inequality and polarisation in health systems responsiveness a cross country analysis the world health report 2000 proposed three fundamental goals for health systems encompassing population health health care finance and health systems responsiveness the goals incorporate both an efficiency and equity dimension while inequalities in population health and health care finance have motivated two important strands of research inequalities in responsiveness have received less attention in health economics this paper examines inequality and polarisation in responsiveness bridging this gap in the literature and contributing towards an integrated analysis of health systems performance it uses data from the world health survey to measure and compare inequalities in responsiveness across 25 european countries in order to respect the inherently ordinal nature of the responsiveness data median based measures of inequality and polarisation are employed the results suggest that in the face of wide differences in the health systems analysed there exists large variability in inequality in responsiveness across countries

cointegration analysis of german and british tourism demand for greece abstract germany and great britain are traditionally two of the most important sources of tourism for greece the purpose of this paper is to investigate changes in the long run demand for tourism to greece by these two countries in order to explain the demand for tourism we are using a number of leading macroeconomic variables including income in origin countries germany and great britain tourism prices in greece and transportation cost and exchanges rates between the three countries annual data from the three countries covering the period from 1960 to 2000 are employed augmented dickey fuller test for unit root is examined in the univariate framework and johansen s maximum likelihood procedure is used to test the cointegration method and to estimate the number of cointegrating vectors of var model error correction models are estimated to explain german and british demand for tourism to greece

forecasting international tourist flows to australia a comparison between the direct and indirect methods this paper compares between the use of direct and indirect forecasting of international tourist flows to australia the indirect method is applicable when time series is a contemporaneous aggregate of others which is often the case for tourist flows time series in this case forecasts are generated by aggregating those of the component variables of aggregation an alternative is the direct method whereby forecasts are generated directly from the aggregated variable this paper uses seasonal arima models regression based models and harvey s structural time series models to compare the accuracy of the two forecasting methods we find evidence strongly in favour of the indirect method using monthly time series for international tourist arrivals to australia

measurement of horizontal inequity in health care utilisation using european panel data measurement of inequity in health care delivery has focused on the extent to which health care utilisation is or is not distributed according to need irrespective of income studies using cross sectional data have proposed various ways of measuring and standardizing for need but inevitably much of the inter individual variation in needs remains unobserved in cross sections this paper exploits panel data methods to improve the measurement by including the time invariant part of unobserved heterogeneity into the need standardization procedure using latent class hurdle models for gp and specialist visits estimated on 8 annual waves of the european community household panel we compute indices of horizontal equity that partition total income related variation in use into a need and a non need related part not only for the observed but also for the unobserved but time invariant component we also propose and compare a more conservative index of horizontal inequity to the conventional statistic we find that many of the cross country comparative results appear fairly robust to the panel data test although the panel based methods lead to significantly higher estimates of horizontal inequity for most countries this confirms that better estimation and control for need often reveals more pro rich distributions of doctor utilisation

measuring socioeconomic inequality in health health care and health financing by means of rank dependent indices a recipe for good practice the tools to be used and other choices to be made when measuring socioeconomic inequalities with rank dependent inequality indices have recently been debated in this journal this paper adds to this debate by stressing the importance of the measurement scale by providing formal proofs of several issues in the debate and by lifting the curtain on the confusing debate between adherents of absolute versus relative health differences we end this paper with a matrix that provides guidelines on the usefulness of several rank dependent inequality indices under varying circumstances

forecasting u s tourist arrivals using optimal singular spectrum analysis this study examines the potential advantages of using singular spectrum analysis ssa for forecasting tourism demand to do this it examines the performance of ssa forecasts using monthly data for tourist arrivals into the unites states over the period 1996 to 2012 the ssa forecasts are compared to those from a range of other forecasting approaches previously used to forecast tourism demand these include arima exponential smoothing and neural networks the results presented show that the ssa approach produces forecasts which perform statistically significantly better than the alternative methods in forecasting total tourist arrivals into the u s forecasts using the ssa approach are also shown to offer a significantly better forecasting performance for arrivals into the u s from individual source countries of the alternative forecasting approaches exponential smoothing and feed forward neural networks in particular were found to perform poorly the key conclusion is that singular spectrum analysis ssa offers significant advantages in forecasting tourist arrivals into the us and is worthy of consideration for other forecasting studies of tourism demand

