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1. 1. Essays on Time Series Analysis : With Applications to Financial Econometrics

   Författare :Daniel Preve; Rolf Larsson; Bent Nielsen; Uppsala universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; non-Gaussian time series; nonnegative autoregression; robust estimation; strong convergence; realized volatility; volatility forecast; forecast comparison; Diebold-Mariano test; Statistics; Statistik;

   Sammanfattning : This doctoral thesis is comprised of four papers that all relate to the subject of Time Series Analysis.The first paper of the thesis considers point estimation in a nonnegative, hence non-Gaussian, AR(1) model. The parameter estimation is carried out using a type of extreme value estimators (EVEs). LÄS MER

3. 2. Applications of Bayesian Econometrics to Financial Economics

   Författare :Christoffer Bengtsson; Nationalekonomiska institutionen; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; economic systems; economic theory; econometrics; Economics; systemic risk; stochastic volatility; jump-diffusion; shrinkage; covariance matrix estimation; estimation risk; portfolio selection; mean-variance optimization; Markov chain Monte Carlo; Bayesian econometrics; ekonomisk politik; ekonomiska system; ekonomisk teori; ekonometri; Nationalekonomi; economic policy;

   Sammanfattning : This PhD thesis consists of four separate papers. What these papers have in common is that Bayesian Econometrics, in combination with Markov chain Monte Carlo (MCMC) methods, is applied to study various problems in financial economics. LÄS MER

4. 3. Mostly Panel Econometrics : Essays on Asymptotic Analysis and Enhanced Inference

   Författare :Ovidijus Stauskas; Joakim Westerlund; Ignace De Vos; Milda Norkute; Nationalekonomiska institutionen; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Econometrics; Panel Data; Factor Models; Bootstrap; Forecasting; Non-Stationary Data; Common Correlated Effects; CCE;

   Sammanfattning : This thesis consists of five chapters which focus on panel data theory. Four of them analyze explicit panel data models and one chapter deals with time series forecasting model, where external panel data help us estimate unobserved explanatory variables. LÄS MER

5. 4. On specification and inference in the econometrics of public procurement

   Författare :David Sundström; Kurt Brännäs; Sofia Lundberg; Michael Visser; Umeå universitet; []
   Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; auctions; dependent variable transformation model; green public procurement; indirect inference; instrumental variable; latent variable; log-generalized gamma distribution; maximum likelihood; measurement error; non-linear least squares; objective effectiveness; orthogonal polynomial regression; prediction; simulation estimation; structural estimation; nationalekonomi; Economics; Econometrics; ekonometri;

   Sammanfattning : In Paper [I] we use data on Swedish public procurement auctions for internal regularcleaning service contracts to provide novel empirical evidence regarding green publicprocurement (GPP) and its effect on the potential suppliers’ decision to submit a bid andtheir probability of being qualified for supplier selection. We find only a weak effect onsupplier behavior which suggests that GPP does not live up to its political expectations. LÄS MER

7. 5. Common features in vector nonlinear time series models

   Författare :Dao Li; Sune Karlsson; Kenneth Carling; Thomas Holgersson; Örebro universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; nonliearity; time series; econometrics; smooth transition; common features; cointegration; forecasting; residual-based; ppp; Statistics; Statistik; Complex Systems – Microdata Analysis;

   Sammanfattning : 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 thesearea.Both stationary and nonstationary time series are concerned. LÄS MER