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A government’s ability to forecast key economic fundamentals accurately can affect business confidence, consumer sentiment, and foreign direct investment, among others. A government forecast based on an econometric model is replicable, whereas one that is not fully based on an econometric model is non-replicable. Governments typically provide non-replicable forecasts (or expert forecasts) of economic fundamentals, such as the inflation rate and real GDP growth rate. In this paper, we develop a methodology for evaluating non-replicable forecasts. We argue that in order to do so, one needs to retrieve from the non-replicable forecast its replicable component, and that it is the difference in accuracy between these two that matters. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the proposed methodological approach. Our main finding is that the undocumented knowledge of the Taiwanese government reduces forecast errors substantially.

Diversities in human physiology have been partially shaped by adaptation to natural environments and changing cultures. Recent genomic analyses have revealed single nucleotide polymorphisms (SNPs) that are associated with adaptations in immune responses, obvious changes in human body forms, or adaptations to extreme climates in select human populations. Here, we report that the human GIP locus was differentially selected among human populations based on the analysis of a nonsynonymous SNP (rs2291725). Comparative and functional analyses showed that the human GIP gene encodes a cryptic glucose-dependent insulinotropic polypeptide (GIP) isoform (GIP55S or GIP55G) that encompasses the SNP and is resistant to serum degradation relative to the known mature GIP peptide. Importantly, we found that GIP55G, which is encoded by the derived allele, exhibits a higher bioactivity compared with GIP55S, which is derived from the ancestral allele. Haplotype structure analysis suggests that the derived allele at rs2291725 arose to dominance in East Asians ∼8100 yr ago due to positive selection. The combined results suggested that rs2291725 represents a functional mutation and may contribute to the population genetics observation. Given that GIP signaling plays a critical role in homeostasis regulation at both the enteroinsular and enteroadipocyte axes, our study highlights the importance of understanding adaptations in energy-balance regulation in the face of the emerging diabetes and obesity epidemics.

It is common practice to evaluate fixed-event forecast revisions in macroeconomics by regressing current revisions on one-period lagged revisions. Under weak-form efficiency, the correlation between the current and one-period lagged revisions should be zero. The empirical findings in the literature suggest that the null hypothesis of zero correlation between the current and one-period lagged revisions is rejected quite frequently, where the correlation can be either positive or negative. In this paper we propose a methodology to be able to interpret such non-zero correlations in a straightforward manner. Our approach is based on the assumption that forecasts can be decomposed into both an econometric model and expert intuition. The interpretation of the sign of the correlation between the current and one-period lagged revisions depends on the process governing intuition, and the correlation between intuition and news.

The paper analyses the leading journals in Neurosciences using quantifiable Research Assessment Measures (RAM), highlights the similarities and differences in alternative RAM, shows that several RAM capture similar performance characteristics of highly cited journals, and shows that some other RAM have low correlations with each other, and hence add significant informational value. Alternative RAM are discussed for the Thomson Reuters ISI Web of Science database (hereafter ISI). The RAM that are calculated annually or updated daily include the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor score, Article Influence score, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, PI-BETA (Papers Ignored - By Even The Authors), 2-year and historical Self-citation Threshold Approval Ratings (STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). The RAM are analysed for 26 highly cited journals in the ISI category of Neurosciences. The paper finds that the Eigenfactor score and PI-BETA are not highly correlated with the other RAM scores, so that they convey additional information regarding journal rankings, that Article Influence is highly correlated with some existing RAM, so that it has little informative incremental value, and that CAI has additional informational value to that of Article Influence. Harmonic mean rankings of the 13 RAM criteria for the 26 highly cited journals are also presented. Emphasizing the 2-year impact factor of a journal to the exclusion of other informative RAM criteria is shown to lead to a distorted evaluation of journal performance and influence, especially given the informative value of several other RAM.

The paper is concerned with analysing what makes a great journal great in the sciences, based on quantifiable Research Assessment Measures (RAM). Alternative RAM are discussed, with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). Various ISI RAM that are calculated annually or updated daily are defined and analysed, including the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, PI-BETA (Papers Ignored - By Even The Authors), Impact Factor Inflation (IFI), and three new RAM, namely Historical Self-citation Threshold Approval Rating (H-STAR), 2 Year Self-citation Threshold Approval Rating (2Y-STAR), and Cited Article Influence (CAI). The RAM data are analysed for the 6 most highly cited journals in 20 highly-varied and well-known ISI categories in the sciences, where the journals are chosen on the basis of 2YIF. The application to these 20 ISI categories could be used as a template for other ISI categories in the sciences and social sciences, and as a benchmark for newer journals in a range of ISI disciplines. In addition to evaluating the 6 most highly cited journals in each of 20 ISI categories, the paper also highlights the similarities and differences in alternative RAM, finds that several RAM capture similar performance characteristics for the most highly cited scientific journals, determines that PI-BETA is not highly correlated with the other RAM, and hence conveys additional information regarding research performance. In order to provide a meta analysis summary of the RAM, which are predominantly ratios, harmonic mean rankings are presented of the 13 RAM for the 6 most highly cited journals in each of the 20 ISI categories. It is shown that emphasizing THE impact factor, specifically the 2-year impact factor, of a journal to the exclusion of other informative RAM can lead to a distorted evaluation of journal performance and influence on different disciplines, especially in view of inflated journal self citations.

Macroeconomic forecasts are often based on the interaction between econometric models and experts. A forecast that is based only on an econometric model is replicable and may be unbiased, whereas a forecast that is not based only on an econometric model, but also incorporates an expert’s touch, is non-replicable and is typically biased. In this paper we propose a methodology to analyze the qualities of combined non-replicable forecasts. One part of the methodology seeks to retrieve a replicable component from the non-replicable forecasts, and compares this component against the actual data. A second part modifies the estimation routine due to the assumption that the difference between a replicable and a non-replicable forecast involves a measurement error. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the methodological approach.

