This study aims to investigate the impact of central bank interest rate effects on the debt-to-equity ratio of major companies in the industrial sector. With an Interrupted Time Series analysis the research examines how changes in the Federal Reserve's policy rates between 2011 and 2019 have influenced corporate financial strategies. Data from 46 of the largest U.S-based industrial firms were analyzed to identify trends in debt ratio before and after interest rate changes. The method involved comparing debt-to-equity ratios over a period of 36 quarters capturing both pre-event and post-event data. The findings indicate an increase in interest led to an increase in the debt ratio among these firms. This suggests that companies may have acted proactively to secure lower debt cost ahead of anticipated rate increases contrary to traditional expectations that higher rates would reduce borrowing. The study concludes that such proactive financial behavior highlights the complexity of corporate decision making in response to macroeconomic policy changes. The results contribute to a deeper understanding of how industrial firms manage their capital structure under varying economic conditions. Future research should explore sector specific responses and the implications for smaller firms to provide a more comprehensive view of the impact of interest rate changes on corporate capital structure. / Denna studie undersöker hur centralbankernas räntehöjningar påverkar skuldsättningsgraden hos stora företag inom industrisektorn. Genom att använda en Interrupted Time Series (ITS)-analys undersöker forskningen hur förändringar i Federal Reserves styrräntor mellan 2011 och 2019 har påverkat företagens finansiella strategier. Data från 46 av de största industriföretagen baserade i USA analyserades för att identifiera trender i skuldsättningen före och efter ränteändringarna. Metodstycket innebar en jämförelse av skuldsättningsgrader över en period av 36 kvartal vilket omfattade både data före och efter ränteändringarna. Resultaten visar på en ökning av skuldsättningsgraden bland dessa företag efter räntehöjningarna. Detta tyder på att företagen kan ha agerat proaktivt för att säkra billigare lån innan de förväntade räntehöjningarna fullt ut realiserades i motsats till den traditionella förväntningen att högre räntor skulle minska belåningen. Studien drar slutsatsen att ett sådant proaktivt finansiellt beteende belyser komplexiteten i företagens beslutsfattande som svar på makroekonomiska politiska förändringar. Resultaten bidrar till en djupare förståelse för hur industriföretag hanterar sin kapitalstruktur under varierande ekonomiska förhållanden. Framtida forskning bör utforska sektorspecifika svar och implikationerna för mindre företag för att ge en mer heltäckande bild av hur ränteförändringar påverkar företagens kapitalstruktur.

Finanskrisens inträde i mitten av 2008 utsattes Sveriges ekonomi för kraftiga påfrestningar. BNP-tillväxten mattades av och vi har till och med sett en negativ tillväxt för första gången sedan krisen i 90-talets början. Samtidigt har både hushållens konsumtion och näringslivets produktion rasat vilket har bidragit till kännbara effekter och en osäker tid för båda parter. Till en följd av detta har många företag tvingats avveckla sin verksamhet helt medan andra fått se över sina kostnader. Detta har i sin tur bidragit till att arbetslösheten ökat med cirka tre procentenheter mellan 2008 och 2010. En konsekvens av detta kan tänkas vara att brottsligheten påverkas. Vi har med hjälp av den statistiska metoden multipel regressionsanalys undersökt om, och i sådana fall hur våldsbrott samt stöld-, rån- och häleribrott påverkas när arbetslösheten förändras. Detta har utförts i två olika modeller, en för varje brottskategori, VB-modellen som behandlar våldsbrott och SB-modellen som innehåller stöld-, rån- och häleribrott. Då det även kan finnas andra variabler som påverkar brottsligheten har vi tagit med ytterligare åtta stycken i vår regression. Dataunderlaget är hämtat SCB, BRÅ och AMS hemsidor och avser samtliga Sveriges kommuner under åren 1996 till 2008. Resultatet av regressionen i VB-modellen visade att, om arbetslösheten ökar med en procentenhet så kommer antalet anmälda våldsbrott att minska med 0,019 brott per 1 000 invånare. När man sedan analyserar resultatet i SB-modellen ser vi att antalet stöld-, rån- och häleribrott per 1 000 invånare ökar med 4,216 om arbetslösheten ökar med en procentenhet. / The financial crisis in the middle of 2008 pushed the Swedish economy to its limits. GDP growth decreased and for the first time since the 1990 crisis, there was a negative growth in GDP. At the same time household expenditure and industrial production fell and lead to noticeable effects and uncertain times for both parties. As a consequence of this many companies have gone out of business. This has contributed to an increase in the unemployment rate with three percentage points between 2008 and 2010. A possible consequence of this could be an increasing crime rate. With the statistical method, multiple regression analysis, we have studied if there is a relationship between crime and unemployment. This has been done with two different models, the VB-model that includes assault crimes and the SB-model that includes property related crimes. Because there are more variables that can affect the crime rate, we include eight more variables in our equation. The data has been collected from SCB (Statistiska Centralbyrån), BRÅ (Brottsförebyggande Rådet) and AMS (Arbetsförmedlingen) webpage’s and concerns all municipalities in Sweden during 1996 to 2008. The result from the regression analysis shows, in the VB-model, if the unemployment increases with one percentage point, the number of reported assault crimes decreases with 0.019 crimes per 1000 residents. The result for the SB-model is that if the unemployment rate increases with one percentage point the number of reported property related crimes would increase with 4.216 crimes per 1000 residents.

