In this thesis we study characterize the dynamic relationships among two electricity price variables (residential and commercial) and six regional economic variables in order to examine each individual variable??s role in regional economic activity. We also answer the question ??Do electricity prices have impact on regional economic variables??? We use two statistical techniques as engines of analysis. First, we use directed acyclic graphs to discover how surprises (innovations) in prices from each variable are communicated to other variables in contemporaneous time. Second, we use time series methods to capture regularities in time lags among the series. Yearly time series data on two electricity prices and six regional economic variables for Montgomery County (Texas) are studied using time series methods. Directed Acyclic Graphs (DAGs) are used to impose restrictions on the Vector Auto Regression model (VAR). Using Innovation Accounting Analysis of the estimated Vector Auto Regression (VAR) model we unravel the dynamic relationships between the eight variables. We conclude that rising electricity prices have a negative impact on allregional economic variables. The commercial average electricity prices lead residential average electricity prices in the time frame we studied (1969-2000). Rising residential electricity prices also have a positive impact on income derived from transfer payments.

Diss. Stockholm : Handelshögsk.

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Yes / Using International Passenger Survey (2017) data, this paper employs unconditional quantile regression (UQR) to analyse the determinants of tourist expenditure amongst inbound tourists to the United Kingdom. UQR allows us to estimate heterogeneous effects at any quantile of the distribution of the dependent variable. It overcomes the econometric limitations of ordinary least squares and quantile regression based estimates typically used to investigate tourism expenditures. However, our results reveal that the effects of our explanatory variables change across the distribution of tourist expenditure. This has important implications for those tasked with devising policies to enhance the UK’s tourist flows and expenditures.

The production or comprehension of linguistic information is often not an isolated task decoupled from the visual environment. Rather, people refer to objects or listen to other people describing objects around them. Previous studies have shown that in such situations people either fixate these objects, often multiple times (Cooper, 1974), or they attend to the objects much longer than is required for mere identification (Meyer, Sleiderink, & Levelt, 1998). Most interestingly, during comprehension people also attend to the location of objects even when those objects were removed (Altmann, 2004). The main focus of this thesis was to investigate the role of the spatial location of objects during language processing. The first part of the thesis tested whether attention to objects’ former locations facilitates language production and comprehension processes (Experiments 1-­‐5). In two initial eye-­‐tracking experiments, participants were instructed to name objects that either changed their positions (Experiment 1) or were withdrawn from the computer screen (Experiment 2) during language production. Production was impaired when speakers did not attend to the original position of the objects. Most interestingly, fixating an empty region in which an object was located resulted in faster articulation and initiation times. During the language comprehension tasks, participants were instructed to evaluate facts presented by talking heads appearing in different positions on the computer screen. During evaluation, the talking heads changed position (Experiment 3) or were withdrawn from the screen (Experiments 4-­‐5). People showed a strong tendency to gaze at the centre of the screen and only moved towards the head’s former locations if the screen was empty and if evaluation was not preceded by an intervening task as tested in Experiment 5. Fixating the former location resulted in faster response time but not in better accuracy of evaluation. The second part of this thesis investigated the role of spatial location representations in reading (Experiments 6-­‐7). Specifically, I examined to what extent people reading garden-­‐path sentences regress to specific target words in order to reanalyse the sentences. The results of two eye-­‐tracking experiments showed that readers do not target very precisely. A spatial representation is used, but it appears to be fairly coarse (i.e., only represents whether information is to the left or to the right of fixation). The findings from this thesis give us a clearer understanding of the influence of spatial location information on language processing. In language production particularly, it appears that spatial location is an integral part of the cognitive model and strongly connected with linguistic and visual representations.

We propose a method to deal simultaneously with model uncertainty and correlated regressors in linear regression models by combining elastic net specifications with a spike and slab prior. The estimation method nests ridge regression and the LASSO estimator and thus allows for a more flexible modelling framework than existing model averaging procedures. In particular, the proposed technique has clear advantages when dealing with datasets of (potentially highly) correlated regressors, a pervasive characteristic of the model averaging datasets used hitherto in the econometric literature. We apply our method to the dataset of economic growth determinants by Sala-i-Martin et al. (Sala-i-Martin, X., Doppelhofer, G., and Miller, R. I. (2004). Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach. American Economic Review, 94: 813-835) and show that our procedure has superior out-of-sample predictive abilities as compared to the standard Bayesian model averaging methods currently used in the literature. (authors' abstract) / Series: Research Report Series / Department of Statistics and Mathematics