This paper examines the long- and short-run asymmetric adjustments and pairs trades for nine pairs of spot and futures prices, itemized as three own pairs for three different bio-fuel ethanol types, three own pairs for three related agricultural products, namely corn, soybeans and sugar, and three cross pairs that included hybrids of the spot price of each of the agricultural products and an ethanol futures price. Most of the spreads’ asymmetric adjustments generally occur during narrowing. The three ethanol pairs that contain the eCBOT futures with each of Chicago spot, New York Harbor spot and Western European (Rotterdam) spot show different long-run adjustments, arbitrage profitable opportunities and price risk hedging capabilities. The asymmetric spread adjustments for the three grains are also different, with corn spread showing the strongest long-run widening adjustment, and sugar showing the weakest narrowing adjustment. Among others, the empirical analysis indicates the importance of potentially hedging the spot prices of agricultural commodities with ethanol futures contracts, which sends an important message that the ethanol futures market is capable of hedging price risk in agricultural commodity markets. The short-run asymmetric adjustments for individual prices in the nine pairs, with the exception of the corn own pair, underscore the importance of futures prices in the price discovery and hedging potential, particularly for ethanol futures.

We examine the impact of R&D and technology imports on firm performance in Taiwan’s manufacturing industry in a policy context of industrial upgrading. To do so, we estimate a Translog production function on two panels (covering 1992-1995 and 1997-2003), using stochastic frontier estimation. We find that the effects of both knowledge inputs become significant (with evidence of complementarities) in a larger number of industries in the second panel. These results suggest that the policies encouraging innovation implemented from 1991 onwards paid off in the second half of the 1990s, with innovation driving firm sales. In traditional industries, the effect of innovation can be interpreted as an effort to catch up with the global technology frontier. In the electronics and high-technology industries, it rather testifies of the emergence of a new domain of specialization for Taiwan - which was largely enabled by the aforementioned innovation policies.

This paper examines the practical usefulness of two new journal performance metrics, namely the Eigenfactor score, which is said to measure “importance”, and Article Influence score, which is said to measure “prestige”, using the most recent ISI data for 2009 for the 200 most highly cited journals in each of the Sciences and Social Sciences, and compares them with two existing ISI metrics, namely Total Citations and the 5-year Impact Factor (5YIF) of a journal. It is shown that the Sciences and Social Sciences are different in terms of the strength of the relationship of journal performance metrics, although the actual relationships are very similar. Moreover, the importance and prestige journal performance metrics are shown to be closely related to the two existing ISI metrics, and hence add little in practical usefulness to what is already known. These empirical results are compared with existing results in the literature.

The paper examines the performance of four multivariate volatility models, namely CCC, VARMA-GARCH, DCC, BEKK and diagonal BEKK, for the crude oil spot and futures returns of two major benchmark international crude oil markets, Brent and WTI, to calculate optimal portfolio weights and optimal hedge ratios, and to suggest a crude oil hedge strategy. The empirical results show that the optimal portfolio weights of all multivariate volatility models for Brent suggest holding futures in larger proportions than spot. For WTI, however, DCC, BEKK and diagonal BEKK suggest holding crude oil futures to spot, but CCC and VARMA-GARCH suggest holding crude oil spot to futures. In addition, the calculated optimal hedge ratios (OHRs) from each multivariate conditional volatility model give the time-varying hedge ratios, and recommend to short in crude oil futures with a high proportion of one dollar long in crude oil spot. Finally, the hedging effectiveness indicates that diagonal BEKK (BEKK) is the best (worst) model for OHR calculation in terms of reducing the variance of the portfolio.

This work describes a novel triple-band bio-telemetry system that is implemented using a miniaturized implantable antenna and triple-band communication circuits for implantable applications. The proposed miniaturized implantable antenna effectively covers three bands for 402 MHz at MICS (medical implant communications service) band, 433 MHz and 2.4 GHz at ISM (industrial, scientific, and medical) band by using radiator of π-shape with stacked and spiral structure. This triple-band communication circuits consist of a 402 MHz data transmission telemetry and a 433 MHz wireless powering transmission circuit, as well as a 2.4 GHz wake-up controller circuit. The system was successively integrated and could substantially improve the life-time of the implantable device.

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, the autoregressive distributed lag (ARDL) model, and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model, are used to investigate the relationship between crude oil price and six global fertilizer prices. Weekly data for 2003-2008 for the seven price series are analyzed. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price, which explains why global fertilizer prices reached a peak in 2008. We also find that that the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods, and that the peak crude oil price caused greater volatility in the crude oil price and global fertilizer prices. As volatility invokes financial risk, the relationship between oil price and global fertilizer prices and their associated volatility is important for public policy relating to the development of optimal energy use, global agricultural production, and financial integration.

The paper is concerned with analysing what makes a great journal great in economics, based on quantifiable measures. Alternative Research Assessment Measures (RAM) are discussed, with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). The various ISI RAM that are calculated annually or updated daily are defined and analysed, including the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor score, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, PI-BETA (Papers Ignored - By Even The Authors), and two new RAM measure, the Self-citation Threshold Approval Rating (STAR) score and the Impact Factor Inflation (IFI) score. The ISI RAM data are analysed for the most highly cited journals in the ISI categories of Economics, Management, Business, and Business - Finance. The journals are chosen on the basis of 2YIF (including self citations by both author and journal). The application to these four ISI categories could be used as a template for other ISI categories in both the Social Sciences and the Sciences, and as a benchmark for newer journals in a range of ISI disciplines. In addition to evaluating high quality research in the most highly cited Economics journals, the paper also compares the most highly cited journals in Management, Business, and Business - Finance, alternative RAM, highlights the similarities and differences in alternative RAM criteria, finds that several ISI RAM capture similar performance characteristics for the most highly cited Economics, Management, Business and Business - Finance journals, determines that the Immediacy and PI-BETA scores are not highly correlated with the other ISI RAM, and hence conveys additional information regarding ISI RAM criteria. Harmonic mean rankings of the 12 RAM criteria for the most highly cited journals in the four categories are also presented. It was shown that emphasizing THE impact factor, specifically the 2-year impact factor, of a journal to the exclusion of other useful and illuminating RAM criteria, can lead to a distorted evaluation of journal performance and influence on the profession.

