Can capital income tax improve welfare in an incomplete market economy with a labor-leisure decision?

This paper is a quantitative exercise in the economic analysis of optimal fiscal policy. We look at an incomplete market economy where agents face idiosyncratic labor productivity shocks and borrowing constraints. We find the steady state equilibrium of this economy and then analyze the effect of a government policy introducing a capital income tax and redistributing the proceeds of tax collection back to the agents in the form of a labor subsidy. We find that this type of policy can indeed improve the welfare of the economy, but its quantitative effect is small. We thus conclude that using capital income tax as fiscal policy instrument is not an effective way to cure the problem of market incompleteness.optimal fiscal policy, incomplete markets, precautionary saving

Natural and synthetic nanomaterials: from nacre to organic-inorganic hybrids

AbstractSedef je svjetlucavi sloj u unutrašnjosti nekih puževa i školjkaša, te je jedan od najbolje istraženih prirodnih nanomaterijala. Vedina volumena sedefa otpada na aragonit (95%), dok ostatak otpada na organske spojeve. Sedef je privukao pažnju znanstvenika zbog iznimne čvrstode, koja daleko nadilazi onu čistog aragonita. Uzrok tome je složena struktura koju čine aragonitne ploče i koje se slažu nasumično ili u stupce s organskim slojem kao vezivom između njih. Aragonitne ploče su poligonalne tvorevine kod kojih su nano-zrnca aragonita povezana na organski kostur od hitina. Osim složene strukture po principu cigle (aragonitne ploče) i žbuke (organski sloj), postoje i tzv. nano-mostovi između ploča kroz organski sloj koji uz hrapavost površine aragonitnih ploča pomažu pri raspršenju energije udarca i pridonose čvrstodi strukture. Modifikacijom poznatih materijala sintetiziran je niz materijala strukturno sličnih sedefu čija mehanička svojstva su vidno poboljšana u odnosu na polazne supstance. U posljednje vrijeme kemija nanomaterijala je sve više usmjerena na sintezu organsko-anorganskih hibridnih materijala u ravnotežnim i neravnotežnim uvjetima. Nastali nanomaterijali su izrazito složeni i mogli bi nadi svoju primjenu u elektronici, kao kapsule za lijekove, senzori, katalizatori i sl. Tri su osnovne tehnike sinteze organsko-anorganskih hibridnih materijala (i) Integrativno samoudruživanje (Integrative self-assembly), (ii) Složeno ravnotežno samoudruživanje (higher-order equilibrium self-assembly) i (iii) Samoudruživanje pradeno transformacijom (transformative self-assembly)

Disrupting technologies:can the planetary technosphere be steered politically toward a post-capitalist metabolism?

The dominant approach in (trans/sub)national governance of ecological crises, mostnotably climate change, is ecological modernisation. As a framing of collectiveaction, ecological modernisation assumes that the structure of economic growth canbe made sustainable by deploying market instruments to drive the sociotechnicaltransition away from the present fossil-fueled technological base. However, scientistsare warning that such a market-driven technology-frst approach, ensconced inthe UNFCCC since at least the Kyoto Protocol, might not be comprehensive andrapid enough to prevent global warming beyond 2°C above the pre-industrial levelsand thus a signifcant breakdown of ecosystems, rendering vulnerable indigenous,low-income, and working-class communities across the world.This thesis analyses how organisations that are operating in the “middle ground,”between the policymaking arena and their social constituencies, are seeking todisrupt the hegemony of technology-frst policies, while at the same time proposingalternative pathways to transition away from the extractivist and capitalist socialmetabolism to a plurality of environmentally livable and socially just futures for all.Taking an iterative theory-building approach, the thesis frst conceptualises thestrategic agency of these social actors: against the historical trajectory of industrialcapitalist social metabolism; within the power-diferentiated social structures of thecapitalist state; and through the framing and distributive struggles sited betweenthe climate action arena and the social feld. By drawing on a set of complementarytheories — ecological Marxism, environmental humanities, science and technology studies, the critical theory of technology, strategic-relational approach, andinstitutional logics theory — it proposes two analytical frameworks to indicatestrategic openings for “middle-ground” organisations to impact sociotechnical andsociometabolic transitions.In a second step, the thesis provides two case studies contrasting two organisations and two environmentalisms: a degrowth-oriented Institute for Political Ecology,hailing from the periphery of European capitalism; and a green new deal-orientedindustrial trade union Unite the Union, hailing from one of the centres of Europeancapitalism. Drawing on interviews, analysis of documents, and joint research withthe two organisations, it argues that they engage the governance terrain as epistemicactors and work with diferent social constituencies to instil distributive justice into climate action. These actors are disrupting the dominant market-driven technologyfrst approach and are thereby re-politicising and re-democratising the environmentalgovernance. In a fnal step, the thesis analyses and speculates on the prospects oftheir counter-proposals in the present political and environmental conjuncture.<br/

Can Capital Income Tax Improve Welfare in an Incomplete Market Economy with a Labor-Leisure Decision?

