Econometric Modelling with Time Series : Specification, Estimation and Testing

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Travel time prediction on signalised urban arterials by applying SARIMA modelling on Bluetooth data

Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging. Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction. The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.

Postoperative chemotherapy for non-small cell lung cancer : a systematic review and meta-analysis

Background Postoperative chemotherapy is currently not recommended for resected non-small cell lung cancer in many countries and centers. Recently, results of several large randomized clinical trials were reported with conflicting evidence. Accordingly, we sought to determine whether postoperative chemotherapy is associated with improved survival compared with that after surgical intervention alone. Methods Randomized clinical trials with cisplatin- or uracil plus ftorafur-containing regimens were included and evaluated separately. A systematic review that included randomized clinical trials performed before 1995 was identified and found to be of adequate quality. Further randomized controlled trials were identified by searching MEDLINE, EMBASE, and the Cochrane Controlled Trials Register from 1995 through 2004. In addition, the reference lists of articles and conference abstracts were searched. The logarithm of the hazard ratio and its standard error were calculated, and a fixed-effect model was used to combine the estimates. Results There were 7200 patients enrolled in 19 trials included in the analyses. An overall estimate of 13% relative reduction in mortality (95% confidence interval, 7%-19%) was found. There was 11% relative reduction in mortality associated with postoperative cisplatin (95% confidence interval, 4%-18%; P = .004) and 17% associated with uracil plus ftorafur (95% confidence interval, 5%-27%; P = .006) compared with that after surgical intervention alone. This means that there would be an additional survivor at 5 years for 25 patients treated with cisplatin or for 30 patients treated with uracil plus ftorafur. Conclusions Postoperative chemotherapy is associated with improved survival compared with that after surgical intervention alone. Selected patients with completely resected non-small cell lung cancer should be offered chemotherapy. Copyright © 2004 by The American Association for Thoracic Surgery.

Plasmodium vivax malaria incidence over time and its association with temperature and rainfall in four counties of Yunnan Province, China

Background Transmission of Plasmodium vivax malaria is dependent on vector availability, biting rates and parasite development. In turn, each of these is influenced by climatic conditions. Correlations have previously been detected between seasonal rainfall, temperature and malaria incidence patterns in various settings. An understanding of seasonal patterns of malaria, and their weather drivers, can provide vital information for control and elimination activities. This research aimed to describe temporal patterns in malaria, rainfall and temperature, and to examine the relationships between these variables within four counties of Yunnan Province, China. Methods Plasmodium vivax malaria surveillance data (1991–2006), and average monthly temperature and rainfall were acquired. Seasonal trend decomposition was used to examine secular trends and seasonal patterns in malaria. Distributed lag non-linear models were used to estimate the weather drivers of malaria seasonality, including the lag periods between weather conditions and malaria incidence. Results There was a declining trend in malaria incidence in all four counties. Increasing temperature resulted in increased malaria risk in all four areas and increasing rainfall resulted in increased malaria risk in one area and decreased malaria risk in one area. The lag times for these associations varied between areas. Conclusions The differences detected between the four counties highlight the need for local understanding of seasonal patterns of malaria and its climatic drivers.

The impact of heatwaves on emergency department visits in Brisbane, Australia : a time series study

Introduction The acute health effects of heatwaves in a subtropical climate and their impact on emergency departments (ED) are not well known. The purpose of this study is to examine overt heat-related presentations to EDs associated with heatwaves in Brisbane. Methods Data were obtained for the summer seasons (December to February) from 2000-2012. Heatwave events were defined as two or more successive days with daily maximum temperature >=34[degree sign]C (HWD1) or >=37[degree sign]C (HWD2). Poisson generalised additive model was used to assess the effect of heatwaves on heat-related visits (International Classification of Diseases (ICD) 10 codes T67 and X30; ICD 9 codes 992 and E900.0). Results Overall, 628 cases presented for heat-related illnesses. The presentations significantly increased on heatwave days based on HWD1 (relative risk (RR) = 4.9, 95% confidence interval (CI): 3.8, 6.3) and HWD2 (RR = 18.5, 95% CI: 12.0, 28.4). The RRs in different age groups ranged between 3-9.2 (HWD1) and 7.5-37.5 (HWD2). High acuity visits significantly increased based on HWD1 (RR = 4.7, 95% CI: 2.3, 9.6) and HWD2 (RR = 81.7, 95% CI: 21.5, 310.0). Average length of stay in ED significantly increased by >1 hour (HWD1) and >2 hours (HWD2). Conclusions Heatwaves significantly increase ED visits and workload even in a subtropical climate. The degree of impact is directly related to the extent of temperature increases and varies by socio-demographic characteristics of the patients. Heatwave action plans should be tailored according to the population needs and level of vulnerability. EDs should have plans to increase their surge capacity during heatwaves.