The paper analyses the leading journals in Neuroscience using quantifiable Research Assessment Measures (RAM). Alternative RAM criteria are discussed for the Thomson Reuters ISI Web of Science database (hereafter ISI). The ISI RAM that are calculated annually or updated daily include the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor score, Article Influence score, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, PI- BETA (Papers Ignored - By Even The Authors), and three new RAM, namely Self-citation Threshold Approval Rating (STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). The RAM criteria are analysed for 26 highly cited journals in the ISI category of Neurosciences. The paper highlights the similarities and differences in alternative RAM criteria, shows that several RAM capture similar performance characteristics of highly cited journals, and finds that the Eigenfactor score and PI-BETA are not highly correlated with the other RAM scores, and hence convey additional information regarding journal rankings. Harmonic mean rankings are also presented of the 13 RAM criteria for the 26 highly cited journals. It is shown that emphasizing the 2-year impact factor of a journal to the exclusion of other informative RAM criteria can lead to a distorted evaluation of journal performance and influence.

The main purpose of this paper is to estimate the volatility in global fertilizer prices. The endogenous structural breakpoint unit root test and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model are estimated for six global fertilizer prices and the crude oil price. Weekly data for 2003-2008 for the seven price series are analysed. The empirical results suggest that the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods, and that the peak crude oil price caused greater volatility in the crude oil price and global fertilizer prices.

This paper examines the novelty and usefulness of two new journal performance metrics, namely the Eigenfactor Score and Article Influence Score, using ISI data for 2009 for the 200 most highly cited journals in each of the sciences and social sciences, and compares them with existing ISI metrics, namely Total Citations and the 5-year Impact Factor (5YIF) of a journal. It is shown that the sciences and social sciences are different in terms of the strength of the relationship of journal performance metrics, although the actual relationships are very similar.

Macro-economic forecasts are often based on the interaction between econometric models and experts. A forecast that is based only on an econometric model is replicable and may be unbiased, whereas a forecast that is not based only on an econometric model, but also incorporates an expert’s touch, is non-replicable and is typically biased. In this paper we propose a methodology to analyze the qualities of combined non-replicable forecasts. One part of the methodology seeks to retrieve a replicable component from the non-replicable forecasts, and compares this component against the actual data. A second part modifies the estimation routine due to the assumption that the difference between a replicable and a non-replicable forecast involves a measurement error. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the methodological approach.

The significant impact of international tourism in stimulating economic growth is especially important from a policy perspective. For this reason, the relationship between international tourism and economic growth would seem to be an interesting and topical empirical issue. The purpose of this paper is to investigate whether tourism specialization is important for economic development in 159 countries over the period 1989-2008. The results from panel threshold regressions show a positive relationship between economic growth and tourism. Instrumental variable estimation of a threshold regression is used to quantify the contributions of tourism specialization to economic growth, while correcting for endogeneity between the regressors and error term. The significant impact of tourism specialization on economic growth in most regressions is robust to different specifications of tourism specialization, as well as to differences in real GDP measurement. However, the coefficients of the tourism specialization variables in the two regimes are significantly different, with a higher impact of tourism on economic growth found in the low regime. These findings do not change with changes in the threshold variables. The empirical results suggest that tourism growth does not always lead to substantial economic growth.

An ultra wide-range delay-locked loop (DLL) has been fabricated in 65nm CMOS technology. The proposed leakage delay unit (LDU) can easily generate a large propagation delay to reduce the difficulties to build up the high-speed digital counter in the cycle-controlled delay unit (CCDU) for a very low-frequency operation. The proposed DLL circuit can operate from 500 KHz to 1 GHz, and the power consumption is 1.8mW @1GHz with very small active area (0.01mm2).

Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover and asymmetric effects across and within the four markets, using three multivariate GARCH models, namely the constant conditional correlation (CCC), vector ARMA-GARCH (VARMA-GARCH) and vector ARMA-asymmetric GARCH (VARMA-AGARCH) models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecast conditional correlations between pairs of crude oil returns have both positive and negative trends. Moreover, the optimal hedge ratios and optimal portfolio weights of crude oil across different assets and market portfolios are evaluated in order to provide important policy implications for risk management in crude oil markets.

A government's ability to forecast key economic fundamentals accurately can affect business confidence, consumer sentiment, and foreign direct investment, among others. A government forecast based on an econometric model is replicable, whereas one that is not fully based on an econometric model is non-replicable. Governments typically provide non-replicable forecasts (or, expert forecasts) of economic fundamentals, such as the inflation rate and real GDP growth rate. In this paper, we develop a methodology to evaluate non-replicable forecasts. We argue that in order to do so, one needs to retrieve from the non-replicable forecast its replicable component, and that it is the difference in accuracy between these two that matters. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the proposed methodological approach. Our main finding is that it is the undocumented knowledge of the Taiwanese government that reduces forecast errors substantially.

