Research

Works in Progress

“Predicting forecaster inattention”

Abstract: I provide new estimates of forecaster inattention and information rigidity related to the sticky information model. While most papers use aggregate-level regressions or model calibrations to estimate the amount of information rigidity, I employ a more granular estimation strategy using micro-level data from the US Survey of Professional Forecasters. I provide evidence that the true amount of forecaster inattention is much smaller than previously thought. I also document novel state-dependence and time series facts. My results imply that some other, stronger source of information rigidity must exist to account for the discrepancy between the aggregate- and micro-level results. A model accounting for information rigidity should not use sticky information as its only nor main mechanism, as doing so could result in incorrect model predictions..

“Optimal income tax progressivity over the business cycle”

Abstract: I study optimal progressive income taxation in an incomplete markets model with a fat-tailed idiosyncratic income growth process of varying skewness. The process follows a two-state regime switching process representing recession and expansion. A Ramsey planner is constrained to two log-linear tax and transfer functions, one for each aggregate state, to allow state-dependent tax progressivity. I take recently created computational techniques used for aggregate MIT shocks and adapt them to work for regime switching processes. I find that the overall negative skewness of income growth leads to higher optimal progressivity overall, but how it is spread between aggregate states barely matters. I also find that progressivity should be significantly higher in economic expansions than in recessions. I find that the welfare change from current to optimal policy in a misspecified model without skewed and fat-tailed income growth is inflated to 2.9% compared to 0.9% using the correctly specified model.

Published Papers

“A study on discrete Ponzi Scheme model through Sturm-Liouville theory”
Recommended citation: Atici, F.M. and Bennett, W.R. (2021) “A study on discrete Ponzi Scheme model through Sturm-Liouville theory”, Int. J. Dynamical Systems and Differential Equations, Vol. 11, Nos. 3/4, pp. 227-240.

Abstract: In this paper, we introduce a second order self-adjoint difference equation which describes the dynamics of Ponzi schemes: a type of investment fraud that promises more than it can deliver. We use the Sturm-Liouville theory to study the discrete equation with boundary conditions. The model is based on a promised, unrealistic interest rate $r_p$, a realised nominal interest rate $r_n$, a growth rate of the deposits $r_i$, and a withdrawal rate $r_w$. Giving some restrictions on the rates $r_p$, $r_i$, and $r_w$, we prove some theorems to when the fund will collapse or be solvent. Two examples are given to illustrate the applicability of the main results.