Un análisis del comportamiento de la demanda turística en España: aplicación con técnicas de cointegración

En este trabajo se analiza la relación entre la evolución de la demanda del conjunto de la economía española frente a la de los principales componentes de gasto turístico, así como el grado de dependencia respecto al comportamiento económico de los principales países emisores de turistas hacia España. Para investigar la existencia de una relación entre estas variables se explican las principales técnicas de cointegración, que en caso de detectar dicha vinculación permiten estimar modelos de corrección del error. En concreto, en el trabajo se evalúa el comportamiento de estas variables a través de test de raíces unitarias para poder desarrollar modelos que permitan detectar con mayor precisión estas relaciones.

Growth, convergence and trade: The services sector in India’s states

India’s success story in services is well documented at the national level, but similar literature does not exist for India’s states. In this paper, we bridge this gap in research by looking at India’s services growth at the sub-national level and in doing so, also challenge existing literature by arguing that this growth has positive implications for income distribution. We find that even as per capita income is not converging across India’s states, per capita services are; evidence is provided both in terms of traditional measures of sigma- and beta-convergence and more recent panel unit root tests. A more disaggregated analysis of services sectors reveals convergence in railways, public administration and financial services. Finally, a Jensen & Kletzer (2005) approach to determining tradability provides evidence of most services being “traded” across India’s states, suggesting the role of such trade in the services growth and convergence story.

Energy consumption, economic growth and prices: A reassessment using panel VECM for developed and developing countries

This paper reinvestigates the energy consumption-GDP growth nexus in a panel error correction model using data on 20 net energy importers and exporters from 1971 to 2002. Among the energy exporters, there was bidirectional causality between economic growth and energy consumption in the developed countries in both the short and long run, while in the developing countries energy consumption stimulates growth only in the short run. The former result is also found for energy importers and the latter result exists only for the developed countries within this category. In addition, compared to the developing countries, the developed countries' elasticity response in terms of economic growth from an increase in energy consumption is larger although its income elasticity is lower and less than unitary. Lastly. the implications for energy policy calling for a more holistic approach are discussed. (c) 2006 Elsevier Ltd. All rights reserved.

Post-Bretton Woods evidence on PPP under different exchange rate regimes

This article investigates the behaviour of exchange rates across different regimes for a post-Bretton Woods period. The exchange rate regime classification is based on the classification of Frankel et al. (2004) who condensed the 10 categories of exchange rate regimes reported by the International Monetary Fund (IMF) into three categories. Panel unitroot tests and panel cointegration are used to examine the Purchasing Power Parity (PPP) hypothesis. The latter test is used to check for both the weak and strong forms of PPP. The panel unit-root tests show no evidence of PPP and suggest there is no difference in the behaviour of exchange rates across different regimes. However, failure to detect PPP across any of the regimes could be due to structural breaks. This assumption is reinforced by the results of cointegration tests, which suggest that there exists at least a weak form of PPP for the different regimes. The evidence for strong PPP decreases as the exchange rate regime moves away from a flexible exchange rate regime.

Early marketing matters:a time-varying parameter approach to persistence modeling

Are persistent marketing effects most likely to appear right after the introduction of a product? The authors give an affirmative answer to this question by developing a model that explicitly reports how persistent and transient marketing effects evolve over time. The proposed model provides managers with a valuable tool to evaluate their allocation of marketing expenditures over time. An application of the model to many pharmaceutical products, estimated through (exact initial) Kalman filtering, indicates that both persistent and transient effects occur predominantly immediately after a brand's introduction. Subsequently, the size of the effects declines. The authors theoretically and empirically compare their methodology with methodology based on unit root testing and demonstrate that the need for unit root tests creates difficulties in applying conventional persistence modeling. The authors recommend that marketing models should either accommodate persistent effects that change over time or be applied to mature brands or limited time windows only.

