Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).

Quantitative trait loci detection and benefits from marker-assisted selection in dairy cattle

Knowing the chromosomal areas or actual genes affecting the traits under selection would add more information to be used in the selection decisions which would potentially lead to higher genetic response. The first objective of this study was to map quantitative trait loci (QTL) affecting economically important traits in the Finnish Ayrshire population. The second objective was to investigate the effects of using QTL information in marker-assisted selection (MAS) on the genetic response and the linkage disequilibrium between the different parts of the genome. Whole genome scans were carried out on a grand-daughter design with 12 half-sib families and a total of 493 sons. Twelve different traits were studied: milk yield, protein yield, protein content, fat yield, fat content, somatic cell score (SCS), mastitis treatments, other veterinary treatments, days open, fertility treatments, non-return rate, and calf mortality. The average spacing of the typed markers was 20 cM with 2 to 14 markers per chromosome. Associations between markers and traits were analyzed with multiple marker regression. Significance was determined by permutation and genome-wise P-values obtained by Bonferroni correction. The benefits from MAS were investigated by simulation: a conventional progeny testing scheme was compared to a scheme where QTL information was used within families to select among full-sibs in the male path. Two QTL on different chromosomes were modelled. The effects of different starting frequencies of the favourable alleles and different size of the QTL effects were evaluated. A large number of QTL, 48 in total, were detected at 5% or higher chromosome-wise significance. QTL for milk production were found on 8 chromosomes, for SCS on 6, for mastitis treatments on 1, for other veterinary treatments on 5, for days open on 7, for fertility treatments on 7, for calf mortality on 6, and for non-return rate on 2 chromosomes. In the simulation study the total genetic response was faster with MAS than with conventional selection and the advantage of MAS persisted over the studied generations. The rate of response and the difference between the selection schemes reflected clearly the changes in allele frequencies of the favourable QTL. The disequilibrium between the polygenes and QTL was always negative and it was larger with larger QTL size. The disequilibrium between the two QTL was larger with QTL of large effect and it was somewhat larger with MAS for scenarios with starting frequencies below 0.5 for QTL of moderate size and below 0.3 for large QTL. In conclusion, several QTL affecting economically important traits of dairy cattle were detected. Further studies are needed to verify these QTL, check their presence in the present breeding population, look for pleiotropy and fine map the most interesting QTL regions. The results of the simulation studies show that using MAS together with embryo transfer to pre-select young bulls within families is a useful approach to increase the genetic merit of the AI-bulls compared to conventional selection.

A dynamic programming model for optimising feeding and slaughter decisions regarding fattening pigs

Costs of purchasing new piglets and of feeding them until slaughter are the main variable expenditures in pig fattening. They both depend on slaughter intensity, the nature of feeding patterns and the technological constraints of pig fattening, such as genotype. Therefore, it is of interest to examine the effect of production technology and changes in input and output prices on feeding and slaughter decisions. This study examines the problem by using a dynamic programming model that links genetic characteristics of a pig to feeding decisions and the timing of slaughter and takes into account how these jointly affect the quality-adjusted value of a carcass. The model simulates the growth mechanism of a pig under optional feeding and slaughter patterns and then solves the optimal feeding and slaughter decisions recursively. The state of nature and the genotype of a pig are known in the analysis. The main contribution of this study is the dynamic approach that explicitly takes into account carcass quality while simultaneously optimising feeding and slaughter decisions. The method maximises the internal rate of return to the capacity unit. Hence, the results can have vital impact on competitiveness of pig production, which is known to be quite capital-intensive. The results suggest that producer can significantly benefit from improvements in the pig's genotype, because they improve efficiency of pig production. The annual benefits from obtaining pigs of improved genotype can be more than €20 per capacity unit. The annual net benefits of animal breeding to pig farms can also be considerable. Animals of improved genotype can reach optimal slaughter maturity quicker and produce leaner meat than animals of poor genotype. In order to fully utilise the benefits of animal breeding, the producer must adjust feeding and slaughter patterns on the basis of genotype. The results suggest that the producer can benefit from flexible feeding technology. The flexible feeding technology segregates pigs into groups according to their weight, carcass leanness, genotype and sex and thereafter optimises feeding and slaughter decisions separately for these groups. Typically, such a technology provides incentives to feed piglets with protein-rich feed such that the genetic potential to produce leaner meat is fully utilised. When the pig approaches slaughter maturity, the share of protein-rich feed in the diet gradually decreases and the amount of energy-rich feed increases. Generally, the optimal slaughter weight is within the weight range that pays the highest price per kilogram of pig meat. The optimal feeding pattern and the optimal timing of slaughter depend on price ratios. Particularly, an increase in the price of pig meat provides incentives to increase the growth rates up to the pig's biological maximum by increasing the amount of energy in the feed. Price changes and changes in slaughter premium can also have large income effects. Key words: barley, carcass composition, dynamic programming, feeding, genotypes, lean, pig fattening, precision agriculture, productivity, slaughter weight, soybeans

