric automobiles have a negative curve. The paper continues: > The crudeness of this approach only increases the difficulty of forecasting and makes it particularly surprising that we nonetheless observe common trends. It might be because it's mostly talking about commodity production. The exceptions, like MonochromeTelevision, are under "Other Industries" and date from WW2 and the post-war era. Photovoltaics, btw, is in the 20-30% range you mentioned. I'm much less convinced about cars and shoes. Also, the Wikipedia page points out that could really just be seen as a an economy of scale. For example, Goddard C (1982) Debunking the learning curve. IEEE Transactions on Components, Hybrids, and Manufacturing Technology 5: 328–335. doi: 10.1109/tchmt.1982.1136009 That PLOSOne article tries to test that, coming to the tentative conclusion that improved productivity is a better for short time scales, and Goddard's model for economy of scale is fine for long time scales. This suggest to me that economy of scale and not improved productivity may be the more relevant factor for the decade long trends you're talking about. Anyway, that's my inner Hermione coming out. :)