measurement of inequity in health care with heterogeneous response of use to need we propose a method of measuring and decomposing inequity in health care utilisation that allows for heterogeneity in the use need relationship this makes explicit inequity that derives from unequal treatment response to variation in need as well as that due to differential effects of non need determinants under plausible conditions concerning heterogeneity in the use need relationship and the distribution of need existing methods that impose homogeneity will underestimate pro rich inequity this prediction is confirmed for four middle income asian countries in those countries around one half of the observed socioeconomic inequality is due to utilisation being more responsive to need among the higher wealth and urban dwelling individuals

tourism demand modelling and forecasting a review of recent research abstract this paper reviews the published studies on tourism demand modelling and forecasting since 2000 one of the key findings of this review is that the methods used in analysing and forecasting the demand for tourism have been more diverse than those identified by other review articles in addition to the most popular time series and econometric models a number of new techniques have emerged in the literature however as far as the forecasting accuracy is concerned the study shows that there is no single model that consistently outperforms other models in all situations furthermore this study identifies some new research directions which include improving the forecasting accuracy through forecast combination integrating both qualitative and quantitative forecasting approaches tourism cycles and seasonality analysis events impact assessment and risk forecasting

unfair inequalities in health and health care inequalities in health and health care are caused by different factors measuring unfair inequalities implies that a distinction is introduced between causal variables leading to ethically legitimate inequalities and causal variables leading to ethically illegitimate inequalities an example of the former could be life style choices an example of the latter is social background we show how to derive measures of unfair inequalities in health and in health care delivery from a structural model of health care and health production direct unfairness linked to the variations in medical expenditures and health in the hypothetical distribution in which all legitimate sources of variation are kept constant fairness gap linked to the differences between the actual distribution and the hypothetical distribution in which all illegitimate sources of variation have been removed these two approaches are related to the theory of fair allocation in general they lead to different results we propose to analyse the resulting distributions with the traditional apparatus of lorenz curves and inequality measures we compare our proposal to the more common approach using concentration curves and analyse the relationship with the methods of direct and indirect standardization we discuss how inequalities in health care can be integrated in an overall evaluation of social inequality

a management orientated approach to combination forecasting of tourism demand abstract volatility exponential smoothing regression and naive 2 models are considered singly and in combination in terms of forecasting demand for international tourism these models generate accurate predictions of tourism flows but their prime utility is when combined with other models usually models are combined by means of purely statistical criteria we show that goal programming gp offers an alternative flexible approach to model combination gp offers planners a practical solution to tourism forecasting problems since the method is more adaptable than conventional minimisation of prediction error by permitting practitioners to prioritise a series of management related goals forecasters can focus on longer and short term goals minimising forecast under and over estimation and or concentrate on prediction errors in tourism flows at various times of the year

employers discriminatory behavior and the estimation of wage discrimination this paper considers the linkage of empirical estimates of wage discrimination between two groups introduced by oaxaca 1973 to a theoretical model of employers discriminatory behavior it is shown that conditional on different assumptions about employers discriminatory tastes oaxaca s estimators of wage discrimination can be derived that the approach is more generally useful is demonstrated by deriving an alternative estimator of wage discrimination based on the assumption that within each type of labor e g unskilled skilled the utility function capturing employers discriminatory tastes is homogeneous of degree zero with respect to labor inputs from each of the two groups the estimators are compared empirically in an application to male female wage differentials

the poverty trap the dual externality model and its policy implications abstract this paper analyzes poverty traps in a monopolistic competition general equilibrium model with aggregate demand externality in our model the central hypothesis is represented by the introduction of externalities in fixed costs that firms have to incur in order to industrialize as a spillover across sectors by this we mean that the fixed cost incurred by a firm in order to start production can reduce the fixed cost that firms in other sectors of the economy must incur with such an assumption we can show the possibility for an economy to be locked in at different stages of development we then proceed to discuss the policy implications and the possible role for government intervention to this end we provide a potential framework of reference that if properly developed may be useful in policy design

