Daily Tourist Arrivals, Exchange Rates and Volatility for Korea and Taiwan

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.exchange rates;GARCH;leverage;asymmetry;long memory;EGARCH;HAR;Korean tourist arrivals;GJR;global financial crisis;approximate price effect

Daily tourist arrivals, exchange rates and volatility for Korea and Taiwan

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.exchange rates;GARCH;leverage;asymmetry;long memory;Asian economic and financial crisis;EGARCH;HAR;Korean tourist arrivals;GJR;approximate price effects;global financial crisis

Aggregation, Heterogeneous Autoregression and Volatility of Daily International Tourist Arrivals and Exchange Rates

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.exchange rates;GARCH;G32;EGARCH;HAR;GJR;global financial crisis;approximate long memory;asymmetry, leverage;daily effects;international tourist arrivals;spatial aggregation;temporal aggregation;weekly effects

What do Experts Know About Ranking Journal Quality? A Comparison with ISI Research Impact in Finance

Experts possess knowledge and information that are not publicly available. The paper is concerned with the ranking of academic journal quality and research impact using a survey of experts from a national project on ranking academic finance journals. A comparison is made with publicly available bibliometric data, namely the Thomson Reuters ISI Web of Science citations database (hereafter ISI) for the Business - Finance category. The paper analyses the leading international journals in Finance using expert scores and quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in the expert scores and alternative RAMs, where the RAMs are based on alternative transformations of citations taken from the ISI database. Alternative RAMs may be calculated annually or updated daily to answer the perennial questions as to When, Where and How (frequently) published papers are cited (see Chang et al. (2011a, b, c)). The RAMs include the most widely used RAM, namely the classic 2-year impact factor including journal self citations (2YIF), 2-year impact factor excluding journal self citations (2YIF*), 5-year impact factor including journal self citations (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, PI-BETA (Papers Ignored - By Even The Authors), 2-year Self-citation Threshold Approval Ratings (2Y-STAR), Historical Self-citation Threshold Approval Ratings (H-STAR), Impact Factor Inflation (IFI), and Cited Article Influence (CAI). As data are not available for 5YIF, Article Influence and CAI for 13 of the leading 34 journals considered, 10 RAMs are analysed for 21 highly-cited journals in Finance. Harmonic mean rankings of the 10 RAMs for the 34 highly-cited journals are also presented. It is shown that emphasizing the 2-year impact factor of a journal, which partly answers the question as to When published papers are cited, to the exclusion of other informative RAMs, which answer Where and How (frequently) published papers are cited, can lead to a distorted evaluation of journal impact and influence relative to the Harmonic Mean rankings. A simple regression model is used to predict expert scores on the basis of RAMs that capture journal impact, journal policy, the number of high quality papers, and quantitative information about a journal.IFI;PI-BETA;STAR;article influence;eigenfactor;h-index;C3PO;impact factor;research assessment measures;C81;C83;C18;expert scores;journal quality

Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets

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.crude oil prices;multivariate GARCH;volatility spillovers;forward returns;futures returns;spot returns;conditional correlation

Estimating Price Effects in an Almost Ideal Demand Model of Outbound Thai Tourism to East Asia

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.tourism demand;almost ideal Demand (AID) model;compensated prices;budget shares;complements;error correction;monthly frequency;price competitiveness;substitutes;uncompensated prices

Modelling Long Memory Volatility in Agricultural Commodity Futures Returns

This paper estimates the long memory volatility model for 16 agricultural commodity futures returns from different futures markets, namely corn, oats, soybeans, soybean meal, soybean oil, wheat, live cattle, cattle feeder, pork, cocoa, coffee, cotton, orange juice, Kansas City wheat, rubber, and palm oil. The class of fractional GARCH models, namely the FIGARCH model of Baillie et al. (1996), FIEGACH model of Bollerslev and Mikkelsen (1996), and FIAPARCH model of Tse (1998), are modelled and compared with the GARCH model of Bollerslev (1986), EGARCH model of Nelson (1991), and APARCH model of Ding et al. (1993). The estimated d parameters, indicating long-term dependence, suggest that fractional integration is found in most of agricultural commodity futures returns series. In addition, the FIGARCH (1,d,1) and FIEGARCH(1,d,1) models are found to outperform their GARCH(1,1) and EGARCH(1,1) counterparts.fractional integration;conditional volatility;long memory;agricultural commodity futures;asymmetric

Are Forecast Updates Progressive?

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.econometric models;intuition;actual value;forecast errors;initial forecast;macro-economic forecasts;primary forecast;progressive forecast updates;revised forecast

How are Journal Impact, Prestige and Article Influence Related? An Application to Neuroscience

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.prestige;IFI;PI-BETA;STAR;eigenfactor;h-index;immediacy;zinfluence;C3PO;impact factor;article Influence;cited article influence

What Makes a Great Journal Great in Economics? The Singer Not the Song.

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.IFI;PI-BETA;STAR;article influence;eigenfactor;h-index;immediacy;impact factors;measures;research assessment;zinfluence;C3PO