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We can teach about economics, which is a good thing. I claim the case of economics is similar. As an empirical scientist I have to conclude from this and other experiences that thinking like an economist is too difficult to be a realistic goal for teaching. I think economics, like philosophy, cannot be taught to nineteen-year olds.
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It is an old man's field. But you cannot teach him a philosophical subject.
In practical terms, the standard principles of economics course is a long march through a bunch of conceptual ideas: opportunity cost, supply and demand, perfect and imperfect competitions, comparative advantage and international trade, externalities and public goods, unemployment and inflation, monetary and fiscal policy, and more. The immediate concern of most students is to master those immediate tools--what McCloskey calls learning "about" economics.vipauto93.ru/profiles/map4.php
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But I do think that in the process of learning "about," many principles students get a meaningful feeling for a the broader subject and mindset. Actually, in my experience, the process works in the other direction. Many students spend the opening weeks of an introductory economics course feeling as if the material is difficult, even impossible, but by the middle and the end of the class, what seemed so difficult early in the term has become obvious and straightforward.
But when you raise your eyes at the end of class, it can be quite astonishing to look back and see how far you have come. As students apply the terms and models they have learned to a series of real and hypothetical examples, they often find to their surprise that they have also imbibed a considerable amount about economic thinking and the real-world economy.
Learning always has an aspect of the miraculous. Thus, I agree with McCloskey that truly "thinking like an economist" is a very rare outcome in a principles course, and unless you are comfortable as a teacher with setting a goal that involves near-universal failure, it's not a useful goal for instructors. But it also seems true to me that the series of topics in a conventional principles of economics course, and how they build on each other, does for many students combine to form a comprehensible narrative by the end of the class.
The students are not thinking like economists. But they have some respect and understanding for how economist think. During the s, a social and legal expectation arose in the United States that single mothers would usually be in the workforce, even when their children were young. In turn, this immediately raised a question of how child care would be provided. Here's are some patterns in the labor force for "prime-age" women between the ages of 25 and 54, broken down by single and married, and children or not.
Back in the early s, for example, single women with no children dark blue line were far more likely to be in the labor force than other women in this age group, and less than half of the married women with children under the age of six green line were in the labor force. But by about , the share of single prime-age women with no children in the labor force has declined, and had roughly converged with labor force participation rates of the other groups shown--except for the labor force participation rates of married women with children under six, which rose but remained noticeably lower.
The report notes: "These married mothers of young children who are out of the labor force are evenly distributed across the educational spectrum, although on average they have somewhat less education than married mothers of young children as a whole.
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Staffing requirements aren't the only rules causing variation in child care costs across states of course. Regulations that require higher-level degrees or other qualifications drive up the wages required to hire and retain staff, increasing the cost of child care.
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Other staff-related regulations that can drive up costs include required background checks and training requirements. In addition to standards regarding staff, many States set minimum requirements for buildings and facilities, including regulating the types and frequency of environmental inspections and the availability of indoor and outdoor space. The report looks at some studies of the effects of these rules. One study estimates "that decreasing the maximum number of infants per staff member by one thereby increasing the minimum staff-to-child ratio decreases the number of center-based care establishments by about 10 percent.
Also, each additional year of education required of center directors decreases the supply of care centers by about 3. It's that states should question their rules, and look at practices elsewhere, bearing in mind that the costs of rules hit harder for those with lower incomes. The other approach to making child care more available is to increase the buying power of low-income households with children, which can be done in a variety of ways.
The Economic Report of the President always brags about the current administration, but it was nonetheless interesting to me that it chose to brag about additional support for child care costs of low-income families: The Trump Administration has mitigated these work disincentives by substantially bolstering child care programs for low-income families. The Child Tax Credit, which was increased in the tax legislation, including "the refundable component of the CTC for those with earnings but no Federal income tax liability.
When it comes to the incentives and opportunities for low-income women to work, child care is of course just one part of the puzzle, and often not the largest part. But it remains a real and difficult hurdle for a lot of households, especially for lower-income women.
