Exchange Rates Responses to Macroeconomic

Exchange Rates Responses to Macroeconomic Surprises: Evidence from the Asia-Pacific Markets Yuen Meng Wong1*, Mohamed Ariff2 and Rubi Ahmad1 1

University of Malaya, Kuala Lumpur, Malaysia 2 Bond University, Queensland, Australia Abstract

This paper reports new findings from Asia-Pacific economies on exchange rate revisions following macroeconomic shocks. Regional macroeconomic shocks are as important as the U.S. macroeconomic shocks in affecting exchange rate returns. All Asia-Pacific currencies with the exception of Thai baht react significantly to local macroeconomic shocks. Australian dollar is identified as the most elastic currency responding to macroeconomic shocks, and is more responsive than the Japanese yen. Interest-rate related shocks are generally the most influential events. We provide a ranking list on the relative impact sensitivity of macroeconomic shocks. The announcement effect of the U.S. open market actions via Fed Rate revisions is recognised as the most significant event among the 107 macroeconomic announcements examined.

Keywords: Macroeconomic shocks, Exchange rates, Asia-Pacific currencies, Economic events JEL Classification: E44, F31, G15

1.0 Introduction As more countries are opening up their economies and moving towards a variation of floating exchange rate regimes, the study of the exchange rate reactions to macroeconomic surprises is a topic worthy of another study. The value of a currency, in the long run, should be a reflection of economic fundamentals. What is the nature of the local macroeconomic shocks remains unidentified since what aspect(s) of the shocks affect the exchange rates are not yet studied especially in markets operating under floating exchange rate regimes. The purchasing power parity (PPP) theory suggests that inflation increases erode currency value, so it depreciates currency value. The reaction response function (Almeida et al., 1998) hypothesises that the central bank will hike interest rate in response to situations of rising inflation. Market participants will likely front-run the central bank by buying a currency in anticipation of a rise in interest rate. More empirical evidence is needed before one can reach a comfortable level of agreement on claims of alleged effects. What then does this paper offer? The 12 Asia-Pacific countries explored are: Australia, China, India, Indonesia, Japan, South Korea, Malaysia, New Zealand, Philippines, Singapore, Taiwan and Thailand. The currencies of these nations are quoted against U.S. dollar (USD), so the macroeconomic data from the U.S. are also included. A number of research questions are investigated. Are currencies more reactive to U.S. macroeconomic shocks as compared macroeconomic shocks arising from domestic information? Which currency is most elastic to macroeconomic surprises? Which macroeconomic announcement has the largest impact on the exchange rates? Using Asia-Pacific countries as a core sample, the results provide answers to these questions in a region of very high trade linkages that encourage currency transactions. Prior studies are few on these questions since such studies are dated and refer to one or two economies.

* Corresponding author. Email address: [email protected]

The rest of the paper is organised as follows: Section 2 contains a brief review of literature to enable meaningful hypotheses to be framed. In Section 3 there is description of the dataset along with briefs on the heterogeneity of foreign exchange markets in our tested economies. The research design and methodology are described in Section 4. Section 5 presents the research findings bearing important practical implications. The last section concludes the paper.

2.0 Related Literature and Research Hypotheses Almost a century of research has contributed richly to policy discussions on exchange rate. However, our review starts with a seminal papers (Meese & Rogoff, 1983): surprisingly, it claims that macroeconomic fundamentals can hardly predict exchange rates movements in the 1970s. Known structural exchange rate models fail to beat a naive random walk model in predicting the exchange rates. This conclusion is very robust, and is able to withstand the test of time. Cheung et al. (2005) use the exchange rates since the 1990s to reach more or less a similar conclusion. This phenomenon of why structural change does not affect currency has come to be known as the fundamental disconnect puzzle. It is considered as one of six major puzzles in international macroeconomics (Obstfeld & Rogoff, 2000). Having learned that it is grim task to fabricate a universally acceptable exchange rate model, many researchers shifted their effort instead to identifying the impacts of the macroeconomic shocks on the exchange rates. Through this about turn, it is hoped that the relationship between the macroeconomic fundamentals and the exchange rates can be better understood. That started a movement. Simpson et al. (2005), Murphy & Zhu (2008) and Mun (2012) report exchange rates react significantly to macroeconomic surprises. Simpson et al. (2005) is an early attempt on exchange rate reaction to macroeconomic events. They find evidence in support of the Mundell-Fleming balance of payment (BOP) approach to exchange rate determination. Exchange rates do not respond to the macroeconomic surprises as dictated by the purchasing power parity (PPP). Rather, as in Murphy & Zhu (2008) exchange rates react against the dictation of PPP to the macroeconomic surprises. They suggest that the investors’ expectation shift follows some domestic or international economic conditions. A rising inflation would likely induces policy makers to slow down inflation by hiking the domestic interest rate, which would lead to a higher currency value consistent with the international Fisher Effect. Hence, the information effect is more complex. Mun (2012), in studying the joint impact of the macroeconomic shocks on the stock and currency markets, reports the reactions of the Japanese yen (JPY) to the macroeconomic shocks. The effects are consistent with economic theories or monetary approach to exchange rate model, or inflation convergence hypothesis or even and portfolio balance approach. He also finds that the shocks emanating from the U.S. are more dominant on non-US markets compared to those from Japan. Most monetary transactions are based on USD, so this finding is unsurprising. The value of JPY against the USD is significantly affected by inflation, interest rate changes and also money growth shocks from the U.S. as well as just the monetary shock from Japan (as observed in 2013 by traders after the monetary easing by Bank of Japan). Cai et al. (2009) claims that U.S. origin shocks are more significant than domestic origin shocks. This leads us to hypothesise that the Asia-Pacific exchange rates are more likely to be responsive to the macroeconomic shocks from the U.S. than those from the region or domestic economy (Hypothesis 1). As is the case with Japan, all the economies in our study are pretty highly exposed to the USD.

Cai et al. (2009), Edwards & Levy-Yeyati (2005) and McKibbin & Chantaphun (2009) shows that emerging market currencies are becoming responsive to shocks. Indonesian rupiah (IDR) and Korean won (KRW) were immune to macroeconomic shocks in the early 2000s: yet these have become more responsive since the middle of 2000s. This observation could be due to the gradual opening up of the economies of the emerging markets. Currencies under flexible exchange rate regime are better absorbers of macroeconomic shocks and hence more elastic to shocks: this along with McKibbin & Chantaphun’s (2009) findings advocate flexible exchange rate regime to be superior to fixed exchange rate regime in this regard. Therefore our hypothesis two takes the position that the currencies under the more flexible exchange rate regime to be more elastic in responding to the macroeconomic shocks (Hypothesis 2). Levy-Yeyati & Sturzenegger (2005) point out that the monetary authority might profess one exchange rate regime but practise another regime: see Moosa (2009) for a similar argument on stock prices. We classify the exchange rate regimes based on the defacto practice in the particular currency market. Next, the existing literature has not yet reached a consensus on which of the macroeconomic shocks has the most impact. Pearce & Solakoglu (2007) find that the shocks from the U.S. non-farm payroll have the largest effect among macroeconomic shocks on the Deutsche mark and the JPY. Shocks related to the real economy such as Industrial Production (IP) and Durable Goods Order (DGO) are generally significant. Almeida et al. (1998) and Andersen et al. (2003) report that shocks from NFP carry the largest impact. Almeida et al. (1998) use DEM while Andersen et al. (2003) use a variety of advanced countries. Simpson et al. (2005) report that shocks from U.S. Treasury, Budget, Trade Balance and Capacity Utilization have the strongest impacts. Some studies exclusively examine monetary policy shocks. Fatum & Scholnick (2008) find exchange rates for DEM, JPY and GBP (united Kingdom) respond only to the surprise component in actual U.S. monetary policy shocks. Rosa (2011) goes a step beyond to decompose the monetary policy shocks from the FOMC announcement of Fed rate into two distinct components: (i) deeds and (ii) words of the FOMC. While the monetary action in hiking or cutting interest rate unexpectedly is highly likely to trigger a significant shock, Rosa shows that the shocks in the monetary policy statement accompanying the policy action contribute more to the exchange rate changes in EUR, GBP, CHF (Swiss), JPY and CAD (Canada). Surprises in policy statements accounted for 80 per cent of the explainable variations in exchange rate changes. Fischer & Ranaldo (2011) shows that FOMC announcement days significantly increase the trading volume in the USD by about 5 per cent. These findings collectively suggest that certain macroeconomic shocks matter more than some other macroeconomic shocks. From this extant literature, we hypothesise that the NFP and FOMC shocks should carry the largest impact on our sample currencies (Hypothesis 3).

3.0 Data 3.1 Exchange rates We selected 12 of the most active and significant Asia-Pacific economies. Their respective currencies: Australian dollar (AUD), Chinese yuan (CNY), Indian rupee (INR), Indonesian rupiah (IDR), Japanese yen (JPY), Korean won (KRW), Malaysian ringgit (MYR), New Zealand dollar (NZD), Philippines peso (PHP), Singapore dollar (SGD), Taiwan dollar (TWD) and Thai baht (THB). The USD is used as the central currency and the exchange rate data are obtained from the Datastream. The study period is from January 1,

1997 to December 31, 2010.1 The prime motivation for the currency choice is the fact that these currencies have yet been researched on macroeconomic shocks. Besides that, these countries are now the main engines of modest to high growth for the world in the period chosen. Table 1 is summary of key characteristics of these countries. (Table 1 about here) In view of the social and economic importance of this region to the peoples of this region, researchers perhaps must generate more studies using the now available data as the main focus. 2 The resulting research output could well help to play catch-up to the vast literature on developed countries. This region also provides a unique situation in which the countries are experiencing different developmental stages. There are some countries in the advanced status while most are in the developing stage. Perhaps for this reason, there is a wide variety of foreign exchange regimes that will be examined in this paper. (Figure 1 about here) On a scale of foreign exchange flexibility, the selected currencies spread evenly across this spectrum as shown in Figure 1. On the extreme left of the scale are fixed exchange rate regimes while the flexible regime is shown on the right. Fixed exchange rate currency regimes do not permit change in currency value to the chosen benchmark or anchor. In between these two extreme poles, there lies a wide variety of exchange rate regimes. The classification of our sample currencies is based on the IMF de facto classification of the exchange rate regimes of member countries. The resulting classification is: free-float regimes are AUD, JPY and NZD;3 most others are managed-float regimes, of which SGD is slightly skewed to the right of the scale because its currency is managed within a band of its nominal effective exchange rate (NEER); IDR, INR, KRW, MYR, PHP, THB and TWD are managedfloat regimes. MYR and IDR are not traded outside of their respective countries. Their values are determined by local market forces with active interventions from the authorities. CNY is categorised under crawling peg regime.4 This diversity of regimes in this research definitely enriches the resulting empirical findings. From a geographical perspective, this paper is a comprehensive study. 3.2 Macroeconomic Announcements We identified a total of 107 macroeconomic disclosures. The data on announcements are collected from the Bloomberg database. The main selection criterion is that the announcements are available as news as prior market consensus information related to actual announcements. This helps to filter out only vital surprise announcements as the only key indicators to attract investment community interest. The availability of market expectation 1

We exclude MYR exchange rates for the period from Sep. 1, 1998 to Jul. 21, 2005 because of its fixed peg to the USD during this period. Meanwhile, CNY is only included from Jul. 22, 2005 onwards after the abandonment of the fixed exchange rate regime in favour of a crawling peg. 2 Previous studies which look at the impact of macroeconomic news in the Asia-Pacific context focus on the stock and bond markets (e.g. Vrugt, 2009 and Andritzky, 2007). 3 These currencies are not entirely free-float because their central banks still intervene in the markets in very rare circumstances for a variety of reasons. Sometimes the interventions are made public but most of the times, the actions are carried out discretely. Perhaps that would make these dirty free-floats? 4 The People’s Bank of China (PBOC) determines the middle point of the CNY against USD at the start of each trading day and subsequently its value is allowed to fluctuate within a limited band.

data is also important to help us in extracting announcement surprises. The breakdown of the macroeconomic events from each individual country is shown in Table 2. (Table 2 about here) The macroeconomic announcements from the U.S. and Japan make up about 50 per cent of our total announcements. The rest of the countries contribute less than 10 per cent each to the total announcements. The U.S. and Japan are the world’s first and second largest economies, at over the test period. Therefore their announcements carry more clout. The announcements from the advanced economies are much more structured and consistent compared to those from developing nations. The numbers provide a modest to good size sample of sufficient observations. We group them into some common categories for meaningful comparison and analyses by the nature of information in disclosures. Three categories are created: (i) interest rates, prices and money (IPM); (ii) production and business activity (PBA); and (iii) total output, international trade and employment (TOITE). The first category, IPM, makes up 28 per cent, and refers to those indicators as monetary announcements as benchmark interest rates, inflation and money supply. The PBA includes industrial production, factory orders, retail sales and consumer confidence, which are indicators related to real economy: 36 per cent. TOITE refer to bigger scale indicators such as GDP, balance of trade and employment levels: 36 per cent. (Table 3 about here) Table 3 is a summary on announcements. The start dates of observations vary depending on data availability: the end dates are in 2010. The announcement related to the Taiwan interest rate has just 25 observations due to late start of data series. The announcement on the U.S. initial jobless claims has the highest number of observations at 707 because of its release on a weekly basis.

4.0 Research Design and Methodology Market clearing exchange rates should reflect relevant available information and the rates will only react significantly with the arrival of new unexpected information (Fama, 1970). The best proxy for new information in the foreign exchange market is the macroeconomic surprises. The event-study analysis (made famous by Ball and Brown) is applied to test for the reaction of exchange rates to surprise elements in forex relevant announcements. Any deviation of returns away from the expected return component is considered as surprise reactions to new information. This relationship is captured as in Equation 1. 𝑁𝑖,𝑡 = 𝐴𝑖,𝑡 − 𝐸𝑖,𝑡

(1)

where all the three variables in the equation are related to the macroeconomic indicator i; N is the unexpected component, A is the actual announcement and E is the market expected value. The unexpected component, N, is also known as ‘news’ or market forecast error. Fatum & Scholnick (2008) extoll the importance of conducting this decomposition as per Equation 1.

