Asymmetric information, Reelection Pressure and Political Decision Making under Uncertainty
This paper examines the interaction of reelection pressure and asymmetric information in decision making under uncertainty by politicians. Using the normal-normal model of Bayesian belief formation, I show that the closer the election, the higher the incumbent politicians refrain from implementing the optimal policy and deviate towards their base’s bias. The model is also extended to endogenize the information gathering of the politicians. The implications of the theoretical model are tested with a dataset on gubernatorial decisions during the national Covid-19 crisis. A difference-in-differences empirical strategy shows that the governors who had an upcoming election in 2020 were biased towards their base. The Democrat and Republican governors who did not face a forthcoming election behaved statistically similar to each other.
Markovian Rainfalls and Desalination Demand
In this paper, I study the rational behavior of decision-making authority in water provision to a municipality. The forward-looking decision-maker optimally chooses the size and time of building a desalination plant. I formulate the question as a discrete-choice dynamic programming problem with uncertainty in rainfalls. Then I solve the problem numerically and study the behavior of the model using simulation. Finally, compare the statistical behavior of the model with the real data and find out that the correlation patterns are similar in simulated and real data.