The Reality of Pareto Optimality

Earlier this week I discussed this question of the Kaldor-Hicks criterion versus Pareto optimality: two standards we use for government intervention from the welfare economics perspective. I argued that unless we constrain our assumptions about the world, a completely Pareto optimal government intervention is impossible to reach. After having thought about the issue some more, I realized that this is really a question about open versus closed systems. In a closed system, we can have a Pareto Optimal solution. A broad long-lasting insurance pool benefits everyone who is a part of that pool, but may raise costs for those outside of it. Foundation grants that fund projects in a single city may benefit everyone who lives in that jurisdiction, but it raises the opportunity costs of those living elsewhere.

Theodore Lowi approaches this idea of policy benefits and burdens from a political science perspective. If you remember from our reading on explaining policy choices, Lowi is associated with the idea that policy shapes politics. He argued that there were four types of policies: distributive, re-distributive, regulatory, and constituent (although his earlier work only acknowledged the first three of these categories) . Key to his argument is the idea that each of these types of policies have their own arenas of power, in other words, each of these types of policies produce different relationships between interest groups, elected officials, and agencies.

For this post, I will focus on distributive policies. The current form of distributive policy would be those earmarks and pork-barrel politics that we discussed during the first week of class. They distribute large benefits to a small group of people, but the burdens they place on others (mostly due to taxes and opportunity costs) are small and diffuse. While these may meet the Kaldor-Hicks criterion, they are certainly not Pareto Optimal. The original use of the term "distributive policy" was to describe 18th and 19th century American land policies. During that time, land in America was considered an almost unlimited resource. The American government was basically giving away land to anyone willing to travel west. From the perspective of 18th and 19th century Americans, I would argue that distributive policies, as defined in this way, were Pareto Optimal. There was enough land to go around, those willing to make the trip to the west could have it, freeing up space and resources for those remaining on the East Coast. Everyone had to travel to the west to benefit, so the opportunity costs were more or less the same for everyone.

I hope that by now you have all recognized the flaws in this argument. This assumes a very closed system. The definition of "American" in this example does not include those who were already living on the land in the West (some of whom had already been displaced from the East Coast), and who were brutalized, killed, and occupied so that American citizens could all benefit from free western land. (Of course, I am talking here about Native Americans/American Indians). Once we extend our system to include Native American/American Indian peoples, we no longer have a Pareto Optimal solution. These policies would not qualify as distributive policies in the modern sense of the term "concentrated benefits with small diffuse burdens", and they would fail the Kaldor-Hicks criterion, as well. The short-term and long-term harms  they imposed (most notably genocide, relocation, and rape) likely outweigh the benefits. This would be true for the colonialist actions of other nations, as well.

The interest in these two criteria for government action in class has allowed me to engage in a thought experiment about what they could look like in real-life. While grounded in economic and policy theory, these arguments are not based on research and should only be taken as thought experiments. I think one lesson here is that policy-makers and analysts need to be weary of solutions that seem to be Pareto Optimal. When burdens of any action seem nonexistent or even small and diffuse, we may be guilty of closed-systems thinking. We,  as responsible members of a global society, need to at least consider the harms and burdens that our actions will cause to those we consider outside our reference group, our society, and our nation. There may still be a good argument for action, but if we don't at least consider these possibilities we risk history's harsh judgement.