Exonuclease 1 (Exo1) is an important nuclease involved in the mismatch repair system that contributes to the maintenance of genomic stability, modulation of DNA recombination and mediation of cell cycle arrest. Potential polymorphisms in Exo1 may alter cancer risks by influencing the repair activity of Exo1. We hypothesized that single-nucleotide polymorphisms (SNPs) in Exo1 might be associated with risks of gastric cancer. In this hospital-based study, the association of Exo1 A-1419G (rs3754093), C-908G (rs10802996), A238G (rs1776177), C498T (rs1635517), K589E (rs1047840), G670E (rs1776148), C723R (rs1635498), L757P (rs9350) and C3114T (rs851797) polymorphisms with gastric cancer risk in a central Taiwanese population was investigated. In total, 179 patients with gastric cancer and 179 age- and gender-matched healthy controls recruited from the China Medical Hospital in central Taiwan were genotyped. A significantly different distribution was found in the frequency of the Exol K589E genotype, but not the other genotypes, between the gastric cancer and control groups. The A allele Exol K589E conferred a significant (P = 0.0094) increased risk of gastric cancer. Gene-environment interactions with smoking were significant for Exo1 K589E polymorphism, which showed that the Exo1 K589E AG/AA genotype in association with smoking conferred an increased risk of 2.07-fold (95% confidence interval = 1.22-3.50) for gastric cancer. Our results provide the first evidence that the A allele of the Exo1 K589E may be associated with the development of gastric cancer and may be a novel and useful marker for primary prevention and anticancer intervention.

We report on the ability to modify the structure and composition of ultrathin oxides grown on Ni and Ni-Al alloy surfaces at room temperature utilizing photon illumination. We find that the nickel-oxide formation is enhanced in the case of oxidation under photo-excitation. The enhanced oxidation kinetics of nickel in 5% Ni-Al alloy is corroborated by experimental and simulation studies of natural and photon-assisted oxide growth on pure Ni(100) surfaces. In case of pure Ni substrates, combined x-ray photoelectron spectroscopy analysis, and atomic force microscope current mapping support the deterministic role of the structure of nickel passive-oxide films on their nanoscale corrosion resistance. Atomistic simulations involving dynamic charge transfer predict that the applied electric field overcomes the activation-energy barrier for ionic migration, leading to enhanced oxygen incorporation into the oxide, enabling us to tune the mixed-oxide composition at atomic length scales. Atomic scale control of ultrathin oxide structure and morphology in the case of pure substrates as well as compositional tuning of complex oxide in the case of alloys leads to excellent passivity as verified from potentiodynamic polarization experiments.

Tourism is a major source of service receipts for many countries, including Taiwan. The two leading tourism countries for Taiwan, comprising a high proportion of world tourist arrivals to Taiwan, are Japan and USA, which are sources of short and long haul tourism, respectively. As it is well known that a strong domestic currency can have adverse effects on international tourist arrivals, daily data from 1 January 1990 to 31 December 2008 are used to model the world price and US$ / New Taiwan $ and Yen/ New Taiwan $ exchange rates, and tourist arrivals from the world, USA and Japan to Taiwan, as well as their associated volatility. The sample period includes the Asian economic and financial crises in 1997, and part of the global financial crisis of 2008-09. Inclusion of the exchange rate allows approximate daily price effects on world, US and Japanese tourist arrivals to Taiwan to be captured. The Heterogeneous Autoregressive (HAR) model does not reproduce the theoretical hyperbolic decay rates associated with fractionally integrated (or long memory) time series models, but it can nevertheless approximate quite accurately and parsimoniously the slowly decaying correlations associated with such models. The HAR model is used to approximate long memory properties in daily exchange rates and international tourist arrivals, to test whether alternative short and long run estimates of conditional volatility are sensitive to the approximate long memory in the conditional mean, to examine asymmetry and leverage in volatility, and to examine the effects of temporal and spatial aggregation. The empirical results show that the conditional volatility estimates are not sensitive to the approximate long memory nature of the conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for world, US and Japanese tourist arrivals to Taiwan, and the world price and US$ / New Taiwan $ and Yen/ New Taiwan $ exchange rates, are statistically adequate and have sensible interpretations. Asymmetry (though not leverage) is found for several alternative HAR models for the world, US and Japanese tourist arrivals to Taiwan. For policy purposes, these empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings as they are generally not independent of the level of aggregation used.

Tourism is a major source of service receipts for many countries, including Taiwan. The two leading tourism countries for Taiwan, comprising a high proportion of world tourist arrivals to Taiwan, are Japan and USA, which are sources of short and long haul tourism, respectively. As it is well known that a strong domestic currency can have adverse effects on international tourist arrivals, daily data from 1 January 1990 to 31 December 2008 are used to model the world price and US$ - New Taiwan $ and Yen - New Taiwan $ exchange rates, and tourist arrivals from the world, USA and Japan to Taiwan, as well as their associated volatility. The sample period includes the Asian economic and financial crises in 1997, and part of the global financial crisis of 2008-09. Inclusion of the exchange rate allows approximate daily price effects on world, US and Japanese tourist arrivals to Taiwan to be captured. The Heterogeneous Autoregressive (HAR) model does not reproduce the theoretical hyperbolic decay rates associated with fractionally integrated (or long memory) time series models, but it can nevertheless approximate quite accurately and parsimoniously the slowly decaying correlations associated with such models. The HAR model is used to approximate long memory properties in daily exchange rates and international tourist arrivals, to test whether alternative short and long run estimates of conditional volatility are sensitive to the approximate long memory in the conditional mean, to examine asymmetry and leverage in volatility, and to examine the effects of temporal and spatial aggregation. The empirical results show that the conditional volatility estimates are not sensitive to the approximate long memory nature of the conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for world, US and Japanese tourist arrivals to Taiwan, and the world price and US$ / New Taiwan $ and Yen/ New Taiwan $ exchange rates, are statistically adequate and have sensible interpretations. Asymmetry (though not leverage) is found for several alternative HAR models for the world, US and Japanese tourist arrivals to Taiwan. For policy purposes, these empirical results suggest that an arbitrary choice of data frequency or spatial aggregation will not lead to robust findings as they are generally not independent of the level of aggregation used.

