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.

Informational efficiency of the European Union emission allowance market

This thesis studies the informational efficiency of the European Union emission allowance (EUA) market. In an efficient market, the market price is unpredictable and profits above average are impossible in the long run. The main research problem is does the EUA price follow a random walk. The method is an econometric analysis of the price series, which includes an autocorrelation coefficient test and a variance ratio test. The results reveal that the price series is autocorrelated and therefore a nonrandom walk. In order to find out the extent of predictability, the price series is modelled with an autoregressive model. The conclusion is that the EUA price is autocorrelated only to a small degree and that the predictability cannot be used to make extra profits. The EUA market is therefore considered informationally efficient, although the price series does not fulfill the requirements of a random walk. A market review supports the conclusion, but it is clear that the maturing of the market is still in process.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Studies on Wage Differentials and Labour Market Transitions

This thesis consists of four studies. The first study examines wage differentials between women and men in the Finnish manufacturing sector. A matched employer-employee data set is used to decompose the overall gender wage gap into the contributions of sex differences in human capital, labour market segregation, and residual within-job wage differentials. The topic of the second study is the relationship between the extended unemployment benefits and labour market transitions of older workers. The analysis exploits a quasi-experimental setting caused by a change in the law that raised the eligibility age of workers benefiting from extended benefits. Roughly half of the unemployed workers with extended benefits are estimated to be effectively withdrawn from labour market search. The risk of unemployment declined and the re-employment probability increased among the age groups directly affected by the reform. The third study provides an empirical analysis of a structural equilibrium search model. Estimation results from various model specifications are compared and discussed. The last study is a methodological study where the difficulties of interpreting the results of competing risks hazard models are discussed and a solution for a particular class of models is proposed. It is argued that a common practice of reporting the results of qualitative response models in terms of marginal effects is also useful in the context of competing risks duration models.

Essays on Labor Market Frictions, Technological Change and Macroeconomic Fluctuations

The dissertation consists of an introductory chapter and three essays that apply search-matching theory to study the interaction of labor market frictions, technological change and macroeconomic fluctuations. The first essay studies the impact of capital-embodied growth on equilibrium unemployment by extending a vintage capital/search model to incorporate vintage human capital. In addition to the capital obsolescence (or creative destruction) effect that tends to raise unemployment, vintage human capital introduces a skill obsolescence effect of faster growth that has the opposite sign. Faster skill obsolescence reduces the value of unemployment, hence wages and leads to more job creation and less job destruction, unambiguously reducing unemployment. The second essay studies the effect of skill biased technological change on skill mismatch and the allocation of workers and firms in the labor market. By allowing workers to invest in education, we extend a matching model with two-sided heterogeneity to incorporate an endogenous distribution of high and low skill workers. We consider various possibilities for the cost of acquiring skills and show that while unemployment increases in most scenarios, the effect on the distribution of vacancy and worker types varies according to the structure of skill costs. When the model is extended to incorporate endogenous labor market participation, we show that the unemployment rate becomes less informative of the state of the labor market as the participation margin absorbs employment effects. The third essay studies the effects of labor taxes on equilibrium labor market outcomes and macroeconomic dynamics in a New Keynesian model with matching frictions. Three policy instruments are considered: a marginal tax and a tax subsidy to produce tax progression schemes, and a replacement ratio to account for variability in outside options. In equilibrium, the marginal tax rate and replacement ratio dampen economic activity whereas tax subsidies boost the economy. The marginal tax rate and replacement ratio amplify shock responses whereas employment subsidies weaken them. The tax instruments affect the degree to which the wage absorbs shocks. We show that increasing tax progression when taxation is initially progressive is harmful for steady state employment and output, and amplifies the sensitivity of macroeconomic variables to shocks. When taxation is initially proportional, increasing progression is beneficial for output and employment and dampens shock responses.

