Evaluation of Pareto/D/1/k Queue by Simulation

The finding that Pareto distributions are adequate to model Internet packet interarrival times has motivated the proposal of methods to evaluate steady-state performance measures of Pareto/D/1/k queues. Some limited analytical derivation for queue models has been proposed in the literature, but their solutions are often of a great mathematical challenge. To overcome such limitations, simulation tools that can deal with general queueing system must be developed. Despite certain limitations, simulation algorithms provide a mechanism to obtain insight and good numerical approximation to parameters of queues. In this work, we give an overview of some of these methods and compare them with our simulation approach, which are suited to solve queues with Generalized-Pareto interarrival time distributions. The paper discusses the properties and use of the Pareto distribution. We propose a real time trace simulation model for estimating the steady-state probability showing the tail-raising effect, loss probability, delay of the Pareto/D/1/k queue and make a comparison with M/D/1/k. The background on Internet traffic will help to do the evaluation correctly. This model can be used to study the long- tailed queueing systems. We close the paper with some general comments and offer thoughts about future work

Employment Adjustment and Labor Utilization

Standard models that formalize and assess the impact of labor adjustment costs on labor demand suppose that firms can only change the size of their workforce (the extensive margin) and not the number of hours of their existing employees (the intensive margin). I relax this assumption and propose a dynamic general equilibrium model that introduces labor adjustment on both intensive and extensive margins. I calibrate the model to a matched employer-employee panel of Danish firms. I then simulate two labor market policies aimed at promoting job creation: an introduction of hiring subsidies and a reduction in the official workweek

Essays on wealth inequality and financial economics

This thesis consists of three chapters on the role of finance in influencing the distribution of wealth. In the first chapter, I study how improvements in entrepreneurial financing affect top wealth inequality. On the one hand, improved financing allows entrepreneurs to scale up, raising top inequality. Simultaneously, extreme wealth trajectories for entrepreneurs become less likely as better financing improves risk sharing, lowering top inequality. It turns out that which of these effects dominates depends on the amount of economic activity that is reallocated to entrepreneurs from elsewhere in the economy. Top wealth inequality rises provided that this reallocation is large enough. In the second chapter, co-authored with Andrew Atkeson, we derive an analytical link between the fast dynamics of measured wealth inequality at the top on the one hand, and the prevalence of newly created fortunes on the other. Specifically, in the context of a random growth model of wealth accumulation, the shape of the top of the wealth distribution changes rapidly only if the pace with which new fortunes are created is fast. In the final chapter, I study whether the rise in measured wealth inequality documented in the Distributional National Accounts (DINA) can be accounted for by the combination of changing asset prices on the one hand, and household heterogeneity in portfolio compositions on the other. In particular, I study the gap between the share of wealth held by individuals at the top of the wealth distribution, and those individuals’ share of the associated capital income flows. I find that the size of this gap varies substantially over time. However, the steady rise in top wealth shares since the late 1970s is not primarily accounted for by a rise in the size of this gap, but by rising concentration in the associated capital income flows

The Role of Agriculture and Human Capital in Economic Growth: Farmers, Schooling, and Health

This survey reviews the existing literature, identifying the contribution of agriculture, schooling, and nutrition to economic growth and development over time and across countries. Particular attention is paid to the roles of improvements in agricultural technology and of the human capital of farmers and farm people. Macroeconomic and microeconomic evidence related to the interactions between human capital, productivity and real income per capita have occurred over the past 250 years. We show that for most countries, development is a process of conversion from primarily agrarian economies to urban industrial and service economies. The evidence is that positive technology shocks to agriculture have played a key role in igniting a transition from traditional to modern agriculture and to long-term economic growth in almost all countries. Improvements in agricultural technologies improve labor productivity and create surplus agricultural labor that can provide workers for the growing urban areas. In some cases, improved nutrition helps raise labor productivity and allows individuals to work for longer hours, which makes human capital investments more attractive. The induced improvements in the skill level of a population have major implications for raising living standards, improving health standards, and altering time allocation decisions. In most currently poor and middle income countries, improved schooling has been more important than improved nutrition or caloric intake in explaining recent economic growth. Nevertheless, the poorest countries of the world continue to have a large share of their labor force in agriculture, and growth cannot occur until they experience their own agricultural transformation.

Optimal minimum wages

We develop a quantitative spatial model with heterogeneous firms and a monopsonistic labour market to derive minimum wages that maximize employment or welfare. Quantifying the model for German micro regions, we find that the German minimum wage, set at 48% of the national mean wage, has increased aggregate worker welfare by about 2.1% at the cost or reducing employment by about 0.3%. The welfare-maximizing federal minimum wage, at 60% of the national mean wage, would increase aggregate worker welfare by 4%, but reduce employment by 5.6%. An employment-maximizing regional wage, set at 50% of the regional mean wage, would achieve a similar aggregate welfare effect and increase employment by 1.1%

Improving Energy Efficiency through Data-Driven Modeling, Simulation and Optimization

