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Serena Ng
Researcher at Columbia University
Publications - 187
Citations - 28024
Serena Ng is an academic researcher from Columbia University. The author has contributed to research in topics: Estimator & Unit root. The author has an hindex of 58, co-authored 187 publications receiving 25829 citations. Previous affiliations of Serena Ng include National Bureau of Economic Research & University of Michigan.
Papers
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Journal ArticleDOI
Looking for evidence of speculative stockholding in commodity markets
TL;DR: In this paper, the authors look for evidence of nonlinearity in the price data and test the theory in the context of threshold autoregressive models under the assumption that shocks to harvest are i.i.d.
Journal ArticleDOI
The ABC of simulation estimation with auxiliary statistics
Jean-Jacques Forneron,Serena Ng +1 more
TL;DR: It is shown that an ideal ABC estimate can be obtained as a weighted average of a sequence of SMD modes, each being the minimizer of the deviations between the data and the model.
Book
Understanding and Comparing Factor-Based Forecasts
Jean Boivin,Serena Ng +1 more
TL;DR: In this paper, the authors assess the extent to which the forecasts are influenced by how the factors are estimated and/or how the forecast is formulated, and find that for simple data-generating processes and when the dynamic structure of the data is known, no one method stands out to be systematically good or bad.
Journal ArticleDOI
Testing for unit roots in flow data sampled at different frequencies
TL;DR: In this paper, the authors examined five unit root tests which correct for serial correlation and found the power of some tests not to be monotonic in the span of the data.
Journal ArticleDOI
The Risky Spread, Investment, and Monetary Policy Transmission: Evidence on the Role of Asymmetric Information.
Serena Ng,Huntley Schaller +1 more
TL;DR: In this article, the authors used Canadian panel data to show that shocks to net worth, as reflected in the risky spread and firm-specific balance sheet variables, can dramatically increase the shadow cost of finance.