Development of Sample Pretreatment and Liquid Chromatographic Techniques for Antioxidative Compounds

In this study, novel methodologies for the determination of antioxidative compounds in herbs and beverages were developed. Antioxidants are compounds that can reduce, delay or inhibit oxidative events. They are a part of the human defense system and are obtained through the diet. Antioxidants are naturally present in several types of foods, e.g. in fruits, beverages, vegetables and herbs. Antioxidants can also be added to foods during manufacturing to suppress lipid oxidation and formation of free radicals under conditions of cooking or storage and to reduce the concentration of free radicals in vivo after food ingestion. There is growing interest in natural antioxidants, and effective compounds have already been identified from antioxidant classes such as carotenoids, essential oils, flavonoids and phenolic acids. The wide variety of sample matrices and analytes presents quite a challenge for the development of analytical techniques. Growing demands have been placed on sample pretreatment. In this study, three novel extraction techniques, namely supercritical fluid extraction (SFE), pressurised hot water extraction (PHWE) and dynamic sonication-assisted extraction (DSAE) were studied. SFE was used for the extraction of lycopene from tomato skins and PHWE was used in the extraction of phenolic compounds from sage. DSAE was applied to the extraction of phenolic acids from Lamiaceae herbs. In the development of extraction methodologies, the main parameters of the extraction were studied and the recoveries were compared to those achieved by conventional extraction techniques. In addition, the stability of lycopene was also followed under different storage conditions. For the separation of the antioxidative compounds in the extracts, liquid chromatographic methods (LC) were utilised. Two novel LC techniques, namely ultra performance liquid chromatography (UPLC) and comprehensive two-dimensional liquid chromatography (LCxLC) were studied and compared with conventional high performance liquid chromatography (HPLC) for the separation of antioxidants in beverages and Lamiaceae herbs. In LCxLC, the selection of LC mode, column dimensions and flow rates were studied and optimised to obtain efficient separation of the target compounds. In addition, the separation powers of HPLC, UPLC, HPLCxHPLC and HPLCxUPLC were compared. To exploit the benefits of an integrated system, in which sample preparation and final separation are performed in a closed unit, dynamic sonication-assisted extraction was coupled on-line to a liquid chromatograph via a solid-phase trap. The increased sensitivity was utilised in the extraction of phenolic acids from Lamiaceae herbs. The results were compared to those of achieved by the LCxLC system.

Effects of environmental variation on ecological and evolutionary dynamics

Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

Pre- and post-copulatory sexual selection in the least killifish, Heterandria formosa

It has been only recently realized that sexual selection does not end at copulation but that post-copulatory processes are often important in determining the fitness of individuals. In this thesis, I experimentally studied both pre- and post-copulatory sexual selection in the least killifish, Heterandria formosa. I found that this species suffers from severe inbreeding depression in male reproductive behaviour, offspring viability and offspring maturation times. Neither sex showed pre-copulatory inbreeding avoidance but when females mated with their brothers, less sperm were retrieved from their reproductive system compared to the situation when females mated with unrelated males. Whether the difference in sperm numbers is due to female or male effect could not be resolved. Based on theory, females should be more eager to avoid inbreeding than males in this species, because females invest more in their offspring than males do. Inbreeding seems to be an important part of this species biology and the severe inbreeding depression has most likely selected for the evolution of the post-copulatory inbreeding avoidance mechanism that I found. In addition, I studied the effects of polyandry on female reproductive success. When females mated with more than one male, they were more likely to get pregnant. However, I also found a cost of polyandry. The offspring of females mated to four males took longer to reach sexual maturity compared to the offspring of monandrous females. This cost may be explained by parent-offspring conflict over maternal resource allocation. In another experiment, in which within-brood relatedness was manipulated, offspring sizes decreased over time when within-brood relatedness was low. This result is partly in accordance with the kinship theory of genomic imprinting. When relatedness decreases, offspring are expected to be less co-operative and demand fewer resources from their mother, which leads to impaired development. In the last chapter of my thesis, I show that H. formosa males do not prefer large females as in other Poeciliidae species. I suggest that males view smaller females as more profitable mates because those are more likely virgin. In conclusion, I found both pre- and post-copulatory sexual selection to be important factors in determining reproductive success in H. formosa.