For the U.S. as well as for some developed country announcements, the market expectation component is relatively easy to compute sine the expected value are being willingly furnished by some institutions prior to announcements. This process could be a challenge for developing countries. In view of this, our macroeconomic shocks for the AsiaPacific countries are greatly constrained by this shortcoming. We use the same-day changes in the spot exchange rate to test for the responses of exchange rates to macroeconomic news. More specifically, we employ the following regression: ∆𝑠𝑡,𝑖 = 𝛼𝑖 + 𝛽𝑖 𝑁𝑗 ,𝑡 + 𝜀𝑡

(2)

where Δst,i is the changes in the log spot exchange rate for currency i recorded on the day of the announcement and 𝑁𝑗 ,𝑡 is the standardized unexpected components of j-th macroeconomic announcement while the ε is the regression residual. Equation 2 is estimated using an ordinary least square (OLS) regression with White’s heteroscedasticity-consistent standard errors and covariance. The unexpected elements of a macroeconomic announcement are standardized by dividing the variable N’s by their respective standard deviations: Equation 3: 𝑁𝑗 ,𝑡 =

𝐴𝑖,𝑡 −𝐸𝑖,𝑡 𝜎𝑗

(3)

With this standardization, the estimated β coefficient is to be interpreted as the percentage change in exchange rate to one standard deviation shock in the macroeconomic announcements. Regression Equation 2 is also used to test for market efficiency (e.g. Almeida et al., 1998 and Andersen et al., 2003). The market is efficient if the estimated α is not significantly different from zero.5 The focus of this paper is on the estimated β shock on exchange rates are measured. We run the above regressions for each macroeconomic announcements: we also do a pooled regression. For the individual exchange rate series, we run a total of 1,284 regressions (12 exchange rates series times 107 macroeconomic indicators). In the pooled analysis, we conduct 107 regressions (107 macroeconomic indicators). 4.1 U.S. and Domestic Macroeconomic Shocks and Their Ranking As our currencies are all quoted in USD, we treat the U.S. macroeconomic announcements separately from other Asia-Pacific announcements. The relationship between U.S. macroeconomic shocks and its exchange rates are quite well researched and have been systematically documented (Pearce & Solakoglu, 2007; Almeida et al., 1998 for different test periods). The domestic macroeconomic shocks on exchange rates are not that well-researched as in this comparison paper. 6 There is no clear original contribution on domestic macroeconomic shocks on exchange rates of small economies. Cai et al. (2009) is the closest literature on the emerging markets macroeconomic shocks. This paper is distinct from theirs because of the vastly different set of currencies, more announcements and longer time period used here.

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The results for the estimated α’s are not reported here. We find that most of the estimated α’s from the total of 1,284 regressions are generally not significant. With the exception of CNY and PHP, all of the other currencies report less than 20 significant α’s. Therefore the currency markets are generally efficient and consistent with the findings in Almeida et al. (1998) and Andersen et al. (2003). 6 Some of the more notable papers which study the effects of emerging market macroeconomic shocks on exchange rates are Cai et al. (2009) and Menkhoff & Schemeling (2008).

Under the U.S. macroeconomic events, we measure the relative impact of their surprise effects on exchange rates. The extent of the shocks is identified by the number of currencies they have significantly impacts on. The shock which impacts the highest number of currencies is considered the most influential. Which of the Asia-Pacific currencies are the most elastic in reacting to these macroeconomic surprises is also examined. The currency which reacts to the highest number of macroeconomic surprises is considered the most elastic. For the domestic macroeconomic shocks, we conduct the same analyses as we have done for the U.S. macroeconomic surprises. We identify the most influential domestic macroeconomic shocks to find out which Asia-Pacific currencies are the most responsive to the surprise announcements. Finally, we combine all the U.S. and domestic macroeconomic shocks for a pooled regression analysis by pooling all 12 Asia-Pacific currencies using a two-stage least square (2LS) regression to estimate Equation 2. Our focus here is to estimate β for each macroeconomic shock. Since the surprises are standardized with their respective standard deviations, the estimated β is comparable to each other. The resulting β estimate is interpreted as the magnitude of change in the pooled exchange rates to one standard deviation shock from macroeconomic surprises. We sort the estimated beta from the pooled regressions according to their absolute t-statistics value. The impact of the macroeconomic shocks should not be naively measured based on the magnitude of the estimated β because the standard error of estimate may distort their comparison with one another. The sorted list provides us with a ranking of the most significant macroeconomic shocks in terms of their relative impact to the Asia-Pacific exchange rates. This is a novel approach and the ranking is one of the major contributions of this paper to the literature. 4.2 Diagnostic Checks and Robustness Tests 4.2.1 Diagnostic Checks Since the data are used in OLS regression, it is important to conduct some of the relevant diagnostic checks to avoid spurious findings. The first check is on stationarity property of the variables, using changes in the spot exchange rates and the surprise components of the macroeconomic announcements. We use the augmented Dickey-Fuller (ADF) test to examine the existence of unit roots since failure to uphold stationarity would make it unsuitable for OLS regression. We correct for the potential heteroscedasticity and autocorrelation in the standard error of estimates by employing White’s robust standard error. We assess the stability of the estimated coefficients through the Ramsey’s RESET test. Finally, we also examine the R-square statistics to gauge goodness-of-fit of the model. However, we do not expect an impressive R-square statistics, as the extant literature have shown, the fundamentals can only explain a small variation of the exchange rate dynamic (e.g. Sarno, 2005) especially with differenced series. 4.2.2 Robustness Tests There are two robustness tests. These robustness tests are only conducted on the pooled exchange rates regressions, and not on individual currency regressions. The diagnostic checks would have ensured the robustness of the results of the individual currency regression. The exchange rates are all quoted in terms of domestic currency per unit of USD (direct quote) and the relative changes are obtained by taking the log differences between two daily observations. This measure may cause biasedness as each exchange rate is quoted in their

respective currency units. We converted the quoted rates to the USD for the value of one unit of the Asia-Pacific currencies. That means the Asia-Pacific currencies are now the numeraire currencies and the USD the term currency. Regression Equation 2 is conducted once more with the change in the quotation units in tests for robustness. The second robustness test involves the changes in the estimation technique of the pooled exchange rate regression. Instead of running a 2LS regression, we rearranged the pooled exchange rate sample into a system format to conduct a seemingly unrelated regression (SUR) to estimate the β values using Equation 2 for each macroeconomic announcement. The ranking list is produced once more and it is used to compare against the ranking list from the main results to see whether the order of events turns out to be the same.

5.0 Empirical Results and Interpretations The focus of this study is on the relative impacts of macroeconomic surprises on the exchange rates. Only the estimated βs in Equation 2 are reported. The magnitude and direction of the exchange rate reactions are only discussed scantily as these areas are considered out-of-scope. We look at the impacts of the U.S. macroeconomic surprises first and then turn to domestic macroeconomic surprises and still later to the joint comparison of all the macroeconomic surprises. 5.1 Impact of United States Macroeconomic Shocks As the largest economy in the world, the announcements made in the U.S. are keenly watched and studied by a sizeable number of interested groups (Simpson et al., 2005). The data from the U.S. are also more carefully recorded and made widely available. Most of these macroeconomic announcements also contain market expectations data. We accessed 33 macroeconomic announcements, and expect most announcements to have significant effect. The estimated beta indicates that the impact of one standard deviation shock in a U.S. macroeconomic announcement on the respective Asia-Pacific exchange rates. The results of the estimated βs for the U.S. macroeconomic shocks are reported in Table 4. (Table 4 about here) A positive beta value indicates appreciation of USD (depreciation of the particular Asia-Pacific currency) and a negative, otherwise. Beta estimates which are significant at the minimum 0.10 level are in bold. Four interesting observations emerge from Table 4. First, out of the 33 U.S. macroeconomic shocks, about 79 per cent show significant impact on at least one currency. That is an U.S. event is indeed important for Asia-Pacific exchange rates. Second, the macroeconomic surprises are mostly not homogenous across all Asia-Pacific countries as the sign of the beta estimates among the currencies are usually different from one another for each shock. The exceptions to this observation are the surprises in the Federal Fund Reserve (FFR) rate, Advance Retail Sales and Trade Balance which show a unanimous sign in the estimated beta. Third, when compared, the responsiveness of the 12 currencies to U.S. shocks can be measured. The currency which responds to the highest number of macroeconomic shocks is deemed the most responsive. Figure 2 displays the assortment from the most to the least responsive currencies in the sample. The AUD and NZD are the most responsive currencies to the U.S. macroeconomic surprises: the reaction is significantly in 10 out of 33 events. This

is followed by JPY and SGD with seven significant events each. The currencies which are least responsive are THB and TWD. (Figure 2 about here) Naturally, one should note that the currencies which fall under the floating exchange-rate regime are more responsive than the currencies under fixed or some sort of managed-float regimes (Edwards & Levy-Yeyati, 2005). Our results support this intuition. Fourth, we extracted the most influential events from Table 4. The event which significantly impacts the highest number of currencies is deemed as the most influential. We selected theses events to present the results in Figure 3. There are seven U.S. macroeconomic announcements which show significant impacts on at least four currencies. The leader of them all is the FFR rate announcement shocks which impacted six currencies. Intuitively, the FFR rate shocks should be highly influential since interest rates (monetary policy) impact the prices of all financial assets across markets (Rosa, 2011). The fact that not all currencies react significantly to this all-important event could be a little mystifying at first glance. From a closer analysis, it is found that, all of the non-reactive currencies are tightly managed by their respective monetary authorities. These currencies are IDR, INR, KRW, PHP, SGD and TWD. Hence this explanation could demystify the finding. The other top U.S. events are Building Permits to which impacted on five currencies, followed by GDP Price Deflator, Import Price Index, Consumer Confidence, Empire Manufacturing and Change in Nonfarm Payroll. In the following section, we shall look at the impact of Asia-Pacific (ex-U.S.) events on the regional exchange rates. (Figure 3 about here) 5.2 Impact of the Domestic Macroeconomic Shocks There are studies showing domestic macroeconomic surprises are not as influential as the U.S. macroeconomic shocks on other exchange rates (e.g. Cai et al., 2009; Mun, 2012). This section presents our results on this issue. We used a total of 74 macroeconomic announcements from the region to test whether the exchange rates react to domestic macroeconomic surprises by running equation 2 for each exchange rate in the sample on each domestic macroeconomic surprise. Similar to sub-section 5.1, the results for the estimated βs are presented in Table 5. (Table 5 about here) The coefficients in bold letters denote significance at the minimum of 0.10 level of confidence. From a quick glance, the reader may notice that these events are significant in influencing the Asia-Pacific exchange rates. The domestic macroeconomic events are as important as the U.S. macroeconomic shocks. There are two noteworthy observations from Table 5. First, all of the currencies with the exception of THB react significantly to their own macroeconomic shocks. The AUD reacts significantly to six out of nine Australian macroeconomic shocks and the CNY reacts to one out of four Chinese macroeconomic shocks. Second, the surprises in the interest-rate-setting announcements are significant for most currency markets: these are significant in Australia, Indonesia, Malaysia, New Zealand and Philippines. Again, THB is not significantly affected. There are some sensible explanations for the THB. It could be due to the low level of surprises in the Thailand

macroeconomic announcements or perhaps there are leakages of information in the local market prior to the actual announcements. Andersen et al. (2003) also suggest the leakages of information in Germany’s macroeconomic announcements to explain the low number of significance among German events. How responsive the Asia-Pacific exchange rates are to domestic macroeconomic surprises? Using the number of significant events, or β, for each exchange rate, the results are graphed as in Figure 4. The AUD reacts significantly to surprises from 16 macroeconomic announcements from Asia-Pacific: this is followed by THB with 14 significant βs. The least responsive currency is the CNY with only six significant βs. First, the THB is a very reactive currency (being second in the ranking) to the Asia-Pacific macroeconomic surprises despite having no significant reaction registered for its own country surprises. The AUD remains the most responsive currency for macroeconomic surprises from local and foreign disclosures. (Figure 4 about here) Finally, from Table 5, we extracted the most influential macroeconomic surprises within the Asia-Pacific region by counting the number of currencies which registered significant β to the particular macroeconomic event. Figure 5 shows the selected regional macroeconomic surprises significantly affecting at least four currencies in the region. There are eight macroeconomic surprises. The Australia-Employment Change and the JapaneseTankan Large Manufacturers Index are the most influential events with each significantly affecting six currencies. This is followed by the Australia-RBA Cash Target, MalaysiaIndustrial Production, New Zealand-RBNZ Official Cash Rate and Taiwan-CPI with five currencies each. Lastly, the Japan-Large Retailers’ Sales and Malaysia-Overnight Rate significantly impact four currency exchange rates. (Figure 5 about here) There are two notable observations from Figure 5. First, out of the Top-8 domestic macroeconomic surprises, four events are interest-rate or monetary policy related. This finding implies that the interest-rate related surprises are not only important in their own respective countries but also have a far-reaching impact on currencies of other countries. Second, from the 12 countries, only 4 countries are represented in the Top-8 macroeconomic events. We expect the macroeconomic surprises from the larger and advanced economies to be more influential. Australia, Japan and Malaysia are represented by two events each while New Zealand and Taiwan by one each. It is noteworthy that Malaysia, a smaller economy relative to other countries, is represented by two events in the Top-8 events. Meanwhile, there is no macroeconomic shock from Singapore or China in the Top-8 events. 5.3 Ranking of Macroeconomic Shocks After looking at the set of macroeconomic surprises separately for each currency, we study all of the sample currencies collectively. We do this by running a pooled cross-section time-series regression using all currencies on each macroeconomic shock. By pooling all the currencies, we are able to determine the relative impact of the macroeconomic surprises to the currencies vis-a-vis the USD. Similarly, the values of the estimated βs are comparable to one another because the macroeconomic shocks have been standardised with their respective

standard deviations. We have sorted and ranked all the 107 macroeconomic events according to their relative significant impacts. The results of the ranking are presented under Table 6.7 (Table 9 about here) Only 43 surprises are significant in affecting exchange rates. This represents about 40 per cent of the total events: that is, the markets treat only to these as having impacts. We find four interesting observations. First, the Federal Fund Reserve (FFR) rate news is the most significant event. This is not surprising as this news has been shown as the event which significantly impacts the highest number of currencies as discussed in sub-section 5.2. This ranking result from pooling has vindicated our interpretation that the FFR rate announcement is the most widely-watched across the world. The second ranked event is the Reserve Bank of Australia (RBA)’s Cash Target Rate announcement. Third, the results here are contrasted with two findings in Simpson et al. (2005). They claim, that the news related to the Treasury Budget, Trade Balance and Capacity Utilization are the most important events whereas our results (for our test period) show that the interestrate setting announcements are the more important. Their key events are ranked much lower than the FFR rate announcement. Two, Simpson et al. (2005) also state that the news related to real economic growth has no significant impact on the exchange rates. We find opposing evidence to this assertion (for our test period). From the Top 10 events in our ranking of relative impacts, four are related to the Production and Business Activities (PBA) a proxy for real economic activities (U.S. Building Permits and Japan Industrial Production). These findings would have us suggest that the exchange rates are tied to the real economy which is also consistent with the results in Pearce & Solakoglu (2007). The fourth interesting point is related to the insignificant finding of the U.S. data on Change in Non-farm Payroll (NFP) announcements. This event has been widely reported as a very important event in affecting exchange rates (e.g. Almeida et al., 1998; Andersen et al., 2003 and Pearce & Solakoglu, 2007). Our result basically finds no support for this claim at least for our test period. Which of the country has the highest number of significant events on the Asia-Pacific exchange rates vis-a-vis the USD? The number of significant events experienced by each country is graphed in Figure 6. It shows that many of the significant macroeconomic surprises are from the U.S., namely 15 events. This is followed by Japan with nine significant events. This is more or less expected, in view of the large number of events selected from these two countries with 33 U.S. events and 20 events from Japan. Moving along this logical explanation, it is surprising to find that none of the New Zealand events are significant in influencing the collective Asia-Pacific currencies despite having a total number of six events in our sample. Even though the Reserve Bank of New Zealand (RBNZ)’s Official Cash Rate announcement affects five individual Asia-Pacific currencies, the collective impact of this announcement is insignificant when the sample currencies are pooled. This robustness test reveals that NZ falls out of influencing rank. (Figure 6 about here)

7

We report only the events which are significant at the minimum of 10% level. Full ranking list can be viewed from Table 7.