The main revenue source for beef cattle farmers is the price they are awarded for carcasses based on carcass value (i.e., carcass weight, conformation and fat score) which is influenced by genetic and environmental factors (e.g., herd management). In order to improve profitability, accurate means of evaluating and improving both sets of factors influencing carcass trait performance are necessary. This would entail optimal management of genetic resources and herd practices. Furthermore, access to a large international germplasm pool would facilitate faster genetic gain. The objective of this thesis was to generate tools for the enhancement of carcass trait genetic and herd management evaluations both at a national and international level. The data used in the thesis originated from the Irish and UK national cattle databases and consisted of 336,944 Irish and 147,876 UK cattle of multiple beef and dairy breeds from 9,572 Irish and 3,385 UK commercial herds. Livestock mature at different rates depending on a number of factors including the genetic background; therefore, the optimum age at which to slaughter the progeny of different sires may differ. Chapter 2 examined sire level genetic profiles for three carcass traits (carcass weight, conformation and fat score) in cattle using data from the Republic of Ireland. Variance components for each trait across age at slaughter were estimated using sire random regression models. Heritability estimates of carcass traits across ages at slaughter varied depending on gender (heifers, steers, young bulls) and the trait in question, and ranged from 0.08 (± 0.02) to 0.34 (± 0.02) for carcass weight, from 0.24 (± 0.02) to 0.42 (± 0.02) for conformation score and from 0.16 (± 0.03) to 0.40 (± 0.02) for fat score. Genetic correlations between traits across ages at slaughter were all significantly less than unity, indicating that different genetic mechanisms control these traits across life. The results from chapter 2 show that genetic variability in the progeny growth trajectory of sires exists and that this variability in the growth profiles of sires for carcass traits may be exploited in breeding programmes. As carcass traits are a function of both the genetics of the animal and the environment in which the animal is reared, chapter 3 aimed to quantify the contribution of the herd environment to the same three beef carcass traits, with particular emphasis on generating finishing herd-specific profiles for carcass traits across different ages at slaughter. The data analysed in chapter 3 was from animals slaughtered in UK abattoirs. Genetic and finishing-herd-year of slaughter parameters were generated using random regression analysis. Across slaughter age and gender, the proportion of phenotypic variance accounted for by finishing-herd-year of slaughter variance was between 30.83%-71.48% for carcass weight, 21.38%-26.29% for conformation score and between 10.88%-44.04% for fat score. These parameters indicate that the finishing herd environment is an at least equally important contributor to carcass trait variability as the genetic background of animals, and amenable to improvement with appropriate management practices. The final study of the thesis was to investigate the feasibility of across-country carcass trait genetic evaluations. Examination of the level of genetic connectedness between Ireland and the UK found 225 distinct bulls common to both countries. These common bulls were related to 80,707 Irish and 23,162 UK animals with carcass records in each population. Genetic correlations for carcass traits between Ireland and the UK were almost unity, ranging from 0.92 (± 0.31) for fat score to 0.96 (± 0.17) for carcass weight, indicating that the carcass traits recorded in both countries are genetically essentially equivalent. These strong genetic correlations between carcass traits in both countries enabled the direct pooling of carcass data for the purpose of across-country genetic evaluations (breeding value estimation). An increased rate of genetic gain for carcass traits per generation was predicted from across-country selection compared to within country selection ranging from 2% (conformation score in Ireland) to 33.77% (conformation score in the UK). This improved gain was primarily due to greater intensity of selection and somewhat more accurate estimated breeding values when carcass records and pedigree information from both countries were combined. The results presented in this thesis demonstrate that routinely collected abattoir data in Ireland and the UK can be exploited to produce additional selection and on-farm management tools. The results also show that access to across-country carcass trait genetic evaluations would allow UK and Irish beef farmers to make more informed decisions on the selection of seed stock needed to increase genetic gain and profits. Outcomes of this thesis pave the way to improvements in national carcass traits genetic evaluations in Ireland and the UK based on appropriate age at slaughter and also demonstrate the feasibility of across-country carcass trait genetic evaluations between Ireland and the UK. The scope for further areas of research includes the identification of specific management practices for optimal herd performance for carcass traits. Additionally, across-country carcass trait genetic evaluations based on random regression models across different ages at slaughter would also be of benefit to beef producers in Ireland and the UK. Finally, the viability of across-country genetic evaluations for additional carcass traits, such as carcass cut weights should be explored.

The purpose of this study is to evaluate if FDI can be used as a proverbial ‘another arrow in the quiver’ for boosting economic growth. The research topic at hand asks if a positive regression can be observed between the employment of external market forces, specifically FDI, and economic growth. The study covers Singapore and South Korea during the period 1972-2019. The theoretical framework includes Solow’s exogenous growth theory, Romer’s endogenous growth theory and the OLI-theory. These theories provide the mechanism and context which explains how FDI can affect an economy, these include capital accumulation and non-rivalising ideas. The data has been tested to see if it complies with the classical assumption of linear regression. The analysis is based on multiple variable regression where a new independent variable is presented for each new regression that is made. The results show that there is no statistically significant coefficient in the regression model between FDI-inflow and economic growth in both countries during the specified time period. This result occurred because the FDI variable for the multiple regressions for each country usually does not show a statistically significant result. This means that the coefficient values presented in the regressions cannot be interpreted as facts because they do not reach the confidence interval below 5% to be seen as trustworthy results.

Panel regressions are used to analyze various measures of state higher education expenditures for 45 states over a time period from 1986 through 2005. Results of panel stationarity tests indicate that each expenditures series contains a unit root. This finding is consistent with the incremental theory of public expenditures and implies that time series of these variables should be differenced if used as dependent variables in regression models. Regression results indicate that changes in state higher education expenditures are significantly procyclical. State higher education spending appears to fully adjust to population growth and over-adjust to CPI inflation. Larger state governments are associated with significantly larger annual adjustments to per capita real state higher education expenditures. No significant evidence is found that state Medicaid or elementary education expenditures crowd out higher education spending.

The Fisher and Seater [Fisher, M.E. and Seater, J.J., 1993. Long run neutrality and superneutrality in an ARIMA framework. American Economic Review 83, 402-415.] methodology is applied to Taylor's [Taylor, A.T., 2002. A century of purchasing power parity. Review of Economics and Statistics 84, 139-150.] data to test for purchasing power parity. Generally, the evidence is supportive of PPP. Further, FS test statistics have no size distortion problem and test power is improved with longer samples.