back propagation learning in improving the accuracy of neural network based tourism demand forecasting abstract traditional tourism demand forecasting techniques concentrate predominantly on multivariate regression models and univariate time series models these single mathematical function based forecasting techniques although they have achieved a certain degree of success in tourism forecasting are unable to represent the relationship of demand for tourism as accurate as a multiprocessing node based feed forward neural network previous research has demonstrated that using a feed forward neural network can accomplish a higher forecasting accuracy than the regression and time series techniques for a set of linearly separable tourism demand data this research extends the applicability of neural networks in tourism demand forecasting by incorporating the back propagation learning process into a non linearly separable tourism demand data empirical results indicate that utilizing a back propagation neural network outperforms regression models time series models and feed forward neural networks in terms of forecasting accuracy

international tourism and export instability export diversification has been suggested as a strategy for decreasing the level of export earnings instability which is experienced by many developing countries in recent years the international tourism sector has made an increasingly important contribution to the economies of many low income countries this article examines whether diversification into the non traditional tourism sector has succeeded in decreasing the instability of export earnings it was found that although tourism has the advantage of high growth rates and is a major source of foreign currency receipts earnings from international tourism did not bring about a significant decrease in the instability of export earnings of most of the developing and industrialised countries considered furthermore a net increase in the instability of earnings from tourism and merchandise exports occurred in a number of countries and may be a particular problem in small open developing economies

predicting tourism demand using fuzzy time series and hybrid grey theory abstract forecasting tourism demand in a capacity constrained service industry has been a major theme in this field this study presents two models that can be used to predict tourism demand both two models are based on artificial intelligent ai neural network theory was first applied to tourism demand forecasting in 2000 and empirically tested using the raw data from hong kong this work provides empirical evidence using grey theory and fuzzy time series which do not need large sample and long past time series these ai models are estimated for tourist arrivals to taiwan from hong kong united states and germany during the period of 1989 2000 gm 1 1 model achieves an accurate forecast when the sample data show a stable increase trend nevertheless the markov modification model can efficiently improved the gm 1 1 model when the sample data show significant fluctuations

the forecasting of international expo tourism using quantitative and qualitative techniques this study predicts the number of visitors to an international tourism expo to be held in korea in 2012 an unprecedented event for the host city forecasting demand for such a mega event has received only limited attention in the literature unlike most studies forecasting international tourism demand forecasting expo demand involves using both quantitative forecasting models and qualitative technique because of data limitations combining quantitative techniques with willingness to visit wtv surveys predicts the expo demand at 8 9 million visitors in comparison using the delphi method experts predict expo demand at 6 8 million visitors for this study the delphi method provides more conservative estimates than estimates from combining quantitative techniques with wtv policy implications presented are directed toward expo planners and practitioners in terms of demand and supply side application of these results in the decision making process and future challenges surrounding demand forecasting

a comparison of three different approaches to tourist arrival forecasting abstract forecasting plays a major role in tourism planning the promotion of tourism projects involving substantial sums of money requires an estimate of future demand and market penetration the commitment to developing tourism would be much easier if it were possible to analyse current and past tourist traffic and predict the nature of changes in tourism demand these extrapolative approaches to forecasting require historical data this paper investigates the application of three time series forecasting techniques namely exponential smoothing univariate arima and elman s model of artificial neural networks ann to predict travel demand i e the number of arrivals from different countries to hong kong exponential smoothing and arima are two commonly used statistical time series forecasting techniques the third approach neural networks is an artificial intelligence technique derived from computer science according to the analysis presented in this paper neural networks seems to be the best method for forecasting visitor arrivals especially those series without obvious pattern

modelling us tourism demand for european destinations abstract an almost ideal demand system model is used to examine us demand for tourism in european destinations the model provides policy makers with useful information concerning the sensitivity of tourism demand to changes in relative prices exchange rates and expenditure the results show that price competitiveness is important for us demand for france italy and spain but is relatively unimportant for the uk france and italy are regarded as substitutes by us tourists as are spain and italy as us expenditure rises the market shares of spain and the uk decline while france and italy benefit the demand modelling and forecasting indicate that in the absence of a tourism price index the choice between alternative price indices does not have a significant effect on the results