Tibetan Market Participation in China

Since the Chinese government began implementing economic reforms in the late 1970s, China has experienced profound economic change and growth. Like other parts of China, Tibetan areas of China have also experienced wide-ranging economic change with growth even higher than the China-wide average in certain years. Though China s strategic policy of developing the West provided many opportunities for economic and business activities, Tibetans have proven poorly equipped to respond to and take advantage of these opportunities. This study is about people, about market participation and specifically about why Tibetans do not effectively participate in the market in the context of China s economic development process. Many political, social, cultural and environmental factors explain the difficulties met by Tibetan communities. However, this study focuses on three factors: the social and culture context, government policy and education. The Buddhistic nature of Tibetan communities, particularly the political and economic system in traditional Tibetan society, explains this, especially after implementation of new national economic policies. An inclusive economic development policy that promotes local people s participation in the market demands serious consideration of local conditions. Unfortunately, such considerations often ignore local Tibetan realities. The economic development policy in Tibetan areas in China is nearly always an attempt to replicate the inland model and open up markets, even though economic and sociopolitical conditions in Tibet are markedly unlike much of China. A consequence of these policies is increasing numbers of non-Tibetan migrants flowing into Tibetan areas with the ensuing marginalization of Tibetans in the marketplace. Poor quality education is another factor contributing to Tibetan inability to effectively participate in the market. Vocational and business education targeting Tibetans is of very low quality and reflective of government failing to consider local circumstances when implementing education policy. The relatively few Tibetans who do receive education are nearly always unable to compete with non-Tibetan migrants in commercial activity. Encouraging and promoting Tibetan participation in business development and access to quality education are crucial for a sustainable and prosperous society in the long term. Particularly, a localized development policy that considers local environmental conditions and production as well as local culture is crucial. Tibet s economic development should be based on local environmental and production conditions, while utilizing Tibetan culture for the benefit of creating a sustainable economy. Such a localized approach best promotes Tibetan market participation. Keywords: Tibet cultural policy education market participation

Residential Differentiation, Housing Policy and Urban Planning in the Transformation from State Socialism to a Market Economy: The Case of Tallinn

The thesis examines urban issues arising from the transformation from state socialism to a market economy. The main topics are residential differentiation, i.e., uneven spatial distribution of social groups across urban residential areas, and the effects of housing policy and town planning on urban development. The case study is development in Tallinn, the capital city of Estonia, in the context of development of Central and Eastern European cities under and after socialism. The main body of the thesis consists of four separately published refereed articles. The research question that brings the articles together is how the residential (socio-spatial) pattern of cities developed during the state socialist period and how and why that pattern has changed since the transformation to a market economy began. The first article reviews the literature on residential differentiation in Budapest, Prague, Tallinn and Warsaw under state socialism from the viewpoint of the role of housing policy in the processes of residential differentiation at various stages of the socialist era. The paper shows how the socialist housing provision system produced socio-occupational residential differentiation directly and indirectly and it describes how the residential patterns of these cities developed. The second article is critical of oversimplified accounts of rapid reorganisation of the overall socio-spatial pattern of post-socialist cities and of claims that residential mobility has had a straightforward role in it. The Tallinn case study, consisting of an analysis of the distribution of socio-economic groups across eight city districts and over four housing types in 1999 as well as examining the role of residential mobility in differentiation during the 1990s, provides contrasting evidence. The third article analyses the role and effects of housing policies in Tallinn s residential differentiation. The focus is on contemporary post-privatisation housing-policy measures and their effects. The article shows that the Estonian housing policies do not even aim to reduce, prevent or slow down the harmful effects of the considerable income disparities that are manifest in housing inequality and residential differentiation. The fourth article examines the development of Tallinn s urban planning system 1991-2004 from the viewpoint of what means it has provided the city with to intervene in urban development and how the city has used these tools. The paper finds that despite some recent progress in planning, its role in guiding where and how the city actually developed has so far been limited. Tallinn s urban development is rather initiated and driven by private agents seeking profit from their investment in land. The thesis includes original empirical research in the three articles that analyse development since socialism. The second article employs quantitative data and methods, primarily index calculation, whereas the third and the fourth ones draw from a survey of policy documents combined with interviews with key informants. Keywords: residential differentiation, housing policy, urban planning, post-socialist transformation, Estonia, Tallinn

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.

Monetary Policy Implementation in the Interbank Market

The liquidity crisis that swept through the financial markets in 2007 triggered multi-billion losses and forced buyouts of some large banks. The resulting credit crunch is sometimes compared to the great recession in the early twentieth century. But the crisis also serves as a reminder of the significance of the interbank market and of proper central bank policy in this market. This thesis deals with implementation of monetary policy in the interbank market and examines how central bank tools affect commercial banks' decisions. I answer the following questions: • What is the relationship between the policy setup and interbank interest rate volatility? (averaging reserve requirement reduces the volatility) • What can explain a weak relationship between market liquidity and the interest rate? (high reserve requirement buffer) • What determines banks' decisions on when to satisfy the reserve requirement? (market frictions) • How did the liquidity crisis that began in 2007 affect interbank market behaviour? (resulted in higher credit risk and trading frictions as well as expected liquidity shortage)