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Serial Correlation (serial + correlation)
Selected AbstractsInfluence of psychotherapist density and antidepressant sales on suicide ratesACTA PSYCHIATRICA SCANDINAVICA, Issue 3 2009N. D. Kapusta Objective:, Antidepressant sales and suicide rates have been shown to be correlated in industrialized countries. The aim was to study the possible effects of psychotherapy utilization on suicide rates. Method:, We assessed the impact of antidepressant sales and psychotherapist density on suicide rates between 1991 and 2005. To adjust for serial correlation in time series, three first-order autoregressive models adjusted for per capita alcohol consumption and unemployment rates were employed. Results:, Antidepressant sales and the density of psychotherapists in the population were negatively associated with suicide rates. Conclusion:, This study provides evidence that decreasing suicide rates were associated with both increasing antidepressant sales and an increasing density of psychotherapists. The decrease of suicide rates could reflect a general improvement in mental health care rather than being caused by antidepressant sales or psychotherapist density alone. [source] Disclosures and Asset ReturnsECONOMETRICA, Issue 1 2003Hyun Song Shin Public information in financial markets often arrives through the disclosures of interested parties who have a material interest in the reactions of the market to the new information. When the strategic interaction between the sender and the receiver is formalized as a disclosure game with verifiable reports, equilibrium prices can be given a simple characterization in terms of the concatenation of binomial pricing trees. There are a number of empirical implications. The theory predicts that the return variance following a poor disclosed outcome is higher than it would have been if the disclosed outcome were good. Also, when investors are risk averse, this leads to negative serial correlation of asset returns. Other points of contact with the empirical literature are discussed. [source] The Dynamic Relation Between Returns and Idiosyncratic VolatilityFINANCIAL MANAGEMENT, Issue 2 2006Xiaoquan Jiang We claim that regressing excess returns on one-lagged volatility provides only a limited picture of the dynamic effect of idiosyncratic risk, which tends to be persistent over time. By correcting for the serial correlation in idiosyncratic volatility, we find that idiosyncratic volatility has a significant positive effect. This finding seems robusrt for various firm size portfolios, sample periods, and measures of idiosyncratic risk. Our findings suggest stock markets mis-price idiosyncratic risk. There may be some measurement problems with idiosyncratic risk. There may be some measurement problems with idiosyncratic risk that could be related to nondiversifiable risk. [source] On linking interannual tree ring variability with observations of whole-forest CO2 fluxGLOBAL CHANGE BIOLOGY, Issue 8 2006ADRIAN V. ROCHA Abstract We used a 10-year record of the CO2 flux by an old growth boreal forest in central Manitoba (the Northern Old Black Spruce Site (NOBS)), a ,150-year-old Picea mariana [Mill.] stand) to determine whether and how whole-forest CO2 flux is related to tree ring width. We compared a 37-year ring width chronology collected at NOBS to a second chronology that was collected at a nearby Black Spruce stand with a different disturbance history, and also to three measures of annual whole-forest photosynthesis [gross ecosystem production (GEP)], two measures of annual respiration (R), and one measure of annual carbon balance [net ecosystem production (NEP)]. The year-to-year ring width fluctuations were well correlated between the two sites; increasing our confidence in the NOBS chronology and implying that ring width variation is driven and synchronized by the physical environment. Both chronologies exhibited serial correlation, with a fluctuation in ring width that had an apparent periodicity of ,7 years. Neither chronology was correlated with variation in annual precipitation or temperature. Ring width and NEP increased, while R decreased from 1995 to 2004. GEP either remained constant or decreased from 1995 to 2004, depending on which measure was considered. The lack of relationship between ring width and GEP may indicate that ring growth is controlled almost entirely by something other than carbon uptake. Alternative explanations for the ring width chronologies include the possibility that wood production varies as a result of shifts in respiration, or that an unidentified aspect of the environment, rather than the balance between GEP and respiration, controls wood production. The serial correlation in ring width may be related to increases and decreases in carbohydrate pools, or to gradual changes in nutrient availability, pathogens, herbivores, soil frost or soil water table. The cause or causes of serial correlation, and the controls on the allocation of photosynthate to wood production, emerge as critical uncertainties for efforts in predicting the carbon balance of boreal ecosystems and inferring past climate from tree rings. [source] An application of fractional integration to a long temperature seriesINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 14 2003L. A. Gil-Alana Abstract Some recently proposed techniques of fractional integration are applied to a long UK temperature series. The tests are valid