Denna uppsats undersöker hur tätt svenskar väljer att föda sina barn och om detta har förändrats över tiden. Vi granskar hur tätheterna ser ut mellan det första och andra barnet samt även mellan det andra och tredje barnet. Vi tittar också på om äldre män och kvinnor föder sina barn tätare än yngre. De data som används är ett register med samtliga svenskfödda män och kvinnor som fått barn under perioden 1970-2008. I slutet av 1980-talet finner vi en minskning i tätheten mellan barnen som förklaras av högkonjunktur och familjepolitiska åtgärder. Tiden mellan barnen ökar igen under 1990-talets lågkonjunktur, för att sedan på nytt gå nedåt under 2000-talet. Äldre föräldrar kan under hela tidsperioden konstateras föda barn med tätare intervall än yngre föräldrar. Vi undersöker huruvida orsaken till 2000-talets nedgång kan bero på att det blir allt vanligare med äldre föräldrar. Detta gör vi med hjälp av regressioner som skattas med OLS. Resultaten visar på att föräldrarnas ålder kan förklara en del, men inte hela, den nedåtgående trend vi ser i början på 2000-talet.

Manitoba has abundant mineral deposits and the mining sector is significant for its economy, especially outside the capital region. This paper examines the Manitoba mining taxation regime, using two approaches. First, a conventional regression analysis is used to estimate the impact of the 2009 mining tax cut on Northern employment and capital investment. This approach potentially offers a general indication of how tax policy influences economic advantages. Unfortunately, data limitations impede the analysis. Second, a mining firm is modelled to directly examine the effect of various tax structures on profitability. A hypothetical underground mine is modelled using discounted cash flow and net present value methods. Monte Carlo simulation will add a further dimensionality to the analysis, evaluating the effects of taxation when making probability assumptions on metal grade, prices, and operating costs. The new mine tax holiday stands out as a significant tax benefit for the miner.

Model CAPM je považován za základní model při oceňování systematického risku aktiv a jeho provázanosti s výnosností trhu. Tato práce využívá této struktury a použitím různých metod, mezi které patří OLS, DCC MGARCH a SSF modelovaní, se snaží najít nejvhodnější metodu z výše zmíněných, která dokáže nejlépe odhadnout koeficienty systematického risku. Tyto koeficienty jsou dále použity pro zajištění rizika portfolií, které jsou vytvořeny z akcií obchodovaných na různých burzách- NYSE Composite a NASDAQ Composite. Na základě obdržených výsledků o výkonu zajištění rizika v každém portfoliu budeme schopni vyhodnotit, která z metod je nejvhodnější pro odhad systematické risku v modelu CAPM. Klíčová slova: CAPM, Systematický risk, Portfolio risk hedge, OLS, DCC MGARCH, SSF model JEL Classification: C22, C58, G11, G12, G15 Author's e-mail: danielsopov@email.cz Supervisor's e-mail: andrlikova@gmail.com

Neoclassical models imply convergence of the entire distribution, not just the mean income levels. In this paper, we analyze convergence in income inequality by using the considerably enlarged data bases, from the World Bank (Povcal) and the World Institute for Development Economic Research (WIDER). Convergence in gini indices of inequality is tested across 55 countries. We consider three sample subsets; one for the developing countries, second of the developed countries and third with all countries together. We test for convergence in gini indices over a period of 5, 10, 15, 20 and 25 years. Additionally we use cross-section (OLS),panel (GMM) and a novel OLS estimation methods. Our results uniformly indicate that inequality levels among developing countries converged. Evidence of convergence is weaker among developed countries. Developing countries appear to converge faster than developed countries.

