The politics of rent control are straightforward. First, rent control involves a money transfer from landlords to tenants, because tenants pay less than they would absent the law, and landlords obtain less revenue. In the short run, due to the inelastic short-run supply, the effect on the quantity of apartments is small, so rent control is primarily just a transfer from landlords to tenants. In a city like New York, the majority of people rent. A tiny fraction of New Yorkers are landlords. Thus, it is easy to attract voters to support candidates who favor rent control—most renters will benefit, while landlords don’t. The numbers, of course, don’t tell the whole story because, while landlords are small in number, they are wealthier on average, and thus likely have political influence beyond the number of votes they cast. However, even with their larger economic influence, the political balance favors renters. In the
The quality-of-life of all patients was estimated at base- line and at 6 months following the introduction of the self-testing intervention. Average quality-of-life scores for the five individual psychological topics, at baseline and 6 months, as well as the minimum and maximum average scores identified, are presented in Table 2 below. A varying number of patients completed all questions for each of the psychological topics, and this variation is also shown. The number of patients who completed the questionnaire at baseline was greater than the number who completed the questionnaire at 6 months, primarily because many patients had not yet reached 6 months self-testing upon completion of the evaluation. Add- itional numbers may then have been missing at each time point for each of the psychological topics due to failure to complete specific questions on each of the topics. The statistical significance of any differences in mean scores was tested using the paired samples t-test, with the null hypothesis being that the difference be- tween mean scores is zero. The null hypothesis could be rejected where the associated p-value was less than 0.05, indicating a statistically significant difference in scores. Results of the t-test were based on the total number of patients who answered all questions related to each psy- chological topic at the two time points.
Results: Ten relevant studies were identified. Six were cost-effectiveness analyses utilizing HSUVs for calculation of QALYs, one was an effectiveness analysis (incremental QALY), and two were QoL studies reporting AML-specific utilities. An additional study reported QoL for patients undergoing stem cell transplantation (SCT). Since no study reported HSUVs for relapse, values from a study of secondary AML patients who failed prior treatment for myelodysplastic syndrome were used. Where multiple HSUVs were available, collected values were given priority over assumed values. AML treatment (induction, consolidation, or SCT) was associated with decreased HSUV, while post-treatment complete remission led to increased HSUV.
Finally, let us assume that: a) groups A, C and E require on average 100 days to produce, i.e. to transform, their products; b) groups B, D and F keep them for 25 days on average, i.e. they keep on average stocks 25 times greater than a day’s total purchases; c) the country considered ) is in stationary economic conditions; d) as a result: ) the flow of new savings is zero; the plant used by A, C and F is sufficient for current production of the respective goods; ) the production of machinery by group A is limited solely to the amount needed to replace any worn-out machinery either in group A or in groups C and F. The complete production cycle, from production start-up as raw materials to their sale as final consumers, lasts 375 days (100 + 25 + 100 + 25 + 100 + 25). In 100 days group A produces machines and other instrumental goods of a higher order equivalent to 1.1 billion Schillings and borrow about 1 billion schillings from the banks, the 10% difference being their profits. Group A uses this amount mainly to pay wages, interest, rents and so on. During the 100-day period group B buys machinery and other instrumental goods of a higher order worth about 1.1 billion from A. However, since only stocks equivalent to 25 times the quantity of the daily purchases are held, group B needs bank loans equal to a quarter of the turnover figure for the 100-day period, i.e. an amount equivalent to 275 million Schillings. Group B will then produce sales equal to about 1.21 billion, with 1 billion coming from the semi-finished goods sold to C and 210 millions from the machines sold to E, plus 10% profit. In 100 days group C produces semi-finished goods worth 3.3 billion at a cost of 3 billion which is made up of 1 billion-worth of machinery and raw materials and 2 billions-worth of wages, interest, rents and so on 21 . Group D buys 3.3 billions of semi-finished goods from C but, like group B, needs bank
Because of some expert advice that you once offered your Aunt Daphne (and because you have a strong background in economics), you have been hired as the economic consultant to her oil change business. She consults you frequently for your advice on changing prices as well as what to expect regarding the number of customers that are likely to patronize her business.
The gender inequality and the poverty are closely related. In my opinion both poverty and gender inequality are correlated, as poverty exacerbates the gender inequality while the gender inequality exacerbates the poverty. In other words poverty worsens the gender inequality and vice versa. As gender inequality causes lack of access to productive resources and employment opportunities for women, so it causes poverty. On the other hand, the poor families have a lack of the economic resources. Accordingly the women and girls remain deprived from the education, better food & clothing and even low self–esteem in these families. As a result, poverty results in the gender inequality.
