Omid M. Ardakani, assistant professor of economics, completed his Ph.D. in Economics at the University of Wisconsin-Milwaukee in 2015. Ardakani’s research has been published in leading journals such as International Statistical Review, Journal of Economic Dynamics and Control and Studies in Nonlinear Dynamics and Econometrics. In 2018, Ardakani was named the Shirley and Philip Solomons, Sr. research fellow for the Department of Economics at Georgia Southern University. Ardakani is founding director of Georgia Southern’s Statistics and Econometrics Research Group (SERG).
Areas of Expertise (4)
Solomons Research Fellow Award
2018 Georgia Southern University
Shirley and Philip Solomons, Sr. Faculty Development Award
2017 Armstrong State University
Research and Scholarship Grant
2016 Armstrong State University
National Bureau of Economic Research Travel Award
Summer Research Grant, Department of Economics
Armstrong State University 2016
University of Wisconsin-Milwaukee: Ph.D, Economics 2015
University of Tehran: M.A., Economics 2009
Yazd University: B.A., Economics 2006
- American Economic Association
- Econometric Society
- American Statistical Association
Ardakani, Omid M., N. Kundan Kishor, and Suyong Song
2018 This paper estimates the treatment effect of inflation targeting on macroeconomic variables using a semiparametric single index method by taking into account the model misspecification of parametric propensity scores. Our study uses a broader set of preconditions for inflation targeting and macroeconomic outcome variables than the existing literature. The results suggest no significant difference in the inflation level and inflation volatility between targeters and non-targeters after the adoption of inflation targeting. We find that inflation targeting reduces sacrifice ratio and interest rate volatility in the developed economies, and that it enhances fiscal discipline in both the industrial and developing countries.
Ardakani, Omid M., Nader Ebrahimi, and Ehsan S. Soofi
2018 The stochastic error distance (SED) introduced by Diebold and Shin (2017) ranks forecast models by divergence between distributions of the errors of the actual and perfect forecast models. The basic SED is defined by the variation distance and provides a representation of the mean absolute error, but by basing ranking on the entire error distribution and divergence, the SED moves beyond the traditional forecast evaluations. First, we establish connections between ranking forecast models by the SED, error entropy and some partial orderings of distributions. Then, we introduce the notion of excess error for forecast errors of magnitudes larger than a tolerance threshold and give the SED representation of the mean excess error (MEE). As a function of the threshold, the MEE is a local risk measure. With the distribution of the absolute error as a prior for the threshold, its Bayes risk is the entropy functional of the survival function, which is a known measure in the information theory and reliability. Notions and results are illustrated using various distributions for the error. The empirical versions of SED, MEE and its Bayes risk are compared with the mean squared error in ranking regression and autoregressive integrated moving average models for forecasting bond risk premia.
Ardakani, Omid M., and N. Kundan Kishor
2014 This paper analyzes the performance of central banks in 27 inflation targeting countries by examining their success in achieving their explicit inflation targets. For this purpose, we decompose the inflation gap, the difference between actual inflation and inflation target, into predictable and unpredictable components. We argue that the central banks are successful if the predictable component in the inflation gap diminishes over time. The predictable component of inflation gap is measured by the conditional mean of a time-varying autoregressive model. Our results find considerable heterogeneity in the success of these IT countries in achieving their targets at the start of this policy regime. Our findings also suggest that the central banks of the IT adopting countries started targeting inflation implicitly before becoming an explicit inflation targeter. The panel data analysis suggests that the relative success of these countries in reducing the gap is influenced by their institutional characteristics particularly by fiscal discipline and macroeconomic performance.