Optimal income taxation in the presence of tax evasion: Expected utility versus prospect theory

The predictions of expected utility theory (EUT) applied to tax evasion are flawed on two counts: (i) They are quantitatively in error by huge orders of magnitude. (ii) Higher taxation is predicted to lower evasion, which is at variance with the evidence. An emerging literature in behavioral economics, most notably based on prospect theory (PT), has shown that behavioral economics is much better at explaining tax evasion. We extend this literature to incorporate issues of optimal taxation. As a benchmark for a successful theory, we require that it should explain, jointly, the facts on the tax rate, tax gap and the level of government expenditure. We find that when taxpayers use EUT (respectively, PT) and the optimal tax is derived from a social welfare function that also uses EUT (respectively, PT), then, the calibration results are completely at odds with the facts. However, when taxpayers use PT but the social welfare function uses standard EUT, there is a very close match between the predictions and the facts. This has important implications for context dependent preferences but also for the newly emerging literature on liberalism versus paternalism in behavioral economics.Prospect theory; Expected utility theory; Tax evasion; Optimal taxation; Normative versus positive economics; Context dependent preferences; Liberalism; Paternalism

EQUITY-PREMIUM PUZZLE: EVIDENCE FROM BRAZILIAN DATA

This paper uses 1992:1-2004:2 quarterly data and two diferent methods (approximation under lognormality and calibration) to evaluate the existence of an equity- premium puzzle in Brazil. In contrast with some previous works in the Brazilian literature, I conclude that the model used by Mehra and Prescott (1985), either with additive or recursive preferences, is not able to satisfactorily rationalize the equity premium observed in the Brazilian data. The second contribution of the paper is calling the attention to the fact that the utility function calculated under the discrete-state approximation may not exist if the data (as it is the case with Brazilian time series) implies the existence of states in which high negative rates of consumption growth are attained with relatively high probability.

Optimal Taxation in an RBC Model: A Linear-Quadratic Approach

We reconsider the optimal taxation of income from labor and capital in the stochastic growth model analyzed by Chari et al. (1994, 1995), but using a linear-quadratic (LQ) approximation to derive a log-linear approximation to the optimal policy rules. The example illustrates how inaccurate "naive" LQ approximation --- in which the quadratic objective is obtained from a simple Taylor expansion of the utility function of the representative household --- can be, but also shows how a correct LQ approximation can be obtained, which will provide a correct local approximation to the optimal policy rules in the case of small enough shocks. We also consider the numerical accuracy of the LQ approximation in the case of shocks of the size assumed in the calibration of Chari et al. We find that the correct LQ approximation yields results that are quite accurate, and similar in most respects to the results obtained by Chari et al. using a more computationally intensive numerical method.

A new comparative approach to macroeconomic modeling and policy analysis

In the aftermath of the global financial crisis, the state of macroeconomic modeling and the use of macroeconomic models in policy analysis has come under heavy criticism. Macroeconomists in academia and policy institutions have been blamed for relying too much on a particular class of macroeconomic models. This paper proposes a comparative approach to macroeconomic policy analysis that is open to competing modeling paradigms. Macroeconomic model comparison projects have helped produce some very influential insights such as the Taylor rule. However, they have been infrequent and costly, because they require the input of many teams of researchers and multiple meetings to obtain a limited set of comparative findings. This paper provides a new approach that enables individual researchers to conduct model comparisons easily, frequently, at low cost and on a large scale. Using this approach a model archive is built that includes many well-known empirically estimated models that may be used for quantitative analysis of monetary and fiscal stabilization policies. A computational platform is created that allows straightforward comparisons of models’ implications. Its application is illustrated by comparing different monetary and fiscal policies across selected models. Researchers can easily include new models in the data base and compare the effects of novel extensions to established benchmarks thereby fostering a comparative instead of insular approach to model development