Perhaps the most illustrious exponent of textual analysis is the self-styled “literary detective” Donald Foster, whose 2001 book  describes how he identified the authors of several anonymous works, including the best-selling roman-à-clef Primary Colors , which satirized the 1992 Clinton presidential campaign. Foster’s methodology examines a broad spectrum of text characteristics, including word choice, punctuation, grammatical structure, and the like. The aim of the exercise in this article is to emulate Foster, though naturally the literary aspects of the approach taken are much more basic~the intent is not to describe a realistic method of textual analysis, but rather to use it to illustrate corre- spondence analysis.
Nansen Bottles (figure 6.16) were deployed from ships stopped at hydro- graphic stations. Hydrographic stations are places where oceanographers mea- sure water properties from the surface to some depth, or to the bottom, using instruments lowered from a ship. Usually 20 bottles were attached at intervals of a few tens to hundreds of meters to a wire lowered over the side of the ship. The distribution with depth was selected so that most bottles are in the upper layers of the water column where the rate of change of temperature in the ver- tical is greatest. A protected reversing thermometer for measuring temperature was attached to each bottle along with an unprotected reversing thermometer for measuring depth. The bottle contains a tube with valves on each end to collect sea water at depth. Salinity was determined by laboratory analysis of water sample collected at depth.
We will now look at the free citation software package Publish or Perish which draws its raw data from Google Scholar. Google and Google Scholar automatically record all citations. They include journals and books as well as ‘grey’ literature such as working papers, conference papers, seminar discussions or teaching materials that has been issued in a less formal or definitive form – often, of course, including versions of material that is later formally published. As a result of this Publish or Perish offers a wider coverage than is provided by the other citation analysis tools which we have discussed and can be considered as a viable alternative. It provides a detailed analysis both of individual authors and of journal titles. Through it one can find the average number of citations per author and per journal title and also the average number of citations per year. Publish or perish also gives the author’s and the journal title’s h-index. As can be seen from the table in section two it provides a further metric, that of Egghe’s g-index, which aims to improve on the h-index by giving more weight to highly-cited articles.
Plant and equipment assets, also known as long-lived assets, are expected to help generate rev- enues over the current and future accoun ng periods because they are used to produce goods, supply services, or used for administra ve purposes. The truck and equipment purchased by Big Dog Carworks Corp. in January are examples of plant and equipment assets that provide economic beneﬁts for more than one accoun ng period. Because plant and equipment assets are useful for more than one accoun ng period, their cost must be spread over the me they are used. This is done to sa sfy the matching principle. For example, the $100,000 cost of a machine expected to be used over ﬁve years is not expensed en rely in the year of purchase because this would cause expenses to be overstated in Year 1 and understated in Years 2, 3, 4, and 5. Therefore, the $100,000 cost must be spread over the asset’s ﬁve-year life.
This chapter discusses various mathematical concepts and constructions which are central to the study of the many fundamental results in analysis. Generalities are kept to a minimum in order to move quickly to the heart of analysis: the structure of the real number system and the notion of limit. The reader should consult the bibliographical references for more details.
Sayama has produced a very comprehensive introduction and overview of complexity. Typically, these topics would occur in many different courses, as a side note or possible behavior of a particular type of mathematical model, but only after overcoming a huge hurdle of technical detail. Thus, initially, I saw this book as a “mile-wide, inch-deep” ap- proach to teaching dynamical systems, cellular automata, networks, and the like. Then I realized that while students will learn a great deal about these topics, the real focus is learning about complexity and its hallmarks through particular mathematical models in which it occurs. In that respect, the book is remarkably deep and excellent at illustrating how complexity occurs in so many different contexts that it is worth studying in its own right. In other words, Sayama sort of rotates the axes from “calculus”, “linear algebra”, and so forth, so that the axes are “self-organization”, “emergence”, etc. This means that I would be equally happy to use the modeling chapters in a 100-level introduction to mod- eling course or to use the analysis chapters in an upper-level, calculus-based modeling course. The Python programming used throughout provides a nice introduction to simula- tion and gives readers an excellent sandbox in which to explore the topic. The exercises provide an excellent starting point to help readers ask and answer interesting questions about the models and about the underlying situations being modeled. The logical struc- ture of the material takes maximum advantage of early material to support analysis and understanding of more difficult models. The organization also means that students expe- riencing such material early in their academic careers will naturally have a framework for later studies that delve more deeply into the analysis and application of particular mathe- matical tools, like PDEs or networks.