5.4 Diagnostic Checks8 and Robustness Tests We test for stationarity property in the OLS regression. It is found that all of the spot exchange rates changes and the macroeconomic news are stationary and hence they are all suitable to be used in the OLS regression analyses. The corrections for potential heteroscedascticity and autocorrelation have been made by adopting White’s robust standard error. The significance of the coefficient estimates is interpreted in a heteroscedasticity and autocorrelation-consistent manner. From the Ramsey’s RESET test, we do not find any evidence of model misspecification in all regressions. The goodness-of-fit of the model as evidenced by the R-square is miserably low, as expected. The reported R-square for most of the regressions is less than 1 per cent. It implies that the surprise elements of the macroeconomic announcements can hardly explain the daily changes in the exchange rates. It must, nevertheless, be noted that it is not the objective of this paper to devise a model which could explain the exchange rate dynamic. Two robustness tests are done to examine the validity and strength of our results as regards the ranking list. These tests are applied to the pooled exchange rates regressions and not on the individual exchange rate regressions. The first robustness test is conducted by changing the numeraire currency to domestic exchange rates whereby all the quotations are now made in terms of the USD. We do not find any marked differences from our main results and they are indeed qualitatively identical. The estimated βs are all consistent and the reported signs are also appropriately in reverse. The results related to the relative ranking of the macroeconomic surprises on the Asia-Pacific currencies are robust to the change in the numeraire currencies. The second robustness test is using a different estimation technique which is the seemingly unrelated regression (SUR) to come out with a ranking of the relative impact of the macroeconomic surprises. We find that the signs of the estimated beta for the two sets of results (between the 2LS and SUR) are consistent. This is an important finding supporting the inferences so far made with regards to the direction of the exchange rate changes as a result of the macroeconomic surprises. The overall order of the ranking changed with the alteration in the estimation technique. Even though the majority of the originally significant events remain significantly high on the alternative ranking list, the order of the ranking has changed quite dramatically. Therefore we caution that the results related to the ranking of the relative impact of the macroeconomic surprises must be interpreted with care and taken with a pinch of salt. The ranking results from the SUR are put up side-by-side with the results from the original 2LS regression under Table 7 for comparison. (Table 7 about here)

6.0 Conclusion This paper has the aim of studying the relative impacts of macroeconomic surprises on the 12 exchange rates in the less researched Asia-Pacific region with major economies included in this sample. Following three research questions are explored: (i) Are currencies more reactive to U.S. macroeconomic shocks than to domestic macroeconomic shocks?; (ii) Which currency is the most elastic to the macroeconomic surprises?; and (iii) Which macroeconomic announcement has the largest impact on the exchange rates? Using a simple 8

Results of the diagnostic tests are not reported because it involves a very large table. The results can be obtained from the authors upon request.

OLS regression (and 2LS regression for pooled sample) of same-day exchange rate changes on 107 macroeconomic surprises from the U.S. and domestic economies, this study makes some new contributions as insights in this topic area for a very recent period, when the Bretton Woods Agreement unravelled. The techniques used to arrive at the results are simple along with robustness testing. Key diagnostic checks and robustness tests thus ensured the findings are not spurious. There are five key results we wish to reemphasise in this conclusion. First, both the U.S. and regional/domestic macroeconomic shocks are also important for exchange rate returns. Close to 80 per cent of the selected U.S. macroeconomic shocks are significant in that these affect exchange rates. The impacts of these shocks are not homogeneous as shown by the different signs in the estimated beta coefficients. This finding could be due to the differences in the institutional characteristics, such as exchange rate regime, of these markets: heterogeneity is always a vexing factor. It could be due to different trade relationships between individual Asia-Pacific country and the U.S. economy. The lesson for the market is that Asia-Pacific currencies respond significantly to most of the macroeconomic shocks emanating from within the country or from the region from Japan and the U.S. Second, Thailand does not react at all to its own macroeconomic shocks but strongly to other regional macroeconomic shocks. Thailand’s macroeconomic shocks do affect other Asia-Pacific currencies. There may be information leakages in the Thailand market prior to the local macroeconomic announcements for this anomalous finding. Third, the AUD is the most responsive currency to U.S. and regional macroeconomic shocks. While THB is the second least responsive currency to the U.S. shocks, THB is the second most elastic currency to the regional macroeconomic shocks. The advanced country currencies (NZD, JPY and SGD) are usually more reactive to the U.S. shocks, but such trend is not so obvious among the regional macroeconomic shocks. It is also noted that freely-floated currencies (those currencies which are resided on the right of the scale in Figure 1) are generally more elastic to the macroeconomic shocks. Fourth, there are certain macroeconomic shocks which are more influential than others. The shocks from the U.S. Federal Open Market Committee announcements on the Federal Funds Reserve rate, the Australian employment shocks and the Japanese Tankan large manufacturing index are identified as the most influential fundamental factors among the 107 macroeconomic shocks. Each of these top shocks significantly affects at least six Asia-Pacific currencies respectively. The interest-rate announcement shocks from other countries such as Australia, New Zealand, Malaysia and Thailand are also influential on others as they respectively affect more than one currency in the region. Finally, in terms of relative impact to the Asia-Pacific exchange rates as a whole, the FOMC announcement on the FFR rate is singled out as the most significant of all. This is followed by the shocks in the Australian RBA rate announcement. This finding implies that the interest-rate (monetary) shocks are both influential and significant for the region’s exchange rate returns. The results relating to the rank order of the relative impact of the macroeconomic surprises must be interpreted with caution because of its failure to stay robust in alterative estimation technique.

References Almeida, A., Goodhart, C., & Payne, R. (1998). The Effects of Macroeconomic News on High Frequency Exchange Rate Behavior. The Journal of Financial and Quantitative Analysis, 33(3), 383-408. Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2003). Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange. The American Economic Review, 93(1), 38-62. Andritzky, J. R., Bannister, G. J., & Tamirisa, N. T. (2007). The impact of macroeconomic announcements on emerging market bonds. Emerging Markets Review, 8(1), 20-37. Cai, F., Joo, H., & Huang, Z. (May 15, 2009). The Impact of Macroeconomic Announcements on Real Time Foreign Exchange Rates in Emerging Markets Fedearal Reserves Board International Finance Discussion Paper, No. 973. Cheung, Y. W., Chinn, M. D., & Pascual, A. G. (2005). Empirical exchange rate models of the nineties: Are any fit to survive? Journal of International Money and Finance, 24(7), 1150-1175. Edwards, S., & Levy Yeyati, E. (2005). Flexible exchange rates as shock absorbers. European Economic Review, 49(8), 2079-2105. Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417. Fatum, R., & Scholnick, B. (2008). Monetary policy news and exchange rate responses: Do only surprises matter? Journal of Banking & Finance, 32(6), 1076-1086. Levy-Yeyati, E., & Sturzenegger, F. (2005). Classifying exchange rate regimes: Deeds vs. words. European Economic Review, 49, 1603-1635. McKibbin, W. J., & Chanthapun, W. P. (2009). Exchange Rate Regimes in the Asia-Pacific Region and the Global Financial Crisis. ADB Working Paper Series on Regional Economic Integration, Oct. 2009(No. 36). Meese, R. A., & Rogoff, K. (1983). Empirical exchange rate models of the seventies : Do they fit out of sample? Journal of International Economics, 14(1-2), 3-24. Menkhoff, L., & Schmeling, M. (2008). Local information in foreign exchange markets. Journal of International Money and Finance, 27(8), 1383-1406. Moosa, Imad, (2009). Modelling the behaviour of technicians and the fundamentalist in the Shanghai market. The International Journal of Banking and Finance, 2008/09 Vol. 6. Number 2: 2009: 1-36 Mun, K.-C. (2012). The joint response of stock and foreign exchange markets to macroeconomic surprises: Using US and Japanese data. Journal of Banking & Finance, 36(2), 383-394. Murphy, A., & Zhu, Y. (2008). Unraveling the complex interrelationships between exchange rates and fundamentals. Journal of Banking & Finance, 32(6), 1150-1160. Obstfeld, M., & Rogoff, K. (2000). The Six Major Puzzles in International Macroeconomics: Is There a Common Cause? NBER Macroeconomics Annual, 15, 339-390. Pearce, D. K., & Solakoglu, M. N. (2007). Macroeconomic news and exchange rates. Journal of International Financial Markets, Institutions and Money, 17(4), 307-325. Rosa, C. (2011). The high-frequency response of exchange rates to monetary policy actions and statements. Journal of Banking & Finance, 35(2), 478-489. Sarno, L. (2005). Viewpoint: Towards a solution to the puzzles in exchange rate economics: where do we stand? Canadian Journal of Economics-Revue Canadienne D Economique, 38(3), 673-708.

Simpson, M. W., Ramchander, S., & Chaudhry, M. (2005). The impact of macroeconomic surprises on spot and forward foreign exchange markets. Journal of International Money and Finance, 24(5), 693-718. Vrugt, E. B. (2009). U.S. and Japanese macroeconomic news and stock market volatility in Asia-Pacific. Pacific-Basin Finance Journal, 17(5), 611-627.

Tables & Figures Table 1: Key Economic Demography of the 12 Asia-Pacific Countries and the World, 2010 The Asia-Pacific region is inhabited by almost half of the world population. The region contributed to about one-third of global output in 2010. The Asia-Pacific region is also growing above the global growth rate and the region is often dubbed as the global growth engine of the 21 st century. The region has become an important area for global socio-economic growth.

Country

Total Population (mil)

GDP (USD bil)

GDP per capita (USD)

GDP growth (%)

Unemployment Rate (%)

CPI (%)

1-month Interest Rate

Total Trade (USD bil)

Total Reserves (USD bil)

Exchange Rate (per USD)

Australia

22

890

41,300

3.30%

5.10%

2.90%

4.80%

512

39

1.0902

China

1,330

9,872

7,400

10.30%

4.15%

5.00%

5.50%

3,335

2,662

6.7852

India

1,173

4,046

3,400

8.30%

10.80%

11.70%

4.75%

765

284

46.16

Indonesia

243

1,033

4,300

6.00%

7.10%

5.10%

6.27%

339

96

9,170

Japan

127

4,338

34,200

3.00%

5.10%

-0.70%

0.18%

1,755

1,096

87.78

South Korea

49

1,467

30,200

6.10%

3.30%

3.00%

2.64%

1,066

275

1154

Malaysia

28

417

14,700

7.20%

3.50%

1.70%

2.82%

428

107

3.0400

New Zealand

4

119

28,000

2.10%

6.50%

2.60%

3.13%

80

18

1.3874

Philippines

100

353

3,500

7.30%

7.30%

3.80%

0.75%

133

62

45.11

Singapore

5

292

57,200

14.70%

2.10%

2.80%

0.19%

870

226

1.3702

Taiwan

23

824

35,800

10.50%

5.20%

1.00%

0.66%

604

387

31.64

Thailand World

66

580

8,700

7.60%

1.20%

3.30%

2.05%

457

176

31.66

6,900

74,480

11,200

4.70%

8.80%

4.00%

-

37,781

-

-

Sources: CIA World Factbook 2010, U.S. Census Bureau and World Trade Organization (WTO)

Figure 1: Scale of Foreign Exchange Regimes Flexibility

CNY-Chinese yuan, INR-Indian rupee, IDR-Indonesian rupiah, KRW-Korean won, MYR-Malaysian ringgit, PHP-Philippines peso, TWD-Taiwanese dollar, THB-Thai baht, SGD-Singapore dollar, AUD-Australian dollar, JPY-Japanese yen, NZD-New Zealand dollar.

Table 2: Descriptive Statistics of Asia-Pacific Spot Exchange Rates: January 1, 1997 to December 31, 2010 The table shows the basic statistics of the Asia-Pacific spot exchange rates for January 1, 1997 to December 31, 2010 – AUD: Australian dollar, CNY: Chinese yuan, IDR: Indonesian rupiah, INR: Indian rupee, JPY: Japanese yen, KRW: South Korean won, MYR: Malaysian ringgit, NZD: New Zealand dollar, PHP: Philippines peso, SGD: Singapore dollar, THB: Thai baht, TWD: Taiwan dollar. The exchange rates are quoted in terms of domestic currency against one unit of U.S. dollar (USD). The weakest point and date denote the lowest value of the particular currency against the USD and the accompanying date when it happened. Meanwhile the strongest point and date show the opposite. The weakest points for most of the Southeast Asian (i.e. IDR, MYR, THB ) and East Asian (i.e. JPY and KRW) currencies were recorded during the height of the Asian Financial Crisis (AFC) 1997/98. The burst of the dot.com bubble in 2000-2001 seem to have cause currencies like AUD, NZD and SGD to depreciate to their lowest level against the USD. The INR and TWD depreciated to their lowest point during the global financial crisis (GFC) 2007/08. As CNY was on a fixed peg against the USD prior to July 2005, its lowest value was recorded during the fixed exchange rate regime. The lowest point of PHP, which was recorded in March 2004, was largely driven by domestic political event. Next, the strongest level for currencies like AUD, CNY, JPY and SGD were recorded in the tail-end of 2010 while the NZD touched its strongest level in 2008. For the rest of the other currencies (i.e. IDR, INR, KRW, MYR, PHP, THB and TWD), they have never recovered to the pre-AFC levels. According to the Jarque-Bera test, the spot exchange rate series are normally distributed.