<p>I denna magisteruppsats undersöks eventuella långsiktiga samband mellan den svenska aktiemarknaden och aktiemarknaderna i Tyskland, Storbritannien, USA och Japan. Detta sker genom en kointegrationsanalys med Engle-Grangers metod. Undersökningen omfattar åren 1992-2010 och resultaten visar inga tecken på att det skulle existera några långsiktiga samband mellan den svenska aktiemarknaden och någon av de utländska aktiemarknaderna. Resultaten ger därmed indikationer om att den svenska aktiemarknaden tillsammans med de utländska aktiemarknaderna i undersökningen är kollektivt effektiva i åtminstone den svaga formen enligt Fama (1970). Då inga långsiktiga samband existerar bör även portföljdiversifiering mellan den svenska aktiemarknaden och de utländska aktiemarknaderna i undersökningen fungera effektivt på lång sikt.</p> / <p>In this master thesis the Engle-Granger method for cointegration analysis is used to examine long-term relationships between stock markets. The analysis is applied on Swedish stock market together with the stock markets in Germany, United Kingdom, United States and Japan. The result shows no significant signs of any form of long-term relationships between the Swedish and the foreign stock markets for the time period 1992 to 2010. The result therefore indicates that the Swedish stock market together with the foreign stock markets in the study is collectively efficient in at least the weak form according to Fama (1970). The result also indicates that portfolio diversification through investing in the Swedish stock market together with any of the foreign stock markets should be effective in the long run.</p>

Diss. Stockholm : Handelshögsk.

Among the parametric nonlinear time series model families, the smooth transition regression (STR) model has recently received attention in the literature. The considerations in this dissertation focus on the univariate special case of this model, the smooth transition autoregression (STAR) model, although large parts of the discussion can be easily generalised to the more general STR case. Many nonlinear univariate time series models can be described as consisting of a number of regimes, each one corresponding to a linear autoregressive parametrisation, between which the process switches. In the STAR models, as opposed to certain other popular models involving multiple regimes, the transition between the extreme regimes is smooth and assumed to be characterised by a bounded continuous function of a transition variable. The transition variable, in turn, may be a lagged value of the variable in the model, or another stochastic or deterministic observable variable. A number of other commonly discussed nonlinear autoregressive models can be viewed as special or limiting cases of the STAR model. The applications presented in the first two chapters of this dissertation, Chapter I: Another look at Swedish Business Cycles, 1861-1988 Chapter II: Modelling asymmetries and moving equilibria in unemployment rates, make use of STAR models. In these two studies, STAR models are used to provide insight into dynamic properties of the time series which cannot be be properly characterised by linear time series models, and which thereby may be obscured by estimating only a linear model in cases where linearity would be rejected if tested. The applications being of interest in their own right, an important common objective of these two chapters is also to develop, suggest, and give examples of various methods that may be of use in discussing the dynamic properties of estimated STAR models in general.Chapter III, Testing linearity against smooth transition autoregression using a parametric bootstrap, reports the result of a small simulation study considering a new test of linearity against STAR based on bootstrap methodology. / <p>Diss. Stockholm : Handelshögskolan, 1999</p>