under general forms of serial correlation and do not require estimation of the fractional differencing parameter. The results show that central England temperatures have increased about 0.23 °C per 100 years in recent history. Attempting to summarize the conclusions for each of the months, we are left with the impression that the highest increase has occurred during the months from October to March. Copyright © 2003 Royal Meteorological Society [source] A scenario-based stochastic programming model for water supplies from the highland lakesINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 3 2000D.W. Watkins Jr Abstract A scenario-based, multistage stochastic programming model is developed for the management of the Highland Lakes by the Lower Colorado River Authority (LCRA) in Central Texas. The model explicitly considers two objectives: (1) maximize the expected revenue from the sale of interruptible water while reliably maintaining firm water supply, and (2) maximize recreational benefits. Input data can be represented by a scenario tree, built empirically from a segment of the historical flow record. Thirty-scenario instances of the model are solved using both a primal simplex method and Benders decomposition, and results show that the first-stage (,here and now') decision of how much interruptible water to contract for the coming year is highly dependent on the initial (current) reservoir storage levels. Sensitivity analysis indicates that model results can be improved by using a scenario generation technique which better preserves the serial correlation of flows. Ultimately, it is hoped that use of the model will improve the LCRA's operational practices by helping to identify flexible policies that appropriately hedge against unfavorable inflow scenarios. [source] Spatial Effects within the Agricultural Land Market in Northern IrelandJOURNAL OF AGRICULTURAL ECONOMICS, Issue 1 2003Myles Patton The importance of dealing properly with spatial effects, such as spatial autocorrelation, in cross-sectional econometric estimation has become more widely recognised in recent years. Spatial autocorrelation is similar in many ways to serial correlation, but while the latter is ordered on a one-dimensional time axis, the former is ordered in two dimensions. The multi-directional nature of spatial dependence means that specialised techniques are needed for diagnostic testing and estimation purposes. This paper uses these specialised diagnostics to test for spatial effects within a hedonic pricing study of the agricultural land market. The tests indicate that spatial autocorrelation (in the form of spatial lag dependence) and spatially distinct sub-markets (or spatial heterogeneity) are present. Ignoring these effects in the estimation process is likely to lead to biased parameter estimates. Consequently, we re-specify the hedonic model to allow for these spatial effects. The presence of spatial lag dependence suggests that there is circularity of price setting within the agricultural land market. This means that agricultural land prices are not solely determined by the inherent characteristics of the land, but tend to reflect also the average local price per acre. [source] How quickly do forecasters incorporate news?JOURNAL OF APPLIED ECONOMETRICS, Issue 6 2006Evidence from cross-country surveys Using forecasts from Consensus Economics Inc., we provide evidence on the efficiency of real GDP growth forecasts by testing whether forecast revisions are uncorrelated. As the forecast data used are multi-dimensional,18 countries, 24 monthly forecasts for the current and the following year and 16 target years,the panel estimation takes into account the complex structure of the variance,covariance matrix due to propagation of shocks across countries and economic linkages among them. Efficiency is rejected for all 18 countries: forecast revisions show a high degree of serial correlation. We then develop a framework for characterizing the nature of the inefficiency in forecasts. For a smaller set of countries, the G-7, we estimate a VAR model on forecast revisions. The degree of inefficiency, as manifested in the serial correlation of forecast revisions, tends to be smaller in forecasts of the USA than in forecasts for European countries. Our framework also shows that one of the sources of the inefficiency in a country's forecasts is resistance to utilizing foreign news. Thus the quality of forecasts for many of these countries can be significantly improved if forecasters pay more attention to news originating from outside their respective countries. This is particularly the case for Canadian and French forecasts, which would gain by paying greater attention than they do to news from the USA and Germany, respectively. Copyright © 2006 John Wiley & Sons, Ltd. [source] Econometric evidence of cross-market effects of generic dairy advertisingAGRIBUSINESS : AN INTERNATIONAL JOURNAL, Issue 1 2010Metin Cakir We estimate a dairy demand system to evaluate generic dairy advertising in the US, 1990,2005. Previous empirical studies of generic dairy advertising focus only on the market of the advertised good, ignoring potential spill-over and feedback effects. We specify an LA/AIDS model of dairy demand, which allows consistent estimation of cross-price and cross-advertising effects across dairy product markets, and is flexible and satisfies the axioms of consumer theory. We use the non-linear 3SLS estimator to address endogenous