On the Economics and Politics of Mobility

Exit, Voice and Political Change: Evidence from Swedish Mass Migration to the United States. During the Age of Mass Migration, 30 million Europeans immigrated to the United States. We study the long-term political effects of this large-scale migration episode on origin communities using detailed historical data from Sweden. To instrument for emigration, we exploit severe local frost shocks that sparked an initial wave of emigration, interacted with within-country travel costs. Because Swedish emigration was highly path dependent, the initial shocks strongly predict total emigration over 50 years. Our estimates show that emigration substantially increased membership in local labor organizations, the strongest political opposition groups at the time. Furthermore, emigration caused greater strike participation, and mobilized voter turnout and support for left-wing parties in national elections. Emigration also had formal political effects, as measured by welfare expenditures and adoption of inclusive political institutions. Together, our findings indicate that large-scale emigration can achieve long-lasting effects on the political equilibrium in origin communities. Mass Migration and Technological Innovation at the Origin. This essay studies the effects of migration on technological innovations in origin communities. Using historical data from Sweden, we find that large-scale emigration caused a long-run increase in patent innovations in origin municipalities. Our IV estimate shows that a ten percent increase in emigration entails a 7 percent increase in a muncipality’s number of patents. Weighting patents by a measure of their economic value, the positive effects are further increased. Discussing possible mechanisms, we suggest that low skilled labor scarcity may be an explanation for these results.  Richer (and Holier) Than Thou? The Impact of Relative Income Improvements on Demand for Redistribution. We use a tailor-made survey on a Swedish sample to investigate how individuals' relative income affects their demand for redistribution. We first document that a majority misperceive their position in the income distribution and believe that they are poorer, relative to others, than they actually are. We then inform a subsample about their true relative income, and find that individuals who are richer than they initially thought demand less redistribution. This result is driven by individuals with prior right-of-center political preferences who view taxes as distortive and believe that effort, rather than luck, drives individual economic success. Wealth, home ownership and mobility. Rent controls on housing have long been thought to reduce labor mobility and allocative efficiency. We study a policy that allowed renters to purchase their rent-controlled apartments at below market prices, and examine the effects of home ownership and wealth on mobility. Treated individuals have a substantially higher likelihood of moving to a new home in a given year. The effect corresponds to a 30 percent increase from the control group mean. The size of the wealth shock predicts lower mobility, while the positive average effect can be explained by tenants switching from the previous rent-controlled system to market-priced condominiums. By contrast, we do not find that the increase in residential mobility leads to a greater probability of moving to a new place of work.

Assessing Non-market Benefits of Seagrass Restoration in the Gulf of Gdańsk

Seagrass meadows (Zostera marina) are an important ecosystem in the coastal environment of the Baltic Sea. This study employs a discrete choice experiment to value a set of non-market benefits provided by seagrass meadows in the Gulf of Gdańsk, Poland. The benefits valued in this study are a reduction of filamentous algae in the water and on the beach; access to seagrass meadows for boaters and divers; and improved water clarity. Results show significant willingness to pay for each attribute and differences of value estimates across different groups of survey respondents. It is discussed how to link choice attributes and estimated values with established ecosystem benefit categories in order to facilitate value transfer.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

Capacity forecasting for radio access networks

The mobile networks market (focus of this work) strategy is based on the consolidation of the installed structure and the optimization of the already existent resources. The increasingly competition and aggression of this market requires, to the mobile operators, a continuous maintenance and update of the networks in order to obtain the minimum number of fails and provide the best experience for its subscribers. In this context, this dissertation presents a study aiming to assist the mobile operators improving future network modifications. In overview, this dissertation compares several forecasting methods (mostly based on time series analysis) capable of support mobile operators with their network planning. Moreover, it presents several network indicators about the more common bottlenecks.

Cascade hydropower capacity increase profitability analysis with optimisation modelling

The electricity market and climate are both undergoing a change. The changes impact hydropower and provoke an interest for hydropower capacity increases. In this thesis a new methodology was developed utilising short-term hydropower optimisation and planning software for better capacity increase profitability analysis accuracy. In the methodology income increases are calculated in month long periods while varying average discharge and electricity price volatility. The monthly incomes are used for constructing year scenarios, and from different types of year scenarios a long-term profitability analysis can be made. Average price development is included utilising a multiplier. The method was applied on Oulujoki hydropower plants. It was found that the capacity additions that were analysed for Oulujoki were not profitable. However, the methodology was found versatile and useful. The result showed that short periods of peaking prices play major role in the profitability of capacity increases. Adding more discharge capacity to hydropower plants that initially bypassed water more often showed the best improvements both in income and power generation profile flexibility.