Long-term relationship between energy consumption and GDP in Latin America: an empirical assessment using panel data

The main objetive of this research is to evaluate the long term relationship between energy consumption and GDP for some Latin American countries in the period 1980-2009 -- The estimation has been done through the non-stationary panel approach, using the production function in order to control other sources of GDP variation, such as capital and labor -- In addition to this, a panel unit root tests are used in order to identify the non-stationarity of these variables, followed by the application of panel cointegration test proposed by Pedroni (2004) to avoid a spurious regression (Entorf, 1997; Kao, 1999)

Identifying stationary series in panels: A Monte Carlo evaluation of sequential panel selection methods

Sequential panel selection methods (spsms — procedures that sequentially use conventional panel unit root tests to identify I(0)I(0) time series in panels) are increasingly used in the empirical literature. We check the reliability of spsms by using Monte Carlo simulations based on generating directly the individual asymptotic pp values to be combined into the panel unit root tests, in this way isolating the classification abilities of the procedures from the small sample properties of the underlying univariate unit root tests. The simulations consider both independent and cross-dependent individual test statistics. Results suggest that spsms may offer advantages over time series tests only under special conditions.

Services growth and convergence: Getting India’s states together

India’s success story in services is well documented at the national level, but similar literature does not exist for India’s states. In this paper, we bridge this gap in research by looking at India’s services growth at the sub-national level and in doing so, also challenge existing literature by arguing that this growth has positive implications for income distribution. The first interesting finding is that even as per capita income is not converging across India’s states, per capita services are and we provide evidence for this both in terms of traditional measures of sigma- and beta-convergence and more recent panel unit root tests. Secondly, not only is external demand an important determinant of services value added at the state level, but this demand also emanates from all over the country rather than being concentrated in the neighbouring or richer states. This suggests that the benefits from services growth are being distributed more widely than may be perceived.

Logique et tests d'hypotheses: reflexions sur les problemes mal poses en econometrie

Dans ce texte, nous analysons les développements récents de l’économétrie à la lumière de la théorie des tests statistiques. Nous revoyons d’abord quelques principes fondamentaux de philosophie des sciences et de théorie statistique, en mettant l’accent sur la parcimonie et la falsifiabilité comme critères d’évaluation des modèles, sur le rôle de la théorie des tests comme formalisation du principe de falsification de modèles probabilistes, ainsi que sur la justification logique des notions de base de la théorie des tests (tel le niveau d’un test). Nous montrons ensuite que certaines des méthodes statistiques et économétriques les plus utilisées sont fondamentalement inappropriées pour les problèmes et modèles considérés, tandis que de nombreuses hypothèses, pour lesquelles des procédures de test sont communément proposées, ne sont en fait pas du tout testables. De telles situations conduisent à des problèmes statistiques mal posés. Nous analysons quelques cas particuliers de tels problèmes : (1) la construction d’intervalles de confiance dans le cadre de modèles structurels qui posent des problèmes d’identification; (2) la construction de tests pour des hypothèses non paramétriques, incluant la construction de procédures robustes à l’hétéroscédasticité, à la non-normalité ou à la spécification dynamique. Nous indiquons que ces difficultés proviennent souvent de l’ambition d’affaiblir les conditions de régularité nécessaires à toute analyse statistique ainsi que d’une utilisation inappropriée de résultats de théorie distributionnelle asymptotique. Enfin, nous soulignons l’importance de formuler des hypothèses et modèles testables, et de proposer des techniques économétriques dont les propriétés sont démontrables dans les échantillons finis.

Monte Carlo Tests with Nuisance Parameters: A General Approach to Finite-Sample Inference and Nonstandard Asymptotics

The technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] provides an attractive method of building exact tests from statistics whose finite sample distribution is intractable but can be simulated (provided it does not involve nuisance parameters). We extend this method in two ways: first, by allowing for MC tests based on exchangeable possibly discrete test statistics; second, by generalizing the method to statistics whose null distributions involve nuisance parameters (maximized MC tests, MMC). Simplified asymptotically justified versions of the MMC method are also proposed and it is shown that they provide a simple way of improving standard asymptotics and dealing with nonstandard asymptotics (e.g., unit root asymptotics). Parametric bootstrap tests may be interpreted as a simplified version of the MMC method (without the general validity properties of the latter).