The main purpose of this paper is to evaluate the effect of crude oil price on global fertilizer prices in both the mean and volatility. The endogenous structural breakpoint unit root test, the autoregressive distributed lag (ARDL) model, and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model, are used to investigate the relationship between crude oil price and six global fertilizer prices. Weekly data for 2003-2008 for the seven price series are analyzed. The empirical results from ARDL show that most fertilizer prices are significantly affected by the crude oil price, which explains why global fertilizer prices reached a peak in 2008. We also find that that the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in other periods, and that the peak crude oil price caused greater volatility in the crude oil price and global fertilizer prices. As volatility invokes financial risk, the relationship between oil price and global fertilizer prices and their associated volatility is important for public policy relating to the development of optimal energy use, global agricultural production, and financial integration.

This paper analyzes the responsiveness of Thai outbound tourism to East Asian destinations, namely China, Hong Kong, Japan, Taiwan and Korea, to changes in effective relative price of tourism, total real total tourism expenditure, and one-off events. The nonlinear and linear Almost Ideal Demand (AID) models are estimated with monthly data to identify the price competitiveness and interdependencies of tourism demand for competing destinations in both long run (static) and short run error correction (dynamic) specifications. The homogeneity and symmetry restricted long run and short run AID models are estimated to calculate elasticities. The income elasticities, and the compensated and uncompensated own-price and cross-price elasticities, provide useful information for public and private tourism agents at the various destinations to maintain and improve price competitiveness. The empirical results show that price competitiveness is important for tourism demand for Japan, Korea and Hong Kong in the long run, and for Hong Kong and Taiwan in the short run. With regard to long run cross-price elasticities, the substitution effect can be found in the following pairs of destinations: China-Korea, Japan-Hong Kong, Taiwan-Hong Kong, Japan-Korea, and Taiwan-Korea. In addition to the substitution effect, the complementary effect can be found in the following pairs of destinations: China-Hong Kong, China-Japan, China-Taiwan, Japan-Taiwan, and Korea-Hong Kong. Contrary to the findings obtained from the long run AID specification, Japan-Korea and Taiwan-Korea are complements in the short run. Furthermore, the real total tourism expenditure elasticities indicate that China’s share of real total tourism expenditure is inelastic in response to a change in real total tourism expenditure, while Korea’s share of real total tourism expenditure is most sensitive to changes in expenditure in the long run. The greatest impact on the share of real total tourism expenditure in the short run is tourism demand for Taiwan.

This paper examines the impact of the three main channels of international trade on domestic innovation, namely outward direct investment, inward direct investment (IDI) and exports. The number of Triadic patents serves as a proxy for innovation. The data set contains 37 countries that are considered to be highly competitive in the world market, covering the period 1994 to 2005. The empirical results show that increased exports and outward direct investment are able to stimulate an increase in patent output. In contrast, IDI exhibits a negative relationship with domestic patents. The paper shows that the impact of IDI on domestic innovation is characterized by two forces, and the positive effect of cross-border mergers and acquisitions by foreigners is less than the negative effect of the remaining IDI.

Macro-economic forecasts typically involve both a model component, which is replicable, as well as intuition, which is non-replicable. Intuition is expert knowledge possessed by a forecaster. If forecast updates are progressive, forecast updates should become more accurate, on average, as the actual value is approached. Otherwise, forecast updates would be neutral. The paper proposes a methodology to test whether forecast updates are progressive and whether econometric models are useful in updating forecasts. The data set for the empirical analysis are for Taiwan, where we have three decades of quarterly data available of forecasts and updates of the inflation rate and real GDP growth rate. The actual series for both the inflation rate and the real GDP growth rate are always released by the government one quarter after the release of the revised forecast, and the actual values are not revised after they have been released. Our empirical results suggest that the forecast updates for Taiwan are progressive, and can be explained predominantly by intuition. Additionally, the one-, two- and three-quarter forecast errors are predictable using publicly available information for both the inflation rate and real GDP growth rate, which suggests that the forecasts can be improved.

Macro-economic forecasts are often based on the interaction between econometric models and experts. A forecast that is based only on an econometric model is replicable and may be unbiased, whereas a forecast that is not based only on an econometric model, but also incorporates an expert’s touch, is non-replicable and is typically biased. In this paper we propose a methodology to analyze the qualities of combined non-replicable forecasts. One part of the methodology seeks to retrieve a replicable component from the non-replicable forecasts, and compares this component against the actual data. A second part modifies the estimation routine due to the assumption that the difference between a replicable and a non-replicable forecast involves a measurement error. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the methodological approach.

This paper investigates the conditional correlations and volatility spillovers between the crude oil and financial markets, based on crude oil returns and stock index returns. Daily returns from 2 January 1998 to 4 November 2009 of the crude oil spot, forward and futures prices from the WTI and Brent markets, and the FTSE100, NYSE, Dow Jones and S&P500 stock index returns, are analysed using the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), VARMA-AGARCH model of McAleer, Hoti and Chan (2008), and DCC model of Engle (2002). Based on the CCC model, the estimates of conditional correlations for returns across markets are very low, and some are not statistically significant, which means the conditional shocks are correlated only in the same market and not across markets. However, the DCC estimates of the conditional correlations are always significant. This result makes it clear that the assumption of constant conditional correlations is not supported empirically. Surprisingly, the empirical results from the VARMA-GARCH and VARMA-AGARCH models provide little evidence of volatility spillovers between the crude oil and financial markets. The evidence of asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances suggests that VARMA-AGARCH is superior to VARMA-GARCH and CCC. The estimation and analysis of the volatility and conditional correlations between crude oil returns and stock index returns can provide useful information for investors, oil traders and government agencies that are concerned with the crude oil and stock markets, especially regarding optimal hedging across the two markets.

