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Presented by PAWIN SIRIPrapanukul Nichchapat Kanjanaudomkan Worapak thitadilok. Predictive Performances of Export Business Index in Predicting Thai Export. At Thammasat University. Introduction.
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Presented by PAWIN SIRIPrapanukul NichchapatKanjanaudomkan Worapakthitadilok Predictive Performances of Export Business Index in Predicting Thai Export At Thammasat University
Introduction • Goal: To measure predictive performance of Export Business Indices in comparison with other popular macroeconomic indicators • Predictive performance in predicting: • Thai-export contraction phrases • Thai-export value • Out-of-sample evaluation
Research Methodology • Part 1: Predicting Thai-Export Contraction Phrase 1a) Identifying contraction phrases of Thai Export 1b) The Probit Model – to identify variables that can best predict such phrases • Part 2: Predicting Thai-Export Value A dynamic model – to identify variables that can best predict the value of Thai Export
Research MethodologyPart 1: Predicting Thai-Export Contraction Phrase 1a) Identifying contraction phrases of Thai Export • Let be binary contraction indicator • Peaks & Troughs : NBER Method or Bry-Boschan algorithm -- Estrella and Mishkin(1998), Diebold and Rudebusch(1991), Karunaratne(2002), Birchenhall, Osborn and Sensier(2001) -- X-12 program to remove seasonal components -- Harding and Pagan (1999) and Harding and Pagan (2002) : the trend component plays an important part in generating cyclical movement -- Apply Bry-Boschan algorithm to the Export Level
Research MethodologyPart 1: Predicting Thai-Export Contraction Phrase 1b) The Probit Model – to identify variables that can best predict Thai-Export contraction phrase • Estrella and Mishkin(1998) • Probit model with an independent variable xt forecast horizon h =1, 3, 6, 9 and 12 months Log likelihood value Lm • Out-of-sample test
Research MethodologyPart 1: Predicting Thai-Export Contraction Phrase • Benchmark: Probit model with only constant Log likelihood value Lc • Measure of accuracy
Research MethodologyPart 2: Predicting Thai-Export Value A Dynamic Model – to identify variables that can best predict the value of Thai Export • Stock and Watson (2003) -- seek the incremental predictive performance from the basic autoregressive model that each indicator contributes • Diebold(1998) -- AR model frequently outperforms Keynesian-based structural model in Out-of-Sample predictions • AR model with an independent variable xt forecast horizon h =1, 3, 6, 9 and 12 months • Out-of-sample test
Research MethodologyPart 2: Predicting Thai-Export Value • Benchmark : AR model without an independent variable forecast horizon h =1, 3, 6, 9 and 12 months • Measure of accuracy
Data • Monthly Data : 2001:m12 - 2011:m5 • Dependent variable : • The probability of Thai Export falling into a contraction phase • The value of Thai export
Data Independent Variables : Group 1
Data Independent Variables : Group 2
Data Independent Variables : Group 2
Data Independent Variables : Group 2
Results • The Results of Identifying Thai-Export Contraction Phases
Results • Predicting • Thai-Export Contraction Phases • : Predictive • Performances • (Pseudo R2)
Results • The List of Best Predictors of Thai-Export Contraction Phrases for Each Forecast Horizon
Results • Predicting • Thai-Export Value • : Predictive • Performances • (Relative MSFE)
Results • The List of Best Predictors of Thai-Export Value for Each Forecast Horizon
Conclusions • Common leading indicators are better predictors of Thai Export (both its contraction phrase and value) than Export Business Indices • Growth of Import Price Index is the best performing indicator in most cases. • Export Inventory Index is the only Export Business Index that outperforms common leading indicators only in the case of 12-month ahead forecast.
Conclusions • An important limitation : Limited number of data • Export Business Indices -- firstly constructed in Dec 2001 • Out-of-sample forecast technique only 50 months of data for evaluation
Future Work ฟ้าไม่แน่ใจว่าอาจารย์จะใส่ part นี้เข้าไปด้วยรึเปล่าค่ะ