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

The Impact of Emissions Trading on the Price of Electricity in Nord Pool : Market Power and Price Determination in the Nordic Electricity Market

The objective of this thesis is to find out how dominant firms in a liberalised electricity market will react when they face an increase in the level of costs due to emissions trading, and how this will effect the price of electricity. The Nordic electricity market is chosen as the setting in which to examine the question, since recent studies on the subject suggest that interaction between electricity markets and emissions trading is very much dependent on conditions specific to each market area. There is reason to believe that imperfect competition prevails in the Nordic market, thus the issue is approached through the theory of oligopolistic competition. The generation capacity available at the market, marginal cost of electricity production and seasonal levels of demand form the data based on which the dominant firms are modelled using the Cournot model of competition. The calculations are made for two levels of demand, high and low, and with several values of demand elasticity. The producers are first modelled under no carbon costs and then by adding the cost of carbon dioxide at 20€/t to those technologies subject to carbon regulation. In all cases the situation under perfect competition is determined as a comparison point for the results of the Cournot game. The results imply that the potential for market power does exist on the Nordic market, but the possibility for exercising market power depends on the demand level. In season of high demand the dominant firms may raise the price significantly above competitive levels, and the situation is aggravated when the cost of carbon dioixide is accounted for. Under low demand leves there is no difference between perfect and imperfect competition. The results are highly dependent on the price elasticity of demand.

Calm or storm? : Wind power actors perceptions of Finnish wind power and its future

Wind power has grown fast internationally. It can reduce the environmental impact of energy production and increase energy security. Finland has turbine industry but wind electricity production has been slow, and nationally set capacity targets have not been met. I explored social factors that have affected the slow development of wind power in Finland by studying the perceptions of Finnish national level wind power actors. By that I refer to people who affect the development of wind power sector, such as officials, politicians, and representatives of wind industries and various organisations. The material consisted of interviews, a questionnaire, and written sources. The perceptions of wind power, its future, and methods to promote it were divided. They were studied through discourse analysis, content analysis, and scenario construction. Definition struggles affect views of the significance and potential of wind power in Finland, and also affect investments in wind power and wind power policy choices. Views of the future were demonstrated through scenarios. The views included scenarios of fast growth, but in the most pessimistic views, wind power was not thought to be competitive without support measures even in 2025, and the wind power capacity was correspondingly low. In such a scenario, policy tool choices were expected to remain similar to ones in use at the time of the interviews. So far, the development in Finland has followed closely this pessimistic scenario. Despite the scepticism about wind electricity production, wind turbine industry was seen as a credible industry. For many wind power actors as well as for the Finnish wind power policy, the turbine industry is a significant motive to promote wind power. Domestic electricity production and the export turbine industry are linked in discourse through so-called home market argumentation. Finnish policy tools have included subsidies, research and development funding, and information policies. The criteria used to evaluate policy measures were both process-oriented and value-based. Feed-in tariffs and green certificates that are common elsewhere have not been taken to use in Finland. Some interviewees considered such tools unsuitable for free electricity markets and for the Finnish policy style, dictatorial, and being against western values. Other interviewees supported their use because of their effectiveness. The current Finnish policy tools are not sufficiently effective to increase wind power production significantly. Marginalisation of wind power in discourses, pessimistic views of the future, and the view that the small consumer demand for wind electricity represents the political views of citizens towards promoting wind power, make it more difficult to take stronger policy measures to use. Wind power has not yet significantly contributed to the ecological modernisation of the energy sector in Finland, but the situation may change as the need to reduce emissions from energy production continues.

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.

Towards a Dynamic Communication Model: A Useful Tool in Relationship Communication

In order to bring insight into the emerging concept of relationship communication, concepts from two research traditions will be combined in this paper. Based on those concepts a new model, the dynamic relationship communication model, will be presented. Instead of a company perspective focusing on the integration of outgoing messages such as advertising, public relations and sales activities, it is suggested that the focus should be on factors integrated by the receiver. Such factors can be historical, future, external and internal factors. Thus, the model put a strong focus on the receiver in the communication process. The dynamic communication model is illustrated empirically using it as a tool on 78 short stories about communication. The empirical findings show that relationship communication occurs in some cases; in some cases it does not occur. The model is a useful tool in displaying relationship communication and how it differs from other communication. The importance of the time dimension, historical and future factors, in relationship communications is discussed. The possibility of reducing communications costs by the notion of relationship communication is discussed in managerial implications.

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).