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

Mean

1.4493

8.0787

8,827

44.35

112.35

1,142

3.6072

1.7124

46.87

1.6129

37.79

32.52

Median

1.3923

8.2771

9,110

44.90

114.45

1,159

3.8000

1.5991

47.92

1.6560

38.50

32.70

Weakest Point

2.0708

8.7130

15,500

51.97

147.27

1,960

4.6853

2.5530

56.46

1.8540

56.00

35.22

Weakest Date

2-Apr-01

Pre-Nov-2002

17-Jun-98

3-Mar-09

11-Aug-98

23-Dec-97

1-Aug-98

18-Oct-00

22-Mar-04

27-Dec-01

12-Jan-98

2-Mar-09

Strongest Point

0.9775

6.5906

2,362

35.69

80.39

844

2.4715

1.2234

26.28

1.2827

22.70

27.31

Strongest Date

31-Dec-10

31-Dec-10

2-Jan-97

25-Jul-97

29-Oct-10

3-Jan-97

15-Jan-97

27-Feb-08

2-Jan-97

4-Nov-10

17-Jun-97

16-Jan-97

Std. Dev.

0.2613

0.7220

1,987

3.41

12.33

159

0.3306

0.3427

7.213827

0.143598

4.95

1.66

Skewness

0.3933

-0.8244

-1.5456

-0.8093

-0.3323

0.4857

-1.6442

0.7183

-0.9161

-0.4347

-0.3335

-0.9973

Kurtosis

2.2452

2.1621

7.3040

3.2809

3.0646

3.8193

6.2013

2.4037

3.6647

1.9857

2.9439

4.2567

Jarque-Bera

180.95

520.74

4,275.18

410.91

67.88

245.88

3,206.68

368.34

578.40

271.72

68.20

846.14

Probability

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Observations

3653

3653

3653

3653

3653

3653

3653

3653

3653

3653

3653

3653

Table 3: Asia-Pacific Macroeconomic Events The table shows the selected 107 macroeconomic events from the Asia-Pacific region. These macroeconomic events come from the 13 countries in this region. The main criterion of this selection is the availability of the market expectation data related to the particular macroeconomic announcements. The existence of market expectation information implies that the particular macroeconomic announcement is important – i.e. economists will not be bothered to forecast a non-important announcement. The macroeconomic events are broadly categorised into three groups based on the nature of the information content. These groups are (i) Interest rate, prices and money (IPM), (ii) Production and business activity (PBA) and (iii) Total output, international trade and employment. The data are collected from Bloomberg database. Country Australia Australia Australia Australia Australia Australia Australia Australia Australia China China China China India India Indonesia Indonesia Indonesia Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Korea, South Korea, South Korea, South Malaysia Malaysia Malaysia

Macroeconomic Indicators Consumer Prices (QoQ) Current Account Balance Employment Change Gross Domestic Product (QoQ) Producer Price Index (QoQ) RBA CASH TARGET Retail Sales s.a. (MoM) Trade Balance Unemployment Rate Consumer Price Index (YoY) Industrial Production (YoY) Producer Price Index (YoY) Trade Balance (USD) Industrial Production YoY Qtrly GDP YoY% Bank Indonesia Reference Rate Inflation NSA (MoM) Total Trade Balance Adjusted Current Account Total All Industry Activity Index (MoM) Coincident Index CI Consumer Confidence Current Account Total Gross Domestic Product (QoQ) Housing Starts (YoY) Industrial Production (MoM) Japan Money Stock M2 YoY Jobless Rate Large Retailers' Sales Leading Index CI Machine Orders (MoM) Machine Orders YOY% Merchnds Trade Balance Total Natl CPI YoY Tankan Lge Manufacturers Index Tertiary Industry Index (MoM) Tokyo CPI YoY Trade Balance - BOP Basis Consumer Price Index (MoM) GDP at Constant Price (YoY) Industrial Production (MoM) CPI YoY GDP YoY% Industrial Production YoY

Category IPM TOITE TOITE TOITE IPM IPM PBA TOITE TOITE IPM PBA IPM TOITE PBA TOITE IPM IPM TOITE TOITE PBA PBA PBA TOITE TOITE PBA PBA IPM TOITE PBA PBA PBA PBA TOITE IPM PBA PBA IPM TOITE IPM TOITE PBA IPM TOITE PBA

From Jan-97 Jan-97 Mar-98 Mar-97 Apr-02 Feb-00 Feb-97 Jan-00 Jan-97 Jan-00 Apr-06 Jul-02 Mar-06 Oct-03 Mar-02 Nov-05 Feb-99 Feb-99 Dec-99 Jan-03 Sep-01 04-May Mar-97 Dec-97 May-00 Apr-00 Feb-00 Feb-00 Feb-00 Sep-01 Feb-00 Apr-02 Feb-00 Sep-01 Oct-98 Mar-00 Sep-01 Sep-02 May-00 Mar-00 Aug-02 Dec-01 Nov-99 Apr-01

To Oct-10 Nov-10 Dec-10 Dec-10 Oct-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Nov-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Nov-10 Dec-10

# Obs 56 53 153 55 36 117 129 112 166 131 51 100 58 87 36 61 138 142 133 93 211 80 150 89 129 239 131 132 130 220 131 88 131 111 50 128 112 100 128 62 102 109 43 117

Malaysia Malaysia New Zealand New Zealand New Zealand New Zealand New Zealand New Zealand Philippines Philippines Philippines Singapore Singapore Singapore Singapore Singapore Singapore Singapore Taiwan Taiwan Taiwan Taiwan Taiwan Taiwan Taiwan Thailand Thailand Thailand Thailand Thailand United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States United States

Overnight Rate Trade Balance Consumer Prices (QoQ) GDP QoQ RBNZ Official Cash Rate Retail Sales (MoM) Trade Balance Unemployment Rate Consumer Price Index NSA (MoM) Gross Domestic Product (YoY) Overnight Borrowing Rate Advance GDP Estimate (QoQ) CPI (YoY) GDP (YoY) Industrial Production YoY Non-oil Domestic Exports (YoY) Retail Sales (YoY) Unemployment Rate (sa) Benchmark Interest Rate CPI YoY% Current Account Balance (USD) GDP - Constant Prices (YoY) Industrial Production (YoY) Total Trade Bal in US$ Billion Unemployment Rate - sa Benchmark Interest Rate Consumer Price Index (YoY) Current Account Balance (USD) Gross Domestic Product (YoY) Manufacturing Production (YoY) Advance Retail Sales Avg Hourly Earning MOM Prod Building Permits Business Inventories Capacity Utilization Change in Manufact. Payrolls Change in Nonfarm Payrolls Chicago Purchasing Manager Consumer Confidence Consumer Price Index (MoM) Current Account Balance Durable Goods Orders Empire Manufacturing Factory Orders FOMC Rate Decision GDP Price Deflator GDP QoQ (Annualized) Housing Starts Import Price Index (MoM) Industrial Production Initial Jobless Claims ISM Manufacturing ISM Non-Manufacturing Leading Indicators New Home Sales Personal Income Personal Spending

IPM TOITE IPM TOITE IPM PBA TOITE TOITE IPM TOITE IPM TOITE IPM TOITE PBA TOITE PBA TOITE IPM IPM TOITE TOITE PBA TOITE TOITE IPM IPM TOITE TOITE PBA PBA IPM PBA PBA PBA TOITE TOITE PBA PBA IPM TOITE PBA PBA PBA IPM IPM TOITE PBA IPM PBA TOITE PBA PBA PBA PBA IPM IPM

Nov-05 Apr-04 Apr-97 Mar-99 Apr-99 Jan-98 May-97 Aug-97 May-05 Jan-00 Sep-05 Oct-03 Apr-99 Nov-98 Mar-99 Jun-99 Feb-99 Feb-99 Mar-06 Feb-00 Feb-00 Feb-00 Jan-00 Feb-00 Apr-01 Oct-05 Jan-04 Feb-00 Mar-00 Feb-00 Jan-97 Jul-98 Aug-02 Jul-97 Jan-97 Jan-99 Jan-97 Jan-97 Feb-97 Jan-97 Mar-98 Nov-97 Nov-02 Jan-97 May-97 Apr-98 Mar-97 Mar-98 Aug-98 Jan-97 Jan-97 Jan-97 Dec-98 Mar-97 Feb-97 Feb-97 Feb-97

Nov-10 Dec-10 Oct-10 Dec-10 Dec-10 Dec-10 10-Nov Nov-10 Dec-10 Nov-10 Dec-10 Oct-10 Dec-10 Nov-10 Dec-10 Dec-10 Dec-10 Oct-10 Dec-10 Dec-10 Nov-10 Nov-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Nov-10 Aug-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10

39 81 54 48 89 152 177 53 68 44 51 29 141 49 144 139 143 47 25 131 43 44 130 131 115 42 84 130 42 127 167 140 101 161 166 144 167 168 166 168 52 158 98 168 116 153 165 154 145 168 707 168 146 165 167 168 167

United States United States United States United States United States United States

Philadelphia Fed. Producer Price Index (MoM) Trade Balance U. of Michigan Confidence Unemployment Rate Wholesale Inventories

PBA IPM TOITE PBA TOITE PBA

Jan-97 Dec-97 Jan-97 May-99 Jan-97 Jan-97

Dec-10 Dec-10 Dec-10 Dec-10 Dec-10 Dec-10

167 156 168 279 166 168

Table 4: Exchange Rates Reaction to the U.S. Macroeconomic Surprises The United States (US) is the largest economy in the world and hence its macroeconomic announcements are closely watched and studied by many interested groups in the world. We estimate the regression of ∆𝑠𝑡 = 𝛼𝑖 + 𝛽𝑖 𝑁𝑖,𝑡 + 𝜀𝑡 where Δs is the one-day change in the exchange rate and N denotes the standardised surprises in the macroeconomic announcement i. The first column shows the name of the US macroeconomic indicators while the second column indicates the category in which the macroeconomic indicators fall into (i.e. IPM = Interest rate, Prices and Money; PBA = Production and Business Activity; TOITE = Total Output, International Trade and Employment. There are two rows to each event: the upper row reports the estimated β coefficient and the lower row the corresponding standard error of estimates. The results for each country are reported in the following 12 columns. The estimated β measures the impact of standard deviation shock of the macroeconomic announcement on the exchange rates for each currency pair in our sample. The values of the β are comparable because the macroeconomic shocks have been standardised. For example, a positive shock of one standard deviation in the Advance Retail Sales announcement will cause a depreciation of 0.13% in the AUD against the USD (i.e. positive implies depreciation against USD while negative otherwise). Meanwhile the same shock will cause the JPY and NZD to depreciate by 0.11% and 0.10% against the USD respectively. This implies that the Advance Retail Sales announcement shock has a larger significant impact on the AUD than the other two currencies, JPY and NZD. Event Avg Hourly Earning MOM Prod Consumer Price Index (MoM) FOMC Rate Decision GDP Price Deflator Import Price Index (MoM) Personal Income Personal Spending Producer Price Index (MoM) Advance Retail Sales Building Permits Business Inventories Capacity Utilization

Category IPM IPM IPM IPM IPM IPM IPM IPM PBA PBA PBA PBA

Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e.

AUD 0.0005 0.0007 -0.0004 0.0007 0.0030 0.0009 -0.0010 0.0007 0.0003 0.0008 0.0004 0.0005 0.0009 0.0005 0.0001 0.0006 0.0013 0.0006 0.0012 0.0008 -0.0003 0.0007 0.0002 0.0007

CNY -0.0001 0.0001 -0.0001 0.0001 0.0002 0.0001 -0.0002 0.0001 0.0000 0.0001 -0.0001 0.0001 -0.0001 0.0001 0.0000 0.0001 0.0001 0.0001 0.0000 0.0001 0.0000 0.0001 -0.0001 0.0001

IDR 0.0011 0.0008 0.0000 0.0006 0.0004 0.0008 -0.0015 0.0006 0.0001 0.0007 0.0009 0.0005 -0.0006 0.0005 0.0001 0.0010 0.0001 0.0005 0.0004 0.0003 -0.0003 0.0009 0.0007 0.0010

INR -0.0001 0.0003 -0.0001 0.0003 0.0005 0.0004 0.0000 0.0002 0.0003 0.0004 -0.0001 0.0004 -0.0002 0.0003 -0.0003 0.0002 0.0001 0.0002 0.0001 0.0003 0.0007 0.0003 -0.0002 0.0003

JPY 0.0003 0.0006 0.0015 0.0006 0.0015 0.0006 -0.0002 0.0004 0.0009 0.0006 -0.0007 0.0006 -0.0003 0.0006 0.0005 0.0005 0.0011 0.0006 0.0019 0.0006 0.0006 0.0005 0.0003 0.0010

KRW 0.0000 0.0004 -0.0012 0.0007 0.0006 0.0012 0.0002 0.0004 0.0013 0.0007 0.0006 0.0006 0.0002 0.0007 -0.0003 0.0005 0.0000 0.0004 0.0014 0.0007 -0.0001 0.0005 -0.0025 0.0026

MYR -0.0013 0.0006 -0.0006 0.0005 0.0012 0.0006 -0.0004 0.0009 0.0009 0.0006 0.0005 0.0003 0.0000 0.0007 0.0005 0.0005 0.0011 0.0007 0.0003 0.0004 -0.0005 0.0008 0.0001 0.0006

NZD 0.0003 0.0008 0.0000 0.0009 0.0048 0.0012 -0.0015 0.0008 -0.0001 0.0009 0.0004 0.0007 0.0005 0.0005 0.0001 0.0006 0.0010 0.0005 0.0018 0.0009 -0.0007 0.0006 0.0009 0.0007

PHP 0.0002 0.0003 0.0001 0.0003 0.0006 0.0005 -0.0006 0.0002 -0.0001 0.0004 0.0000 0.0003 0.0007 0.0004 0.0004 0.0004 0.0002 0.0003 0.0010 0.0003 -0.0005 0.0004 -0.0003 0.0006

SGD -0.0001 0.0003 0.0005 0.0003 0.0009 0.0006 -0.0004 0.0003 0.0006 0.0003 0.0000 0.0002 -0.0003 0.0002 0.0001 0.0003 0.0001 0.0003 0.0006 0.0003 0.0000 0.0002 0.0003 0.0003

THB 0.0004 0.0003 0.0002 0.0003 0.0004 0.0002 0.0000 0.0003 0.0007 0.0003 -0.0003 0.0002 0.0006 0.0006 -0.0004 0.0004 0.0003 0.0003 -0.0003 0.0005 0.0000 0.0003 0.0001 0.0005

TWD 0.0000 0.0002 -0.0003 0.0002 0.0003 0.0006 -0.0004 0.0001 0.0005 0.0002 0.0000 0.0002 0.0003 0.0002 0.0002 0.0002 0.0000 0.0002 0.0002 0.0003 0.0003 0.0002 -0.0001 0.0004

Table 4: Exchange Rates Reaction to the United States Macroeconomic Surprises (continued) Event Chicago Purchasing Manager Consumer Confidence Durable Goods Orders Empire Manufacturing Factory Orders Housing Starts Industrial Production ISM Manufacturing ISM Non-Manufacturing Leading Indicators New Home Sales Philadelphia Fed. U. of Michigan Confidence Wholesale Inventories Change in Manufact. Payrolls Change in Nonfarm Payrolls

Category PBA PBA PBA PBA PBA PBA PBA PBA PBA PBA PBA PBA PBA PBA TOITE TOITE

Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e.