Modelagem univariada e regressão múltipla na análise da oferta e do preço do boi gordo no mercado brasileiro

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Agronomia e Medicina Veterinária, Programa de Pós-Graduação em Agronegócios, 2016.

Regulatory governance of ‘training markets’, ‘market failure’, and ‘quasi’ markets: historical dimensions of the post-initial training market in the Netherlands

This article examines regulatory governance of the post-initial training market in The Netherlands. From an historical perspective on policy formation processes, it examines market formation in terms of social, economic, and cultural factors in the development of provision and demand for post-initial training; the roles of stakeholders in the longterm construction of regulatory governance of the market; regulation of and public providers; policy responses to market failure; and tripartite division of responsibilities between the state, social partners, commercial and publicly-funded providers. Historical description and analysis examine policy narratives of key stakeholders with reference to: a) influence of societal stakeholders on regulatory decision-making; b) state regulation of the post-initial training market; c) public intervention regulating the market to prevent market failure; d) market deregulation, competition, employability and individual responsibility; and, e) regulatory governance to prevent ‘allocative failure’ by the market in non-delivery of post-initial training to specific target groups, particularly the low-qualified. Dominant policy narratives have resulted in limited state regulation of the supply-side, a tripartite system of regulatory governance by the state, social partners and commercial providers as regulatory actors. Current policy discourses address interventions on the demand-side to redistribute structures of opportunity throughout the life courses of individuals. Further empirical research from a comparative historical perspective is required to deepen contemporary understandings of regulatory governance of markets and the commodification of adult learning in knowledge societies and information economies. (DIPF/Orig.)

Active versus passive management : the case of BOVESPA

Mestrado em Finanças

Exchange market pressure and incidence of currency crises in Norway

Mestrado em Economia Monetária e Financeira

Time-of-use electricity tariffs with smart meters

This paper proposes a method for scheduling tariff time periods for electricity consumers. Europe will see a broader use of modern smart meters for electricity at residential consumers which must be used for enabling demand response. A heuristic-based method for tariff time period scheduling and pricing is proposed which considers different consumer groups with parameters studied a priori, taking advantage of demand response potential for each group and the fairness of electricity pricing for all consumers. This tool was applied to the case of Portugal, considering the actual network and generation costs, specific consumption profiles and overall electricity low voltage demand diagram. The proposed method achieves valid results. Its use will provide justification for the setting of tariff time periods by energy regulators, network operators and suppliers. It is also useful to estimate the consumer and electric sector benefits from changes in tariff time periods.

ELECTROCATALYTIC PROCESSING OF RENEWABLE BIOMASS-DERIVED COMPOUNDS FOR PRODUCTION OF CHEMICALS, FUELS AND ELECTRICITY

The dual problems of sustaining the fast growth of human society and preserving the environment for future generations urge us to shift our focus from exploiting fossil oils to researching and developing more affordable, reliable and clean energy sources. Human beings had a long history that depended on meeting our energy demands with plant biomass, and the modern biorefinery technologies realize the effective conversion of biomass to production of transportation fuels, bulk and fine chemicals so to alleviate our reliance on fossil fuel resources of declining supply. With the aim of replacing as much non-renewable carbon from fossil oils with renewable carbon from biomass as possible, innovative R&D activities must strive to enhance the current biorefinery process and secure our energy future. Much of my Ph.D. research effort is centered on the study of electrocatalytic conversion of biomass-derived compounds to produce value-added chemicals, biofuels and electrical energy on model electrocatalysts in AEM/PEM-based continuous flow electrolysis cell and fuel cell reactors. High electricity generation performance was obtained when glycerol or crude glycerol was employed as fuels in AEMFCs. The study on selective electrocatalytic oxidation of glycerol shows an electrode potential-regulated product distribution where tartronate and mesoxalate can be selectively produced with electrode potential switch. This finding then led to the development of AEMFCs with selective production of valuable tartronate or mesoxalate with high selectivity and yield and cogeneration of electricity. Reaction mechanisms of electrocatalytic oxidation of ethylene glycol and 1,2-propanediol were further elucidated by means of an on-line sample collection technique and DFT modeling. Besides electro-oxidation of biorenewable alcohols to chemicals and electricity, electrocatalytic reduction of keto acids (e.g. levulinic acid) was also studied for upgrading biomass-based feedstock to biofuels while achieving renewable electricity storage. Meanwhile, ORR that is often coupled in AEMFCs on the cathode was investigated on non-PGM electrocatalyst with comparable activity to commercial Pt/C. The electro-biorefinery process could be coupled with traditional biorefinery operation and will play a significant role in our energy and chemical landscape.

