The main objective of this paper is to equip the trade policy analyst with an appropriate method of seasonally adjusting trade data with weekly observations. To that end, a structural time series model containing a trend, seasonal and irregular component is specified. The seasonal component is represented by a time-varying periodic spline. Casting the model in state-space form enables time-varying parameters as well as use of the powerful Kalman filter for trend estimation. The resulting trend can then be interpreted as a seasonally adjusted series. A simulation exercise shows that the correct trend is identified with an average absolute error of 0.4 percent. An application to Swedish imports during 2017-2021 shows that the model produces a reasonable trend estimate when applied in 'real-time' and that its application is preferred to smoothing the series using a simple moving average.

Time series data is very common in our daily life. Since they are related to time, most of them show a periodicity. The existence of this periodic in uence leads to our research problem, seasonal adjustment. Seasonal adjustment is generally applied around us, especially in areas of economy and nance. Over the last few decades, scholars around the world made a lot of contributions in this area, and one of the latest methods is X-13ARIMA-SEATS, which is built on ARIMA models and linear lters. On the other hand, state space modelling (abbreviated to SSM) is also a popular method to solve this problem and researchers including J. Durbin, S.J. Koopman and and A. Harvery have contributed a lot of work to it. Unlike linear lters and ARIMA models, the study on SSM starts relatively late, thus it has not been studied and developed widely for the seasonal adjustment problem. And SSMs have a lot advantages over those ARIMA-based and lter-based methods such as exibility, the understandable structure and the potential to do partial pooling, but in practice, its default decomposition result behaves bad in some cases, such as excessively spiky trend series; on the contrary, X-13ARIMA-SEATS could output good decomposition result for us to analyze, but it can't be tweaked or combined as easily as generative models and behaves like a black-box. In this paper, we shall use Bayesian inference to combine both methods' characteristics together. Simultaneously, to show the advantage of using SSMs concretely, we shall give a simple application in partial pooling and talk about how to apply the Bayesian analysis to partial pooling.

Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. The state space approach is then extended to discuss direct and indirect seasonal adjustments. This is achieved by applying a seasonal level model with no trend and some specific input variances that render different signal-to-noise ratios. This is illustrated for a system consisting of two artificial time series. Relative efficiencies between direct, indirect and multivariate, i.e. optimal, variances are then analyzed. In practice, standard seasonal adjustment packages do not support optimal/multivariate seasonal adjustments, so a univariate approach to simultaneous estimation is presented by specifying a Holt-Winters exponential smoothing method. This is applied to two sets of time series systems by defining a total loss function that is specified with a trade-off weight between the individual series’ loss functions and their aggregate loss function. The loss function is based on either the more conventional squared errors loss or on a robust Huber loss. The exponential decay parameters are then estimated by minimizing the total loss function for different trade-off weights. It is then concluded what approach, direct or indirect seasonal adjustment, is to be preferred for the two time series systems. The dynamic linear modeling approach is also applied to Swedish political opinion polls to assert the true underlying political opinion when there are several polls, with potential design effects and bias, observed at non-equidistant time points. A Wiener process model is used to model the change in the proportion of voters supporting either a specific party or a party block. Similar to stock market models, all available (political) information is assumed to be capitalized in the poll results and is incorporated in the model by assimilating opinion poll results with the model through Bayesian updating of the posterior distribution. Based on the results, we are able to assess the true underlying voter proportion and additionally predict the elections. / <p>At the time of doctoral defence the following papers were unpublished and had a status as follows: Paper 3: Manuscript; Paper 4: Manuscripts</p>

Urbana parker är en central del i människors välbefinnande. De är platser för rekreation, aktiviteter och sociala utbyten. Forskning visar att undervinterhalvåret minskar användandet av parker i tempererade klimat vilket kan medföra negativa hälsoeffekter för människor. Att parker står obrukade delar av året är negativt både utifrån ett socialt- och resursperspektiv. Syftet med följande arbete är att undersöka hur kvartersparker kan anpassas för att öka användningen året runt. Målet är sedan att presentera en visualisering av förbättringsförslaget för Stenebergsparken i Gävle. En variation av metoder användes för att genomföra arbetet, där samtliga grundar sig i tidigare vetenskapliga publikationer. Platsanalys, webbenkät, intervjuer och en solstudie är de metoder som användes för att besvara studiens frågeställningar. Utifrån resultaten av dessa gestaltades ett förbättringsförslag somvisualiserades med renderingar och en video. Under arbetets gång framkom tre koncept som anpassning av parker i tempererade klimat bör utgå ifrån vid förändring, mikroklimat, aktivitet och utformning. Mikroklimat innebär att skapa behagliga klimat som erbjuder vistelse i olika typer av önskade väderförhållanden. Exempelvis möjligheten till sol- och skuggytor samt skydd mot nederbörd och vind. Utifrån aktivitet behöver parker erbjuda en variation av sysselsättningar för att kunna tillgodose flera behov. Denna aktivering innebär att en större mängd människor lockas till platsen. Utformning handlar om att tillgängliggöra ytor samt placera aktiviteter utifrån olika mikroklimat i parker. För att validera förbättringsförslaget presenterades det till två objektiva sakkunniga inom arkitektur och landskapsarkitektur. Följande studie visar på att vid utformning av kvartersparker i tempererade klimat behöver de tre koncepten mikroklimat, aktivitet och utformning tas i beaktning. Omplanerare, kommuner och politiker ser till dessa tre koncept ger de människor förutsättningar för att bruka parker under hela året i större utsträckning. / Urban parks are important components of people’s well-being and everyday life. These parks are a place for recreation, activities and social encounters.Previous research show that during the colder seasons the use of parks in temperate climates decreases, which in turn can have a negative outcome on people’s general health. The fact that urban parks are unused for a considerable part of the year is negative from both a social- and resource perspective. Therefore, the aim of this study is to investigate how neighborhood parks in temperate climates can be adapted to increase use all year round. Following the objective to present a visualization of the presented proposal for the case study of Stenebergsparken in Gävle. A combination of different methods was used and all methods were based on previous research. Site analysis, web survey, interviews and a solar study are the selected methods used to help answer the study's research questions. Throughout the process three concepts regarding adjustments of parks in temperate climates emerged, these were microclimate, activity and design. These concepts are essential to be taken in consideration during the planning process to create lively parks year around. Microclimates means to create pleasant environmentsthat enables visits in different types of desired weather conditions. This can be achieved through creating places that provide both sun and shade or creation of protection against precipitation. For activity parks need to offer a variety ofactivities to satisfy multiple interests. In turn, this attracts a greater number of visitors to the place. The design of a park involves the availability of the park and placement of activity surfaces regarding microclimate aspects. To validate the proposed improvements renderings together with a checklist was presented to two unbiased experts in architecture and landscape architecture.The produced proposal in this case study, regarding seasonal adjustment of neighborhood parks in tempered climates, is based upon the three emerging concepts microclimate, activity and design. If planners, municipalities and politicians look to these three concepts, they enable people to use parks throughout the year to a greater extent.