Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations

This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

Stock market integration between new EU member states and the Euro-zone

This paper measures the degree in stock market integration between five Eastern European countries and the Euro-zone. A potentially gradual transition in correlations is accommodated by smooth transition conditional correlation models. We find that the correlation between stock markets has increased from 2001 to 2007. In particular, the Czech and Polish markets show a higher correlation to the Euro-zone. However, this is not a broad-based phenomenon across Eastern Europe. We also find that the increase in correlations is not a reflection of a world-wide phenomenon of financial integration but appears to be specific to the European market. JEL classifications: C32; C51; F36; G15 Keywords: Multivariate GARCH; Smooth Transition Conditional Correlation; Stock Return Comovement; New EU Members.

Progress Towards to Equity Market Integration in Eastern Europe

The advent of the European Union has decreased the diversification benefits available from country based equity market indices in the region. This paper measures the increase in stock integration between the three largest new EU members (Hungary, the Czech Republic and Poland who joined in May 2004) and the Euro-zone. A potentially gradual transition in correlations is accommodated in a single VAR model by embedding smooth transition conditional correlation models with fat tails, spillovers, volatility clustering, and asymmetric volatility effects. At the country market index level all three Eastern European markets show a considerable increase in correlations in 2006. At the industry level the dates and transition periods for the correlations differ, and the correlations are lower although also increasing. The results show that sectoral indices in Eastern European markets may provide larger diversification opportunities than the aggregate market. JEL classifications: C32; C51; F36; G15 Keywords: Multivariate GARCH; Smooth Transition Conditional Correlation; Stock Return Comovement; Sectoral correlations; New EU Members

A fractionally integrated approach to monetary policy and inflation dynamics

This paper relaxes the standard I(0) and I(1) assumptions typically stated in the monetary VAR literature by considering a richer framework that encompasses the previous two processes as well as other fractionally integrated possibilities. First, a timevarying multivariate spectrum is estimated for post WWII US data. Then, a structural fractionally integrated VAR (VARFIMA) is fitted to each of the resulting time dependent spectra. In this way, both the coefficients of the VAR and the innovation variances are allowed to evolve freely. The model is employed to analyze inflation persistence and to evaluate the stance of US monetary policy. Our findings indicate a strong decline in the innovation variances during the great disinflation, consistent with the view that the good performance of the economy during the 80’s and 90’s is in part a tale of good luck. However, we also find evidence of a decline in inflation persistence together with a stronger monetary response to inflation during the same period. This last result suggests that the Fed may still play a role in accounting for the observed differences in the US inflation history. Finally, we conclude that previous evidence against drifting coefficients could be an artifact of parameter restriction towards the stationary region. Keywords: monetary policy, inflation persistence, fractional integration, timevarying coefficients, VARFIMA. JEL Classification: E52, C32

Hours worked - Productivity puzzle: identification in fractional integration settings

A recent finding of the structural VAR literature is that the response of hours worked to a technology shock depends on the assumption on the order of integration of the hours. In this work we relax this assumption, allowing for fractional integration and long memory in the process for hours and productivity. We find that the sign and magnitude of the estimated impulse responses of hours to a positive technology shock depend crucially on the assumptions applied to identify them. Responses estimated with short-run identification are positive and statistically significant in all datasets analyzed. Long-run identification results in negative often not statistically significant responses. We check validity of these assumptions with the Sims (1989) procedure, concluding that both types of assumptions are appropriate to recover the impulse responses of hours in a fractionally integrated VAR. However, the application of longrun identification results in a substantial increase of the sampling uncertainty. JEL Classification numbers: C22, E32. Keywords: technology shock, fractional integration, hours worked, structural VAR, identification

Breaking the panels: an application to the GDP per capita

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different speci¿cations are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is ¿exible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have an exact limit distribution with a good ¿nite sample performance. Its application to a typical panel data set of real per capita GDP gives support to the trend stationarity of these series

Breaking the panels: an application to the GDP per capita

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different speci¿cations are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is ¿exible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have an exact limit distribution with a good ¿nite sample performance. Its application to a typical panel data set of real per capita GDP gives support to the trend stationarity of these series

Continuous-time random-walk model for financial distributions

We apply the formalism of the continuous-time random walk to the study of financial data. The entire distribution of prices can be obtained once two auxiliary densities are known. These are the probability densities for the pausing time between successive jumps and the corresponding probability density for the magnitude of a jump. We have applied the formalism to data on the U.S. dollardeutsche mark future exchange, finding good agreement between theory and the observed data.