Analysis of forest soil chemistry and hydrology with a dynamic model ACIDIC.

In this study we analyze how the ion concentrations in forest soil solution are determined by hydrological and biogeochemical processes. A dynamic model ACIDIC was developed, including processes common to dynamic soil acidification models. The model treats up to eight interacting layers and simulates soil hydrology, transpiration, root water and nutrient uptake, cation exchange, dissolution and reactions of Al hydroxides in solution, and the formation of carbonic acid and its dissociation products. It includes also a possibility to a simultaneous use of preferential and matrix flow paths, enabling the throughfall water to enter the deeper soil layers in macropores without first reacting with the upper layers. Three different combinations of routing the throughfall water via macro- and micropores through the soil profile is presented. The large vertical gradient in the observed total charge was simulated succesfully. According to the simulations, gradient is mostly caused by differences in the intensity of water uptake, sulfate adsorption and organic anion retention at the various depths. The temporal variations in Ca and Mg concentrations were simulated fairly well in all soil layers. For H+, Al and K there were much more variation in the observed than in the simulated concentrations. Flow in macropores is a possible explanation for the apparent disequilibrium of the cation exchange for H+ and K, as the solution H+ and K concentrations have great vertical gradients in soil. The amount of exchangeable H+ increased in the O and E horizons and decreased in the Bs1 and Bs2 horizons, the net change in whole soil profile being a decrease. A large part of the decrease of the exchangeable H+ in the illuvial B horizon was caused by sulfate adsorption. The model produces soil water amounts and solution ion concentrations which are comparable to the measured values, and it can be used in both hydrological and chemical studies of soils.

A modell of socially optimal hydro reservoir usage - yelding socially optimal outcomes in nordic electricity markets

An extensive electricity transmission network facilitates electricity trading between Finland, Sweden, Norway and Denmark. Currently most of the area's power generation is traded at NordPool, where the trading volumes have steadily increased since the early 1990's, when the exchange was founded. The Nordic electricity is expected to follow the current trend and further integrate with the other European electricity markets. Hydro power is the source for roughly a half of the supply in the Nordic electricity market and most of the hydro is generated in Norway. The dominating role of hydro power distinguishes the Nordic electricity market from most of the other market places. Production of hydro power varies mainly due to hydro reservoirs and demand for electricity. Hydro reservoirs are affected by water inflows that differ each year. The hydro reservoirs explain remarkably the behaviour of the Nordic electricity markets. Therefore among others, Kauppi and Liski (2008) have developed a model that analyzes the behaviour of the markets using hydro reservoirs as explanatory factors. Their model includes, for example, welfare loss due to socially suboptimal hydro reservoir usage, socially optimal electricity price, hydro reservoir storage and thermal reservoir storage; that are referred as outcomes. However, the model does not explain the real market condition but rather an ideal situation. In the model the market is controlled by one agent, i.e. one agent controls all the power generation reserves; it is referred to as a socially optimal strategy. Article by Kauppi and Liski (2008) includes an assumption where an individual agent has a certain fraction of market power, e.g. 20 % or 30 %. In order to maintain the focus of this thesis, this part of their paper is omitted. The goal of this thesis is two-fold. Firstly we expand the results from the socially optimal strategy for years 2006-08, as the earlier study finishes in 2005. The second objective is to improve on the methods from the previous study. This thesis results several outcomes (SPOT-price and welfare loss, etc.) due to socially optimal actions. Welfare loss is interesting as it describes the inefficiency of the market. SPOT-price is an important output for the market participants as it often has an effect on end users' electricity bills. Another function is to modify and try to improve the model by means of using more accurate input data, e.g. by considering pollution trade rights effect on input data. After modifications to the model, new welfare losses are calculated and compared with the same results before the modifications. The hydro reservoir has the higher explanatory significance in the model followed by thermal power. In Nordic markets, thermal power reserves are mostly nuclear power and other thermal sources (coal, natural gas, oil, peat). It can be argued that hydro and thermal reservoirs determine electricity supply. Roughly speaking, the model takes into account electricity demand and supply, and several parameters related to them (water inflow, oil price, etc.), yielding finally the socially optimal outcomes. The author of this thesis is not aware of any similar model being tested before. There have been some other studies that are close to the Kauppi and Liski (2008) model, but those have a somewhat different focus. For example, a specific feature in the model is the focus on long-run capacity usage that differs from the previous studies on short-run market power. The closest study to the model is from California's wholesale electricity markets that, however, uses different methodology. Work is constructed as follows.