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Globally, labor-productivity growth in construction has averaged only 1 percent a year over the past two decades, compared with growth of 2.8 percent for the total world economy and 3.6 percent in the case of manufacturing (McKinsey, 2017).

The most common market failures / problems in the construction industry are:

  • asymmetric information
  • corruption
  • industry fragmentation
  • ismatch between the agents of risk allocations & rewards
  • dependence on public-sector demand.

I found many organizational answers to this question: improve communication between agents, introduce shorter contracts, improve on-site execution, etc.

However, I personally think internalization would be a great choice: bringing together the agents (like Elon Musk did at Tesla). Then the agents could optimize on a vaster decision set, and the result would be Pareto-efficient. The big question is: how?

My question is: how can a decision maker improve the construction productivity? What would be the answer from an Economist point of view?

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    $\begingroup$ A key reason why productivity is improving slower is that it's hard to automate as long as a big chunk of the work is done on site and not in a factory. Also, much of the construction business consists of short series (many buildings are one-of-a-kind), reducing reusability to patterns. So much of the work spent on construction design and planning is not reusable on the next building and assembly requires a lot of manual labor on-site. $\endgroup$ – Klas Lindbäck Mar 20 '18 at 9:48
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A great many things can be said on the question. But it might be worth pointing out that people have been building stuff for a very very long time, so maybe 1% productivity growth is not a bad result.

The most difficult is anti-corruption. You could compare the free press + independent judiciary + empowered investigative authorities within specified limits + free elections ... with the approach of President Xi, whose name is now entrenched in the Chinese constitution.

However, it seems that you're more interested to motivate a specific theory. So perhaps you could develop that and come back with a question that is more aligned to what you want to know. For example, you could be additionally descriptive about what it is about Tesla's operations that might have broader lessons in construction? (Note that Tesla makes cars, not ports, not bridges and not roads.)

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