prices and serial correlation, and conduct bootstrapping to generate empirical distributions of elasticity estimates. Results suggest that cross-market effects are economically and statistically important. Thus, econometric dairy demand models that ignore cross-advertising and cross-price effects are mis-specified. Previous work that ignores substitution between fluid milk and cheese overstates producers' returns to generic advertising for either product. © 2010 Wiley Periodicals, Inc. [source] Related-variables selection in temporal disaggregationJOURNAL OF FORECASTING, Issue 4 2009Kosei Fukuda Abstract Two related-variables selection methods for temporal disaggregation are proposed. In the first method, the hypothesis tests for a common feature (cointegration or serial correlation) are first performed. If there is a common feature between observed aggregated series and related variables, the conventional Chow,Lin procedure is applied. In the second method, alternative Chow,Lin disaggregating models with and without related variables are first estimated and the corresponding values of the Bayesian information criterion (BIC) are stored. It is determined on the basis of the selected model whether related variables should be included in the Chow,Lin model. The efficacy of these methods is examined via simulations and empirical applications. Copyright © 2008 John Wiley & Sons, Ltd. [source] Modelling longitudinal semicontinuous emesis volume data with serial correlation in an acupuncture clinical trialJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 4 2005Paul S. Albert Summary., In longitudinal studies, we are often interested in modelling repeated assessments of volume over time. Our motivating example is an acupuncture clinical trial in which we compare the effects of active acupuncture, sham acupuncture and standard medical care on chemotherapy-induced nausea in patients being treated for advanced stage breast cancer. An important end point for this study was the daily measurement of the volume of emesis over a 14-day follow-up period. The repeated volume data contained many 0s, had apparent serial correlation and had missing observations, making analysis challenging. The paper proposes a two-part latent process model for analysing the emesis volume data which addresses these challenges. We propose a Monte Carlo EM algorithm for parameter estimation and we use this methodology to show the beneficial effects of acupuncture on reducing the volume of emesis in women being treated for breast cancer with chemotherapy. Through simulations, we demonstrate the importance of correctly modelling the serial correlation for making conditional inference. Further, we show that the correct model for the correlation structure is less important for making correct inference on marginal means. [source] Averaged Periodogram Spectral Estimation with Long-memory Conditional HeteroscedasticityJOURNAL OF TIME SERIES ANALYSIS, Issue 4 2001Marc Henry The empirical relevance of long-memory conditional heteroscedasticity has emerged in a variety of studies of long time series of high frequency financial measurements. A reassessment of the applicability of existing semiparametric frequency domain tools for the analysis of time dependence and long-run behaviour of time series is therefore warranted. To that end, in this paper the averaged periodogram statistic is analysed in the framework of a generalized linear process with long-memory conditional heteroscedastic innovations according to a model specification first proposed by Robinson (Testing for strong serial correlation and dynamic conditional heteroscedasticity in multiple regression. J. Economet. 47 (1991), 67,84). It is shown that the averaged periodogram estimate of the spectral density of a short-memory process remains asymptotically normal with unchanged asymptotic variance under mild moment conditions, and that for strongly dependent processes Robinson's averaged periodogram estimate of long memory (Semiparametric analysis of long memory time series. Ann. Stat. 22 (1994), 515,39) remains consistent. [source] The Determinants of Contract Length in Temporary Help EmploymentLABOUR, Issue 3 2006Tommaso Nannicini A simple theoretical model is developed, in order to depict the choice of contract length made by a firm that recruits temporary agency workers to deal with activity peaks. Assuming that the hiring of a new worker is associated with selection and training costs, longer contracts have an option value in face of a greater persistence of positive shocks. The model has two testable implications. First, the degree of serial correlation in market demand positively affects contract length. Second, the shortage of alternative employment opportunities negatively affects contract length. Using data on Italian temporary agency workers, both implications are confirmed by the econometric analysis. [source] Bayesian longitudinal plateau model of adult grip strengthAMERICAN JOURNAL OF HUMAN BIOLOGY, Issue 5 2010Ramzi W. Nahhas Objectives: This article illustrates the use of applied Bayesian statistical methods in modeling the trajectory of adult grip strength and in evaluating potential risk factors that may influence that trajectory. Methods: The data consist of from 1 to 11 repeated grip strength measurements from each of 498 men and 533 women age 18,96 years in the Fels Longitudinal Study (Roche AF. 1992. Growth, maturation and body composition: the Fels longitudinal