86 research outputs found
Calendar Effects in Daily ATM Withdrawals
This paper analyses the calendar effects present in Automated Teller Machines (ATM) withdrawals of residents, using daily data for Portugal for the period from January 1st 2001 to December 31st 2008. The results presented may allow for a better understanding of consumer habits and for adjusting the original series for calendar effects. Considering the Quarterly National Accountsâ procedure of adjusting data for seasonality and working days effects, this correction is important to ensure the use of the ATM series as an instrument to nowcast private consumption.
The Effects of Additive Outliers and Measurement Errors when Testing for Structural Breaks in Variance
This paper discusses the asymptotic and finite-sample properties of CUSUM-based tests for detecting structural breaks in volatility in the presence of stochastic contamination, such as additive outliers or measurement errors. This analysis is particularly relevant for financial data, on which these tests are commonly used to detect variance breaks. In particular, we focus on the tests by InclĂĄn and Tiao [IT] (1994) and Kokoszka and Leipus [KL] (1998, 2000), which have been intensively used in the applied literature. Our results are extensible to related procedures. We show that the asymptotic distribution of the IT test can largely be affected by sample contamination, whereas the distribution of the KL test remains invariant. Furthermore, the break-point estimator of the KL test renders consistent estimates. In spite of the good large-sample properties of this test, large additive outliers tend to generate power distortions or wrong break-date estimates in small samples.
ON THE SMALL SAMPLE PROPERTIES OF DICKEY FULLER AND MAXIMUM LIKELIHOOD UNIT ROOT TESTS ON DISCRETE-SAMPLED SHORT-TERM INTEREST RATES
Testing for unit roots in short-term interest rates plays a key role in the empirical modelling of these series. It is widely assumed that the volatility of interest rates follows some time-varying function which is dependent of the level of the series. This may cause distortions in the performance of conventional tests for unit root nonstationarity since these are typically derived under the assumption of homoskedasticity. Given the relative unfamiliarity on the issue, we conducted an extensive Monte Carlo investigation in order to assess the performance of the DF unit root tests, and examined the effects on the limiting distributions of test procedures (t- and likelihood ratio tests) based on maximum likelihood estimation of models for short-term rates with a linear drift.Unit root, interest rates, CKLS model.
Efficient Tests of the Seasonal Unit Root Hypothesis*
In this paper we derive, under the assumption of Gaussian errors with known error covariance matrix, asymptotic local power bounds for seasonal unit root tests for both known and unknown deterministic scenarios and for an arbitrary seasonal aspect. We demonstrate that the optimal test of a unit root at a given spectral frequency behaves asymptotically independently of whether unit roots exist at other frequencies or not. We also develop modified versions of the optimal tests which attain the asymptotic Gaussian power bounds under much weaker conditions. We further propose near-efficient regression-based seasonal unit root tests using pseudo-GLS de-trending and show that these have limiting null distributions and asymptotic local power functions of a known form. Monte Carlo experiments indicate that the regression-based tests perform well in finite samples.Point optimal invariant (seasonal) unit root tests, asymptotic local power bounds, near seasonal integration
The behaviour of seasonal unit root tests under neglected local drifts
This paper analyses the limit distributions of the seasonal unit root test procedures proposed by Dickey, Hasza and Fuller (1984) and Hylleberg, Engle, Granger and Yoo (1990), when local trends at different frequencies are present in data generation processes, but ignored in the test regressions used. The findings presented explicitly show that neglected deterministic trends have negative effects on the distributions of the test statistics. Analytical observations and Monte Carlo simulations reveal that seasonal unit root test statistics become severely undersized as the values of standardized local trends increase. Hence, failure to consider local trends may often bear the undesirable effect of biasing decisions towards non-rejection of unit roots.info:eu-repo/semantics/publishedVersio
Finite Sample Performance of Frequency and Time Domain Tests for Seasonal Fractional Integration
Testing the order of integration of economic and financial time series has become a conventional procedure prior to any modelling exercise. In this paper, we investigate and compare the finite sample properties of the frequency domain tests proposed by Robinson (1994) and the time domain procedure proposed by Hassler, Rodrigues and Rubia (2008) when applied to seasonal data.
A Class of Robust Tests in Augmented Predictive Regressions
This paper focuses on the analytical discussion of a robust t-test for predictability and on the analysis of its finite-sample properties. Our analysis shows that the procedure proposed exhibits approximately correct size even in fairly small samples. Furthermore, the test is well-behaved under short-run dependence, and can exhibit improved power performance over
alternative procedures. These appealing properties, together with the fact that the test can be applied in a simple and direct way in the linear regression context, suggests that the modified t-statistic introduced in this paper is well suited for addressing predictability in empirical applications.
Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns
Over recent years several methods to deal with high-frequency data (economic, financial and other) have been proposed in the literature. An interesting example is for instance interval valued time series described by the temporal evolution of high and low prices of an asset. In this paper a new class of threshold models capable of capturing asymmetric e¤ects in interval-valued data is introduced as well as new forecast loss functions and descriptive statistics of the forecast quality proposed. Least squares estimates of the threshold parameter and the regression slopes are obtained; and forecasts based on the proposed threshold model computed. A new forecast procedure based on the combination of this model with the k nearest neighbors method is introduced. To illustrate this approach, we report an application to a weekly sample of S&P500 index returns. The results obtained are encouraging and compare very favorably to available procedures.
Determinants of the EONIA spread and the financial crisis
The financial markets turmoil of 2007-09 impacted on the overnight segment, which is the first step of monetary policy implementation. We model the volatility of the EONIA spread as an EGARCH. However, the nature of the EGARCH considered will be different in the period before the fixed rate full allotment policy of the ECB (2004 - 2008) where we follow the approach of Hamilton (1996) and in the period afterwards (2008 - 2009) where a conventional EGARCH seems sufficient to capture the behaviour of volatility. The results suggest a greater difficulty during the turmoil for the ECB to steer the level of the EONIA spread relative to the main reference rate. The liquidity effect has been reduced since 2007 and in particular since the full allotment policy at the refinancing operations. On the other hand, the liquidity policy and especially the provision of long-term liquidity followed was effective in reducing market volatility. Liquidity provision conditions were also found to have influenced the EONIA spread only since the financial market turmoil. Fine-tuning operations contributed to stabilize money market conditions, especially during the turmoil. The EGARCH parameter estimates also suggest a structural change in the behaviour of the EONIA spread in reaction to shocks.
From Motivations to Yield Paths of Tourism Development: The Case of the Algarve
This paper develops new measurements of tourist yield in the context of the Algarve, which is a sun and sand destination where tourism demand persistently grows, in spite of the signs of destination maturity. This growth contradicts the essence of maturity and drove this research, which attempts to identify the critical preferences which are able to improve destination positioning.
According to Pine and Gilmore (1999) in the emerging experience economy, consumers seek unique experiences. This new demand for unique and memorable experiences leads destinations to offer a distinct value-added provision for products and services when they have already achieved a consistent, high level of functional quality. New tourists are more concerned with sophistication, specialization and innovation of tourism products. Thus, because tourism products contain a large number and range of attributes, each tourist experience becomes distinct. Moreover, the overall attractiveness of a destination has long been regarded as a critical criterion in tourism consumer decision making and choice (Crouch, 2011).
Hence, the uniqueness of those experiences relies on the declared tourists preferences, which will be treated as motivations in this research (Decrop, 2000; Goodall, 1991; Hsu et al, 2009). However, another stream of research shows that motivations are of paramount importance for the positioning of destinations (Seddighi & Theocharous, 2002), and that these motivations are dynamic (Crompton & McKay, 1997).
Motivations and preferences are treated as indistinguishable constructs since we only focus on attributes of the destination and therefore, the tangibility of these motivations may be assumed as preferences. Despite the slight difference outlined by Decrop (2000), it seems widely accepted that motivations may be regarded as comprising two stages, the first one is the driving force that pushes tourists to travel and the other, related with the destination and type of holidays chosen,44
are the so called pull motivations that in essence reflect tourists preferences. Under this theoretical background, pull motivations may be assumed as a proxy for preferences.The contribution of this study lies in the scope of microeconomic theories, namely stated preference theory, which is a descriptive theory in the field of consumer choice as well as in a wide range of other applications within choice-theoretic economics (Hands, 2012). Thus, following this theoretical framework could help the understanding of the role of behavioural variables as proxies of tourist yield when managing and planning tourism destinations for higher competitiveness. On the other hand, this paper also has important managerial implications, in particular in new tourist yield measures for marketing/promotion of the destination.This research starts by exploring the way international tourists value a number of attributes comprised by the Algarve. After identification of the most important attributes, these were evaluated based on the number of overnight stays per tourist and tourist daily spending. This research is supported by secondary data, provided by a self-administrated questionnaire survey applied to international tourists during their departure from Faro international airport. The methodology included a first selection of the motivations that present higher heterogeneity acrossyears. The sample consists of 15542 observations collected from 2007 to 2010 (Correia & PimpĂŁo, 2012). Therefore, this paper identifies the high-yield visitors by country based on tourist preferences. Previous results reveal that preferences with higher yield expenditure markets are: sightseeing and excursions; information available; price; accommodation; and gastronomy.
In this light, the aims of this study are:
- to identify patterns of value-added given by international tourists for each motivation;
- to analyse the high-yield visitors by motivations across nationalities;
- to contribute to the understanding of how the yield potential of different source markets and segments can underpin destination marketing by destination sector organisations
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