Applications of Treatment Effects Models and Semiparametric Estimation

This thesis is composed of an introductory chapter and four applications each of them constituting an own chapter. The common element underlying each of the chapters is the econometric methodology. The applications rely mostly on the leading econometric techniques related to estimation of causal effects. The first chapter introduces the econometric techniques that are employed in the remaining chapters. Chapter 2 studies the effects of shocking news on student performance. It exploits the fact that the school shooting in Kauhajoki in 2008 coincided with the matriculation examination period of that fall. It shows that the performance of men declined due to the news of the school shooting. For women the similar pattern remains unobserved. Chapter 3 studies the effects of minimum wage on employment by employing the original Card and Krueger (1994; CK) and Neumark and Wascher (2000; NW) data together with the changes-in-changes (CIC) estimator. As the main result it shows that the employment effect of an increase in the minimum wage is positive for small fast-food restaurants and negative for big fast-food restaurants. Therefore, it shows that the controversial positive employment effect reported by CK is overturned for big fast-food restaurants and that the NW data are shown, in contrast to their original results, to provide support for the positive employment effect. Chapter 4 employs the state-specific U.S. data (collected by Cohen and Einav [2003; CE]) on traffic fatalities to re-evaluate the effects of seat belt laws on the traffic fatalities by using the CIC estimator. It confirms the CE results that on the average an implementation of a mandatory seat belt law results in an increase in the seat belt usage rate and a decrease in the total fatality rate. In contrast to CE, it also finds evidence on compensating-behavior theory, which is observed especially in the states by the border of the U.S. Chapter 5 studies the life cycle consumption in Finland, with the special interest laid on the baby boomers and the older households. It shows that the baby boomers smooth their consumption over the life cycle more than other generations. It also shows that the old households smoothed their life cycle consumption more as a result of the recession in the 1990s, compared to young households.

The regional differences between countries in traffic safety: A cross-cultural study and Turkish Case

Road traffic accidents are a large problem everywhere in the world. However, regional differences in traffic safety between countries are considerable. For example, traffic safety records are much worse in Southern Europe and the Middle East than in Northern and Western Europe. Despite the large regional differences in traffic safety, factors contributing to different accident risk figures in different countries and regions have remained largely unstudied. The general aim of this study was to investigate regional differences in traffic safety between Southern European/Middle Eastern (i.e., Greece, Iran, Turkey) and Northern/Western European (i.e., Finland, Great Britain, The Netherlands) countries and to identify factors related to these differences. We conducted seven sub-studies in which I applied a traffic culture framework, including a multi-level approach, to traffic safety. We used aggregated level data (national statistics), surveys among drivers, and data on traffic accidents and fatalities in the analyses. In the first study, we investigated the influence of macro level factors (i.e., economic, societal, and cultural) on traffic safety across countries. The results showed that a high GNP per capita and conservatism correlated with a low number of traffic fatalities, whereas a high degree of uncertainty avoidance, neuroticism, and egalitarianism correlated with a high number of traffic fatalities. In the second, third, and fourth studies, we examined whether the conceptualisation of road user characteristics (i.e., driver behaviour and performance) varied across traffic cultures and how these factors determined overall safety, and the differences between countries in traffic safety. The results showed that the factorial agreement for driver behaviour (i.e., aggressive driving) and performance (i.e., safety skills) was unsatisfactory in Greece, Iran, and Turkey, where the lack of social tolerance and interpersonal aggressive violations seem to be important characteristics of driving. In addition, we found that driver behaviour (i.e., aggressive violations and errors) mediated the relationship between culture/country and accidents. Besides, drivers from "dangerous" Southern European countries and Iran scored higher on aggressive violations and errors than did drivers from "safe" Northern European countries. However, "speeding" appeared to be a "pan-cultural" problem in traffic. Similarly, aggressive driving seems largely depend on road users' interactions and drivers' interpretation (i.e., cognitive biases) of the behaviour of others in every country involved in the study. Moreover, in all countries, a risky general driving style was mostly related to being young and male. The results of the fifth and sixth studies showed that among young Turkish drivers, gender stereotypes (i.e., masculinity and femininity) greatly influence driver behaviour and performance. Feminine drivers were safety-oriented whereas masculine drivers were skill-oriented and risky drivers. Since everyday driving tasks involve not only erroneous (i.e., risky or dangerous driving) or correct performance (i.e., normal habitual driving), but also "positive" driver behaviours, we developed a reliable scale for measuring "positive" driver behaviours among Turkish drivers in the seventh study. Consequently, I revised Reason's model [Reason, J. T., 1990. Human error. Cambridge University Press: New York] of aberrant driver behaviour to represent a general driving style, including all possible intentional behaviours in traffic while evaluating the differences between countries in traffic safety. The results emphasise the importance of economic, societal and cultural factors, general driving style and skills, which are related to exposure, cognitive biases as well as age, sex, and gender, in differences between countries in traffic safety.

