{"id":10473,"date":"2014-12-01T05:00:14","date_gmt":"2014-12-01T10:00:14","guid":{"rendered":"http:\/\/marcfbellemare.com\/wordpress\/?p=10473"},"modified":"2014-11-30T11:35:36","modified_gmt":"2014-11-30T16:35:36","slug":"the-futility-of-development-policy","status":"publish","type":"post","link":"https:\/\/marcfbellemare.com\/wordpress\/10473","title":{"rendered":"The Futility of Development Policy"},"content":{"rendered":"

A recent post over at Worthwhile Canadian Initiative on the staples trap<\/a>\u00a0made me dust off an idea I had a few years ago about the futility of development policy. The staple trap is such that<\/p>\n

While exporting [natural] resources can generate great wealth, the danger of such a path is that a staples economy becomes overspecialized in raw material extraction to meet foreign needs, and runs up large external and domestic debts over-developing the resource base and associated infrastructure. These become hard to service if and when external demand collapses, setting the stage for widespread financial dislocation along with painful losses of jobs and output.<\/p><\/blockquote>\n

What I discuss in this post is\u00a0similar to the staples trap, but it is not quite the same. The staples trap is generally the result of market forces: As demand for a staple increases, the industry surrounding that staple develops and generates side industries (e.g., processing, packaging, exporting, etc.)<\/p>\n

What I discuss here is the result of policy making–and it illustrates the futility of development policy, by which I mostly mean “industrial policy” rather than specific development policies like building roads and bringing clean water into villages. If I can be Minnesota nice about it, this post\u00a0illustrates the development policy trap.<\/p>\n

Two Examples<\/h3>\n

At the turn of the previous century, the state of North Carolina’s economic development relied primarily on tobacco, textiles, and furniture (timber)<\/a>.\u00a0As the 20th century progressed, those three industries progressively disappeared from North Carolina’s economic landscape, and by the turn of this century, they were all but gone.<\/p>\n

Likewise, from\u00a0about 1910 to about 1970, the economic development of the city of Detroit and the state of Michigan relied almost exclusively on the automobile industry. From about the 1980s onward, the US\u00a0automobile industry\u00a0declined in both\u00a0absolute and relative importance as a result of competition from abroad–primarily Asia, but also Europe.\u00a0In 2008, US taxpayers had to bail out the US auto industry<\/a>\u00a0to the tune of $17.4 billion dollars.*<\/p>\n

The point I want to make in this post is simple, yet I believe it is underappreciated by social scientists and policy makers. That point is this:<\/p>\n

Though a given development policy P<\/em>\u00a0might be optimal at time T<\/em>, there comes a point T<\/em> + t<\/em>\u00a0(with t<\/em> > 0) where\u00a0P<\/em> is no longer optimal, and an alternative policy\u00a0P’<\/em> should be preferred instead. Generally, social and political forces will make it difficult to abandon\u00a0P<\/em>\u00a0to adopt\u00a0P’<\/em>.<\/p><\/blockquote>\n

The Development Policy Trap<\/h3>\n

The two examples I gave in the introduction illustrate the development policy trap. This is especially the case for the bailout of the auto industry in 2008, which illustrates how a number of factors — an endowment effect among auto industry workers, political capture by the Big Three, the importance of Michigan for the 2008 presidential election, and the seductive narrative that is the sunk cost fallacy — led to “throwing good money after bad.”<\/p>\n

From an economic perspective, the Big Three bailout was especially ill-advised considering that no matter how much Barack Obama wants you to believe otherwise, manufacturing jobs are not coming back. Unlike the agricultural sector, the manufacturing sector enjoys very little protection from foreign competition, and when given\u00a0to locate in the US and hire highly qualified\u00a0workers who demand a high wage or to locate abroad and hire less qualified\u00a0workers who demand a lower wage, manufacturing firms will generally opt for the latter.<\/p>\n

This is especially so given the theory of induced innovation, which states that as one factor of production becomes more expensive (e.g., labor becoming costly because workers are highly qualified) relative to another factor of production (e.g., machines), firms will innovate by developing production technologies that allow economizing on the relatively more expensive factor of production (e.g., firms will develop machines that can replace highly qualified workers).<\/p>\n

So in sum, even if you know with certainty what kind of policy intervention a city, region, or country needs to develop in the foreseeable future (and that is a big if considering that there is generally a trade-off between internal validity — credible estimates of causal effect — and external validity — how widely those estimates apply — and considering the complex environment in which development policy is implemented), on a long enough timeline, that\u00a0policy intervention will\u00a0no longer be the right thing to do.<\/p>\n

This wouldn’t be so bad if development policy could be changed seamlessly, but in a world of finite resources, adopting new\u00a0development policies usually means letting entire industries die off because other countries are much better at it than you are, and supporting them would be like keeping a terminally ill patient who is suffering on life support indefinitely. People in the industries that have to be let go of will typically fight tooth and nail to keep their subsidies, benefits, and what they have come to see as\u00a0entitlements.<\/p>\n

So what are development wonks to do?\u00a0“Nothing” does not seem like an option, especially given that chronic economic underdevelopment is, at least in theory, the result of multiple market failures which have to be overcome simultaneously, and that coordination failures often prevent us from doing that. So the right solution might well be to build enough flexibility in development policy, and codify that flexibility into whatever law allocates subsidies and benefits to specific industries. The kind of flexibility I have in mind would mean that subsidies and benefits would be terminated by law when it becomes obvious that an industry has outlived its usefulness. But codifying that kind of flexibility into specific economic rules and regulations has to be industry-specific, and therefore extremely difficult. All of this points to the futility of development policy.<\/p>\n

Note that this relates to the idea of path dependence, but only to a point. As per Wikipedia, path dependence<\/a> is the idea that “the set of decisions one faces for any given circumstance is limited by the decisions one has made in the past, even though past circumstances may no longer be relevant.” As such, path dependence is a backward-looking concept (you are stuck today because of something that was decided in the past). What I discuss above is more of a forward-looking thing, whereby one has to be conscious today of how the economic environment will change in the future so as to afford development policy maximum flexibility.<\/p>\n

 <\/p>\n

* With 90.7 million taxpayers in the US in 2008<\/a>, this amounts to about $190 per taxpayer. Had the auto industry obtained the $50 billion bailout it initially asked for, the Big Three bailout would have cost about $550 per taxpayer.<\/p>\n","protected":false},"excerpt":{"rendered":"

A recent post over at Worthwhile Canadian Initiative on the staples trap\u00a0made me dust off an idea I had a few years ago about the<\/p>\n

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