Monetary policy rules and estimated reaction functions for the European Central Bank

This thesis studies the interest-rate policy of the ECB by estimating monetary policy rules using real-time data and central bank forecasts. The aim of the estimations is to try to characterize a decade of common monetary policy and to look at how different models perform at this task.The estimated rules include: contemporary Taylor rules, forward-looking Taylor rules, nonlinearrules and forecast-based rules. The nonlinear models allow for the possibility of zone-like preferences and an asymmetric response to key variables. The models therefore encompass the most popular sub-group of simple models used for policy analysis as well as the more unusual non-linear approach. In addition to the empirical work, this thesis also contains a more general discussion of monetary policy rules mostly from a New Keynesian perspective. This discussion includes an overview of some notable related studies, optimal policy, policy gradualism and several other related subjects. The regression estimations are performed with either least squares or the generalized method of moments depending on the requirements of the estimations. The estimations use data from both the Euro Area Real-Time Database and the central bank forecasts published in ECB Monthly Bulletins. These data sources represent some of the best data that is available for this kind of analysis. The main results of this thesis are that forward-looking behavior appears highly prevalent, but that standard forward-looking Taylor rules offer only ambivalent results with regard to inflation. Nonlinear models are shown to work, but on the other hand do not have a strong rationale over a simpler linear formulation. However, the forecasts appear to be highly useful in characterizing policy and may offer the most accurate depiction of a predominantly forward-looking central bank. In particular the inflation response appears much stronger while the output response becomes highly forward-looking as well.

Optimal Use of Treatment Modalities and Treatment Results of Osteosarcoma and Soft Tissue Sarcomas

Soft tissue sarcomas are malignant tumours of mesenchymal origin. Because of infiltrative growth pattern, simple enucleation of the tumour causes a high rate of local recurrence. Instead, these tumours should be resected with a rim of normal tissue around the tumour. Data on the adequate margin width are scarce. At Helsinki University Central Hospital (HUCH) a multidisciplinary treatment group started in 1987. Surgical resection with a wide margin (2.5 cm) is the primary aim. In case of narrower margin radiation therapy is necessary. The role of adjuvant chemotherapy remains unclear. Our aims were to study local control by the surgical margin and to develop a new prognostic tool to aid decision-making on which patients should receive adjuvant chemotherapy. Patients with soft tissue sarcoma of the extremity or the trunk wall referred to HUCH during 1987-2002 form material in Studies I and II. External validation material comes from the Lund university sarcoma registry. The smallest surgical margin of at least 2.5 centimetres yielded local control of 89 per cent at five years. Amputation rate was 9 per cent. The proposed prognostic model with necrosis, vascular invasion, size on a continuous scale, depth, location and grade worked well both in Helsinki material and in the validation material, and it also showed good calibration. Based on the present study, we recommend the smallest surgical margin of 2-3 centimetres in soft tissue sarcoma irrespective of grade. Improvement in local control was present but modest in margins wider than 1 centimetre. In cases where gaining a wider margin would lead to a considerable loss of function, smaller margin is to be considered combined to radiation therapy. Patients treated with inadequate margins should be offered radiation therapy irrespective of tumour grade. Our new prognostic model to estimate 10-year survival probability in patients with soft tissue sarcoma of the extremities or trunk wall showed good dicscrimination and calibration. For time being the prognostic model is available for scientific use and further validations. In the future, the model may aid in clinical decision-making. For operable osteosarcoma, neoadjuvant multidrug chemotherapy followed by delayed surgery and multidrug adjuvant chemotherapy is the treatment of choice. Overall survival rates at five years are approximately 75 per cent in modern trials with classical osteosarcoma. All patients diagnosed and reported to the Finnish Cancer Registry with osteosarcoma in Finland during 1971-2005 form the material in Studies III and IV. Limb-salvage rate increased from 23 per cent to 78 per cent during 1971-2005. The 10-year sarcoma-specific survival for the whole study population improved from 32 per cent to 62 per cent. It was 75 per cent for patients with a local high-grade osteosarcoma of the extremity diagnosed during 1991-2005. This study outlines the improved prognosis of osteosarcoma patients in Finland with modern chemotherapy. The 10-year survival rates are good also in an international scale. Nonetheless, their limb-salvage rate remains inferior to those seen for highly selected patient series. Overall, the centralisation of osteosarcoma treatment would most likely improve both survival and limb-salvage rates even further.

Nonnegative integral solution of linear equations

A method to obtain a nonnegative integral solution of a system of linear equations, if such a solution exists is given. The method writes linear equations as an integer programming problem and then solves the problem using a combination of artificial basis technique and a method of integer forms.

Existence Theorems for Generalized Hammerstein Equations

In this paper we obtain existence theorems for generalized Hammerstein-type equations K(u)Nu + u = 0, where for each u in the dual X* of a real reflexive Banach space X, K(u): X -- X* is a bounded linear map and N: X* - X is any map (possibly nonlinear). The method we adopt is totally different from the methods adopted so far in solving these equations. Our results in the reflexive spacegeneralize corresponding results of Petry and Schillings.