correcting the concentration index a comment abstract in a recent article in this journal erreygers erreygers g 2008 correcting the concentration index journal of health economics has proposed a new measure of income related health inequality to overcome three shortcomings of the concentration index ci i think erreygers is absolutely right to probe on these issues and i welcome his generalization of my normalization which was specific to the case of a binary health indicator however i have misgivings about his paper his goal of correcting the ci so as to make it usable with interval scale variables seems misguided the ci reflects a commitment on the part of the analyst to measuring relative inequality armed only with an interval scale variable one simply has to accept that one can meaningfully measure only differences and therefore settle for measuring absolute inequality erreygers index inevitably ends up as a measure of absolute inequality his objection to my approach to getting round the bounds problem is that my normalization of the ci does not produce a measure of absolute inequality but that was never my intention in this comment i also show that somewhat paradoxically at first glance my index is also not a pure index of relative inequality this seems to be an inevitable consequence of tackling the bounds issue

modelling the uncertainty in monthly international tourist arrivals to the maldives abstract the indian ocean tsunami of 26 december 2004 made clear the devastating short term impact in lost lives as well as the longer term impact in lost livelihoods and an uncertain future tourism was one of the more obvious non human casualties of this tragic natural phenomenon tourism is the principal industry in the maldives accounting for more than 30 of gdp and more than 60 of foreign exchange earnings as over 55 of government tax revenue arises from tourism related taxes and monthly government budget financing depends largely on international tourist arrivals the monitoring of daily weekly and monthly international tourist arrivals is essential for fiscal policy evaluation over 600 000 tourists visited the maldives in 2004 this paper examines the time series properties of monthly international tourist arrivals to the maldives from eight major tourist source countries namely italy germany uk japan france switzerland austria and the netherlands from 1 january 1994 to 31 december 2003 monthly international tourist arrivals and the associated uncertainty are estimated for the eight principal tourist source countries univariate and multivariate time series models of conditional volatility or uncertainty are estimated and tested the conditional correlations are estimated and examined to ascertain whether there is specialization diversification or segmentation in the international tourism demand shocks from the major tourism source countries to the maldives the estimated static conditional correlations for monthly international tourist arrivals as well as for the respective transformed series were found to be significantly different from zero but also relatively low this indicates that the government of the maldives and the major tour operators that organise tourist vacations have to emphasise their marketing efforts independently of each tourist source country

tourism forecasting to combine or not to combine abstract existing non tourism related literature shows that forecast combination can improve forecasting accuracy this study tests this proposition in the tourism context by examining the efficiency of combining forecasts based on three different combination methods the data used for this study relate to tourist arrivals in hong kong from the top ten tourism generating countries regions the forecasts are derived from four different forecasting models autoregressive integrated moving average arima model autoregressive distributed lag model adlm error correction model ecm and vector autoregressive var model all forecasts are ex post and the empirical results show that the relative performance of combination versus single model forecasts varies according to the origin destination tourist flow under consideration which parallels previous findings regarding the relative performance of individual forecasting methods the results also vary with the combination techniques used furthermore although the combined forecasts do not always outperform the best single model forecasts almost all the combined forecasts are not outperformed by the worst single model forecasts this suggests that forecast combination can considerably reduce the risk of forecasting failure this conclusion also implies that combined forecasts are likely to be preferred to single model forecasts in many practical situations

combining volatility and smoothing forecasts of uk demand for international tourism abstract univariate volatility models are applied to uk tourism demand to the country s most popular international destinations volatility is a concept borrowed from finance the fact that significant volatility models are found for ten of the twelve destinations examined shows that the volatility concept has relevance to tourism demand volatility models are able to quantify the impacts of positive and negative shocks on tourism demand the impacts of negative shocks vary in magnitude and duration according to the destination involved and the nature of the shock the forecasting capability of these models has never been assessed in the tourism field they are shown to generate highly accurate forecasts but become optimal when combined with forecasts obtained from exponential smoothing models two methods of combining individual forecasts are considered bias in individual volatility and smoothing models and in combinations of them is examined