The significant impact of international tourism in stimulating economic growth is especially important from a policy perspective. For this reason, the relationship between international tourism and economic growth would seem to be an interesting and topical empirical issue. The purpose of this paper is to investigate whether tourism specialization is important for economic development in 159 countries over the period 1989-2008. The results from panel threshold regressions show a positive relationship between economic growth and tourism. Instrumental variable estimation of a threshold regression is used to quantify the contributions of tourism specialization to economic growth, while correcting for endogeneity between the regressors and error term. The significant impact of tourism specialization on economic growth in most regressions is robust to different specifications of tourism specialization, as well as to differences in real GDP measurement. However, the coefficients of the tourism specialization variables in the two regimes are significantly different, with a higher impact of tourism on economic growth found in the low regime. These findings do not change with changes in the threshold variables. The empirical results suggest that tourism growth does not always lead to substantial economic growth.

The paper discusses alternative Research Assessment Measures (RAM), with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). The various ISI RAM that are calculated annually or updated daily are defined and analysed, including the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor score, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, and PI-BETA (Papers Ignored - By Even The Authors). The ISI RAM data are analysed for 8 leading econometrics journals and 4 leading statistics journals. The application to econometrics can be used as a template for other areas in economics, for other scientific disciplines, and as a benchmark for newer journals in a range of disciplines. In addition to evaluating high quality research in leading econometrics journals, the paper also compares econometrics and statistics, alternative RAM, highlights the similarities and differences in alternative RAM criteria, finds that several ISI RAM capture similar performance characteristics for the leading econometrics and statistics journals while the new PI-BETA criterion is not highly correlated with any of the other ISI RAM, and hence conveys additional information regarding ISI RAM, highlights major research areas in leading journals in econometrics, and discusses some likely future uses of RAM.

Both domestic and international tourism are a major source of service export receipts for many countries worldwide, and is also increasingly important in Taiwan. One of the three leading tourism source countries for Taiwan is the Republic of Korea, which is a source of short haul tourism. Daily data from 1 January 1990 to 31 December 2008 are used to model the Korean Won / New Taiwan $ exchange rate and tourist arrivals from Korea to Taiwan, as well as their associated volatility. The sample period includes the Asian economic and financial crises in 1997, and a significant part of the global financial crisis of 2008-09. Inclusion of the exchange rate allows approximate daily price effects on Korean tourism arrivals to Taiwan to be captured. The Heterogeneous Autoregressive (HAR) model is used to capture long memory properties in exchange rates and Korean tourist arrivals, to test whether alternative estimates of conditional volatility are sensitive to the long memory in the conditional mean, and to examine asymmetry and leverage in volatility. The empirical results show that the conditional volatility estimates are not sensitive to the long memory nature of the conditional mean specifications. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for Korean tourist arrivals to Taiwan and the Korean Won / New Taiwan $ exchange rate are statistically adequate and have sensible interpretations. Asymmetry (though not leverage) is found for several alternative HAR models.

The DNA repair gene xeroderma pigmentosum group D (XPD), an important caretaker of the overall genome stability, is thought to play a major role in the development of human malignancy. Polymorphic variants of XPD, at codon 312 (rs1799793), 751 (rs13181) and promoter-114 (rs3810366), were chosen to be studied for their association with bladder cancer susceptibility in a central Taiwanese population.In this hospital-based case-control study, bladder cancer patients (308) and age- and gender-matched healthy controls (308) were recruited and their genotypes were analyzed by a polymerase chain reaction-based restriction fragment length polymorphism (PCR-RFLP) method.A significant difference in the frequency of the XPD codon 312 genotype, but not the XPD codon 751 or promoter-114 genotypes, was found between the bladder cancer and control groups. Those who had G/A or A/A at XPD codon 312 showed a 1.85-fold (95% confidence interval=1.34-2.56) increased risk of bladder cancer compared to those with G/G. As for XPD codon 312 and promoter-114, there was no difference in distribution between the bladder cancer and control groups.The heterozygous and homozygous A allele of the XPD codon 312 may be responsible for bladder carcinogenesis and useful in the early detection and prediction of bladder cancer.

The significant impact of international tourism in stimulating economic growth is especially important from a policy perspective. For this reason, the relationship between international tourism and economic growth would seem to be an interesting empirical issue. In particular, if there is a causal link between international tourism demand and economic growth, then appropriate policy implications may be developed. The purpose of this paper is to investigate whether tourism specialization is important for economic development in East Asia and the Pacific, Europe and Central Asia, Latin America and the Caribbean, the Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa, over the period 1991-2008. The impact of the degree of tourism specialization, which is incorporated as a threshold variable, on economic growth is examined for a wide range of countries at different stages of economic development. The empirical results from threshold estimation identify two endogenous cut-off points, namely 14.97% and 17.50%. This indicates that the entire sample should be divided into three regimes. The results from panel threshold regression show that there exists a positive and significant relationship between economic growth and tourism in two regimes, the regime with the degree of tourism specialization lower than 14.97% (regime 1) and the regime with the degree of tourism specialization between 14.97% and 17.50% (regime 2). However, the magnitudes of the impact of tourism on economic growth in those two regimes are not the same, with the higher impact being found in regime 2. An insignificant relationship between economic growth and tourism is found in regime 3, in which the degree of tourism specialization is greater than 17.50%. The empirical results suggest that tourism growth does not always lead to economic growth.