This thesis consists of four papers and the main theme present is dependence, through time as in serial correlation, and across individuals, as in random effects. The individual papers may be grouped in many different ways. As is, the first two are concerned with autoregressive dynamics in a single time series and then a panel context, while the subject of the final two papers is parametric covariance modeling. Though set in a panel context the results in the latter are generally applicable. The approach taken is Bayesian. This choice is prompted by the coherent framework that the Bayesian principle offers for quantifying uncertainty and subsequently making inference in the presence of it. Recent advances in numerical methods have also made the Bayesian choice simpler. In the first paper an existing model to conduct inference directly on the roots of the autoregressive polynomial is extended to include seasonal components and to allow for a polynomial trend of arbitrary degree. The resulting highly flexible model robustifies against misspecification by implicitly averaging over different lag lengths, number of unit roots and specifications for the deterministic trend. An application to the Swedish real GDP illustrates the rich set of information about the dynamics of a time series that can be extracted using this modeling framework. The second paper offers an extension to a panel of time series. Limiting the scope, but at the same time simplifying matters considerably, the mean model is dropped restricting the applicability to non-trending panels. The main motivation of the extension is the construction of a flexible panel unit root test. The proposed approach circumvents the classical confusing problem of stating a relevant null hypothesis. It offers the possibility of more distinct inference with respect to unit root composition in the collection of time series. It also addresses the two important issues of model uncertainty and cross-section correlation. The model is illustrated using a panel of real exchange rates to investigate the purchasing power parity hypothesis. Many interesting panel models imply a structure on the covariance matrix in terms of a small number of parameters. In the third paper, exploiting this structure it is demonstrated how common panel data models lend themselves to direct sampling of the variance parameters. Not necessarily always practical, the implementation can be described by a simple and generally applicable template. For the method to be practical, simple to program and quick to execute, it is essential that the inverse of the covariance matrix can be written as a reasonably simple function of the parameters of interest. Also preferable but in no way necessary is the availability of a computationally convenient expression for the determinant of the covariance matrix as well as a bounded support for the parameters. Using the template, the computations involved in direct sampling and effect selection are illustrated in the context of a one- and two-way random effects model respectively. Having established direct sampling as a viable alternative in the previous paper, the generic template is applied to panel models with serial correlation in the fourth paper. In the case of pure serial correlation, with no random effects present, applying the template and using a Jeffreys type prior leads to very simple computations. In the very general setting of a mixed effects model with autocorrelated errors direct sampling of all variance parameters does not appear to be possible or at least not obviously practical. One important special case is identified in the model with the random individual effects model with autocorrelation. / <p>Diss. Stockholm : Handelshögskolan i Stockholm, 2004 viii s., s. 1-9: sammanfattning, s. 10-116: 4 uppsatser</p>

I denna magisteruppsats undersöks eventuella långsiktiga samband mellan den svenska aktiemarknaden och aktiemarknaderna i Tyskland, Storbritannien, USA och Japan. Detta sker genom en kointegrationsanalys med Engle-Grangers metod. Undersökningen omfattar åren 1992-2010 och resultaten visar inga tecken på att det skulle existera några långsiktiga samband mellan den svenska aktiemarknaden och någon av de utländska aktiemarknaderna. Resultaten ger därmed indikationer om att den svenska aktiemarknaden tillsammans med de utländska aktiemarknaderna i undersökningen är kollektivt effektiva i åtminstone den svaga formen enligt Fama (1970). Då inga långsiktiga samband existerar bör även portföljdiversifiering mellan den svenska aktiemarknaden och de utländska aktiemarknaderna i undersökningen fungera effektivt på lång sikt. / In this master thesis the Engle-Granger method for cointegration analysis is used to examine long-term relationships between stock markets. The analysis is applied on Swedish stock market together with the stock markets in Germany, United Kingdom, United States and Japan. The result shows no significant signs of any form of long-term relationships between the Swedish and the foreign stock markets for the time period 1992 to 2010. The result therefore indicates that the Swedish stock market together with the foreign stock markets in the study is collectively efficient in at least the weak form according to Fama (1970). The result also indicates that portfolio diversification through investing in the Swedish stock market together with any of the foreign stock markets should be effective in the long run.

