7,428 research outputs found

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

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    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, PIBETA (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.Expert scores; Journal quality; Research assessment measures; Impact factor; IFI; C3PO; PI-BETA; STAR; Eigenfactor; Article Influence; h-index

    How Should Journal Quality be Ranked? An Application to Agricultural, Energy, Environmental and Resource Economics

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    The Thomson Reuters ISI Web of Science citations database (hereafter ISI) category of Economics has one of the largest numbers of journals, at 304, of any ISI discipline, and hence has wide coverage. The paper analyses the leading international journals in the Economics sub-disciplines of Energy, Environmental and Resource Economics using quantifiable Research Assessment Measures (RAMs), and highlights the similarities and differences in alternative RAMs. 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 one of the 20 journals considered, 13 RAMs are analysed for 19 highly-cited journals in Energy, Environmental and Resource Economics in the ISI category of Economics. Harmonic mean rankings of the 13 RAMs for the 19 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.Research assessment measures; Impact factor; IFI; C3PO; PI-BETA; STAR; Eigenfactor; Article Influence; h-index

    Using the Asymptotically Ideal Model to estimate the impact of knowledge on labour productivity: An application to Taiwan in the 1990s.

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    This paper examines the impact of embodied and disembodied knowledge on labour productivity in Taiwan’s manufacturing industry, using the Asymptotically Ideal Model. The model is estimated on a panel of 27,754 firms observed from 1992 to 1995, using three estimations procedures: fixed-effect regression, random-effect GLS, and Hausman-Taylor estimation. Our findings show that, in traditional industries, labour productivity is mostly driven by embodied knowledge, whereas in high-tech industries, labour productivity depends on both embodied and disembodied knowledge. The latter result may be the consequence of the Industrial Upgrading Statute implemented in Taiwan after 1991.Asymptotically Ideal Model; Disembodied Knowledge; Embodied Knowledge; Labour Productivity; Newly Industrialized Countries.

    Knowledge sourcing and firm performance in an industrializing economy: The case of Taiwan (1992-2003)

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    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 models. We find that the effects of both knowledge inputs become significant 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.Manufacturing Industries, Newly Industrialized Countries, Technology Imports - Stochastic Frontier Estimation.

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

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    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 exchangerateandtouristarrivalsfromKoreatoTaiwan,aswellastheirassociatedvolatility.ThesampleperiodincludestheAsianeconomicandfinancialcrisesin1997,andasignificantpartoftheglobalfinancialcrisisof200809.InclusionoftheexchangerateallowsapproximatedailypriceeffectsonKoreantourismarrivalstoTaiwantobecaptured.TheHeterogeneousAutoregressive(HAR)modelisusedtocapturelongmemorypropertiesinexchangeratesandKoreantouristarrivals,totestwhetheralternativeestimatesofconditionalvolatilityaresensitivetothelongmemoryintheconditionalmean,andtoexamineasymmetryandleverageinvolatility.Theempiricalresultsshowthattheconditionalvolatilityestimatesarenotsensitivetothelongmemorynatureoftheconditionalmeanspecifications.TheQMLEfortheGARCH(1,1),GJR(1,1)andEGARCH(1,1)modelsforKoreantouristarrivalstoTaiwanandtheKoreanWon/NewTaiwan 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.

    Industrial Agglomeration, Geographic Innovation and Total Factor Productivity: The Case of Taiwan

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    The paper analyses the impact of geographic innovation on Total Factor Productivity (TFP) in Taiwan. Using 242 four-digit standard industrial classification (SIC) industries in Taiwan in 2001, we compute TFP by estimating Translog production functions with K, L, E and M inputs, and measure the geographic innovative activity using both Krugman's Gini coefficients and the location Herfindahl index. We also consider the geographic innovation variable as an endogenous variable and use 2SLS to obtain a consistent, albeit inefficient, estimator. The empirical results show a significantly positive effect of geographic innovation, as well as R&D expenditure, on TFP. These results are robust for the Gini coefficients and location Herfindahl index, when industry characteristics and heteroskedasticity are controlled. Moreover, according to the endogeneity of geographic innovation, the Hausman test shows that the geographic innovation variable should be treated as endogenous, which supports the modern theory of industrial clustering about innovation spillovers within clusters.Industry agglomeration; Geographic innovation; Total factor productivity; Cluster; Research and Development