Analysis of Transmission System Adequacy Considering the Constrained Fuzzy Power Flow

Power flow calculations are one of the most important tools for power system planning and operation. The need to account for uncertainties when performing power flow studies led, among others methods, to the development of the fuzzy power flow (FPF). This kind of models is especially interesting when a scarcity of information exists, which is a common situation in liberalized power systems (where generation and commercialization of electricity are market activities). In this framework, the symmetric/constrained fuzzy power flow (SFPF/CFPF) was proposed in order to avoid some of the problems of the original FPF model. The SFPF/CFPF models are suitable to quantify the adequacy of transmission network to satisfy “reasonable demands for the transmission of electricity” as defined, for instance, in the European Directive 2009/72/EC. In this work it is illustrated how the SFPF/CFPF may be used to evaluate the impact on the adequacy of a transmission system originated by specific investments on new network elements

Increasing the value of household appliances by adding a heat pump system

Historically, domestic tasks such as preparing food and washing and drying clothes and dishes were done by hand. In a modern home many of these chores are taken care of by machines such as washing machines, dishwashers and tumble dryers. When the first such machines came on the market customers were happy that they worked at all! Today, the costs of electricity and customers’ environmental awareness are high, so features such as low electricity, water and detergent use strongly influence which household machine the customer will buy. One way to achieve lower electricity usage for the tumble dryer and the dishwasher is to add a heat pump system. The function of a heat pump system is to extract heat from a lower temperature source (heat source) and reject it to a higher temperature sink (heat sink) at a higher temperature level. Heat pump systems have been used for a long time in refrigerators and freezers, and that industry has driven the development of small, high quality, low price heat pump components. The low price of good quality heat pump components, along with an increased willingness to pay extra for lower electricity usage and environmental impact, make it possible to introduce heat pump systems in other household products. However, there is a high risk of failure with new features. A number of household manufacturers no longer exist because they introduced poorly implemented new features, which resulted in low quality and product performance. A manufacturer must predict whether the future value of a feature is high enough for the customer chain to pay for it. The challenge for the manufacturer is to develop and produce a high-performance heat pump feature in a household product with high quality, predict future willingness to pay for it, and launch it at the right moment in order to succeed. Tumble dryers with heat pump systems have been on the market since 2000. Paper I reports on the development of a transient simulation model of a commercial heat pump tumble dryer. The measured and simulated results were compared with good similarity. The influence of the size of the compressor and the condenser was investigated using the validated simulation model. The results from the simulation model show that increasing the cylinder volume of the compressor by 50% decreases the drying time by 14% without using more electricity.  Paper II is a concept study of adding a heat pump system to a dishwasher in order to decrease the total electricity usage. The dishwasher, dishware and water are heated by the condenser, and the evaporator absorbs the heat from a water tank. The majority of the heat transfer to the evaporator occurs when ice is generated in the water tank. An experimental setup and a transient simulation model of a heat pump dishwasher were developed. The simulation results show a 24% reduction in electricity use compared to a conventional dishwasher heated with an electric element. The simulation model was based on an experimental setup that was not optimised. During the study it became apparent that it is possible to decrease electricity usage even more with the next experimental setup.

The Commission, the Single Market and the Crisis: The Limits of Purposeful Opportunism

The economic and financial crisis opened a window of opportunity to place the Single Market back on top of the European agenda as part of a two-tiered crisis response, which also included reinforced financial supervision and economic co-ordination. We argue that the Commission acted as a ‘purposeful opportunist’ in both tiers; but whereas in economic governance issues there was breakthrough change in the Commission's achievements and competences, in the Single Market realm policy change was fairly modest. Using process tracing analysis our goal is to explain why the Commission did not succeed in furthering a genuine Single Market reform. Our findings suggest that the Commission's entrepreneurship was constrained by the limited salience of Single Market issues in the crisis context and by the lack of actual political commitment from the other relevant stakeholders. Thus, our research highlights the limits of the Commission's opportunistic behaviour in less advantageous circumstances.

Coordinated Scheduling of Wind-Thermal Gencos in Day-Ahead Markets

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modeled by variable costs, start-up costs and technical operating constraints, such as: ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, aiming to maximize the expected profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.