study 1929,1991. Cambridge: Cambridge University Press). In this analysis, the Bayesian framework was particularly useful for fitting a nonlinear mixed effects plateau model with two unknown change points and for the joint modeling of a time-varying covariate. Multiple imputation (MI) was used to handle missing values with posterior inferences appropriately adjusted to account for between-imputation variability. Results: On average, men and women attain peak grip strength at the same age (36 years), women begin to decline in grip strength sooner (age 50 years for women and 56 years for men), and men lose grip strength at a faster rate relative to their peak; there is an increasing secular trend in peak grip strength that is not attributable to concurrent secular trends in body size, and the grip strength trajectory varies with birth weight (men only), smoking (men only), alcohol consumption (men and women), and sports activity (women only). Conclusions: Longitudinal data analysis requires handling not only serial correlation but often also time-varying covariates, missing data, and unknown change points. Bayesian methods, combined with MI, are useful in handling these issues. Am. J. Hum. Biol. 22:648,656, 2010. © 2010 Wiley-Liss, Inc. [source] Evaluating measurement error in estimates of worker exposure assessed in parallel by personal and biological monitoringAMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 2 2007Elaine Symanski PhD Abstract Background While studies indicate that the attenuating effects of imperfectly measured exposure can be substantial, they have not had the requisite data to compare methods of assessing exposure for the same individuals monitored over common time periods. Methods We examined measurement error in multiple exposure measures collected in parallel on 32 groups of workers. Random-effects models were applied under both compound symmetric and exponential correlation structures. Estimates of the within- and between-worker variances were used to contrast the attenuation bias in an exposure-response relationship that would be expected using an individual-based exposure assessment for different exposure measures on the basis of the intra-class correlation coefficient (ICC). Results ICC estimates ranged widely, indicative of a great deal of measurement error in some exposure measures while others contained very little. There was generally less attenuation in the biomarker data as compared to measurements obtained by personal sampling and, among biomarkers, for those with longer half-lives. The interval ICC estimates were oftentimes wide, suggesting a fair amount of imprecision in the point estimates. Ignoring serial correlation tended to over estimate the ICC values. Conclusions Although personal sampling results were typically characterized by more intra-individual variability than inter-individual variability when compared to biological measurements, both types of data provided examples of exposure measures fraught with error. Our results also indicated substantial imprecision in the estimates of exposure measurement error, suggesting that greater emphasis needs to be given to studies that collect sufficient data to better characterize the attenuating effects of an error-prone exposure measure. Am. J. Ind. Med. 50:112,121, 2007. © 2006 Wiley-Liss, Inc. [source] Optimal Valuation of Noisy Real AssetsREAL ESTATE ECONOMICS, Issue 3 2002Paul D. Childs We study the optimal valuation of real assets when true asset values are unobservable. In our model, the observed value cointegrates with the unobserved true asset value to cause serial correlation in the time series of observed values. Autocorrelation as well as total variance in the observed value are used to calculate an efficient unbiased estimate of the true asset value (the time,filtered value). The optimal value estimate is shown to have three time,weighted terms: a deterministic forward value, a comparison of observed values with previously determined time,filtered values, and a convexity correction for incomplete information. The residual variance measures the precision of the value estimate, which can increase or decrease monotonically over time as well as display a linear or nonlinear time trend. We also show how to revise time,filtered estimates based on the arrival of new information. Our results relate to work on illiquid asset markets, including appraisal smoothing, tests of market efficiency, and the valuation of options on real assets. [source] Presidential and Congressional Vote-Share EquationsAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 1 2009Ray C. Fair Three vote-share equations are estimated and analyzed in this article, one for presidential elections, one for on-term House elections, and one for midterm House elections. The sample period is 1916,2006. Considering the three equations together allows one to test whether the same economic variables affect each and to examine various serial correlation and coattail possibilities. The main conclusions are (1) there is strong evidence that the economy affects all three vote shares and in remarkably similar ways; (2) there is no evidence of any presidential coattail effects on the on-term House elections; (3) there is positive serial correlation in the House vote, which likely reflects a positive incumbency effect for elected representatives; and (4) the presidential vote share has a negative effect on the next midterm House vote share, which