AUD 0.0015 0.0006 0.0017 0.0007 0.0000 0.0007 -0.0014 0.0009 0.0011 0.0007 0.0003 0.0005 -0.0001 0.0007 0.0007 0.0006 -0.0012 0.0005 -0.0014 0.0008 -0.0009 0.0006 -0.0002 0.0006 -0.0004 0.0006 -0.0010 0.0007 0.0017 0.0007 0.0013 0.0007

CNY 0.0000 0.0001 0.0001 0.0001 0.0000 0.0001 -0.0001 0.0001 -0.0001 0.0001 0.0000 0.0001 -0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0000 0.0001 0.0000 0.0001 -0.0001 0.0001 -0.0002 0.0002 -0.0001 0.0001 0.0000 0.0001

IDR 0.0002 0.0007 0.0008 0.0017 -0.0007 0.0009 -0.0009 0.0004 -0.0002 0.0005 -0.0002 0.0007 0.0025 0.0012 -0.0013 0.0011 0.0011 0.0008 -0.0004 0.0004 0.0004 0.0006 0.0015 0.0016 0.0002 0.0003 -0.0031 0.0017 -0.0013 0.0008 -0.0015 0.0018

INR 0.0002 0.0002 0.0004 0.0002 -0.0006 0.0003 -0.0008 0.0004 0.0008 0.0004 0.0001 0.0002 -0.0002 0.0003 0.0004 0.0003 -0.0002 0.0002 -0.0005 0.0004 0.0001 0.0002 0.0003 0.0003 -0.0001 0.0001 0.0001 0.0003 0.0002 0.0002 0.0003 0.0002

JPY 0.0009 0.0006 -0.0009 0.0012 0.0000 0.0005 0.0011 0.0008 -0.0001 0.0005 0.0008 0.0005 -0.0002 0.0009 0.0008 0.0005 0.0001 0.0004 0.0005 0.0007 0.0000 0.0005 0.0005 0.0007 0.0005 0.0003 -0.0001 0.0006 0.0012 0.0006 0.0018 0.0006

KRW -0.0006 0.0007 0.0021 0.0014 0.0005 0.0015 -0.0004 0.0008 0.0002 0.0005 0.0005 0.0004 -0.0038 0.0029 0.0002 0.0007 -0.0002 0.0003 -0.0010 0.0007 -0.0007 0.0003 -0.0031 0.0019 0.0000 0.0004 0.0007 0.0008 0.0003 0.0005 0.0001 0.0006

MYR 0.0010 0.0006 0.0003 0.0008 -0.0004 0.0004 -0.0010 0.0006 0.0002 0.0003 0.0002 0.0004 0.0001 0.0005 -0.0012 0.0009 0.0001 0.0003 -0.0008 0.0005 0.0008 0.0010 0.0000 0.0006 -0.0003 0.0002 -0.0005 0.0007 0.0003 0.0005 -0.0013 0.0009

NZD 0.0011 0.0006 0.0018 0.0007 0.0002 0.0007 -0.0006 0.0009 0.0007 0.0007 0.0001 0.0006 0.0007 0.0008 0.0008 0.0006 -0.0014 0.0006 -0.0009 0.0008 -0.0005 0.0007 0.0001 0.0007 -0.0003 0.0005 -0.0013 0.0006 0.0017 0.0007 0.0015 0.0007

PHP 0.0003 0.0003 0.0004 0.0003 -0.0004 0.0003 -0.0004 0.0004 0.0003 0.0003 0.0004 0.0003 0.0005 0.0006 0.0004 0.0004 0.0003 0.0003 0.0002 0.0004 -0.0004 0.0005 -0.0009 0.0004 0.0004 0.0006 0.0002 0.0005 0.0000 0.0003 -0.0005 0.0004

SGD 0.0001 0.0003 0.0008 0.0004 -0.0002 0.0002 -0.0002 0.0003 0.0004 0.0003 0.0002 0.0003 0.0004 0.0002 -0.0001 0.0003 -0.0001 0.0002 -0.0008 0.0004 0.0001 0.0002 0.0002 0.0003 0.0002 0.0001 -0.0002 0.0003 -0.0001 0.0002 0.0004 0.0002

THB -0.0003 0.0005 0.0003 0.0005 0.0001 0.0005 -0.0003 0.0004 -0.0010 0.0010 -0.0002 0.0004 0.0003 0.0004 -0.0003 0.0004 0.0000 0.0003 -0.0003 0.0005 0.0002 0.0006 0.0008 0.0006 0.0003 0.0003 -0.0005 0.0006 -0.0002 0.0003 -0.0008 0.0005

TWD 0.0000 0.0003 0.0004 0.0003 0.0000 0.0001 -0.0004 0.0002 -0.0001 0.0002 0.0001 0.0002 0.0000 0.0003 0.0002 0.0002 0.0000 0.0001 0.0001 0.0002 0.0001 0.0002 -0.0004 0.0003 0.0000 0.0001 -0.0002 0.0003 0.0000 0.0002 0.0001 0.0002

Table 4: Exchange Rates Reaction to the United States Macroeconomic Surprises (continued) Event Current Account Balance GDP QoQ (Annualized) Initial Jobless Claims Trade Balance Unemployment Rate

Category TOITE TOITE TOITE TOITE TOITE

Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e. Coef. s.e.

AUD 0.0016 0.0015 0.0013 0.0009 0.0002 0.0003 0.0006 0.0006 -0.0004 0.0007

CNY -0.0001 0.0001 -0.0001 0.0001 0.0000 0.0000 0.0000 0.0001 0.0000 0.0002

IDR -0.0003 0.0015 -0.0008 0.0009 0.0010 0.0006 0.0012 0.0008 -0.0002 0.0011

INR 0.0001 0.0006 0.0000 0.0003 0.0003 0.0001 0.0001 0.0003 -0.0001 0.0003

JPY 0.0002 0.0009 0.0007 0.0005 -0.0005 0.0003 0.0005 0.0005 -0.0010 0.0006

KRW 0.0020 0.0015 -0.0012 0.0010 0.0005 0.0004 0.0002 0.0007 -0.0010 0.0007

MYR 0.0013 0.0012 0.0000 0.0008 0.0001 0.0003 0.0001 0.0006 0.0003 0.0005

NZD 0.0013 0.0014 0.0013 0.0008 0.0001 0.0003 0.0014 0.0011 -0.0001 0.0007

PHP 0.0008 0.0006 -0.0004 0.0003 0.0001 0.0002 0.0001 0.0003 0.0001 0.0003

SGD 0.0012 0.0005 0.0003 0.0003 0.0001 0.0001 0.0000 0.0003 -0.0004 0.0002

THB 0.0011 0.0008 0.0000 0.0003 0.0001 0.0002 0.0002 0.0004 -0.0003 0.0004

TWD -0.0001 0.0005 -0.0002 0.0002 0.0002 0.0001 0.0003 0.0002 -0.0002 0.0002

Figure 2: Responsiveness of the Asia-Pacific Currencies to the U.S. Macroeconomic Shocks 12 10 8 6 4 2 0 AUD

NZD

JPY

SGD

INR

KRW MYR

IDR

PHP

CNY

THB

TWD

The graph shows the number of significant United States (US) macroeconomic surprises detected for each exchange rate in Asia-Pacific. The number implies the responsiveness of the exchange rate to the US macroeconomic surprises. AUD and NZD are the most responsive currencies with 10 significant events followed by JPY and SGD with seven (7) events each. The least responsive currencies are THB and TWD with only two (2) events reported for each currency. THB and TWD are the least responsive currencies to the surprises in the US macroeconomic announcements. We observe that the developed/ rich economies display greater responsiveness to the US macroeconomic surprises.

Figure 3: Selected U.S. Macroeconomic Events 7 6 5 4 3 2 1 0 FOMC Rate Decision

Building Permits

GDP Price Deflator

Import Price Index (MoM)

Consumer Confidence

Empire Manufacturing

Change in Nonfarm Payrolls

The graph shows the selected U.S. macroeconomic surprises which display significant impact to at least four (4) currencies. The surprises in the Federal Fund Reserve rate is the most influential among the US macroeconomic events as it significantly impacts six (6) currencies in the Asia-Pacific region followed by Building Permits surprises which impact five (5) currencies. The surprises of the GDP Price Deflator, Import Price Index, Consumer Confidence, Empire Manufacturing and Change in Nonfarm Payroll show significant impact to four (4) currencies each.

Table 5: Exchange Rates Reaction to the Asia-Pacific Macroeconomic Surprises The table below shows the beta estimate and the corresponding standard error of estimate of equation 4.6: Δs i,t=αi+βiNj,t+εt, with the Asia-Pacific (ex-US) macroeconomic surprises. These events are considered domestic macroeconomic surprises in our paper. The first column shows the name of the country and followed by the macroeconomic event in the second column. The third column indicates the category of the events which we have broadly segregated into three groups namely (i) Total Output, International Trade and Employment = TOITE, (ii) Interest rates, Prices and Money = IPM and (iii) Production and Business Activity = PBA. There are two rows to each macroeconomic event in which the upper row reports the β coefficient while the lower one the corresponding standard error of estimates. The next twelve columns display the result for each currency in our sample. We used a total of 74 domestic macroeconomic indicators and among these, Japan contributes the highest number of indicators (i.e. 20 indicators) followed by Australia with nine (9) indicators. The bolded coefficients denote significance at the minimum of 10% level of confidence. The estimated beta coefficients are comparable as the regressor has been standardized with its respective standard deviation. For example, a positive shock of one standard deviation in the Australia-Current Account Balance will cause the AUD to significantly appreciate by 0.28% against the USD. At the same time, a similar shock in the Australia-Consumer Prices will cause the AUD to significantly appreciate by 0.32% against the USD. In this instance, the surprises in Australia-Consumer Prices give bigger impact to the AUD exchange rate. However, this comparison must be interpreted with caution as the standard error of estimate should also be taken into account. The comparison of t-statistic may give a better picture of the relative impact of the macroeconomic indicators. Two (2) interesting observations are gathered from this table. (i) Most of the Asia-Pacific exchange rates react significantly to their own macroeconomic surprises with the exception of THB which only shows significant reaction to other countries’ macroeconomic surprises. (ii) The Interest Rate setting announcements are significant in most of the currency markets. The Australia (RBA), Indonesia (BI reference rate), Malaysia (BNM overnight rate), New Zealand (RBNZ official rate) and Philippines (overnight borrowing rate) are all significant within their own respective currency markets. The only exception is the Thailand’s benchmark interest rate which shows no significant to any currency exchange rate. Country Australia

Australia

Australia

Australia

Australia

Australia

Australia

Australia

Australia

Event Current Account Balance

Consumer Prices (QoQ)

Employment Change

Gross Domestic Product (QoQ)

Producer Price Index (QoQ)

RBA Cash Target

Retail Sales s.a. (MoM)

Trade Balance

Unemployment Rate

Category

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

-0.0028

0.0001

-0.0001

-0.0002

0.0007

-0.0001

0.0000

-0.0012

0.0013

-0.0004

-0.0002

0.0006

TOITE

Coef. s.e.

0.0011

0.0002

0.0006

0.0007

0.0008

0.0013

0.0006

0.0011

0.0007

0.0003

0.0004

0.0003

IPM

Coef.

-0.0032

-0.0001

0.0003

0.0005

0.0002

0.0010

-0.0011

-0.0019

-0.0002

-0.0003

-0.0003

0.0008

s.e.

0.0012

0.0001

0.0008

0.0007

0.0010

0.0009

0.0012

0.0012

0.0011

0.0004

0.0005

0.0004

TOITE

Coef.

0.0005

0.0005

0.0008

0.0001

0.0004

-0.0001

0.0021

-0.0001

0.0000

0.0002

-0.0003

-0.0002

s.e.

0.0002

0.0008

0.0002

0.0001

0.0001

0.0002

0.0046

0.0002

0.0003

0.0001

0.0001

0.0000

TOITE

Coef.

-0.0018

0.0000

-0.0020

0.0006

-0.0014

-0.0014

0.0018

0.0004

0.0001

0.0006

0.0009

0.0001

s.e.

0.0012

0.0001

0.0014

0.0004

0.0011

0.0009

0.0011

0.0015

0.0007

0.0004

0.0010

0.0002

IPM

Coef.

-0.0035

-0.0001

0.0008

0.0002

0.0009

-0.0009

0.0000

-0.0021

-0.0010

0.0001

-0.0001

-0.0001

s.e.

0.0019

0.0001

0.0007

0.0008

0.0008

0.0011

0.0007

0.0017

0.0006

0.0007

0.0005

0.0007

IPM

Coef.

-0.0011

0.0002

-0.0007

0.0002

-0.0003

-0.0032

-0.0010

-0.0004

-0.0008

-0.0004

-0.0005

-0.0006

s.e.

0.0010

0.0002

0.0005

0.0007

0.0006

0.0014

0.0004

0.0009

0.0005

0.0003

0.0003

0.0003

PBA

Coef.

-0.0021

-0.0001

-0.0003

0.0003

0.0013

-0.0003

0.0002

-0.0016

0.0001

-0.0001

0.0021

0.0003

s.e.

0.0007

0.0001

0.0011

0.0002

0.0008

0.0005

0.0005

0.0007

0.0004

0.0004

0.0026

0.0002

TOITE

Coef.

-0.0010

0.0001

-0.0008

-0.0006

0.0003

-0.0005

-0.0002

-0.0002

-0.0004

0.0000

-0.0002

-0.0004

s.e.

0.0010

0.0001

0.0005

0.0004

0.0007

0.0010

0.0005

0.0011

0.0003

0.0004

0.0003

0.0004

TOITE

Coef.

0.0014

-0.0001

-0.0019

-0.0001

0.0003

-0.0003

0.0010

0.0010

0.0010

0.0001

0.0003

0.0003

s.e.

0.0005

0.0001

0.0016

0.0003

0.0005

0.0007

0.0006

0.0007

0.0005

0.0002

0.0005

0.0002

Table 5: Exchange Rates Reaction to the Asia-Pacific Macroeconomic Surprises (continued) Country

Event

Category

China

Consumer Price Index (YoY)

IPM

China

China

China

Indonesia

Indonesia

Indonesia

India

India

Japan

Japan

Japan

Industrial Production (YoY)

Producer Price Index (YoY)

Trade Balance (USD)

Bank Indonesia Reference Rate

Inflation NSA (MoM)

Total Trade Balance

Industrial Production YoY

Qtrly GDP YoY%

Adjusted Current Account Total

All Industry Activity Index (MoM)

Current Account Total

PBA

IPM

TOITE

IPM

IPM

TOITE

PBA

TOITE

TOITE

PBA

TOITE

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

Coef.