Non-homologous end-joining (NHEJ) system is a major route in repairing double strand breaks (DSBs), and is important in maintaining the genome stability. The gene XRCC4 is a central role of the NHEJ system, and it is critical in carcinogenesis. In order to reveal the association between XRCC4 and lung cancer, we recruited 164 lung cancer patients and 649 healthy controls from central Taiwan, investigated seven novel polymorphic variants of XRCC4, includes C-1622T (rs7727691), G-1394T (rs6869366), G-652T (rs2075685), C-571T (rs2075686), intron3 DIP (rs28360071), S247A (rs3734091) and intron7 DIP (rs28360317), and analyzed the association of specific genotype with lung cancer susceptibility. The results showed that the XRCC4 G-1394T is significant in Taiwanese lung cancer and the GT genotype of G-1394T is an obvious risk factor of lung cancer susceptibility (P = 0.0049), and the G allele is a risky factor (P = 0.0087). As for XRCC4 C-1622T (rs7727691), G-652T (rs2075685), C-571T (rs2075686), intron3 DIP (rs28360071), S247A (rs3734091) and intron7 DIP (rs28360317) polymorphism sites, there was no difference in the distribution between the lung cancer and control groups. The analyzing results of joint effect for smoking habit and XRCC4 G-1394T polymorphism was that people with GT genotype and smoking habit present the highest risk of lung cancer than other groups (OR = 2.31, 95% CI = 1.43-3.72). The G allele of the XRCC4 G-1394T may be responsible for lung carcinogenesis and maybe useful in early detection and prevention of lung cancer.

The hypothalamus/pituitary axis is central to the regulation of neuroendocrine homeostasis in vertebrates. Based on homologous searches of genome sequences, our laboratory and that of Dr. Y. Takei independently discovered intermedin (also known as adrenomedullin 2) as a novel calcitonin/CGRP/amylin/adrenomedullin family peptide. Intermedin is expressed in a variety of tissues and signals through the CLR/RAMP receptor complexes. In addition to having potent effects on the cardiovascular system, intermedin exhibits unique functional characteristics in the regulation of neuroendocrine system and pituitary hormone secretion. Based on physiological and molecular analyses, we proposed that in the pituitary intermedin could function as a prolactin-releasing factor participating in the estrogen-regulated prolactin release during reproduction. While the exact physiological role and the therapeutic potential of this novel peptide remain to be analyzed, recently progress has pointed to pleiotropic roles in diverse physiological systems in humans and other vertebrates.

Accumulating evidence suggests a pivotal role of the calcitonin receptor-like receptor (CRLR) signaling pathway in preventing damage of the lung by stabilizing pulmonary barrier function. Intermedin (IMD), also termed adrenomedullin-2, is the most recently identified peptide targeting this receptor. Here we investigated the effect of hypoxia on the expression of IMD in the murine lung and cultured murine pulmonary microvascular endothelial cells (PMEC) as well as the role of IMD in regulating vascular permeability. Monoclonal IMD antibodies were generated, and transcript levels were assayed by quantitative RT-PCR. The promoter region of IMD gene was analyzed, and the effect of hypoxia-inducible factor (HIF)-1α on IMD expression was investigated in HEK293T cells. Isolated murine lungs and a human lung microvascular endothelial cell monolayer model were used to study the effect of IMD on vascular permeability. IMD was identified as a pulmonary endothelial peptide by immunohistochemistry and RT-PCR. Hypoxia caused an upregulation of IMD mRNA in the murine lung and PMEC. As shown by these results, HIF-1α enhances IMD promoter activity. Our functional studies showed that IMD abolished the increase in pressure-induced endothelial permeability. Moreover, IMD decreased basal and thrombin-induced hyperpermeability of an endothelial cell monolayer in a receptor-dependent manner and activated PKA in these cells. In conclusion, IMD is a novel hypoxia-induced gene and a potential interventional agent for the improvement of endothelial barrier function in systemic inflammatory responses and hypoxia-induced vascular leakage.

The purpose of this paper is to investigate the volatility spillovers between the returns on crude oil futures and oil company stocks using alternative multivariate GARCH models, namely the CCC model of Bollerslev (1990), VARMA-GARCH model of Ling and McAleer (2003), and VARMA-AGARCH model of McAleer et al. (2008). The paper investigates WTI crude oil futures returns and the stock returns of ten oil companies, which comprise the "supermajor" group of oil companies, namely Exxon Mobil (XOM), Royal Dutch Shell (RDS), Chevron Corporation (CVX), ConocoPhillips (COP), BP (BP) and Total S.A. (TOT), and four other large oil and gas companies, namely Petrobras (PBRA), Lukoil (LKOH), Surgutneftegas (SNGS), and Eni S.p.A. (ENI). Estimates of the conditional correlations between the WTI crude oil futures returns and oil company stock returns are found to be quite low using the CCC model, while the VARMA-GARCH and VARMA-AGARCH models suggest no significant volatility spillover effects in any pairs of returns. The paper also presents evidence of the asymmetric effects of negative and positive shocks of equal magnitude on the conditional variances in all pairs of returns.

Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at- Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia- Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover effects across and within the four markets, using three multivariate GARCH models, namely the CCC, VARMA-GARCH and VARMA-AGARCH models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecasted conditional correlations between pairs of crude oil returns have both positive and negative trends.

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand , respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese tourists to New Zealand and Taiwan are different, and indicate that the former has an asymmetric effect on risk from positive and negative shocks of equal magnitude, while the latter has no asymmetric effect. Moreover, there is a leverage effect in the monthly growth rate of Japanese tourists to New Zealand, whereby negative shocks increase volatility but positive shocks of very similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics, and hence also the issues related to risk and leverage effects, are also applicable to international tourism flows.