The Determinants of Exit in Argentina: Core and Peripheral Regions

This paper analyses the regional determinants of exit in Argentina. We find evidence of a dynamic revolving door by which past entrants increase current exits, particularly in the peripheral regions. In the central regions, current and past incumbents cause an analogous displacement effect. Also, exit shows a U-shaped relationship with respect to the informal economy, although the positive effect is weaker in the central regions. These findings point to the existence of a core-periphery structure in the spatial distribution of exits. Key words: firm exit, count data models, Argentina JEL: R12; R30; C33

Forecasting tourism demand using consumer expectations

Abstract Purpose- There is a lack of studies on tourism demand forecasting that use non-linear models. The aim of this paper is to introduce consumer expectations in time-series models in order to analyse their usefulness to forecast tourism demand. Design/methodology/approach- The paper focuses on forecasting tourism demand in Catalonia for the four main visitor markets (France, the UK, Germany and Italy) combining qualitative information with quantitative models: autoregressive (AR), autoregressive integrated moving average (ARIMA), self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. The forecasting performance of the different models is evaluated for different time horizons (one, two, three, six and 12 months). Findings- Although some differences are found between the results obtained for the different countries, when comparing the forecasting accuracy of the different techniques, ARIMA and Markov switching regime models outperform the rest of the models. In all cases, forecasts of arrivals show lower root mean square errors (RMSE) than forecasts of overnight stays. It is found that models with consumer expectations do not outperform benchmark models. These results are extensive to all time horizons analysed. Research limitations/implications- This study encourages the use of qualitative information and more advanced econometric techniques in order to improve tourism demand forecasting. Originality/value- This is the first study on tourism demand focusing specifically on Catalonia. To date, there have been no studies on tourism demand forecasting that use non-linear models such as self-exciting threshold autoregressions (SETAR) and Markov switching regime (MKTAR) models. This paper fills this gap and analyses forecasting performance at a regional level. Keywords Tourism, Forecasting, Consumers, Spain, Demand management Paper type Research paper

Another Look at the Null of Stationary Real Exchange Rates: Panel Data with Structural Breaks and Cross-section Dependence

This paper re-examines the null of stationary of real exchange rate for a panel of seventeen OECD developed countries during the post-Bretton Woods era. Our analysis simultaneously considers both the presence of cross-section dependence and multiple structural breaks that have not received much attention in previous panel methods of long-run PPP. Empirical results indicate that there is little evidence in favor of PPP hypothesis when the analysis does not account for structural breaks. This conclusion is reversed when structural breaks are considered in computation of the panel statistics. We also compute point estimates of half-life separately for idiosyncratic and common factor components and find that it is always below one year.

El Creuament d'indicadors de fonts diferenciades : instrument de millora en l'anàlisi i la planificació de les polítiques públiques de seguretat

El Projecte que aquí es presenta, té la voluntat d’aprofundir en una nova metodologia -emprada en altres països del nostre entorn europeu-, consistent en l’encreuament de varies fonts d’informació. En aquest cas, les dues principals i, fins els moment, utilitzades en les anàlisis de l’estat de la seguretat a Catalunya; la pròpiament estreta del registre policial i la de la victimització i la percepció ciutadana. Aquest anàlisi se centra en l’àmbit territorial de la ciutat de Barcelona i en els seus 10 districtes. De manera més específica, l’anàlisi pretén mostrar la correlació entre ambdós resultats i la consistència dels diferents indicadors triats, tant respecte el nivell de victimització com respecte la percepció de seguretat i la valoració de la policia. Aquest estudi, doncs, pretén esdevenir una eina útil per a la diagnosi, ja sigui respecte un determinat àmbit territorial o tipologia delinqüencial, mitjançant la definició de determinats blocs d’indicadors prou fiables i, que alhora, puguin ajudar a la presa de decisions dels òrgans directius de l’Ajuntament de Barcelona i del Departament d’Interior, Relacions Institucionals i Participació. Així com senyalar, en quins àmbits concrets és aconsellable l’estudi, la planificació i el desenvolupament de polítiques públiques de seguretat. Alhora que, amb l’establiment d’aquest estudi de manera periòdica, es podrà disposar d’unes sèries temporals suficientment estables, així com facilitar el seguiment, l’evolució i avaluació de l’àmbit concret analitzat.

Leading indicator properties of US high-yield credit spreads

In this paper we examine the out-of-sample forecast performance of high-yield credit spreads regarding real-time and revised data on employment and industrial production in the US. We evaluate models using both a point forecast and a probability forecast exercise. Our main findings suggest the use of few factors obtained by pooling information from a number of sector-specific high-yield credit spreads. This can be justified by observing that, especially for employment, there is a gain from using a principal components model fitted to high-yield credit spreads compared to the prediction produced by benchmarks, such as an AR, and ARDL models that use either the term spread or the aggregate high-yield spread as exogenous regressor. Moreover, forecasts based on real-time data are generally comparable to forecasts based on revised data. JEL Classification: C22; C53; E32 Keywords: Credit spreads; Principal components; Forecasting; Real-time data.

State-dependent threshold STAR models

In this paper we consider extensions of smooth transition autoregressive (STAR) models to situations where the threshold is a time-varying function of variables that affect the separation of regimes of the time series under consideration. Our specification is motivated by the observation that unusually high/low values for an economic variable may sometimes be best thought of in relative terms. State-dependent logistic STAR and contemporaneous-threshold STAR models are introduced and discussed. These models are also used to investigate the dynamics of U.S. short-term interest rates, where the threshold is allowed to be a function of past output growth and inflation.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants