How Fear of the Future Causes Political Gridlock
Gridlock can occur even when the same political party controls both houses of the U.S. Congress, as we have seen through the beginning of the Trump presidency. Gridlock bogs down the wheels of bureaucracy and makes it difficult to agree even on legislation that is beneficial to both parties. A paper by Wioletta Dziuda from the University of Chicago and Antoine Loeper from the Universidad Carlos III de Madrid seeks to explain the reasons behind political gridlock and why even sympathetic legislators can fail to achieve consensus. Furthermore, their model predicts polarization and describes why legislators cannot always react swiftly to economic shocks.
We regularly see the disparity between a desirable action and the actual response in legislative governmental bodies such as Congress. Dziuda and Loeper construct a simple model with a left-leaning legislator named L and a right-leaning legislator named R. First, they examine the legislators’ actions in different time periods; a policy enacted today will become tomorrow’s status quo. The two legislators have opposing preferences, which causes conflict between passing a socially desirable action and the most preferred outcome of the legislators.
If R’s party is in power, she may choose not to raise taxes even when such a policy change is needed, as she can anticipate that L’s party might oppose tax cuts in the future. Similarly, if L’s party is in power and all parties agree that cutting taxes would be the best economic policy in the current economic climate, L would anticipate that R’s party would oppose raising taxes in the future. Therefore, L’s party might prefer to maintain an inefficiently high tax rate in the present out of fear that, should taxes be cut now, they could not be raised in the future.
Unfortunately, this equilibrium is self-reinforcing and results in a vicious cycle of gridlock. Because the players act in a polarized manner, the opposing party is more likely to act in a similarly divergent manner, which in turn reinforces the polarization of the first party. Ultimately, this drifting can be the cause of political gridlock. Fear of future battles casts a long shadow over the current policy negotiations and may lead legislators to act against the interests of society.
Dziuda and Loeper also recognize the applicability of this model to political bodies aside from the U.S. Congress. They acknowledge that any negotiation operates in the context of the previous negotiation, which is the status quo. Given this awareness, many multilateral negotiations, such as trade agreements or contracts, are affected by this threat. Indeed, whenever an arrangement is to be negotiated by members with differing preferences, the necessity of future negotiations will color the initial discussion and push both parties towards their ideological extremes, as well as decrease the chances of arriving at an agreement.
The authors acknowledge that this model cannot explain all of the polarization or gridlock that occurs in legislative bodies. However, the model does suggest that the voting records of legislators may not accurately represent their true ideological stances. Given the incentives to distort their votes both in terms of fear in the face of future negotiations and compromise that becomes the new status quo, legislators might vote against their apparent interests. Indeed, the lack of flexible and enforceable agreements creates a conflict that spills over into the negotiating stage. If legislators could credibly commit to short-term solutions, they might be more responsive to economic shocks. However, change to the status quo has such an effect on future negotiations that it overshadows the needs of the current policy climate. Indeed, even in the event of seemingly irrational gridlock, legislators are actually acting in a rational manner, taking into account previous agreements and future possibilities.
Article source: Dziuda, Wioletta and Antoine Loeper. “Dynamic Collective Choice with Endogenous Status Quo.” Journal of Political Economy 124 (4) (2016): 1148-1186.
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