An additional issue is that some households will prefer formal child care, and thus will be benefit more from policies aimed directly at formal child care, while others will rely more informal networks of family and friends, and will benefit more from policies that increase income that be used for any purpose. Solar geoengineering refers to putting stuff in the atmosphere that would have the effect of counteracting greenhouse gases. Yes, there would be risks in undertaking geoengineering.
However, those who argue that substantial dangers of climate change are fairly near-term must be willing to consider potentially unpleasant answers. Even if the risks of geoengineering are too substantial right now, given the present state of climate change, if the world as a whole doesn't move forward with steps to hold down emissions of greenhouse gases, then perhaps the risks of geoengineering will look more acceptable in a decade or two?
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The emphasis on governance seems appropriate to me, because there's not a huge mystery over how to do solar geoengineering. The question of governance is about who decides when and what would be done. For example, what if one country or a group of countries decided to deploy geoengineering in the atmosphere? Perhaps that area is experiencing particular severe weather where the public is demanding that its politicians take action. Perhaps it's the "Greenfinger" scenario, in which a very wealthy person decides that its up to them to save the planet.
Thus, it's important to think both about governance of institutions that would consider deploying geoengineering, but it may be even more important to think about governance of institutions that would decide how to respond when someone else undertake geoengineering. Perhaps we can learn from other international agreements, like those affecting nuclear nonproliferation, cybersecurity, even international monetary policy.
But countries and regions are likely to be affected differently by climate change, and thus are likely to weigh the costs and benefits of geoengineering differently. Agreement won't be easy. But like the nuclear test-ban treaty, one can imagine rules that allow nation to monitor other nations, to see if they are undertaking geoengineering efforts.
A common argument among these authors is that geoengineering will happen.
ItFor example, Lucas Stanczyk writes: "Looking at the limited range of options available to mitigate the coming climate crisis, it is difficult to escape the conclusion that some form of solar geoengineering will be deployed on a global scale this century. Consider the decision of whether to enroll in a high-risk medical trial. Faced with a bad case of cancer, the standard treatment is high-dose chemotherapy.
Now consider as an alternative treatment an experimental bone-marrow transplant. All too often, however, psychology intervenes, including that of doctors. Errors of commission get weighted more heavily; expected lives are sacrificed. The Hippocratic Oath bans the intention of harm, not its possibility. To be sure, errors of commission incur greater blame or self-blame than those of omission when something bad happens, a major source of their greater weight.
But blame is surely small potatoes relative to survival, whether of a patient or of the Earth. Hence, we assert once again, italics and all: Where climate change and solar geoengineering are concerned, errors of commission and omission should be weighted equally. That also implies that the dangers of SG [solar geoengineering] — and they are real — should be weighed objectively and dispassionately on an equal basis against the dangers of an unmitigated climate path for planet Earth. The precautionary principle, however tempting to invoke, makes little sense in this context.
It would be akin to suffering chronic kidney disease, and being on the path to renal failure, yet refusing a new treatment that has had short-run success, because it could have long-term serious side effects that tests to date have been unable to discover.
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Failure to assiduously research geoengineering and, positing no red-light findings, to experiment with it would be to allow rising temperatures to go unchecked, despite great uncertainties about their destinations and dangers. That is hardly a path of caution. For an earlier post on this topic, see "Geoengineering: Forced Upon Us? The idea of "statistical significance" has been a basic concept in introductory statistics courses for decades. If you spend any time looking at quantitative research, you will often see in tables of results that certain numbers are marked with an asterisk or some other symbol to show that they are "statistically significant.
For example, if I flip a coin 10 times and get six heads and four tails, this could easily happen by chance even with a fair and evenly balanced coin. But if I flip a coin 10 times and get 10 heads, this is extremely unlikely to happen by chance. Or if I flip a coin 10, times, with a result of 6, heads and 4, tails essentially, repeating the flip coin experiment 1, times , I can be quite confident that the coin is not a fair one.
Given the omnipresence of "statistical significance" in pedagogy and the research literature, it was interesting last year when the American Statistical Association made an official statement "ASA Statement on Statistical Significance and P-Values" discussed here which includes comments like: "Scientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.
A p-value, or statistical significance, does not measure the size of an effect or the importance of a result.