Human genetic variation in the Baltic Sea region: Features of population history and natural selection

In this thesis, the genetic variation of human populations from the Baltic Sea region was studied in order to elucidate population history as well as evolutionary adaptation in this region. The study provided novel understanding of how the complex population level processes of migration, genetic drift, and natural selection have shaped genetic variation in North European populations. Results from genome-wide, mitochondrial DNA and Y-chromosomal analyses suggested that the genetic background of the populations of the Baltic Sea region lies predominantly in Continental Europe, which is consistent with earlier studies and archaeological evidence. The late settlement of Fennoscandia after the Ice Age and the subsequent small population size have led to pronounced genetic drift, especially in Finland and Karelia but also in Sweden, evident especially in genome-wide and Y-chromosomal analyses. Consequently, these populations show striking genetic differentiation, as opposed to much more homogeneous pattern of variation in Central European populations. Additionally, the eastern side of the Baltic Sea was observed to have experienced eastern influence in the genome-wide data as well as in mitochondrial DNA and Y-chromosomal variation – consistent with linguistic connections. However, Slavic influence in the Baltic Sea populations appears minor on genetic level. While the genetic diversity of the Finnish population overall was low, genome-wide and Y-chromosomal results showed pronounced regional differences. The genetic distance between Western and Eastern Finland was larger than for many geographically distant population pairs, and provinces also showed genetic differences. This is probably mainly due to the late settlement of Eastern Finland and local isolation, although differences in ancestral migration waves may contribute to this, too. In contrast, mitochondrial DNA and Y-chromosomal analyses of the contemporary Swedish population revealed a much less pronounced population structure and a fusion of the traces of ancient admixture, genetic drift, and recent immigration. Genome-wide datasets also provide a resource for studying the adaptive evolution of human populations. This study revealed tens of loci with strong signs of recent positive selection in Northern Europe. These results provide interesting targets for future research on evolutionary adaptation, and may be important for understanding the background of disease-causing variants in human populations.

Kin selection, social polymorphism, and reproductive allocation in ants

Social groups are common across animal species. The reasons for grouping are straightforward when all individuals gain directly from cooperating. However, the situation becomes more complex when helping entails costs to the personal reproduction of individuals. Kin selection theory has offered a fruitful framework to explain such cooperation by stating that individuals may spread their genes not only through their own reproduction, but also by helping related individuals reproduce. However, kin selection theory also implicitly predicts conflicts when groups consist of non-clonal individuals, i.e. relatedness is less than one. Then, individual interests are not perfectly aligned, and each individual is predicted to favour the propagation of their own genome over others. Social insects provide a solid study system to study the interplay between cooperation and conflict. Breeding systems in social insects range from solitary breeding to eusocial colonies displaying complete division of reproduction between the fertile queen and the sterile worker caste. Within colonies, additional variation is provided by the presence of several reproductive individuals. In many species, the queen mates multiply, which causes the colony to consist of half-sib instead of full-sib offspring. Furthermore, in many species colonies contain multiple breeding queens, which further dilutes relatedness between colony members. Evolutionary biology is thus faced with the challenge to answer why such variation in social structure exists, and what the consequences are on the individual and population level. The main part of this thesis takes on this challenge by investing the dynamics of socially polymorphic ant colonies. The first four chapters investigate the causes and consequences of different social structures, using a combination of field studies, genetic analyses and laboratory experiments. The thesis ends with a theoretical chapter focusing on different social interactions (altruism and spite), and the evolution of harming traits. The main results of the thesis show that social polymorphism has the potential to affect the behaviour and traits of both individuals and colonies. For example, we found that genetic polymorphism may increase the phenotypic variation between individuals in colonies, and that socially polymorphic colonies may show different life history patterns. We also show that colony cohesion may be enhanced even in multiple-queen colonies through patterns of unequal reproduction between queens. However, the thesis also demonstrates that spatial and temporal variation between both populations and environments may affect individual and colony traits, to the degree that results obtained in one place or at one time may not be applicable in other situations. This opens up potential further areas of research to explain these differences.