Abstract This thesis is focus on exploring the effect that domestic manufacturing vendors investing in Mainland China vs. Taiwan domestic employment issue. That the trend of the Taiwan unemployment rate gradually increasing these years is whether not related to the domestic vendors investing in Mainland China is the main topic of what we are discovering from the research. We have been observing the yearly tendency toward investing in other countries and change of the domestic labor demand and supply. According to the labor demand theory and other factors of labor demand affected we simultaneously consider one real model is built. Afterwards, we have divided manufacturing into 15 industries that categorizes labor intensity and capital intensity depended on industry characteristic. Based on the 1991-2202 pooling data calculated by OLS, we proceed to get the real evidential analysis of the domestic labor demand effect by investing in China. The result found: labor intensity of manufacturing who invest in China have outstandingly negative effect on the Taiwan domestic labor demand that means the employment opportunity in Taiwan is dramatically decreasing. The higher the investment percentage is, the lower the domestic labor demand is. Capital intensity of manufacturing, however, have positive effect that is not that outstanding at this moment. Therefore, the reason of unemployment rate yearly increasing in general is the manufacturers¡¦ enthusiastic investing behavior to Mainland China that only happened in labor intensity of manufacturing. Beside the factor of labor manufacture, the domestic economy downside is decreasing labor demand that is one of the reasons for unemployment rate increasing.

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Syftet med denna uppsats är att undersöka hur social bakgrund påverkar mäns uttag av föräldraledighet. Enligt tidigare forskning råder en ojämn fördelning av föräldraledighetsuttag mellan könen. Faktorer som har visat sig påverka hur föräldrar delar upp föräldraledighet är utbildning, lön samt ett instiftande av reserverad ledighet för den ena partnern. Trots upprepade försök att minska det ojämlika uttaget av föräldraledighet mellan könen delas den idag inte lika. Vi vill därför i denna uppsats analysera om det finns andra mekanismer än de nämnda ovan som påverkar uppdelning av föräldraledighet. Enligt genusteorier handlar män och kvinnor utifrån en reproduktion av förväntade beteenden som de har lärt sig genom den socialisationsprocess de exponeras för. Den primära socialisationen, som innebär att människor reproducerar sina föräldrars beteenden under de första åren i ens liv, kan komma att påverka ens handlingar i ett senare skede. Vi vill därför besvara frågeställningen hur påverkas män av sina föräldrars handlingar, gällande uttag av föräldraledighet? Analyserna görs med hjälp av ett riksrepresentativt datamaterial från LNU. Hypoteserna som ska besvaras är mäns uttag av föräldraledighet påverkas av deras föräldrars utbildningsnivå samt mäns uttag av föräldraledighet påverkas av deras fäders uttag av föräldraledighet. Resultaten visar inte att mäns uttag av föräldraledighet påverkas av deras föräldrars utbildningsnivå eller deras fäders uttag av föräldraledighet. Båda hypoteserna förkastas. Resultaten indikerar att det är andra faktorer som påverkar mäns uttag av föräldraledighet. Det behövs därför dels göras vidare studier på vilka faktorer dessa kan vara samt studier på nyare data då detta är ett fenomen som är i ständig förändring.

abstract: A least total area of triangle method was proposed by Teissier (1948) for fitting a straight line to data from a pair of variables without treating either variable as the dependent variable while allowing each of the variables to have measurement errors. This method is commonly called Reduced Major Axis (RMA) regression and is often used instead of Ordinary Least Squares (OLS) regression. Results for confidence intervals, hypothesis testing and asymptotic distributions of coefficient estimates in the bivariate case are reviewed. A generalization of RMA to more than two variables for fitting a plane to data is obtained by minimizing the sum of a function of the volumes obtained by drawing, from each data point, lines parallel to each coordinate axis to the fitted plane (Draper and Yang 1997; Goodman and Tofallis 2003). Generalized RMA results for the multivariate case obtained by Draper and Yang (1997) are reviewed and some investigations of multivariate RMA are given. A linear model is proposed that does not specify a dependent variable and allows for errors in the measurement of each variable. Coefficients in the model are estimated by minimization of the function of the volumes previously mentioned. Methods for obtaining coefficient estimates are discussed and simulations are used to investigate the distribution of coefficient estimates. The effects of sample size, sampling error and correlation among variables on the estimates are studied. Bootstrap methods are used to obtain confidence intervals for model coefficients. Residual analysis is considered for assessing model assumptions. Outlier and influential case diagnostics are developed and a forward selection method is proposed for subset selection of model variables. A real data example is provided that uses the methods developed. Topics for further research are discussed. / Dissertation/Thesis / Ph.D. Statistics 2012