is likely explained by a balance argument. [source] Improving robust model selection tests for dynamic modelsTHE ECONOMETRICS JOURNAL, Issue 2 2010Hwan-sik Choi Summary, We propose an improved model selection test for dynamic models using a new asymptotic approximation to the sampling distribution of a new test statistic. The model selection test is applicable to dynamic models with very general selection criteria and estimation methods. Since our test statistic does not assume the exact form of a true model, the test is essentially non-parametric once competing models are estimated. For the unknown serial correlation in data, we use a Heteroscedasticity/Autocorrelation-Consistent (HAC) variance estimator, and the sampling distribution of the test statistic is approximated by the fixed- b,asymptotic approximation. The asymptotic approximation depends on kernel functions and bandwidth parameters used in HAC estimators. We compare the finite sample performance of the new test with the bootstrap methods as well as with the standard normal approximations, and show that the fixed- b,asymptotics and the bootstrap methods are markedly superior to the standard normal approximation for a moderate sample size for time series data. An empirical application for foreign exchange rate forecasting models is presented, and the result shows the normal approximation to the distribution of the test statistic considered appears to overstate the data's ability to distinguish between two competing models. [source] Dynamics of intraday serial correlation in the Italian futures marketTHE JOURNAL OF FUTURES MARKETS, Issue 1 2006Simone Bianco The serial correlation of high-frequency intraday returns on the Italian stock index futures (FIB30) in the period 2000,2002 is studied. It is found that intraday autocorrelation is mostly negative for time scales lower than 20 minutes, mainly due to the bid,ask bounce effect. Although this supports the efficiency of the Italian futures market, evidence that intraday serial correlation becomes positive in high-volatility regimes is also provided. Moreover, it is found that it is mainly unexpected volatility that makes serial correlation rise, and not its predictable part. The results are supportive of the K. Chan (1993) model. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:61,84, 2006 [source] Intradaily periodicity and volatility spillovers between international stock index futures marketsTHE JOURNAL OF FUTURES MARKETS, Issue 6 2005Chunchi Wu This paper examines short-run information transmission between the U.S. and U.K. markets using the S&P 500 and FTSE 100 index futures. Ultrahighfrequency futures data are employed,which have a number of advantages over the low-frequency spot data commonly used in previous studies,in establishing that volatility spillovers are in fact bidirectional. The generalized autoregressive conditionally heteroskedastic model (GARCH) is employed to estimate the mean and volatility spillovers of intraday returns. A Fourier flexible function is utilized to filter the intradaily periodic patterns that induce serial correlation in return volatility. It was found that estimates of volatility persistence and speed of information transmission are seriously affected by intradaily periodicity. The bias in parameter estimation is removed by filtering out the intradaily periodic component of the transaction data. Contrary to previous findings, there is evidence of spillovers in volatility between the U.S. and U.K. markets. Results indicate that the volatility of the U.S. market is affected by the most recent volatility surprise in the U.K. market. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:553,585, 2005 [source] Random-coefficients hidden-Markov Poisson regression models for inferring a competitor's promotion strategyAPPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 4 2007Johannes Ledolter Abstract In this paper we consider the case of a drug manufacturer who has physician-level information on the prescription volume for its own brand and its competitor, has complete physician-level data on its own free-sampling plan, but has only sparse data on the competitor's promotion strategy. We investigate whether one is able to predict the competitor's promotion strategy from such limited data. We treat the competitor's promotion as a latent (unobservable) event, and propose a hidden Markov model (HMM) to describe its progression over time. Analysis of actual and simulated data shows that the HMM improves our ability to infer the missing promotion event if promotions are serially correlated. A simpler model assuming that the probability of transition from one sampling state to the other is independent of the current state is adequate if the serial correlation among promotions is weak. Copyright © 2007 John Wiley & Sons, Ltd. [source] Generation of synthetic sequences of half-hourly temperatureENVIRONMETRICS, Issue 8 2008L. Magnano Abstract We present tools to generate synthetic sequences of half-hourly temperatures with similar statistical characteristics to observed historical data. Temperatures are generated using a combination of daily and half-hourly temperature models which account for intra-day and intra-year seasonality, as well as short-and long-term serial correlations. Details of the model estimation are given as well as a description of the synthetic generation. Copyright © 2008 John Wiley & Sons, Ltd. [source] | ||||||||||||||||||||||||||||||||||