-0.0002

0.0000

-0.0003

0.0001

0.0006

0.0009

0.0005

-0.0006

0.0003

0.0002

0.0002

0.0003

s.e.

0.0008

0.0001

0.0004

0.0004

0.0006

0.0008

0.0005

0.0007

0.0004

0.0003

0.0007

0.0003

Coef.

0.0004

-0.0003

-0.0016

-0.0003

-0.0006

-0.0005

-0.0007

-0.0013

-0.0004

-0.0003

-0.0002

-0.0003

s.e.

0.0011

0.0001

0.0006

0.0005

0.0012

0.0010

0.0005

0.0013

0.0006

0.0004

0.0004

0.0004

Coef.

-0.0011

0.0001

0.0002

0.0005

0.0002

0.0011

0.0002

-0.0004

0.0002

-0.0001

0.0000

-0.0001

s.e.

0.0008

0.0001

0.0003

0.0005

0.0004

0.0011

0.0003

0.0007

0.0004

0.0003

0.0004

0.0002

Coef.

-0.0005

0.0001

-0.0003

0.0005

0.0018

0.0001

-0.0006

0.0006

-0.0003

0.0000

0.0000

0.0006

s.e.

0.0012

0.0001

0.0006

0.0006

0.0009

0.0018

0.0005

0.0013

0.0005

0.0005

0.0003

0.0002

Coef.

0.0000

-0.0002

0.0013

0.0002

0.0001

0.0007

-0.0005

-0.0004

0.0006

0.0003

-0.0001

0.0004

s.e.

0.0008

0.0001

0.0007

0.0006

0.0007

0.0008

0.0002

0.0013

0.0005

0.0003

0.0004

0.0003

Coef.

-0.0001

-0.0002

0.0010

0.0001

0.0002

-0.0002

0.0001

-0.0002

0.0001

-0.0002

-0.0001

-0.0001

s.e.

0.0007

0.0002

0.0005

0.0002

0.0006

0.0005

0.0006

0.0006

0.0003

0.0003

0.0003

0.0002

Coef.

0.0002

0.0001

-0.0001

-0.0004

0.0002

-0.0004

-0.0002

-0.0001

-0.0001

0.0000

0.0000

-0.0001

s.e.

0.0006

0.0001

0.0003

0.0004

0.0006

0.0005

0.0005

0.0006

0.0003

0.0003

0.0003

0.0003

Coef.

-0.0021

-0.0011

-0.0002

-0.0003

0.0003

0.0002

0.0001

-0.0012

0.0001

-0.0001

0.0000

0.0001

s.e.

0.0005

0.0007

0.0003

0.0001

0.0003

0.0004

0.0025

0.0003

0.0001

0.0001

0.0001

0.0002

Coef.

-0.0005

-0.0001

0.0000

-0.0007

0.0008

-0.0019

-0.0007

-0.0011

-0.0003

-0.0007

-0.0012

-0.0006

s.e.

0.0015

0.0002

0.0007

0.0011

0.0013

0.0010

0.0012

0.0015

0.0007

0.0005

0.0008

0.0003

Coef.

-0.0001

-0.0002

0.0009

0.0000

0.0001

-0.0002

0.0006

-0.0004

0.0003

0.0001

-0.0002

0.0000

s.e.

0.0007

0.0002

0.0013

0.0002

0.0006

0.0005

0.0005

0.0007

0.0004

0.0003

0.0004

0.0003

Coef.

-0.0006

0.0000

-0.0005

-0.0001

-0.0005

-0.0003

-0.0004

-0.0005

0.0001

-0.0001

-0.0004

-0.0003

s.e.

0.0007

0.0001

0.0006

0.0003

0.0005

0.0004

0.0005

0.0009

0.0004

0.0003

0.0002

0.0002

Coef.

0.0000

-0.0002

0.0009

0.0002

0.0003

-0.0003

0.0004

0.0004

0.0001

0.0003

0.0002

-0.0001

s.e.

0.0008

0.0001

0.0009

0.0003

0.0005

0.0005

0.0004

0.0008

0.0004

0.0003

0.0004

0.0002

Table 5: Exchange Rates Reaction to the Asia-Pacific Macroeconomic Surprises (continued)

Country

Event

Category

Japan

Consumer Confidence

PBA

Japan

Japan

Japan

Japan

Japan

Japan

Japan

Japan

Japan

Japan

Japan

Coincident Index CI

Gross Domestic Product (QoQ)

Housing Starts (YoY)

Industrial Production (MoM)

Leading Index CI

Large Retailers' Sales

Japan Money Stock M2 YoY

Machine Orders (MoM)

Machine Orders YOY%

Merchnds Trade Balance Total

Natl CPI YoY

PBA

TOITE

PBA

PBA

PBA

PBA

IPM

PBA

PBA

TOITE

IPM

Coef.

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

0.0007

0.0001

0.0004

-0.0006

0.0008

0.0002

0.0006

0.0006

-0.0001

0.0001

0.0000

0.0005

0.0005

0.0010

0.0008

0.0009

0.0006

0.0011

0.0004

0.0003

0.0003

0.0004

0.0003

-0.0004

-0.0002

0.0001

0.0001

0.0001

-0.0001

s.e.

0.0011

0.0001

Coef.

-0.0001

0.0000

0.0006

0.0006

-0.0003

s.e.

0.0004

0.0001

0.0003

0.0002

0.0004

0.0003

0.0003

0.0005

0.0003

0.0002

0.0004

0.0002

Coef.

-0.0002

0.0001

-0.0017

0.0001

0.0003

0.0014

-0.0022

-0.0005

-0.0008

-0.0003

-0.0012

0.0000

s.e.

0.0006

0.0003

0.0018

0.0002

0.0007

0.0012

0.0008

0.0007

0.0003

0.0003

0.0012

0.0001

Coef.

0.0012

0.0001

0.0005

0.0006

0.0002

0.0007

0.0004

0.0006

0.0001

0.0002

0.0004

0.0003

s.e.

0.0007

0.0001

0.0004

0.0004

0.0005

0.0004

0.0002

0.0007

0.0003

0.0002

0.0005

0.0002

Coef.

-0.0012

0.0001

-0.0001

-0.0006

-0.0004

-0.0008

-0.0002

-0.0005

-0.0002

-0.0001

-0.0001

-0.0003

s.e.

0.0007

0.0001

0.0003

0.0003

0.0004

0.0005

0.0003

0.0007

0.0002

0.0002

0.0002

0.0002

Coef.

-0.0003

0.0000

-0.0005

0.0000

0.0003

-0.0007

-0.0001

0.0001

0.0001

0.0001

0.0006

-0.0001

s.e.

0.0005

0.0001

0.0003

0.0001

0.0003

0.0004

0.0002

0.0005

0.0002

0.0002

0.0003

0.0001

Coef.

-0.0012

0.0000

-0.0007

0.0002

-0.0009

-0.0008

-0.0015

-0.0006

-0.0009

-0.0001

-0.0001

-0.0001

s.e.

0.0005

0.0001

0.0006

0.0003

0.0005

0.0005

0.0006

0.0006

0.0003

0.0002

0.0004

0.0002

Coef.

-0.0004

0.0000

0.0004

-0.0005

0.0000

0.0000

-0.0007

0.0006

-0.0001

-0.0002

0.0007

-0.0002

s.e.

0.0009

0.0001

0.0008

0.0003

0.0005

0.0006

0.0005

0.0007

0.0004

0.0003

0.0003

0.0002

Coef.

0.0006

0.0000

0.0002

-0.0005

-0.0012

-0.0006

-0.0002

-0.0005

0.0003

0.0000

-0.0003

-0.0002

0.0002

0.0005

0.0006

0.0007

0.0008

0.0003

0.0002

0.0004

0.0002

-0.0003

-0.0006

0.0001

-0.0003

s.e.

0.0010

0.0001

0.0006

Coef.

0.0002

0.0000

-0.0003

-0.0010

-0.0014

-0.0007

-0.0009

-0.0002

s.e.

0.0013

0.0001

0.0007

0.0003

0.0005

0.0008

0.0006

0.0011

0.0004

0.0003

0.0005

0.0003

Coef.

-0.0018

0.0001

-0.0007

-0.0002

-0.0003

-0.0014

-0.0004

-0.0009

-0.0004

-0.0003

-0.0004

-0.0005

s.e.

0.0008

0.0001

0.0005

0.0003

0.0006

0.0007

0.0004

0.0008

0.0003

0.0003

0.0004

0.0003

Coef.

-0.0011

-0.0001

-0.0004

-0.0005

-0.0006

0.0008

-0.0001

-0.0005

0.0002

-0.0003

-0.0005

-0.0004

s.e.

0.0006

0.0001

0.0004

0.0004

0.0005

0.0007

0.0004

0.0008

0.0004

0.0002

0.0003

0.0002

Table 5: Exchange Rates Reaction to the Asia-Pacific Macroeconomic Surprises (continued)

Country

Event

Category

Japan

Tankan Lge Manufacturers Index

PBA

Japan

Japan

Japan

Japan Korea, South Korea, South Korea, South Malaysia

Malaysia

Malaysia

Malaysia

Malaysia

Trade Balance - BOP Basis

Tokyo CPI YoY

Tertiary Industry Index (MoM)

Jobless Rate

Consumer Price Index (MoM)

GDP at Constant Price (YoY)

Industrial Production (MoM)

CPI YoY

GDP YoY%

Industrial Production YoY

Overnight Rate

Trade Balance

TOITE

IPM

PBA

TOITE

IPM

TOITE

PBA

IPM

TOITE

PBA

IPM

TOITE

Coef.

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

-0.0009

-0.0002

-0.0028

0.0005

-0.0015

0.0002

-0.0004

-0.0019

-0.0001

-0.0011

-0.0008

0.0004

s.e.

0.0010

0.0001

0.0013

0.0003

0.0009

0.0008

0.0006

0.0009

0.0005

0.0004

0.0003

0.0003

Coef.

-0.0006

0.0000

-0.0005

-0.0001

-0.0005

-0.0003

-0.0004

-0.0005

0.0001

-0.0001

-0.0004

-0.0003

s.e.

0.0007

0.0001

0.0006

0.0003

0.0005

0.0004

0.0005

0.0009

0.0004

0.0003

0.0002

0.0002

Coef.

-0.0003

-0.0001

0.0001

-0.0001

0.0002

0.0006

0.0007

-0.0013

-0.0001

0.0000

0.0001

0.0000

s.e.

0.0006

0.0001

0.0003

0.0004

0.0005

0.0006

0.0003

0.0007

0.0004

0.0002

0.0003

0.0002

Coef.

-0.0001

-0.0002

-0.0004

-0.0001

0.0002

0.0003

-0.0004

-0.0003

-0.0001

-0.0001

0.0002

-0.0001

s.e.

0.0005

0.0001

0.0005

0.0003

0.0005

0.0006

0.0006

0.0006

0.0003

0.0002

0.0003

0.0002

Coef.

-0.0002

0.0000

0.0001

-0.0007

0.0004

-0.0004

-0.0004

-0.0002

-0.0004

-0.0001

0.0003

0.0000

s.e.

0.0008

0.0001

0.0005

0.0005

0.0006

0.0006

0.0005

0.0008

0.0004

0.0003

0.0006

0.0002

Coef.

-0.0006

0.0002

0.0001

0.0000

0.0001

-0.0009

-0.0006

-0.0004

0.0002

-0.0003

-0.0004

-0.0002

s.e.

0.0006

0.0002

0.0004

0.0003

0.0005

0.0006

0.0004

0.0006

0.0004

0.0002

0.0002

0.0002

Coef.

-0.0004

0.0000

0.0004

0.0002

0.0005

-0.0008

-0.0004

-0.0001

0.0006

0.0000

0.0003

0.0002

s.e.

0.0012

0.0001

0.0005

0.0001

0.0005

0.0004

0.0008

0.0015

0.0004

0.0002

0.0005

0.0004

Coef.

-0.0010

0.0001

-0.0010

-0.0001

0.0006

-0.0008

-0.0002

-0.0003

-0.0003

0.0001

0.0000

-0.0002

s.e.

0.0013

0.0001

0.0008

0.0008

0.0006

0.0015

0.0005

0.0011

0.0004

0.0003

0.0004

0.0005

Coef.

-0.0006

-0.0001

-0.0005

-0.0007

0.0011

0.0000

-0.0001

-0.0007

-0.0004

0.0004

0.0004

0.0001

s.e.

0.0010

0.0001

0.0005

0.0004

0.0006

0.0006

0.0003

0.0012

0.0005

0.0006

0.0003

0.0002

Coef.

-0.0007

0.0000

-0.0007

-0.0013

0.0002

-0.0007

-0.0005

-0.0015

-0.0010

-0.0010

-0.0007

-0.0007

s.e.

0.0014

0.0001

0.0012

0.0008

0.0009

0.0010

0.0010

0.0012

0.0007

0.0004

0.0007

0.0005

Coef.

0.0001

-0.0001

-0.0004

-0.0003

-0.0011

-0.0006

-0.0003

-0.0001

-0.0005

-0.0006

-0.0004

-0.0004

s.e.

0.0011

0.0001

0.0004

0.0002

0.0004

0.0003

0.0007

0.0009

0.0003

0.0002

0.0002

0.0001

Coef.

-0.0016

0.0001

-0.0012

-0.0015

-0.0019

-0.0022

-0.0014

-0.0009

0.0003

0.0012

0.0000

-0.0003

s.e.

0.0023

0.0001

0.0007

0.0006

0.0021

0.0009

0.0006

0.0021

0.0004

0.0008

0.0006

0.0005

Coef.

0.0001

0.0004

0.0002

0.0000

0.0008

-0.0013

0.0001

-0.0002

-0.0004

0.0001

-0.0003

-0.0002

s.e.

0.0009

0.0004

0.0005

0.0004

0.0009

0.0009

0.0003

0.0008

0.0005

0.0003

0.0004

0.0003

Table 5: Exchange Rates Reaction to the Asia-Pacific Macroeconomic Surprises (continued)

Country New Zealand New Zealand New Zealand New Zealand New Zealand New Zealand Philippines

Philippines

Philippines

Singapore

Singapore

Singapore

Singapore

Singapore

Event Consumer Prices (QoQ)

GDP QoQ

RBNZ Official Cash Rate

Retail Sales (MoM)

Trade Balance

Unemployment Rate

Consumer Price Index NSA (MoM)

Gross Domestic Product (YoY)

Overnight Borrowing Rate

Advance GDP Estimate (QoQ)

CPI (YoY)

GDP (YoY)

Industrial Production YoY

Non-oil Domestic Exports (YoY)

Category IPM

TOITE

IPM

PBA

TOITE

TOITE

IPM

TOITE

IPM

TOITE

IPM

TOITE

PBA

TOITE

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

-0.0018

-0.0001

-0.0003

0.0001

-0.0001

0.0003

-0.0006

-0.0028

0.0011

-0.0003

0.0014

0.0001

s.e.

