Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

Vad säger statistik om arbetslöshet? : En analys av den offentliga debattenom arbetslösheten i Sverige inför valet 2005

This essay examines the public debate concerning the unemployment of Sweden just before the general election 2005. Its main purpose is to analyse what lies behind the huge differences in statistics, as presented by the two leading factions in the debate. It concludes that these differences are foremost a problem of semantics, and that although the two factions have statistical proof of their claims, it is their use of terminology that is in fact their main weapon in the debate.The key word here is the swedish word for employment – sysselsättning – which the two facitons use in entirely different ways, creating a lot of possabilities for interpretation. This has caused a type of debate which is actually about the reinterpretation this word, and those who are to be included in the statistics as being “sysselsatt”, therefore, it is semantics that affects the number of unemployed people in the statistics.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

Passive solar options for reducing heating demand and maintain indoor climate in a multifamily house in Sweden

This research was carried out by studying possible renovation of a two-storey detached multifamily building by using passive solar design options in a cold climate in Borlänge, Sweden where the heating Degree Days are 4451 (base 20°C). Borlänge`s housing company, Tunabyggen, plans to renovate the project house located inthe multicultural district, Jakobsgårdarna. The goal of the thesis was to suggest a redesign of the current building, decrease the heating energy use, by applying passive solar design and control strategies, in a most reasonable way. In addition ensure a better thermal comfort for the tenants in the dwellings. Literatures have been studied, from which can be inferred that passive design should be abasic design consideration for all housing constructions, because it has advantages to ensure thermal comfort, and reduce the energy use. In addition further savings can be achieved applying different types of control strategies, from which the house will be more personalized, and better adapted to the user’s needs.The proposed method is based on simulations by using TRNSYS software. First a proper building model was set up, which represents the current state of the project building. Then the thermal insulation and the windows were upgraded, based on today's building regulations. The developments of the passive solar options were accomplished in two steps. First of all the relevant basic passive design elements were considered, then those advantages were compared to the advantages of applying new conventional thermostat, and shading control strategies.The results show that there is significant potential with the different types of passive solar design; their usage depends primarily on the location of the site as well as the orientation of the project building. Applying the control strategies, such as thermostat, and shading control, along the thermal insulation upgrade, may lead to significant energy savings (around 40 %), by comparison to the reference building without any upgrade.

Extended local labor markets due to high speed trains : Visualization of estimations in the Swedish national travel demand forecasting tool, SAMPERS

Wider economic benefits resulting from extended geographical mobility is one argument for investments in high-speed rail. More specifically, the argument for high-speed trains in Sweden has been that they can help to further spatially extend labor market regions which in turn has a positive effect on growth and development. In this paper the aim is to cartographically visualize the potential size of the labor markets in areas that could be affected by possible future high-speed trains. The visualization is based on the forecasts of labor mobility with public transport made by the Swedish national mobility transport forecasting tool, SAMPERS, for two alternative high-speed rail scenarios. The analysis, not surprisingly, suggests that the largest impact of high-speed trains results in the area where the future high speed rail tracks are planned to be built. This expected effect on local labor market regions of high-speed trains could mean that possible regional economic development effects also are to be expected in this area. However, the results, in general, from the SAMPERS forecasts indicaterelatively small increases in local labor market potentials.