This paper is a quantitative exercise in the economic analysis of optimal fiscal policy. We look at an incomplete market economy where agents face idiosyncratic labor productivity shocks and borrowing constraints. We find the steady state equilibrium of this economy and then analyze the effect of a government policy introducing a capital income tax and redistributing the proceeds of tax collection back to the agents in the form of a labor subsidy. We find that this type of policy can indeed improve the welfare of the economy, but its quantitative effect is small. We thus conclude that using capital income tax as fiscal policy instrument is not an effective way to cure the problem of market incompleteness

Hierarchical testing using the power-divergence family of statistics

Methodology for discrete multivariate data based on the loglikelihood ratio statistic G[superscript]2, and Pearson\u27s statistic X[superscript]2 is extended to the power-divergence family of goodness-of-fit statistics (Cressie and Read, 1984), which is indexed by the parameter [lambda] (-[infinity] \u3c [lambda] \u3c [infinity]). This family includes G[superscript]2, X[superscript]2, the Freeman-Tukey statistic, the modified loglikelihood ratio statistic, and the Neyman-modified chi-squared statistic;Ideas employed by Watson and Nguyen (1985) and Watson (1987) to plot confidence regions in a ternary diagram, based on Pearson\u27s X[superscript]2, are extended to the power-divergence family. This results in confidence regions of diverse shapes and sizes. Also, a comparison based on the accuracy of confidence level and the area of confidence region finds the family members [lambda] = 2/3 and [lambda] = 1/2 to be the best performers;Maximum likelihood methods (e.g., Bishop, Fienberg, and Holland, 1975, Chapters 4 and 14) for testing hierarchical parametric models are extended to the power-divergence family. It is shown that, under Birch\u27s conditions (Birch, 1964), an analysis of divergence is possible with the power-divergence family, analogous to the usual partitioning of G[superscript]2 given, e.g., in Fienberg (1980, pp. 58-59). Further, an algorithm similar to iterative proportional fitting, for finding cell probability estimates, is given. To illustrate these ideas loglinear models are fit to several data sets and analyses of divergence are carried out;Methodology for hierarchically assessing homogeneity in product-multinomial distributions, based on the power-divergence statistics, is developed. It is shown that, under mild assumptions, an analysis of divergence for the power-divergence statistics is possible. To demonstrate this methodology, a data set is considered and an analysis of divergence is performed

A Case for Government Enforcement: A Game Theory Analysis

This paper seeks to address the risks of extending credit to those without collateral through a game theory analysis. There is relatively low risk when lending to someone with collateral, such as a house or a car, however a potential borrower without collateral is seen as a much larger risk. The three major issues of lending: Moral Hazard, Adverse Selection and Enforcement are seen as the three main obstacles that must be overcome and addressed for credit to be available to those without collateral. As will be displayed throughout this paper, there are not three issues that must be addressed, but rather, one. The single issue of extending credit to the collateral-less is enforcement. By addressing the issue of enforcement, both moral hazard as well as adverse selection are addressed. The rationale behind this is that when there is full enforcement capability by the lender (Guaranteed Repayment), the issue of moral hazard is addressed and the issue of asymmetric information becomes relatively insignificant. Moral hazard is addressed in two ways: First, the borrower understands that they will be forced to repay the loan which creates incentives for the borrowers to abstain from utilizing credit for endeavors that previously they would have been limited in liability for. A good example of this is student loans; students don’t take out loans with the assumption that they can default and file for bankruptcy to remedy their debts because under U.S. law they are unable to do so. Secondly, the lenders are aware of the game facing the borrowers, and therefore they can assume that any borrower attempting to utilize credit is risky due to moral hazard, which increases the borrowers’ ability to extend credit. Adverse selection and asymmetric information become relatively unimportant because there cannot be negative implications from asymmetric information if there is full enforcement capability. This holds true in two ways: First off, if someone has asymmetric information that makes likely to default on their loan, it makes no difference because they will still be forced to repay. Secondly, if they have asymmetric information which makes their payoffs higher than the lender is aware of, it is not valuable to keep this as asymmetric information because it benefits both the lender and the borrower, and therefore the potential borrower would make that information known to the lender. When comparing a government backed lending entity versus a private lending entity, as well as in comparing a corrupt government backed entity to a non-corrupt government backed entity utilizing a potential borrower without collateral, game theory allows us to draw conclusions on solutions to social dilemmas within lending. All games were three-player, multi-strategy games with expected payoffs represented in the present value of the long term. Nature was brought into each game to represent the uncertainty that is associated with all credit transactions. The four games solutions supported the hypothesis of enforcement being the singular issue when analyzing whether to or not to extend credit to a collateral-less borrower. When investigating the effects of corruption, expected payoff functions were utilized to assess the incentives to seek rents by government backed entities in comparison to a private entity. Additionally, assessing the ability of the borrower to identify rent-seeking in the market for credit was assessed to see the costs and benefits of a private entity relative to a government backed entity. After concluding these studies, it became apparent that enforcement was the key issue to collateral-less borrowing, but also, that there would be less corruption with a government backed entity than a private entity, due to the relative expected payoffs of corrupt behavior