0.0010

0.0003

0.0007

0.0004

0.0013

0.0006

0.0008

0.0012

0.0010

0.0004

0.0010

0.0004

Coef.

-0.0002

NA

0.0007

0.0005

0.0005

0.0003

-0.0008

-0.0025

0.0003

0.0002

0.0001

-0.0001

Coef.

s.e.

0.0010

NA

0.0013

0.0004

0.0005

0.0004

0.0009

0.0008

0.0003

0.0003

0.0005

0.0002

Coef.

-0.0002

0.0001

-0.0001

0.0002

0.0007

0.0010

-0.0017

-0.0026

0.0012

0.0006

0.0006

0.0001

s.e.

0.0014

0.0003

0.0011

0.0002

0.0010

0.0006

0.0007

0.0013

0.0004

0.0003

0.0002

0.0001

Coef.

0.0002

0.0002

-0.0012

0.0002

0.0000

0.0003

0.0005

-0.0011

0.0005

-0.0001

-0.0005

0.0003

s.e.

0.0007

0.0001

0.0007

0.0003

0.0004

0.0004

0.0003

0.0009

0.0006

0.0004

0.0005

0.0002

Coef.

0.0009

0.0001

-0.0003

0.0000

0.0008

0.0007

-0.0003

0.0001

-0.0001

-0.0002

-0.0001

0.0002

s.e.

0.0012

0.0001

0.0004

0.0002

0.0005

0.0009

0.0003

0.0013

0.0002

0.0002

0.0003

0.0002

Coef.

-0.0001

0.0002

0.0024

-0.0002

0.0016

-0.0016

-0.0008

0.0033

0.0003

0.0006

0.0013

0.0001

s.e.

0.0015

0.0002

0.0025

0.0010

0.0025

0.0013

0.0009

0.0018

0.0005

0.0007

0.0006

0.0006

Coef.

-0.0012

0.0001

-0.0001

0.0002

-0.0001

-0.0004

0.0000

-0.0007

0.0001

0.0002

0.0014

0.0001

s.e.

0.0010

0.0001

0.0005

0.0005

0.0009

0.0007

0.0004

0.0012

0.0006

0.0004

0.0005

0.0002

Coef.

-0.0029

0.0001

-0.0004

-0.0013

-0.0002

-0.0019

-0.0011

-0.0027

0.0000

-0.0004

0.0001

0.0000

s.e.

0.0014

0.0001

0.0009

0.0007

0.0016

0.0014

0.0005

0.0017

0.0006

0.0006

0.0004

0.0004

Coef.

0.0017

0.0000

-0.0001

0.0004

-0.0009

0.0018

0.0007

0.0018

0.0006

0.0002

-0.0013

-0.0002

s.e.

0.0011

0.0001

0.0004

0.0005

0.0010

0.0017

0.0007

0.0009

0.0002

0.0002

0.0005

0.0002

Coef.

-0.0034

0.0000

-0.0020

0.0003

-0.0010

-0.0019

-0.0017

-0.0021

-0.0008

-0.0037

-0.0009

-0.0003

s.e.

0.0037

0.0003

0.0015

0.0012

0.0017

0.0042

0.0006

0.0020

0.0008

0.0011

0.0005

0.0005

Coef.

-0.0015

-0.0001

-0.0002

0.0001

0.0000

0.0007

0.0000

-0.0015

-0.0001

-0.0003

-0.0005

0.0001

s.e.

0.0008

0.0001

0.0004

0.0004

0.0005

0.0005

0.0003

0.0009

0.0004

0.0003

0.0004

0.0002

Coef.

0.0023

0.0001

-0.0029

0.0006

-0.0016

0.0020

0.0004

0.0012

0.0021

0.0002

-0.0001

0.0004

s.e.

0.0018

0.0001

0.0024

0.0007

0.0016

0.0013

0.0008

0.0015

0.0014

0.0006

0.0008

0.0004

Coef.

-0.0003

0.0000

0.0002

-0.0006

-0.0002

0.0008

0.0000

-0.0008

0.0001

0.0000

0.0006

0.0000

s.e.

0.0007

0.0001

0.0005

0.0004

0.0005

0.0006

0.0007

0.0007

0.0006

0.0003

0.0007

0.0002

Coef.

0.0003

0.0001

-0.0004

0.0003

-0.0003

0.0010

0.0005

0.0007

0.0001

0.0001

-0.0003

0.0003

s.e.

0.0005

0.0001

0.0004

0.0003

0.0005

0.0006

0.0005

0.0007

0.0004

0.0002

0.0004

0.0002

Table 5: Exchange Rates Reaction to the Asia-Pacific Macroeconomic Surprises (continued)

Country Singapore

Singapore

Thailand

Thailand

Thailand

Thailand

Thailand

Taiwan

Taiwan

Taiwan

Taiwan

Taiwan

Taiwan

Taiwan

Event Retail Sales (YoY)

Unemployment Rate (sa)

Benchmark Interest Rate

Consumer Price Index (YoY)

Gross Domestic Product (YoY)

Manufacturing Production (YoY)

Current Account Balance (USD)

Benchmark Interest Rate

CPI YoY%

Current Account Balance (USD)

GDP - Constant Prices (YoY)

Industrial Production (YoY)

Total Trade Bal in US$ Billion

Unemployment Rate - sa

Category PBA

TOITE

IPM

IPM

TOITE

PBA

TOITE

IPM

IPM

TOITE

TOITE

PBA

TOITE

TOITE

Coef.

AUD

CNY

IDR

INR

JPY

KRW

MYR

NZD

PHP

SGD

THB

TWD

0.0000

0.0000

0.0006

0.0005

-0.0001

0.0006

0.0001

0.0003

0.0002

0.0000

0.0010

0.0005

s.e.

0.0008

0.0001

0.0007

0.0003

0.0005

0.0005

0.0004

0.0008

0.0003

0.0003

0.0004

0.0002

Coef.

-0.0011

-0.0001

-0.0008

0.0007

-0.0012

-0.0017

-0.0002

0.0001

-0.0001

-0.0006

-0.0007

0.0000

s.e.

0.0008

0.0001

0.0007

0.0005

0.0006

0.0010

0.0003

0.0008

0.0004

0.0004

0.0005

0.0003

Coef.

-0.0006

0.0000

0.0008

0.0001

0.0002

0.0007

0.0005

-0.0019

0.0009

-0.0004

0.0002

0.0002

s.e.

0.0008

0.0001

0.0007

0.0006

0.0011

0.0013

0.0006

0.0013

0.0008

0.0006

0.0007

0.0005

Coef.

0.0005

0.0000

-0.0002

0.0000

-0.0003

0.0000

-0.0003

0.0002

0.0003

-0.0004

0.0001

0.0001

s.e.

0.0010

0.0003

0.0003

0.0007

0.0009

0.0017

0.0004

0.0009

0.0005

0.0004

0.0004

0.0004

Coef.

0.0009

0.0001

0.0002

-0.0001

0.0000

0.0026

0.0001

0.0023

-0.0002

0.0005

0.0005

0.0004

s.e.

0.0014

0.0001

0.0008

0.0005

0.0011

0.0010

0.0007

0.0015

0.0004

0.0003

0.0005

0.0004

Coef.

-0.0005

0.0001

-0.0005

-0.0003

0.0001

-0.0012

-0.0003

-0.0001

-0.0005

0.0000

0.0002

0.0000

s.e.

0.0013

0.0001

0.0005

0.0003

0.0005

0.0009

0.0003

0.0011

0.0003

0.0003

0.0003

0.0004

Coef.

-0.0005

0.0001

-0.0003

-0.0002

-0.0004

-0.0009

0.0005

-0.0005

0.0001

-0.0001

0.0007

-0.0002

s.e.

0.0007

0.0001

0.0004

0.0005

0.0005

0.0006

0.0005

0.0009

0.0004

0.0003

0.0013

0.0002

Coef.

0.0030

NA

-0.0006

0.0008

0.0025

0.0009

NA

0.0002

0.0009

0.0012

0.0009

0.0000

s.e.

0.0020

NA

0.0012

0.0013

0.0009

0.0040

NA

0.0020

0.0009

0.0008

0.0009

0.0007

Coef.

0.0006

-0.0001

-0.0004

-0.0002

-0.0002

-0.0002

-0.0030

0.0011

0.0001

0.0000

0.0002

0.0002

s.e.

0.0004

0.0005

0.0001

0.0001

0.0002

0.0002

0.0026

0.0003

0.0001

0.0001

0.0001

0.0001

Coef.

-0.0004

0.0000

0.0006

0.0003

-0.0011

0.0007

0.0004

-0.0006

0.0003

-0.0008

-0.0001

0.0001

s.e.

0.0014

0.0000

0.0004

0.0004

0.0009

0.0013

0.0003

0.0012

0.0006

0.0004

0.0007

0.0003

Coef.

0.0008

-0.0001

-0.0012

0.0004

-0.0021

-0.0016

-0.0008

0.0002

0.0004

-0.0005

-0.0010

-0.0006

s.e.

0.0023

0.0001

0.0008

0.0007

0.0016

0.0019

0.0008

0.0019

0.0010

0.0005

0.0003

0.0003

Coef.

-0.0002

0.0000

-0.0001

-0.0009

-0.0004

-0.0013

-0.0001

-0.0007

-0.0004

0.0000

-0.0005

-0.0002

s.e.

0.0008

0.0001

0.0003

0.0006

0.0006

0.0007

0.0004

0.0008

0.0003

0.0004

0.0003

0.0002

Coef.

0.0009

0.0000

-0.0004

0.0003

-0.0003

0.0012

0.0005

0.0006

0.0003

-0.0002

-0.0001

0.0000

s.e.

0.0012

0.0001

0.0004

0.0003

0.0005

0.0010

0.0003

0.0013

0.0004

0.0004

0.0003

0.0004

Coef.

-0.0001

0.0000

0.0001

0.0007

-0.0008

0.0006

-0.0001

0.0000

0.0004

0.0001

0.0000

0.0004

s.e.

0.0007

0.0001

0.0003

0.0005

0.0009

0.0012

0.0004

0.0012

0.0005

0.0005

0.0003

0.0005

Figure 4: Responsiveness of the Asia-Pacific Currencies on Domestic Macroeconomic Shocks 18 16 14 12 10 8 6 4 2 0 AUD

THB

TWD

JPY

NZD

KRW MYR

PHP

SGD

INR

IDR

CNY

The graph shows the number of significant events detected for each currency in the Asia-Pacific. The AUD is the most reactive currency among its Asia-Pacific counterparts with 16 significant events followed by THB and TWD with 14 and 13 significant events respectively. The CNY is the least responsive to the domestic macroeconomic surprises in the Asia-Pacific. Two interesting observations are worthy of mentioning from this result. (1) The THB, which reports no significant reaction to its own country macroeconomic surprises and only to two US macroeconomic surprises, responds to many other countries’ macroeconomic surprises. (2) AUD remains the most responsive currency to macroeconomic surprises, at home and abroad.

Figure 5: Selected Asia-Pacific Macroeconomic Shocks 7 6 5 4 3 2 1 0 AU JP - Tankan AU - RBA Employment Lge Cash Target Change Manufacturers Index

MY Industrial Production YoY

NZ - RBNZ Official Cash Rate

TW - CPI YoY%

JP - Large Retailers' Sales

MY Overnight Rate

The graph show the selected macroeconomic surprises from the Asia-Pacific which display significant impact to at least four (4) currency exchange rates. Both the Australia-Employment Change and the Japan-Tankan Large Manufacturers Index report significant impact to six currency exchange rates each. This is followed by the Australia-RBA Cash Target, Malaysia-Industrial Production, New Zealand-RBNZ Official Cash Rate and Taiwan-CPI with five (5) currency exchange rates each. Lastly, the Japan-Large Retailers’ Sales and MalaysiaOvernight Rate significantly impact four (4) currency exchange rates. Two interesting observations are derived from this result. (1) Half of the Top-8 macroeconomic surprises above are related to interest rate announcements. (2) Only five (5) countries are represented in the Top8 macroeconomic surprises.

Table 6: Macroeconomic Surprises on Pooled Asia-Pacific Exchange Rates The table below provides a ranking of the most significant macroeconomic surprises to the pooled Asia-Pacific exchange rates. The first column shows the country while the second column displays the particular macroeconomic indicator and followed by the third column which indicates the broad category of the events (i.e. IPM=Interest rate, Prices and Money; PBA=Production and Business Activity; TOITE=Total Output, International Trade and Employment). The fourth column shows the β estimate of equation 4.6: Δs t=α+βNt+εt, which measures the reaction of the Asia-Pacific exchange rate to one standard deviation of shock of the respective macroeconomic indicators. Columns five (5) to eight (8) indicate the corresponding standard error of estimate, t-statistic value, p-value and the absolute t-statistics values. Only those events which are statistically significant at the conventional level of at least 10% are shown below. The full ranking list is viewable under Table 7. The ranking is obtained by sorting the absolute t-statistics value – the largest being the most significant. 43 out of the total 107 macroeconomic indicators’ surprises are significant with the US Federal Reserve Rate and the Australia Cash Target Rate leading the pack. Country

Events

Category

Coef. Est.

