I
Ivana Komunjer
Researcher at University of California, San Diego
Publications - 53
Citations - 2127
Ivana Komunjer is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Quantile & Estimator. The author has an hindex of 19, co-authored 53 publications receiving 1916 citations. Previous affiliations of Ivana Komunjer include University of California & California Institute of Technology.
Papers
More filters
Journal ArticleDOI
What Goods Do Countries Trade? A Quantitative Exploration of Ricardo’s Ideas
TL;DR: The Ricardian model predicts that countries should produce and export rela- tively more in industries in which they are relatively more productive as mentioned in this paper, which has received little attention in the empirical literature since the mid-1960s.
Posted Content
What Goods Do Countries Trade? A Quantitative Exploration of Ricardo's Ideas
TL;DR: The Ricardian model predicts that countries should produce and export relatively more in industries in which they are relatively more productive as mentioned in this paper, which has received virtually no attention in the empirical literature since the mid-sixties The main reason behind this lack of popularity is the absence of clear theoretical foundations to guide the empirical analysis.
Journal ArticleDOI
Evaluation and Combination of Conditional Quantile Forecasts
TL;DR: In this paper, an encompassing test for comparing conditional quantile forecasts in an out-of-sample framework is proposed, which provides a basis for forecast combination when encompassing is rejected.
Journal ArticleDOI
Biases in Macroeconomic Forecasts: Irrationality or Asymmetric Loss?
TL;DR: This paper showed that existing rationality tests are not robust to even small deviations from symmetric loss and hence have little ability to tell whether the forecaster is irrational or the loss function is asymmetric.
Journal ArticleDOI
Evaluation and Combination of Conditional Quantile Forecasts
TL;DR: In this paper, the authors proposed a method for comparing and combining conditional quantile forecasts based on the principle of "encompassing", which is a test of superior predictive ability, constructed as a Wald-type test on the coefficients of an optimal combination of alternative forecasts.