Economic statistics are often taken as given facts, assumed to describe exactly, actual phenomena in society. Many economic series are published in various forms from preliminary, via revisions to definitive estimates. Preliminary series are issued for a number of central economic processes in order to allow for rapid, up-to-date signals. This dissertation focuses on qualitative aspects of available data, and effects of possible inaccuracy when data are used for economic modelling, analysis and planning. Four main questions are addressed: How to characterize quality of data for central economic time series? What effects may possible inaccuracies in data have when used in econometric modelling? What effects do inaccuracies and errors in data have when models are used for economic analysis and planning? Is it possible to specify a criterion for deciding the cost-effective quality of data to be produced as input for economic policy analysis? The various realizations of economic variables often show considerable systematic as well as stochastic discrepancies for the same quantity. Preliminary series are generally found to be of questionable quality, but still considerably better than simple trend forecasts. Compared with the situation in a few other industrialized countries, the variability of Swedish economic statistics is, though, not extraordinary. Illustrations of effects of using inaccurate data, especially of combining preliminary, revised and definitive observations in the same model, are presented. Such inconsistent combinations of various realizations are in actual fact found in many open sources. Inclusion of preliminary series tends to indicate stronger changes in the economy than when definite observations are used throughout. The study is concluded with a section on cost-benefit aspects of economic statistics, and a sketch model for appraising data of variable quality is proposed. / Diss. Stockholm : Handelshögsk.

The goal of this thesis will be to formulate an economic model that exposes the relationship between consumption of luxury goods and selected factors which includes advertising, disposable income, interest rate, price index and stock premium. By building the Multiple Linear Regressions model to formulate the consumption function and using the Ordinary Least Squares (OLS) as the method, it becomes apparent that advertising, disposable income and the previous quarter´s disposable income are the major variables to affect luxury good consumption, of all the factors. Furthermore, the previous quarter´s disposable income has a slightly higher effect than the current one on luxury consumption. Similar studies, which focus on luxury items, have proposed models that test a single or a few variables at a time, and others that concentrate on durable goods have a wide range of variables to examine. I attempt to combine both in my model to test luxury consumption with a wide range of variables. / 1.Abstrsact: short (1/2 page)The very specific purpose of your studyThe finding ( results) The method: statistical method, the data , the theoretical data,Compare your results with the results from similar studies.2.Introduction (1 and half page)A general idea ( 4-6 lines)Make references to theoretical and empirical research paper.Names, dates, and contribution.The purpose of your studyMethodLimitationOutline of the paper3.Conclusion (1 page)The purpose of the studyThe resultsThe methodComparison with the results from similar studiesCritical discussion of your own studiesFurther studies4. consider opponents points too

Hur påverkar högre utbildningsnivå brottslighet? Den här uppsatsen undersöker effekt av eftergymnasial utbildning på våldsbrott respektive stöld-, rån- och häleribrott. Vår första hypotes är att eftergymnasial utbildning har en minskande effekt på våldsbrott genom högre alternativkostnad av brott samt att psykologiska faktorer påverkas positivt. Vår andra hypotes är att eftergymnasial utbildning har en ökande effekt på stöld-, rån- och häleribrott via högre avkastning till följd av mer kunskap för planering och utförande av denna typen av brott. Vidare förmodas en högre utbildningsnivå  generera mer tillgänglig egendom vilket leder till tilltagande incitament för stöld-, rån- och häleribrott. Förhållandena analyseras ekonometriskt med paneldata över Sveriges 21 län under tidsperioden 2000 till 2008. Prais-Winsten estimering används för skattning av linjär regression, där kontrollvariabler för bland annat demografi och arbetsmarknadseffekter inkluderas. Resultatet visar att eftergymnasial utbildning har en signifikant negativ effekt  på våldsbrott. Vi finner vidare att verkan av eftergymnasial utbildning på stöld-, rån och häleribrott är signifikant positiv. / How does higher education affect crime? This thesis examines the effect of post-secondary education on crime of violence and property related crime. Our first hypothesis is that a higher education level reduces crime of violence through higher opportunity costs and that psychological factors are affected in a positive way. Our second hypothesis is that a higher education level raises the return of property related crimes and therefore increases the same. This is due to more knowledge to be used for planning and execution of this type of crime and that the available property is assumed to be of a greater magnitude, which in turn leads to higher incentives for property related crime. The relationships are being econometrically analyzed with panel data consisting of observations of the 21 Swedish regions over the time period 2000 to 2008. The method of Prais-Winsten estimation is used to estimate a linear relationship, controlling for variables such as demographic and labor market effects. The results show that a higher education level has a significant negative effect on crime of violence. Furthermore we find that the effect of a higher education level on property related crime is significantly positive.