PhD with specialization in Statistics and Econometrics (UWA, 2012)

An electronic copy of my current CV is available here, otherwise please see some information about my research and teaching below. 

 Current Position: 
 Lecturer in Economics
 
 Contact Details:
 Newcastle University Business School
 5 Barrack Road
 Newcastle-upon-Tyne
 NE14SE UK
 Email: patrick.wongsa-art@ncl.ac.uk

Teaching (at Newcastle University Business School)
NBS8257 Applied Econometrics (Semester 2: 2015)

Teaching (at Mathematics and Statistics, University of Canterbury)
STAT201/FORE222 Applied Statistics(Semester 1: 2012, 2013, 2014)
STAT470 Advanced Time Series (Financial Econometrics), (Semester 2: 2013, 2014)
STAT317/STAT425 Time Series Methods (Semester 2: 2012, 2013, 2014)
ECON323 Time Series Methods (Semester 2: 2012, 2013, 2014) 
EMTH119 Engineering Mathematics (Semester 2: 2013, 2014)
MATH407 Mathematical Finance (Semester 2: 2012)

Other teaching
Mathematical Economics (UG: 2010 University of Adelaide)
Mathematical Statistics (UG: 2010 University of Adelaide)
Introductory Econometrics (UG: 2011 Monash University, 2005 Lincoln University)
Advanced Macroeconomics (PG: 2005 Lincoln University)
  



 
 

 

  

 

 
 
 
 
 

Research Interest:

I have a strong interest in statistical methods and their applications to data and problems in Economics and Finance. My research specialty lays in the following areas of statistics: (1) Semiparametric/Nonparametric Statistics; (2) Time Series Analysis; (3) Longitudinal Data Analysis; (4) Functional Data Analysis; and (5) Functional Time Series.


I have applied these techniques in various areas of research in Economics and Finance. Some selected projects are as follows.

  • "Asymmetric Conditional Correlations in Stock Returns"  This project investigates the driving forces behind the time-varying behavior of co-movements of the Dow30 returns.
  • "Volatility Modeling and Forecasting" This project introduces a new tool to estimate the functional volatility process and to perform volatility forecasting.
  • "Contagion in International Stock Markets" This project develops a new tool for analyzing the correlations of international returns during turbulent periods compared to prosperous times and how they changes over time. 
  • "Measuring Intensity of Price Changes as an Alternative Measure of Price Variation" This project develops a new tool for testing the distribution of the waiting times between price changes in the NYSE as an alternative measure of price variation.
  • "Modeling the Temporal Dependence and Forecasting of Yield Curves with Functional Time Series Approach" This project views the Yield Curves as curve time series and model their temporal dependence in a stationary framework in a Hilbert space.
  • "Modeling Monetary Policy in a Small Open Economy" This project focuses on building a multivariate time series model to explain the effects of monetary policy on the New Zealand economy.



Publications and Publication in Progress

  • Shape invariant analysis of regression curve under endogeneity with application to empirical engel curves, Working Paper. Paper  (Submitted) (N. Kim) 
  • Asymmetric Conditional Correlations in Stock Returns, Annals of Applied Statistics 2016, forthcoming (Y. Xia and H. Jiang) Paper
  • A misspecification test for multiplicative error models of nonnegative time series, Journal of Econometrics 2015, 189(2), 346-359. (J. Gao and N. H. Kim) Paper SuppMaterial 
  • Semiparametric Methods in Nonlinear Time Series Analysis, Journal of Nonparametric Statistics 2014, 26(1), 141-169. (J. Gao and N. H. Kim) Paper
  • Semiparametric Autoregressive Conditional Duration, Econometric Reviews 2015, 34(6-10), 849-881. (J. Gao and D. Allen)
  • Modeling Monetary Policy in a Small Open Economy Model: Evidence from a SVAR Model, Economia Internazionale 2004, 57(1), 77-115. (B. D. Ward)

Working Paper Stage:

  • Forecasting of Return Correlation under Functional Time Series Framework, Working Paper
  • Optimal Bandwidth in Semiparametric Regression with Generated Regressors, Working Paper. (N. H. Kim)
  • Semiparametric Partially Model with Endogeneity, Working Paper. (N. H. Kim)


Papers in Progress:

  • Modeling the Temporal Dependence and Forecasting of Yield Curves with Functional Time Series Approach (N. Viegi and G. Fazio)
  • Modeling Spatial Dependence in Functional Data Analysis: A New Approach to the Longitudinal Data (P. Robinson)