An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationarity Tests.

Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. in this paper, we first show that this least squares bias induces a significant increase in the bias and mean-squared error of kernel-based estimators.

Reviewing the sustainability/stationarity of current account imbalances with tests for bounded integration

We investigate for 26 OECD economies whether their current account imbalances to GDP are driven by stochastic trends. Regarding bounded stationarity as the more natural counterpart of sustainability, results from Phillips–Perron tests for unit root and bounded unit root processes are contrasted. While the former hint at stationarity of current account imbalances for 12 economies, the latter indicate bounded stationarity for only six economies. Through panel-based test statistics, current account imbalances are diagnosed as bounded non-stationary. Thus, (spurious) rejections of the unit root hypothesis might be due to the existence of bounds reflecting hidden policy controls or financial crises.

Exploring the nexus between tourism and output in Cook Islands: An ARDL bounds approach

Tourism plays an important role in the development of Cook Islands. In this paper we examine the nexus between tourism and growth using quarterly data over the period 2009Q1–2014Q2 using the recently upgraded ARDL bounds test to cointegration tool, Microfit 5.01, which provides sample adjusted bounds and hence is more reliable for small sample size studies. We perform the cointegration using the ARDL bounds test and examine the direction of causality. Using visitor arrival and output in per capita terms as respective proxy for tourism development and growth, we examine the long-run association and report the elasticity coefficient of tourism and causality nexus, accordingly. Using unit root break tests, we note that 2011Q1 and 2011Q2 are two structural break periods in the output series. However, we note that this period is not statistically significant in the ARDL model and hence excluded from the estimation. Subsequently, the regression results show the two series are cointegrated. The long-run elasticity coefficient of tourism is estimated to be 0.83 and the short-run is 0.73. A bidirectional causality between tourism and income is noted for Cook Islands which indicates that tourism development and income mutually reinforce each other. In light of this, socio-economic policies need to focus on broad-based, inclusive and income-generating tourism development projects which are expected to have feedback effect.

What causes economic growth in Portugal: exports or inward FDI?

The purpose of this paper is to analyse possible casual relationships between exports, inward foreign investment and economic growth in Portugal and identify their direction. The paper uses the three stage procedure based on unit root, cointegration and causalty tests applied to annual data from 1977 to 2004.

Identification, Weak Instruments and Statistical Inference in Econometrics

We discuss statistical inference problems associated with identification and testability in econometrics, and we emphasize the common nature of the two issues. After reviewing the relevant statistical notions, we consider in turn inference in nonparametric models and recent developments on weakly identified models (or weak instruments). We point out that many hypotheses, for which test procedures are commonly proposed, are not testable at all, while some frequently used econometric methods are fundamentally inappropriate for the models considered. Such situations lead to ill-defined statistical problems and are often associated with a misguided use of asymptotic distributional results. Concerning nonparametric hypotheses, we discuss three basic problems for which such difficulties occur: (1) testing a mean (or a moment) under (too) weak distributional assumptions; (2) inference under heteroskedasticity of unknown form; (3) inference in dynamic models with an unlimited number of parameters. Concerning weakly identified models, we stress that valid inference should be based on proper pivotal functions —a condition not satisfied by standard Wald-type methods based on standard errors — and we discuss recent developments in this field, mainly from the viewpoint of building valid tests and confidence sets. The techniques discussed include alternative proposed statistics, bounds, projection, split-sampling, conditioning, Monte Carlo tests. The possibility of deriving a finite-sample distributional theory, robustness to the presence of weak instruments, and robustness to the specification of a model for endogenous explanatory variables are stressed as important criteria assessing alternative procedures.