    Citations and Impact of ISI Tourism and Hospitality Journals

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    The paper analyses the leading international journals in Tourism and Hospitality Research using quantifiable Research Assessment Measures (RAMs), highlights the similarities and differences in alternative RAMs, shows that several RAMs capture similar performance characteristics of highly cited journals, and shows that some other RAMs have low correlations with each other, and hence add significant informational value. Several RAMs are discussed for the Thomson Reuters ISI Web of Science database (hereafter ISI). Alternative RAMs may be calculated annually or updated daily to answer the questions as to When, Where and How (frequently) published papers are cited. 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 11 of the 14 journals considered, 10 RAMs are analysed for 14 highly-cited journals in Tourism and Hospitality in the ISI category of Hospitality, Leisure, Sports & Tourism. Harmonic mean rankings of the 10 RAMs for the 14 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.Research assessment measures, Impact factor, IFI, C3PO, PI-BETA, STAR, Eigenfactor, Article Influence, h-index.

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

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    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/NewTaiwan / New Taiwan and Yen/ New Taiwan exchangerates,andtouristarrivalsfromtheworld,USAandJapantoTaiwan,aswellastheirassociatedvolatility.ThesampleperiodincludestheAsianeconomicandfinancialcrisesin1997,andpartoftheglobalfinancialcrisisof200809.Inclusionoftheexchangerateallowsapproximatedailypriceeffectsonworld,USandJapanesetouristarrivalstoTaiwantobecaptured.TheHeterogeneousAutoregressive(HAR)modeldoesnotreproducethetheoreticalhyperbolicdecayratesassociatedwithfractionallyintegrated(orlongmemory)timeseriesmodels,butitcanneverthelessapproximatequiteaccuratelyandparsimoniouslytheslowlydecayingcorrelationsassociatedwithsuchmodels.TheHARmodelisusedtoapproximatelongmemorypropertiesindailyexchangeratesandinternationaltouristarrivals,totestwhetheralternativeshortandlongrunestimatesofconditionalvolatilityaresensitivetotheapproximatelongmemoryintheconditionalmean,toexamineasymmetryandleverageinvolatility,andtoexaminetheeffectsoftemporalandspatialaggregation.Theempiricalresultsshowthattheconditionalvolatilityestimatesarenotsensitivetotheapproximatelongmemorynatureoftheconditionalmeanspecifications.TheQMLEfortheGARCH(1,1),GJR(1,1)andEGARCH(1,1)modelsforworld,USandJapanesetouristarrivalstoTaiwan,andtheworldpriceandUS 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 andYen/NewTaiwan 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.

    Knowledge sourcing and firm performance in an industrializing economy: the case of Taiwan in the 1990s.

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    This paper examines the impact of R&D and technology imports on firm performance in Taiwan’s manufacturing industry. Using a panel of 27,754 firms observed from 1992 to 1995, we estimate Translog production functions in twenty 2-digit industries. We implement four estimations procedures: fixed-effect regression, random-effect GLS, Hausman-Taylor estimator, and Stochastic Frontier Estimation. Our most reliable estimates, obtained with fixed effect and Hausman-Taylor models, show that knowledge inputs have a significant impact on firm sales in a small number of industries, and suggest that R&D and technology imports are more likely to be complements rather than substitutes.Manufacturing Industries; Newly Industrialized Countries; Technology Imports.

    Innovation Strategy and Total Factor Productivity Growth : Micro Evidence from Taiwanese Manufacturing Firms

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    This paper investigates the relationship between firms’ innovation practices and performance in Taiwan. Using a panel of 4000 firms, we examine the effects of importing technology (versus doing R&D) on Total Factor Porductivity (TFP) growth. The relationship between these two innovation strategies is also explored. We find that R&D strongly contributes to the growth of TFP, whereas the importation of technology is only weakly significant, which makes it difficult to qualify the type of relationship (complementarity or substitutability) that exists between the two innovation strategies.Importation of technology;Newly industrializzed countries;Productivity growth;Firm-level panel data; Manufacturing industries
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