Time course analysis of hypoxia, granulation tissue and blood vessel growth, and remodeling in healing rat cutaneous incisional primary intention wounds

Hypoxia and the development and remodeling of blood vessels and connective tissue in granulation tissue that forms in a wound gap following full-thickness skin incision in the rat were examined as a function of time. A 1.5 cm-long incisional wound was created in rat groin skin and the opposed edges sutured together. Wounds were harvested between 3 days and 16 weeks and hypoxia, percent vascular volume, cell proliferation and apoptosis, α-smooth muscle actin, vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 expression in granulation tissue were then assessed. Hypoxia was evident between 3 and 7 days while maximal cell proliferation at 3 days (123.6 ± 22.2 cells/mm 2, p < 0.001 when compared with normal skin) preceded the peak percent vascular volume that occurred at 7 days (15.83 ± 1.10%, p < 0.001 when compared with normal skin). The peak in cell apoptosis occurred at 3 weeks (12.1 ± 1.3 cells/mm 2, p < 0.001 when compared with normal skin). Intense α-smooth muscle actin labeling in myofibroblasts was evident at 7 and 10 days. Vascular endothelial growth factor receptor-2 and vascular endothelial growth factor-A were detectable until 2 and 3 weeks, respectively, while transforming growth factor-β 1 protein was detectable in endothelial cells and myofibroblasts until 3-4 weeks and in the extracellular matrix for 16 weeks. Incisional wound granulation tissue largely developed within 3-7 days in the presence of hypoxia. Remodeling, marked by a decline in the percent vascular volume and increased cellular apoptosis, occurred largely in the absence of detectable hypoxia. The expression of vascular endothelial growth factor-A, vascular endothelial growth factor receptor-2, and transforming growth factor-β 1 is evident prior, during, and after the peak of vascular volume reflecting multiple roles for these factors during wound healing.

Transitioning to energy efficient vehicles: An analysis of the potential rebound effects and subsequent impact upon emissions

Given the shift toward energy efficient vehicles (EEVs) in recent years, it is important that the effects of this transition are properly examined. This paper investigates some of these effects by analyzing annual kilometers traveled (AKT) of private vehicle owners in Stockholm in 2008. The difference in emissions associated with EEV adoption is estimated, along with the effect of a congestion-pricing exemption for EEVs on vehicle usage. Propensity score matching is used to compare AKT rates of different vehicle owner groups based on the treatments of: EEV ownership and commuting across the cordon, controlling for confounding factors such as demographics. Through this procedure, rebound effects are identified, with some EEV owners found to have driven up to 12.2% further than non-EEV owners. Although some of these differences could be attributed to the congestion-pricing exemption, the results were not statistically significant. Overall, taking into account lifecycle emissions of each fuel type, average EEV emissions were 50.5% less than average non-EEV emissions, with this reduction in emissions offset by 2.0% due to rebound effects. Although it is important for policy-makers to consider the potential for unexpected negative effects in similar transitions, the overall benefit of greatly reduced emissions appears to outweigh any rebound effects present in this case study.

Parameterizing Unconditional Skewness in Models for Financial Time Series

In this paper we consider the third-moment structure of a class of time series models. It is often argued that the marginal distribution of financial time series such as returns is skewed. Therefore it is of importance to know what properties a model should possess if it is to accommodate unconditional skewness. We consider modeling the unconditional mean and variance using models that respond nonlinearly or asymmetrically to shocks. We investigate the implications of these models on the third-moment structure of the marginal distribution as well as conditions under which the unconditional distribution exhibits skewness and nonzero third-order autocovariance structure. In this respect, an asymmetric or nonlinear specification of the conditional mean is found to be of greater importance than the properties of the conditional variance. Several examples are discussed and, whenever possible, explicit analytical expressions provided for all third-order moments and cross-moments. Finally, we introduce a new tool, the shock impact curve, for investigating the impact of shocks on the conditional mean squared error of return series.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

Impact of a new mandatory reporting law on reporting and identification of child sexual abuse: A seven year time trend analysis

Child sexual abuse is widespread and difficult to detect. To enhance case identification, many societies have enacted mandatory reporting laws requiring designated professionals, most often police, teachers, doctors and nurses, to report suspected cases to government child welfare agencies. Little research has explored the effects of introducing a reporting law on the number of reports made, and the outcomes of those reports. This study explored the impact of a new legislative mandatory reporting duty for child sexual abuse in the State of Western Australia over seven years. We analysed data about numbers and outcomes of reports by mandated reporters, for periods before the law (2006-08) and after the law (2009-12). Results indicate that the number of reports by mandated reporters of suspected child sexual abuse increased by a factor of 3.7, from an annual mean of 662 in the three year pre-law period to 2448 in the four year post-law period. The increase in the first two post-law years was contextually and statistically significant. Report numbers stabilised in 2010-12, at one report per 210 children. The number of investigated reports increased threefold, from an annual mean of 451 in the pre-law period to 1363 in the post-law period. Significant decline in the proportion of mandated reports that were investigated in the first two post-law years suggested the new level of reporting and investigative need exceeded what was anticipated. However, a subsequent significant increase restored the pre-law proportion, suggesting systemic adaptive capacity. The number of substantiated investigations doubled, from an annual mean of 160 in the pre-law period to 327 in the post-law period, indicating twice as many sexually abused children were being identified.