In October 2014, the EU leaders agreed upon three key targets for the year 2030: a reduction by at least 40% in greenhouse gas emissions, savings of at least 27% for renewable energy, and improvements by at least 27% in energy efficiency. The increase in computational power combined with advanced modeling and simulation tools makes it possible to derive new technological solutions that can enhance the energy efficiency of systems and that can reduce the ecological footprint. This book compiles 10 novel research works from a Special Issue that was focused on data-driven approaches, machine learning, or artificial intelligence for the modeling, simulation, and optimization of energy systems

Essays in quantitative macroeconomics : income, inequality, income risk and optimal redistribution

Defence date: 5 November 2021; Examining Board: Prof. Árpád Ábrahám (University of Bristol and European University Institute); Prof. Philipp Kircher (Cornell University); Prof. Kjetil Storesletten (University of Oslo); Prof. Ludo Visschers (University of Edinburgh)The first PDF is the PhD Thesis. The second PDF is an addendum containing the complete citations of the two datasets.This thesis contains four independent essays in heterogeneous agent macroeconomics. They explore the sources of income inequality and income risk and study the optimal design of public redistribution and insurance. The first chapter, joint with Filip Rozsypal, studies the origins of idiosyncratic earnings risk in frictional labor markets, with a particular focus on the role of firms for worker earnings risk. First, using administrative matched employer-employee data from Denmark, we document key properties of the worker earnings growth distribution, the firm revenue growth distribution, and their joint distribution. The worker earnings and firm revenue growth distributions exhibit strong deviations from normality, in particular excess kurtosis, with many workers and firms experiencing very small changes to their earnings/revenues, but a significant minority experiencing very large changes. Large earnings losses are more likely for workers in firms with negative revenue growth, driven both by separations to unemployment and earnings losses on the job. Second, we develop a model framework consistent with the data, with four key features: i) frictional labor markets and on the job search to capture unemployment risk and wage growth through a job ladder, ii) multi-worker firms to capture gross and net worker flows, iii) risk averse workers such that earnings risk matters, and iv) contracting with two-sided limited commitment because earnings of job stayers are changing infrequently in the data. Third, we use the model to explore policies designed to mitigate earnings fluctuations. The second chapter, joint with Annika Bacher and Lukas Nord, studies one particular private insurance margin against individual income risk only available to couples, which is the so called added worker effect. Specifically, we study how this intra-household insurance against individual job loss through increased spousal labor market participation varies over the life cycle. We show in U.S. data that the added worker effect is much stronger for young than for old households. A stochastic life cycle model of two-member households with job search in a frictional labor market is capable of replicating this finding. The model suggests that a lower added worker effect for the old is driven primarily by better insurance through asset holdings. Human capital differences between employed young and old contribute to the difference but are quantitatively less important, while differences in job arrival rates play a limited role. In the third chapter, joint with Axelle Ferriere, Gaston Navarro, and Oliko Vardishvili, we study optimal redistribution, taking into account not just the large income and wealth inequality in the data, but also the distribution of income risk that is key in the first two chapters. The U.S. fiscal system redistributes through a rich set of taxes and transfers, the latter accounting for a large part of the income of the poor. Motivated by this, we study the optimal joint design of transfers and income taxes. Within a simple heterogeneous-household framework, we derive analytical results on the optimal relationship between transfers and tax progressivity. Higher transfers are associated with lower optimal income tax progressivity. Redistribution is achieved with generous transfers while efficiency is preserved via a lower progressivity of income taxes. As such, the optimal tax-and-transfer system features larger progressivity of average than of marginal tax rates. We then quantify the optimal tax-and-transfer system in a rich incomplete-market model with realistic distributions of income, wealth, and income risk. The model features a novel flexible functional form for progressive income taxes and means-tested transfers. Relative to the current U.S. fiscal system, the optimal policy consists of more generous means-tested transfers, which phase-out at a slower rate. These larger transfers are financed with higher tax rates, but the taxes are not more progressive than the current system. The fourth chapter, joint with Axelle Ferriere and Dominik Sachs, also studies optimal redistribution, but instead of considering a stationary environment it analyzes the dynamics of the equity-efficiency trade-off along the growth path. To do so, we incorporate the optimal income taxation problem into a state-of-the-art multi-sector structural change general equilibrium model with non-homothetic preferences. We identify two key opposing forces. First, long-run productivity growth allows households to shift their consumption expenditures away from necessities. This implies a reduction in the dispersion of marginal utilities, and therefore calls for a welfare state that declines along the growth path. Yet, economic growth is also systematically associated with an increase in the skill premium, which raises inequality and the desire to redistribute. We quantitatively analyze these opposing forces for two countries: the U.S. from 1950 to 2010, and China from 1989 to 2009. Optimal redistribution decreases at early stages of development, as the role of non-homotheticities prevails. At later stages of development the rising income inequality dominates and the welfare state should become more generous.1 Firm Dynamics and Earnings Risk 2 Joint Search over the Life Cycle 3 Larger Transfers Financed with More Progressive Taxes? On the Optimal Design of Taxes and Transfers 4 Redistribution in Growing Economie