US

FOMC Rate Decision

IPM

0.001244

AU

RBA CASH TARGET

IPM

US

Building Permits

PBA

JP

Merchnds Trade Balance Total

TOITE

JP

Industrial Production (MoM)

PBA

SG

Advance GDP Estimate (QoQ)

TOITE

US

Consumer Confidence

PBA

PH

Gross Domestic Product (YoY)

TOITE

JP

Large Retailers' Sales

PBA

TW

Industrial Production (YoY)

JP US

s.e.

t-stat

p-value

Abs. t-stat

0.000253

4.9253

0.0000

4.9253

-0.000735

0.000156

-4.7035

0.0000

4.7035

0.000752

0.000175

4.2954

0.0000

4.2954

-0.000630

0.000164

-3.8370

0.0001

3.8370

-0.000391

0.000111

-3.5228

0.0004

3.5228

-0.001476

0.000425

-3.4722

0.0006

3.4722

0.000740

0.000214

3.4534

0.0006

3.4534

-0.000914

0.000265

-3.4464

0.0006

3.4464

-0.000529

0.000155

-3.4145

0.0007

3.4145

TOITE

-0.000432

0.000134

-3.2196

0.0013

3.2196

Tankan Lge Manufacturers Index

PBA

-0.000792

0.000248

-3.1999

0.0015

3.1999

GDP Price Deflator

IPM

-0.000531

0.000168

-3.1608

0.0016

3.1608

JP

Housing Starts (YoY)

PBA

0.000448

0.000146

3.0816

0.0021

3.0816

MY

GDP YoY%

TOITE

-0.000735

0.000243

-3.0232

0.0026

3.0232

TW

Benchmark Interest Rate

TOITE

0.000980

0.000337

2.9102

0.0040

2.9102

US

Import Price Index (MoM)

IPM

0.000438

0.000152

2.8910

0.0039

2.8910

US

Leading Indicators

PBA

-0.000438

0.000167

-2.6210

0.0088

2.6210

US

Current Account Balance

TOITE

0.000779

0.000309

2.5258

0.0118

2.5258

TH

Gross Domestic Product (YoY)

TOITE

0.000637

0.000254

2.5090

0.0125

2.5090

US

Change in Manufact. Payrolls

TOITE

0.000339

0.000137

2.4705

0.0136

2.4705

JP

Machine Orders YOY%

PBA

-0.000474

0.000194

-2.4388

0.0149

2.4388

US

Empire Manufacturing

PBA

-0.000446

0.000183

-2.4377

0.0149

2.4377

US

Wholesale Inventories

PBA

-0.000535

0.000225

-2.3747

0.0177

2.3747

MY

Overnight Rate

IPM

-0.000786

0.000341

-2.3090

0.0214

2.3090

US

Chicago Purchasing Manager

PBA

0.000360

0.000157

2.2902

0.0221

2.2902

SG

Retail Sales (YoY)

PBA

0.000333

0.000148

2.2529

0.0245

2.2529

MY

Industrial Production YoY

PBA

-0.000396

0.000176

-2.2479

0.0248

2.2479

CH

Industrial Production (YoY)

PBA

-0.000508

0.000230

-2.2070

0.0277

2.2070

SG

CPI (YoY)

IPM

-0.000278

0.000128

-2.1717

0.0301

2.1717

US

Advance Retail Sales

PBA

0.000431

0.000203

2.1291

0.0334

2.1291

US

Trade Balance

TOITE

0.000425

0.000204

2.0832

0.0374

2.0832

AU

Trade Balance

TOITE

-0.000316

0.000153

-2.0599

0.0396

2.0599

US

Initial Jobless Claims

TOITE

0.000194

0.000095

2.0585

0.0396

2.0585

JP

Natl CPI YoY

IPM

-0.000316

0.000157

-2.0120

0.0444

2.0120

IN

Qtrly GDP YoY%

TOITE

-0.000605

0.000306

-1.9740

0.0491

1.9740

US

Unemployment Rate

TOITE

-0.000315

0.000166

-1.8998

0.0576

1.8998

JP

All Industry Activity Index (MoM)

PBA

-0.000318

0.000169

-1.8828

0.0600

1.8828

JP

Trade Balance - BOP Basis

TOITE

-0.000318

0.000169

-1.8828

0.0600

1.8828

AU

Producer Price Index (QoQ)

IPM

-0.000481

0.000266

-1.8075

0.0716

1.8075

TW

GDP - Constant Prices (YoY)

IPM

-0.000537

0.000300

-1.7876

0.0745

1.7876

SG

Unemployment Rate (sa)

TOITE

-0.000488

0.000283

-1.7265

0.0855

1.7265

KR

Industrial Production (MoM)

PBA

-0.000270

0.000159

-1.6972

0.0899

1.6972

KR

Consumer Price Index (MoM)

IPM

-0.000236

0.000139

-1.6941

0.0905

1.6941

Figure 6: Number of Significant Events from Each Country to the Pooled Asia-Pacific Exchange Rates 16 14 12 10 8 6 4 2 0 US

JP

SG

AU

MY

TW

KR

TH

IN

PH

CH

NZ

ID

The graph above shows the number of macroeconomic events from each country in the Asia-Pacific which significantly affects the pooled regional exchange rates. We can reasonably expect US and Japan to contribute higher number of significant events because the macroeconomic indicators from these two countries are the largest in our sample. One interesting observation is gathered from this result: none of the New Zealand macroeconomic indicator has any significant impact to the pooled Asia-Pacific exchange rates despite its status as an advanced economy. The most likely reason for this observation is the early time zone for the announcement of New Zealand data which makes the effect of the surprises fades off throughout the day.

Table 7: Comparison of the Ranking of the Most Significant Macroeconomic Shocks to Exchange Rates from Changing in Estimation Technique 2LS Regression Country

Events

US

FOMC Rate Decision

AU

RBA CASH TARGET

US

Building Permits

JP

Merchnds Trade Balance Total

SUR

Ranking

Coef. Est.

Abs. t-stat

Ranking

Coef. Est.

Abs. t-stat

1

0.001244

4.9253

20

0.000315

4.9253

2

-0.000735

4.7035

9

-0.000278

4.7035

3

0.000752

4.2954

4

-0.000630

3.8370

28 69

0.000192 -0.000052

4.2954 3.8370

JP

Industrial Production (MoM)

SG

Advance GDP Estimate (QoQ)

US

Consumer Confidence

PH

Gross Domestic Product (YoY)

JP

Large Retailers' Sales

TW

Industrial Production (YoY)

JP

Tankan Lge Manufacturers Index

US

GDP Price Deflator

JP

Housing Starts (YoY)

MY

GDP YoY%

TW

Benchmark Interest Rate

US

Import Price Index (MoM)

US

Leading Indicators

US

Current Account Balance

TH

Gross Domestic Product (YoY)

US

Change in Manufact. Payrolls

JP

Machine Orders YOY%

US

Empire Manufacturing

US

Wholesale Inventories

MY

Overnight Rate

US

Chicago Purchasing Manager

SG

Retail Sales (YoY)

MY

Industrial Production YoY

CH

Industrial Production (YoY)

SG

CPI (YoY)

US

Advance Retail Sales

US

Trade Balance

AU

Trade Balance

US

Initial Jobless Claims

JP

Natl CPI YoY

5

-0.000391

3.5228

101

-0.000003

3.5228

6

-0.001476

3.4722

1

-0.000923

3.4722

7

0.000740

3.4534

16

0.000213

3.4534

8

-0.000914

3.4464

13

-0.000371

3.4464

9

-0.000529

3.4145

31

-0.000169

3.4145

10

-0.000432

3.2196

21

-0.000150

3.2196

11

-0.000792

3.1999

12

-0.000386

3.1999

12

-0.000531

3.1608

10

-0.000292

3.1608

13

0.000448

3.0816

42

0.000100

3.0816

14

-0.000735

3.0232

24

-0.000389

3.0232

15

0.000980

2.9102

7

0.000799

2.9102

16

0.000438

2.8910

14

0.000186

2.8910

17

-0.000438

2.6210

105

-0.000001

2.6210

18

0.000779

2.5258

77

0.000070

2.5258

19

0.000637

2.5090

29

0.000281

2.5090

20

0.000339

2.4705

57

-0.000067

2.4705

21

-0.000474

2.4388

43

-0.000112

2.4388

22

-0.000446

2.4377

18

-0.000268

2.4377

23

-0.000535

2.3747

36

-0.000134

2.3747

24

-0.000786

2.3090

5

-0.000504

2.3090

25

0.000360

2.2902

50

0.000100

2.2902

26

0.000333

2.2529

25

0.000189

2.2529

27

-0.000396

2.2479

4

-0.000302

2.2479

28

-0.000508

2.2070

3

-0.000288

2.2070

29

-0.000278

2.1717

27

-0.000114

2.1717

30

0.000431

2.1291

40

0.000112

2.1291

31

0.000425

2.0832

88

0.000016

2.0832

32

-0.000316

2.0599

74

0.000029

2.0599

33

0.000194

2.0585

72

0.000018

2.0585

34

-0.000316

2.0120

26

-0.000198

2.0120

IN

Qtrly GDP YoY%

US

Unemployment Rate

JP

All Industry Activity Index (MoM)

JP

Trade Balance - BOP Basis

AU

Producer Price Index (QoQ)

TW

GDP - Constant Prices (YoY)

SG

Unemployment Rate (sa)

KR

Industrial Production (MoM)

KR

Consumer Price Index (MoM)

TH

Manufacturing Production (YoY)

JP

Gross Domestic Product (QoQ)

IN

Industrial Production YoY

NZ

Unemployment Rate

JP

Machine Orders (MoM)

US

Change in Nonfarm Payrolls

TW

Total Trade Bal in US$ Billion

US

Avg Hourly Earning MOM Prod

SG

GDP (YoY)

SG

Non-oil Domestic Exports (YoY)

PH

Overnight Borrowing Rate

JP

Consumer Confidence

AU

Consumer Prices (QoQ)

US

Housing Starts

TH

Current Account Balance (USD)

JP

Current Account Total

AU

Unemployment Rate

NZ

Trade Balance

CH

Consumer Price Index (YoY)

US

ISM Non-Manufacturing

AU

Gross Domestic Product (QoQ)

35

-0.000605

1.9740

22

-0.000373

1.9740

36

-0.000315

1.8998

47

-0.000076

1.8998

37

-0.000318

1.8828

93

-0.000015

1.8828

38

-0.000318

1.8828

94

-0.000015

1.8828

39

-0.000481

1.8075

8

-0.000306

1.8075

40

-0.000537

1.7876

2

-0.000610

1.7876

41

-0.000488

1.7265

6

-0.000307

1.7265

42

-0.000270

1.6972

91

0.000015

1.6972

43

-0.000236

1.6941

86

0.000024

1.6941

44

-0.000249

1.6062

38

0.000115

1.6062

45

-0.000367

1.5233

34

-0.000209

1.5233

46

-0.000315

1.4987

71

0.000080

1.4987

47

0.000678

1.4901

37

0.000243

1.4901

48

-0.000214

1.3803

80

0.000030

1.3803

49

0.000227

1.3590

52

0.000082

1.3590

50

0.000239

1.3351

60

0.000059

1.3351

51

0.000197

1.3295

83

-0.000028

1.3295

52

0.000404

1.3008

41

0.000145

1.3008

53

0.000193

1.2802

65

0.000049

1.2802

54

0.000383

1.2421

64

0.000069

1.2421

55

0.000259

1.2346

30

0.000176

1.2346

56

-0.000333

1.2252

59

0.000138

1.2252

57

0.000200

1.2173

53

0.000074

1.2173

58

-0.000188

1.1937

104

0.000001

1.1937

59

0.000191

1.1516

73

-0.000040

1.1516

60

0.000227

1.1075

82

0.000029

1.1075

61

0.000165

1.0648

33

0.000092

1.0648

62

0.000152

1.0218

79

-0.000030

1.0218

63

-0.000134

1.0215

55

0.000060

1.0215

64

-0.000265

0.9858

49

-0.000142

0.9858

AU

Current Account Balance

NZ

Consumer Prices (QoQ)

US

Personal Spending

ID

Bank Indonesia Reference Rate

JP

Jobless Rate

US

Factory Orders

US

New Home Sales

US

Personal Income

AU

Employment Change

CH

Trade Balance (USD)

TW

Unemployment Rate - sa

TW

CPI YoY%

US

ISM Manufacturing

ID

Total Trade Balance

US

Durable Goods Orders

JP

Coincident Index CI

MY

CPI YoY

US

Philadelphia Fed.

NZ

RBNZ Official Cash Rate

US

GDP QoQ (Annualized)

NZ

Retail Sales (MoM)

US

U. of Michigan Confidence

JP

Adjusted Current Account Total

MY

Trade Balance

US

Capacity Utilization

JP

Leading Index CI

JP

Tertiary Industry Index (MoM)

JP

Tokyo CPI YoY

US

Producer Price Index (MoM)

KR

GDP at Constant Price (YoY)

65

-0.000199

0.9228

102

-0.000003

0.9228

66

-0.000244

0.8885

100

-0.000012

0.8885

67

0.000157

0.8775

67

-0.000059

0.8775

68

0.000201

0.8713

70

-0.000052

0.8713

69

-0.000130

0.8505

58

-0.000056

0.8505

70

0.000184

0.8161

95

-0.000009

0.8161

71

-0.000117

0.7366

85

0.000027

0.7366

72

0.000126

0.7275

51

-0.000083

0.7275

73

0.000126

0.7165

98

0.000013

0.7165

74

0.000169

0.6999

23

0.000194

0.6999

75

0.000104

0.6619

99

0.000006

0.6619

76

0.000123

0.6479

107

0.000001

0.6479

77

0.000114

0.6320

15

0.000249

0.6320

78

-0.000076

0.6305

63

0.000046

0.6305

79

-0.000111

0.6144

76

-0.000035

0.6144

80

0.000087

0.6115

90

0.000014

0.6115

81

-0.000090

0.5305

61

-0.000062

0.5305

82

-0.000109

0.5214

84

-0.000023

0.5214

83

0.000114

0.5196

19

0.000299

0.5196

84

0.000089

0.4628

62

-0.000064

0.4628

85

-0.000071

0.4343

17

0.000212

0.4343

86

0.000041

0.3838

68

-0.000032

0.3838

87

0.000064

0.3808

45

-0.000113

0.3808

88

-0.000069

0.3540

11

-0.000425

0.3540

89

-0.000070

0.3485

32

-0.000112

0.3485

90

-0.000051

0.3464

81

0.000026

0.3464

91

-0.000058

0.3424

39

-0.000111

0.3424

92

-0.000042

0.2716

92

-0.000016

0.2716

93

0.000066

0.2496

103

-0.000002

0.2496

94

0.000064

0.2414

35

0.000155

0.2414

CH

Producer Price Index (YoY)

US

Business Inventories

ID

Inflation NSA (MoM)

TH

Benchmark Interest Rate

PH

Consumer Price Index NSA (MoM)

TW

Current Account Balance (USD)

SG

Industrial Production YoY

US

Industrial Production

NZ

GDP QoQ

JP

Japan Money Stock M2 YoY

AU

Retail Sales s.a. (MoM)

US

Consumer Price Index (MoM)

TH

Consumer Price Index (YoY)

95

0.000039

0.2357

97

0.000007

0.2357

96

-0.000047

0.2322

48

0.000098

0.2322

97

0.000039

0.2316

87

0.000026

0.2316

98

0.000060

0.1983

75

-0.000039

0.1983

99

-0.000026

0.1257

66

0.000038

0.1257

100

-0.000041

0.1240

46

-0.000083

0.1240

101

-0.000018

0.1161

89

-0.000016

0.1161

102

0.000022

0.1114

54

-0.000062

0.1114

103

-0.000023

0.1068

78

0.000052

0.1068

104

-0.000010

0.0585

44

-0.000129

0.0585

105

-0.000013

0.0397

106

-0.000001

0.0397

106

-0.000005

0.0285

56

-0.000058

0.0285

107

-0.000002

0.0109

96

0.000013

0.0109