The influence of eutrophication on sexual selection in sticklebacks

Jordens ekologiska system undergår för tillfället stora förändringar pga. människans aktiviteter. Ett växande antal studier visar att dessa förändringar påverkar naturliga och sexuella urvalet och därmed evolutiva processer. Målet med detta arbete var att undersöka effekterna av omgivningsförändringar på sexuella urvalet genom att använda den ökade övergödningen inom storpiggen Gasterosteus aculeatus lekområden som modell system. Sexuella urvalet är en viktig evolutiv kraft med följder på populations- och artnivå (Kapitel 1). Avhandlingens olika delar fokuserar på övergödningens effekter på upptäckandet av partners, användningen av visuella- och doftsignaler i partnersval, och fördelningen av parningsframgången mellan bobyggande hanar. I Kapitel II och III simuleras hur grumlighet orsakad av fytoplankton påverkar hastigheten med vilken potentiella partners påträffas, genom effekter på synligheten. Resultaten visar att normala algblomningar i Östersjön har en måttlig effekt på finnandet av potentiella partners. Detta tyder på att algblomningarna troligen inte kommer att minska på selektiva parningen pga. ökade sökkostnader. I Kapitel IV visas att storspiggen ändrar relativa användningen av olika signaler när vattnets grumlighet ökar; visuella signaler minskar i betydelse medan doftsignaler ökar i betydelse. Samtidigt underlättas användandet av doftsignaler av ändringar i vattnets kemiska sammansättning då fotosyntesen intensifieras (Kapitel V). Lek i övergödda vatten kan ändå vara kostsamt både på individ- och populationsnivån, då parasiterade hanar, som troligen är dåligt genetiskt anpassade till sin miljö, lyckas få mer ägg i sina bon än friskare hanar som troligen är av högre genetisk kvalitet (Kapitel VI). Övergödningen påverkar således partnersval och konkurrensen om partners genom att påverka upptäckandet av potentiella partners, evalueringen av partners och fördelningen av partners inom lekområdena. De följder detta kan ha för evolutionen av sexuellt selekterad egenskaper och för populationers dynamik och livskraft är dock oklara. Avhandlingen visar på svårigheten att förutse följderna av omgivningsförändringar för sexuella urvalet och effekterna på individ och populationsnivå.

Dynamic nature of proteins - interpretation of residual dipolar couplings

Protein conformations and dynamics can be studied by nuclear magnetic resonance spectroscopy using dilute liquid crystalline samples. This work clarifies the interpretation of residual dipolar coupling data yielded by the experiments. It was discovered that unfolded proteins without any additional structure beyond that of a mere polypeptide chain exhibit residual dipolar couplings. Also, it was found that molecular dynamics induce fluctuations in the molecular alignment and doing so affect residual dipolar couplings. The finding clarified the origins of low order parameter values observed earlier. The work required the development of new analytical and computational methods for the prediction of intrinsic residual dipolar coupling profiles for unfolded proteins. The presented characteristic chain model is able to reproduce the general trend of experimental residual dipolar couplings for denatured proteins. The details of experimental residual dipolar coupling profiles are beyond the analytical model, but improvements are proposed to achieve greater accuracy. A computational method for rapid prediction of unfolded protein residual dipolar couplings was also developed. Protein dynamics were shown to modulate the effective molecular alignment in a dilute liquid crystalline medium. The effects were investigated from experimental and molecular dynamics generated conformational ensembles of folded proteins. It was noted that dynamics induced alignment is significant especially for the interpretation of molecular dynamics in small, globular proteins. A method of correction was presented. Residual dipolar couplings offer an attractive possibility for the direct observation of protein conformational preferences and dynamics. The presented models and methods of analysis provide significant advances in the interpretation of residual dipolar coupling data from proteins.