The ethyl 5-(2'-alkoxycarbonyl-substituted phenoxy)furan-2-carboxylates (1C-13C) showed good anti-platelet aggregation,(1)) anti-allergic(2)) and anti-inflammatory activities.(2)) A series of 5-(2'-alkoxycarbonyl-substituted phenoxy)furfurals (1F-13F) were prepared for comparing the above activities. The objectives of this research are the synthesis and structural pattern recognition of compounds 1F-13F. The Silica Gel 60 column chromatography method was employed to separate and purify pure compounds 1F-13F by three solvent systems. For the structure elucidation of compounds 1F-13F, four spectroscopic methods were used: electron impact mass (EI-MS), UV-VIS, IR and NMR spectrometers. With the help of spectrometers, investigations can be performed on spectroscopic data. A simple methodology for recognizing structural patterns was carried out with the aid of statistical analysis designed to establish the classification model of the structural skeleton in this research. It was found that compounds 1C-13C and 1F-13F have similar chemical profiles and are clustered into one group. The pattern plots revealed valuable information and showed good correlation between compounds 1C-13C and 1F-13F. These findings correlate directly with the resulting spectroscopic data. These results with those obtained by EI-MS and NMR patterns give insight into a reliable pattern recognition for determining both 1C-13C and 1F-13F skeletons.

The DNA repair gene XRCC4, a member of NHEJ for double strand breaks, is very important in maintaining the overall genome stability, and may play an important role in carcinogenesis. To reveal the relationship between XRCC4 and bladder cancer, seven polymorphic variants of XRCC4, including C-1622T (rs7727691), G-1394T (rs6869366), G-652T (rs2075685), C-571T (rs2075686), intron3 DIP (rs28360071), S247A (rs3734091) and intron7 DIP (rs28360317) were investigated and analyzed for their association with bladder cancer susceptibility.In this case-control study, the association of these variants of XRCC4 with bladder carcinogenesis in Taiwan was investigated. Bladder cancer patients (158) and 158 age- and gender-matched healthy controls were recruited and their genotypes were analyzed by PCR-based restriction fragment length polymorphism method.It was found that XRCC4 G-1394T is a significant SNP in bladder carcinogenesis after analyzing the frequencies of each variant in both bladder cancer and control groups. The data indicated that the heterogeneous G of G-1394T is an obvious risk factor of bladder cancer susceptibility (p=0.005) and the data of G allele also showed a similar situation (p=0.0099). As for the other six polymorphisms, there was no difference between the bladder cancer and control groups.These findings suggest that the G allele of XRCC4 G-1394T may be involved in bladder carcinogenesis and useful in early detection of bladder cancer.

International tourism is a major source of export receipts for many countries worldwide. Although it is not yet one of the most important industries in Taiwan (or the Republic of China), an island in East Asia off the coast of mainland China (or the People's Republic of China), the leading tourism source countries for Taiwan are Japan, followed by USA, Republic of Korea, Malaysia, Singapore, UK, Germany and Australia. These countries reflect short, medium and long haul tourist destinations. Although the People's Republic of China and Hong Kong are large sources of tourism to Taiwan, the political situation is such that tourists from these two sources to Taiwan are reported as domestic tourists. Daily data from 1 January 1990 to 30 June 2007 are obtained from the National Immigration Agency of Taiwan. The Heterogeneous Autoregressive (HAR) model is used to capture long memory properties in the data. In comparison with the HAR(1) model, the estimated asymmetry coefficients for GJR(1,1) are not statistically significant for the HAR(1,7) and HAR(1,7,28) models, so that their respective GARCH(1,1) counterparts are to be preferred. These empirical results show that the conditional volatility estimates are sensitive to the long memory nature of the conditional mean specifications. Although asymmetry is observed for the HAR(1) model, there is no evidence of leverage. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for international tourist arrivals to Taiwan are statistically adequate and have sensible interpretations. However, asymmetry (though not leverage) was found only for the HAR(1) model, and not for the HAR(1,7) and HAR(1,7,28) models.

International tourism is a major source of export receipts for many countries worldwide. Although it is not yet one of the most important industries in Taiwan (or the Republic of China), an island in East Asia off the coast of mainland China (or the People's Republic of China), the leading tourism source countries for Taiwan are Japan, followed by USA, Republic of Korea, Malaysia, Singapore, UK, Germany and Australia. These countries reflect short, medium and long haul tourist destinations. Although the People's Republic of China and Hong Kong are large sources of tourism to Taiwan, the political situation is such that tourists from these two sources to Taiwan are reported as domestic tourists. Daily data from 1 January 1990 to 30 June 2007 are obtained from the National Immigration Agency of Taiwan. The Heterogeneous Autoregressive (HAR) model is used to capture long memory properties in the data. In comparison with the HAR(1) model, the estimated asymmetry coefficients for GJR(1,1) are not statistically significant for the HAR(1,7) and HAR(1,7,28) models, so that their respective GARCH(1,1) counterparts are to be preferred. These empirical results show that the conditional volatility estimates are sensitive to the long memory nature of the conditional mean specifications. Although asymmetry is observed for the HAR(1) model, there is no evidence of leverage. The QMLE for the GARCH(1,1), GJR(1,1) and EGARCH(1,1) models for international tourist arrivals to Taiwan are statistically adequate and have sensible interpretations. However, asymmetry (though not leverage) was found only for the HAR(1) model, and not for the HAR(1,7) and HAR(1,7,28) models.

International and domestic tourism are leading economic activities in the world today. Tourism has been known to generate goods and services directly and indirectly, attract foreign currency, stimulate employment, and provide opportunities for investment. It has also been recognized as an important means for achieving economic development. Substantial research has been conducted to evaluate the role of international tourism, and its associated volatility, within and across various economies. This paper applies several recently developed models of multivariate conditional volatility to investigate the interdependence of international tourism demand, as measured by international tourist arrivals, and its associated volatility in the four leading destinations in ASEAN, namely Indonesia, Malaysia, Singapore and Thailand. Each of these countries has attractive tourism characteristics, such as significant cultural and natural resources. Shocks to international tourism demand volatility could affect, positively or negatively, the volatility in tourism demand of neighbouring countries. The empirical results should encourage regional co-operation in tourism development among ASEAN member countries, and also mobilize international and regional organizations to provide appropriate policy actions.