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.

Metaanalys av vargforskningen i Sverige/Norgemellan åren 2000-2014

Vargens återkomst har gett upphov till olika attitydsyttringar, boende i vargområden är i regel mernegativa till vargen än de som bor utanför dessa områden. Genom att mäta vilka attityder som finnstill varg kan forskare ge incitament till makthavare om hur vargförvaltningen upplevs avallmänheten.Den här studien är en kartläggning av forskningsläget under åren 2000 – 2014 rörande attityder tillvarg i Sverige och Norge. De variabler/grupper av individer som forskare inom området använderför att mäta vem som har vilken attityd är jägare, djurägare, boende på landsbygd utanför vargområde, boende på landsbygd i vargområde, boende i stad med flera. Vi finner att studierna tar uppteorierna social representation, centrum och periferi och NIMBY (Not In My Backyard). Manproblematiserar dessa i varierande grad utifrån de teorier som används. Något vi menar ärproblematiskt då forskningen blir enkelspårig och grund. Vi vill se en bredare problematiseringutifrån de teorier som redan framkommit i forskningen och ifrågasätter varför inte fler teorier ochvariabler undersöks. Vi efterfrågar ett vidare perspektiv där forskaren exempelvis gör tolkningarutifrån olika samhälleliga maktfigurationer.