From a tree to a stand in Finnish boreal forests: biomass estimation and comparison of methods

There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61º50' N, 24º22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg/yr for understorey spruce to 7 kg/yr for dominant pine) when the trees were 100 years old. Tree biomass was estimated to be about 70 Mg/ha in Young-Stand and about 220 Mg/ha in Mature-Stand. In the region (58.00-62.13 ºN, 14-34 ºE, ≤ 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg/ha at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg/ha with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg/ha. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

Remote sensing of boreal land cover: estimation of forest attributes and extent

Remote sensing provides methods to infer land cover information over large geographical areas at a variety of spatial and temporal resolutions. Land cover is input data for a range of environmental models and information on land cover dynamics is required for monitoring the implications of global change. Such data are also essential in support of environmental management and policymaking. Boreal forests are a key component of the global climate and a major sink of carbon. The northern latitudes are expected to experience a disproportionate and rapid warming, which can have a major impact on vegetation at forest limits. This thesis examines the use of optical remote sensing for estimating aboveground biomass, leaf area index (LAI), tree cover and tree height in the boreal forests and tundra taiga transition zone in Finland. The continuous fields of forest attributes are required, for example, to improve the mapping of forest extent. The thesis focus on studying the feasibility of satellite data at multiple spatial resolutions, assessing the potential of multispectral, -angular and -temporal information, and provides regional evaluation for global land cover data. Preprocessed ASTER, MISR and MODIS products are the principal satellite data. The reference data consist of field measurements, forest inventory data and fine resolution land cover maps. Fine resolution studies demonstrate how statistical relationships between biomass and satellite data are relatively strong in single species and low biomass mountain birch forests in comparison to higher biomass coniferous stands. The combination of forest stand data and fine resolution ASTER images provides a method for biomass estimation using medium resolution MODIS data. The multiangular data improve the accuracy of land cover mapping in the sparsely forested tundra taiga transition zone, particularly in mires. Similarly, multitemporal data improve the accuracy of coarse resolution tree cover estimates in comparison to single date data. Furthermore, the peak of the growing season is not necessarily the optimal time for land cover mapping in the northern boreal regions. The evaluated coarse resolution land cover data sets have considerable shortcomings in northernmost Finland and should be used with caution in similar regions. The quantitative reference data and upscaling methods for integrating multiresolution data are required for calibration of statistical models and evaluation of land cover data sets. The preprocessed image products have potential for wider use as they can considerably reduce the time and effort used for data processing.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Analysis of Heterogeneous IP Traffic in Wireless Environment

Wireless access is expected to play a crucial role in the future of the Internet. The demands of the wireless environment are not always compatible with the assumptions that were made on the era of the wired links. At the same time, new services that take advantage of the advances in many areas of technology are invented. These services include delivery of mass media like television and radio, Internet phone calls, and video conferencing. The network must be able to deliver these services with acceptable performance and quality to the end user. This thesis presents an experimental study to measure the performance of bulk data TCP transfers, streaming audio flows, and HTTP transfers which compete the limited bandwidth of the GPRS/UMTS-like wireless link. The wireless link characteristics are modeled with a wireless network emulator. We analyze how different competing workload types behave with regular TPC and how the active queue management, the Differentiated services (DiffServ), and a combination of TCP enhancements affect the performance and the quality of service. We test on four link types including an error-free link and the links with different Automatic Repeat reQuest (ARQ) persistency. The analysis consists of comparing the resulting performance in different configurations based on defined metrics. We observed that DiffServ and Random Early Detection (RED) with Explicit Congestion Notification (ECN) are useful, and in some conditions necessary, for quality of service and fairness because a long queuing delay and congestion related packet losses cause problems without DiffServ and RED. However, we observed situations, where there is still room for significant improvements if the link-level is aware of the quality of service. Only very error-prone link diminishes the benefits to nil. The combination of TCP enhancements improves performance. These include initial window of four, Control Block Interdependence (CBI) and Forward RTO recovery (F-RTO). The initial window of four helps a later starting TCP flow to start faster but generates congestion under some conditions. CBI prevents slow-start overshoot and balances slow start in the presence of error drops, and F-RTO reduces unnecessary retransmissions successfully.

Quantifying Time Awake Posturographically

This thesis focuses on the issue of testing sleepiness quantitatively. The issue is relevant to policymakers concerned with traffic- and occupational safety; such testing provides a tool for safety legislation and -surveillance. The findings of this thesis provide guidelines for a posturographic sleepiness tester. Sleepiness ensuing from staying awake merely 17 h impairs our performance as much as the legally proscribed blood alcohol concentration 0.5 does. Hence, sleepiness is a major risk factor in transportation and occupational accidents. The lack of convenient, commercial sleepiness tests precludes testing impending sleepiness levels contrary to simply breath testing for alcohol intoxication. Posturography is a potential sleepiness test, since clinical diurnal balance testing suggests the hypothesis that time awake could be posturographically estimable. Relying on this hypothesis this thesis examines posturographic sleepiness testing for instrumentation purposes. Empirical results from 63 subjects for whom we tested balance with a force platform during wakefulness for maximum 36 h show that sustained wakefulness impairs balance. The results show that time awake is posturographically estimable with 88% accuracy and 97% precision which validates our hypothesis. Results also show that balance scores tested at 13:30 hours serve as a threshold to detect excessive sleepiness. Analytical results show that the test length has a marked effect on estimation accuracy: 18 s tests suffice to identify sleepiness related balance changes, but trades off some of the accuracy achieved with 30 s tests. The procedure to estimate time awake relies on equating the subject s test score to a reference table (comprising balance scores tested during sustained wakefulness, regressed against time awake). Empirical results showed that sustained wakefulness explains 60% of the diurnal balance variations, whereas the time of day explains 40% of the balance variations. The latter fact implies that time awake estimations also must rely on knowing the local times of both test and reference scores.