The development and use of thermal models is an integral part of the design process in existing buildings due for refurbishment. Energy predictions for existing buildings are often based on models which assume thermal property values of the building construction elements. However, once built, the actual thermal properties may differ significantly from their estimated values. Possible reasons include thermal bridging, material distortion and moisture content, sub-standard construction on-site and unavailability of construction details. The uncertainties can be reduced if the modelling process can also make use of operational measurements, such as the fuel use and internal temperatures, which have been recorded in the building during operation. To make use of operational data, performance-based models can be used. Performance-based models rely on measured data for the development of the model s architecture and for informing the estimation of the model parameters that would otherwise be based on the modeller s assumptions of the building s characteristics. One solution to the challenge of using performance-based models for existing buildings is to use the Lumped Parameter modelling approach. The Lumped Parameter modelling technique is often used for performance-based modelling of existing buildings due to the moderate knowledge of the building s physical properties required and the limited operational data needed for model training. This thesis investigates the potential of performance-based modelling techniques for existing UK domestic buildings, based on the Lumped Parameter thermal modelling technique, and the use of measured operational data to inform the model structure and parameters. Operational data have been collected in 20 homes as part of the REFIT project, an EPSRC-funded research project on Smart Meters and Smart Homes (REFIT, 2016). This thesis explores 11 houses from the REFIT dataset and, in particular, the temperature, gas and electricity measurements from the participating households, and develops whole-house and sub-system performance-based models using the Lumped Parameter technique. The suitability of simple performance-based Lumped Parameter models in representing typical UK domestic buildings using mainstream operational data such as temperatures and gas consumption measurements is explored. This thesis concludes on the adequacy of the operational data as measured. High correlations (>0.9) between whole-house average indoor temperatures and individual room air temperature measurements prove the use of averages adequate for representing the main rooms of the houses, whereas individual representation of the house s main rooms in use in the same model can prove challenging. A similar result is observed for whole-house radiator representation and the individual radiators. The relationships between the operational data is explored to inform the model structure and to identify collinearity and multi collinearity in the measurements. In terms of whole-house modelling, when using constraints for the parameter values during the model calibration to the measured data the resulting model parameters can be realistic and a good agreement to the measured data can be achieved (on average an RMSE of 1.03 for air temperature). The most significant parameters affecting the mean value of internal air temperatures are the external envelope resistance Re, the non-inertia elements (e.g. windows and doors) resistance, the window area for solar gains, boiler efficiency and the infiltration rate. The indoor air and internal element heat capacitance had the greatest impact on the swing in the internal air temperature (a 75% decrease in the capacitance value resulted in a 190.70% increase in the standard deviation value on average across the 11 houses). The building envelope heat capacitance and the envelope node positioning were the two parameters with the least impact on the model goodness of fit (a 75% decrease in capacitance and a value of 0.9 in envelope node positioning resulted in a 2.57% and 6.68% increase respectively in the RMSE on average across all 11 houses). Finally, the heating system representation using the Lumped Parameter model showed that the whole-house gas consumption data at the meter level, consisting of gas used for space heating as well as other purposes, is inadequate to drive the heating system model. A temperature threshold (e.g. of 1oC) indicating model overprediction can be used to remove the time-stamps of mixed use gas consumption from the model calibration. The heating system model can then be used to quantify gas consumption for space heating and non-space heating uses. In the 11 houses under study, 82.96% of the total gas consumption served for space heating, with 17.04% serving for other non-space heating purposes.

This study uses a random coefficient estimation procedure to analyze the U.S. gasoline market from 1960-1995 with three main objectives: (1) provide an empirical methodology that can estimate a gasoline demand function capable of performing well in prediction; (2) evaluate the elasticities of the models presented to determine which model is more accurate at capturing supply shocks that impacted gasoline demand; and (3) evaluate the behavior of the elasticites of the beta coefficients. This research will show that the variation from historical economic patterns was a result of supply shocks. I argue that when the OLS model of the gasoline market developed by William H. Greene is used supply shocks are not well captured because the coefficients are fixed. If the random coefficient model developed by P.A.V.B. Swamy is introduced, the coefficients vary over time, and thereby, enable supply shocks to be included in the model and more accurate forecasts are produced, as well as, meaningful time patterns in the beta coefficients. / Master of Arts