Ocjena točnosti različitih metoda strojnog učenja na satelitskim snimkama RapidEye i PlanetScope

Since the first satellite imagery of RapidEye and PlanetScope became available, numerous studies have been conducted. However, only a few authors have focused on evaluating the accuracy of more than two machine learning methods in land cover classification. This paper evaluates the accuracy of four different machine learning methods, namely: support vector machine, artificial neural network, naive Bayes, and random forest. All analysis was conducted on cities in Croatia, Varaždin and Osijek. On Varaždin area on RapidEye satellite imagery support vector machine achieved overall kappa value 0.80, artificial neural network 0.37, naive Bayes 0.84 and random forest 0.76. On Varaždin area on PlanetScope satellite imagery support vector machine achieved overall kappa value 0.77, artificial neural network 0.38, naive Bayes 0.76 and random forest 0.75. On Osijek area on RapidEye satellite imagery support vector machine achieved overall kappa value 0.75, artificial neural network 0.36, naive Bayes 0.85 and random forest 0.76. On Osijek area on PlanetScope satellite imagery support vector machine achieved overall kappa value 0.64, artificial neural network 0.23, naive Bayes 0.72 and random forest 0.63. Performance time of each method is also evaluated. Naive Bayes and random forest have best performance time in every scenario.Otkako su prve satelitske snimke senzora RapidEye i PlanetScope postale dostupne, na njima su provedena brojna istraživanja. Međutim, samo se nekoliko autora usredotočilo na ocjenu točnosti više od dvije metode strojnog učenja pri klasifikaciji pokrova zemljišta. U ovom radu daje se ocjena točnosti četiri različite metode strojnog učenja: metode potpornih vektora, metode umjetnih neuronskih mreža, metode naivni Bayes i metode slučajnog šuma. Sve su analize provedene na gradovima u Hrvatskoj: Varaždinu i Osijeku. Na satelitskom snimku senzora RapidEye, za područje Varaždina, metoda potpornih vektora postigla je ukupnu kappa vrijednost 0,80, metoda umjetnih neuronskih mreža 0,37, metoda naivni Bayes 0,84 i metoda slučajnog šuma 0,76. Na satelitskom snimku senzora PlanetScope, za područje Varaždina, metoda potpornih vektora postigla je ukupnu kappa vrijednost 0,77, metoda umjetnih neuronskih mreža 0,38, metoda naivni Bayes 0,76 i metoda slučajnog šuma 0,75. Na satelitskom snimku senzora RapidEye, za područje Osijeka, metoda potpornih vektora postigla je ukupnu kappa vrijednost 0,75, metoda umjetnih neuronskih mreža 0,36, metoda naivni Bayes 0,85 i metoda slučajnog šuma 0,76. Na satelitskom snimku senzora PlanetScope, za područje Osijeka, metoda potpornih vektora postigla je ukupnu kappa vrijednost 0,64, metoda umjetnih neuronskih mreža 0,23, metoda naivni Bayes 0,72 i metoda slučajnog šuma 0,63. U radu se također mjeri i vrijeme izvedbe svake metode. Metoda naivni Bayes i metoda slučajnog šuma imaju najbolje vrijeme izvedbe u svim slučajevima

Effects of COVID-19 on doctors burnout

The impact of COVID-19 on the mental health of doctors who come into contact with suspects or sick people is being studied worldwide. Appropriate questionnaires sent by e-mail to the surveyed groups are used for this. The most common respondents are anaesthesiologists working at the ICU and HED. Women experience stress and anxiety more often than men. Physicians' mental health is affected by their age, workplace and access to personal protective equipment. A review of the literature shows the negative impact of the growing number of SARS-CoV-2 cases on the level of stress, anxiety and satisfaction with the work of doctors