Browsing by Author "Baharumshah, Ahmad Zubaidi"

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Open Access
US-China trade and exchange rate dilemma: The role of trade data discrepancy
(Te Herenga Waka—Victoria University of Wellington, 2016) Shaar, Karam; Baharumshah, Ahmad Zubaidi
The US and China report substantially different figures regarding their trade with each other. Empirical studies suggest that neither the US nor China can be solely blamed for this discrepancy. Previous empirical studies investigating the effects of Yuan depreciation on US-China trade largely retrieved the data from one side only without even citing which side it is. This study extends the literature regarding the dynamic effects of exchange rate on trade balance, known as the J-Curve Theory, by employing the trade data reported by the US and China independently in empirical assessment. We tested 38 trade commodities over the period 1987-2012 and found that: (i) discrepancy in trade data affects the accuracy of testing the J-Curve considerably. (ii) the coefficients suggesting that Yuan depreciation increases the US bilateral trade deficit with China seem much less inconsistent compared with the coefficients claiming the opposite. This applies to short and long run. We propose Mutual Confirmation as a robustness check for the empirical assessment of the J-Curve Theory.
Open Access
US-China trade: Who is telling the truth?
(Te Herenga Waka—Victoria University of Wellington, 2016) Shaar, Karam; Baharumshah, Ahmad Zubaidi
Econometric studies investigating the US-China trade have largely retrieved data from one side only, mainly the US. There is a considerable difference between what each partner claims to have actually traded with the other. In 2013, the US-reported trade deficit with China was $346.3 billion, while the figure stood at $215.7 billion according to China’s reports, which accumulates merely 62% of the former’s claim. To answer the question of which data source is more reliable for research purposes, we assess the dynamic magnitude of the discrepancy for the period 1984-2013 and review the causes behind it. Through grouping the causes into two categories based on the causative factors, this study concludes there is no enough evidence to trust the data of one side more than the other. We highly encourage more in-depth studies to reconcile the data. Researchers who still prefer to utilize unreconciled data are recommended to express more caution.