Welcome to my website! I am a 5th year graduate student at Princeton University. My research interests are in macroeconomics, finance, and trade. My full CV can be found here and you can contact me at nikolakoudis@princeton.edu.
"Price Level and Inflation Dynamics in Heterogeneous Agent Economies," with Greg Kaplan and Giovanni L. Violante. Paper, Non-Technical Summary. August 2023. Revise and resubmit, Econometrica.
"The Economics of Segmented Housing Markets." Paper, SSRN Link. May 2024.
Works in Progress
"Informational Gravity," with Elena Aguilar.
We develop a model of exporter dynamics in which aggregate uncertainty is endogenous to the exporting decisions of firms within a given market. Exporting firms provide an imperfect signal regarding the returns to exporting to rival firms within the same industry. This creates an informational externality arising through the extensive margin that can lead to informational ``cascades" and multiple stochastic steady states in aggregate exports. The presence of this externality creates additional dynamic gains from the reduction in trade costs, which amplify the canonical static gains. The magnitude of these dynamic gains are decreasing in firm productivity dispersion and increasing in the (industry-level) elasticity of substitution. Our analysis suggests that temporary increases in trade costs can result in secular declines in aggregate exports through a permanent increase in firm-level uncertainty. We leverage text-based measures of uncertainty for OECD countries to test the theory.
"Rational Inattention: Signals and Precision."
This paper analyzes the continuous action rational inattention problem with binary states. I show that it is generally never optimal for an agent to acquire linearly dependent signals, which as a corollary implies that an agent will never choose more actions than there are states of the world. I demonstrate that the agent's optimal signal structure can be completely characterized through a single, univariate function. An intuitive condition on local convexity on this function determines the entire set of priors for which strictly positive information acquisition is optimal. Finally, I characterize state-dependent precision in information choice. In the widely used case of quadratic utility, I show that signal precision is invariant to the realization of the underlying state, thus providing a counterpart to the canonical Quadratic-Gaussian case when states are binary (Jung et al., 2019). I show that a necessary condition for state-dependent signal precision is variation in the convexity of marginal utility along the action space.