Optimal multispecies fishery management in the Baltic Sea: A bioeconomic analysis

The aim of the thesis is to assess the fishery of Baltic cod, herring and sprat by simulation over 50 years time period. We form a bioeconomic multispecies model for the species. We include species interactions into the model because especially cod and sprat stocks have significant effects on each other. We model the development of population dynamics, catches and profits of the fishery with current fishing mortalities, as well as with the optimal profit maximizing fishing mortalities. Thus, we see how the fishery would develop with current mortalities, and how the fishery should be developed in order to yield maximal profits. Especially cod stock has been quite low recently and by optimizing the fishing mortality it could get recovered. In addition, we assess what would happen to the fisheries of the species if more favourable environmental conditions for cod recruitment dominate in the Baltic Sea. The results may yield new information for the fisheries management. According to the results the fishery of Baltic cod, herring and sprat are not at the most profitable level. The fishing mortalities of each species should be lower in order to maximize the profits. By fishing mortality optimizing the net present value would be almost three times higher in the simulation period. The lower fishing mortality of cod would result in a cod stock recovery. If the environmental conditions in the Baltic Sea improved, cod stock would recover even without a decrease in the fishing mortality. Then the increased cod stock would restrict herring and sprat stock remarkably, and harvesting of these species would not be as profitable anymore.

Adaptive optimal load balancing in a nonhomogeneous multiserver system with a central job scheduler

A model comprising several servers, each equipped with its own queue and with possibly different service speeds, is considered. Each server receives a dedicated arrival stream of jobs; there is also a stream of generic jobs that arrive to a job scheduler and can be individually allocated to any of the servers. It is shown that if the arrival streams are all Poisson and all jobs have the same exponentially distributed service requirements, the probabilistic splitting of the generic stream that minimizes the average job response time is such that it balances the server idle times in a weighted least-squares sense, where the weighting coefficients are related to the service speeds of the servers. The corresponding result holds for nonexponentially distributed service times if the service speeds are all equal. This result is used to develop adaptive quasi-static algorithms for allocating jobs in the generic arrival stream when the load parameters are unknown. The algorithms utilize server idle-time measurements which are sent periodically to the central job scheduler. A model is developed for these measurements, and the result mentioned is used to cast the problem into one of finding a projection of the root of an affine function, when only noisy values of the function can be observed

Performance prediction and loss analysis of low specific speed submersible pumps

A performance prediction procedure is presented for low specific speed submersible pumps with a review of loss models given in the literature. Most of the loss theories discussed in this paper are one dimensional and improvements are made with good empiricism for the prediction to cover the entire range of operation of the low specific speed pumps. Loss correlations, particularly in the low flow range, are discussed. Prediction of the shape of efficiency-capacity and total head-capacity curves agrees well with the experimental results in almost the full range of operating conditions. The approach adopted in the present analysis, of estimating the losses in the individual components of a pump, provides means for improving the performance and identifying the problem areas in existing designs of the pumps. The investigation also provides a basis for selection of parameters for the optimal design of the pumps in which the maximum efficiency is an important design parameter. The scope for improvement in the prediction procedure with the nature of flow phenomena in the low flow region has been discussed in detail.

Optimal explicit guidance of multistage launch vehicle along three-dimensional trajectory

Details of an efficient optimal closed-loop guidance algorithm for a three-dimensional launch are presented with simulation results. Two types of orbital injections, with either true anomaly or argument of perigee being free at injection, are considered. The resulting steering-angle profile under the assumption of uniform gravity lies in a canted plane which transforms a three-dimensional problem into an equivalent two-dimensional one. Effects of thrust are estimated using a series in a recursive way. Encke's method is used to predict the trajectory during powered flight and then to compute the changes due to actual gravity using two gravity-related vectors. Guidance parameters are evaluated using the linear differential correction method. Optimality of the algorithm is tested against a standard ground-based trajectory optimization package. The performance of the algorithm is tested for accuracy, robustness, and efficiency for a sun-synchronous mission involving guidance for a multistage vehicle that requires large pitch and yaw maneuver. To demonstrate applicability of the algorithm to a range of missions, injection into a geostationary transfer orbit is also considered. The performance of the present algorithm is found to be much better than others.

Occurrence of maximum Tc at an optimal carrier concentration in superconducting bismuth and thallium cuprates

The superconducting transition temperatures in Bi2Ca1−xLnxSr2Cu2O8+δ, TlCa1−xLnxSr2Cu2O6+δ, and Tl0.8Ca1−xLnxBa2Cu23O6+δ (Ln=Y or rare earth) vary with composition and show a maximum at a specific value of x or δ. This observation suggests that an optimal carrier concentration is required to attain maximum Tc in such cuprates which seem to be two‐band systems

An optimal parallel algorithm for sparse matrix bandwidth reduction on a linear array

A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is proposed. It involves column-row permutations and is well-suited to map onto the linear array topology of the SIMD architectures. The efficiency of the algorithm is compared with the other existing algorithms. The interconnectivity and the memory requirement of the linear array are discussed and the complexity of its layout area is derived. The parallel version of the algorithm mapped onto the linear array is then introduced and is explained with the help of an example. The optimality of the parallel algorithm is proved by deriving the time complexities of the algorithm on a single processor and the linear array.

Estimating national contributions of greenhouse gas emissions :The CSE-WRI controversy

Analysts have identified four related questions that need to be asked and answered before agreements to respond to global warming will be possible.1 Which countries bear responsibility for causing the problem? What quantities and mix of greenhouse gases should each country be allowed to emit? Which countries have the resources to do something about the problem? Where are the best opportunities for undertaking projects to respond to the problem? Failure to distinguish among these four questions, or willingness to accept superficial answers, promotes unnecessary controversy.

A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm

The K-means algorithm for clustering is very much dependent on the initial seed values. We use a genetic algorithm to find a near-optimal partitioning of the given data set by selecting proper initial seed values in the K-means algorithm. Results obtained are very encouraging and in most of the cases, on data sets having well separated clusters, the proposed scheme reached a global minimum.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.