|
Read the rules in the OP before posting, please.In order to ensure that this thread continues to meet TL standards and follows the proper guidelines, we will be enforcing the rules in the OP more strictly. Be sure to give them a re-read to refresh your memory! The vast majority of you are contributing in a healthy way, keep it up! NOTE: When providing a source, explain why you feel it is relevant and what purpose it adds to the discussion if it's not obvious. Also take note that unsubstantiated tweets/posts meant only to rekindle old arguments can result in a mod action. |
On May 24 2016 07:14 LegalLord wrote:Show nested quote +On May 24 2016 06:13 Plansix wrote:On May 24 2016 06:10 GreenHorizons wrote: I'm not sure amuses me more, when people here get in a math/science tizzy or when they try to discuss women. When they manage to discuss both at the same time it's pure awesome though Your comment about everyone on TL being a huge math nerd and pouncing on the topic like the only girl at the party hold true to this day. And the discussions about women/sexism always start and end in the exact same place, no matter how many times we go over the same points. And the women's studies meme continues to be a thing. Secretly I'm hoping Trump will say something provocative enough in the next few hours that this discussion becomes sidelined in the process.
We could joke that the Virginia gov moved to give voting rights back to felons because he knew he'd be joining them.
|
On May 24 2016 07:54 Lord Tolkien wrote:Show nested quote +On May 24 2016 07:49 Naracs_Duc wrote: iirc isn't agent based modeling also used in public health, atmospheric modeling (usually in air pollution research), forestry (usually fires), etc... Or am I misunderstanding it as something else? It is. It's being increasingly adopted in biology, ecology, and environmental studies to better understand epidemics, invasive species, etc, but I mostly mentioned it because as a statistical model and analytical tool, it was originally pioneered by social science departments (to dispel the notion that social sciences are not empirical).
Yeah, econometrics in general is getting very big in industry level research. Even though a lot of Economics was derived from epidemiology, they're definitely expanding it to be the one of the newest source of scientific practices.
|
A public records request from Oregon Public Broadcasting reveals that Nevada Rancher Cliven Bundy's defense lawyer tried to get the Koch brothers to help cover Bundy's legal bills.
According to the e-mail obtained by OPB, Bundy's lawyer Joel Hansen reached out to Republican Utah state Rep. Ken Ivory, a mover and shaker in the transferring federal lands movement. Ivory sponsored legislation that became law in 2012, which transferred Utah fed lands back to the state although the lands still remain in federal control today. Hansen asked if Ivory might be able to reach out to the Koch brothers and see if they would be interested in helping pay for Bundy's legal defense.
"I cannot represent Cliven for free. I'm not independently wealthy," Hansen wrote in the e-mail to Ivory. "I understand from news articles that the Koch brothers are helping to fund Cliven's efforts to return our lands to the states. I would like to speak with someone about helping to fund the legal fees associated with this case."
Hansen is a Nevada-based lawyer who says he has been friends with Bundy for years and has worked in the state for 38 years. He's been active in land disputes with the federal government before, defending Cliff Gardner, another Nevada rancher who went head to head with the feds over grazing his cattle.
Hansen went on to say that the case would "be huge" and that the "legal fees will not be insignificant" as there are to be 19 defendants.
Bundy currently faces charges from his 2014 armed ranch standoff in Nevada.
Source
|
On May 24 2016 07:44 Lord Tolkien wrote:Show nested quote +On May 24 2016 07:13 cLutZ wrote:On May 24 2016 07:03 Naracs_Duc wrote:On May 24 2016 06:52 WhiteDog wrote:Modern agent-based modelling, for instance (which has the potential to tackle one of the common criticisms of the economic "rational actor" and of social sciences in general), was born out of game theory and computational sociology, and, with further refinement, has major implications for social science and fields like biology/ecology. What's the definite use of agent based modelling ? Agent modelling is mainly used in microeconomy, it has some use in regards to various micro problems like insurance. It's very weak to understand anything relevant from a macroeconomic standpoint. Just saying, but let's take an exemple : principal agent models all conclude that social insurance system are inefficient due to information asymetry, while we know that the opposite is true. You're deluding yourself into thinking such models are solid enough that they can change social sciences. In fact, in social sciences, models cannot be fully proven, but cannot be discarded either : social sciences are not popperian, you can't "refute" what is historical. There is no objective way to discard a model. So the new goal post is that if can't discard a model its not science? Looking at LT's applications of "feminist modes and frames of analysis" As noted, I have not seriously studied in the field, but I have examined, for instance, Latin American history through a feminist/gendered lens to understand societal constructs of the time. It was quite useful as a added mode of analysis in that history/humanities course. I have no comments on it's value as a social science.
No, I was just saying the two activities behave so differently, require such different skillsets, and have such different procedures that calling them one thing (in this case science) is not good application of language. Its like grouping Horses and Cuttlefish in the same taxonomic group. You can do it by being incredibly broad, but that category confers very little information then about what it describes.
It seems to me that one category, social studies, wants to (and I feel silly using this word because its so overused) appropriate the legitimacy the public has ascribed the the word "science" to their own works.
|
I believe I've got a general idea of what you've been talking about. You are referring to Popper and his philosophy of science. That scientific theories cannot be proven, only falsified, and that models and theories "evolve" based on the fittest (over which best advances scientific knowledge). Your argument is that, as social science theories cannot be falsified, they do not, in the Popperian sense, technically constitute a science, due to being historical in nature (I'll have to ponder this part), but they still advance scientific and human knowledge and are still essentially sciences despite not fitting the technical term. Have I gotten your viewpoint correct? It's been a long time since I last read Popper so feel free to correct me. I believe we agree for the most part, but I would like to be sure. Yes you understood me. Recent epistemology view social science as "sciences" that oscillate from quantitative thinking (and every equal abstractions) to historical analysis (and contextualized assertions), never entirely pure. They rely on incomplete abstraction/concepts that can never be entirely anhistorical nor entirely refutable.
As for agent-based modelling, as far as I understand, it is being talked about in economics circles because it has good potential to replace the current DSGE models if it can be greatly upscaled, with the ability to create complex and ultimately volatile systems (which were difficult to do under old DSGE modelling), which, given development, would allow for much better forecasting. Similar such models allow for greater predictions of volatility among sample groups, and better address the criticism of inaccuracies in generalized, rational actor models. Modelization in economy is largely above my head, but from my understanding it is all very limited. Agent based modelling have very weak prediction capacities, but the guys who use them tweek them each time they fail until they match reality. They are also individualist. Economists like those models because they can give good enough result with still having micro economic foundation, which is the big game since Lucas' critic. Most impressive work I've seen on models are based on differential equation inspired from meteorology (things like Lorenz's model on climate) : + Show Spoiler +
Really seducing from my point as it leads to various unstable equilibriums (but that does not break down). Here is an exemple with Keen's model, based on Minsky's work on debt : + Show Spoiler +![[image loading]](http://debunkingeconomics.com/wp-content/uploads/2013/06/060113_1349_2.png) This very simplified model of a capitalist economy with finance, which has been constructed via "stylized fact" extensions to Goodwin' s growth cycle model, is able to demonstrate this key prediction of Minsky's hypothesis. Using plausible values for real interest rates, capitalist expectations of profit during booms can lead them to incur more debt than the system is capable of financing. The breakdown that occurs is analogous to a debt-induced depression in an actual economy. When such an event occurs, the model indicates a forever-increasing level of capitalist indebtedness. In the real world, however, the system continues but with some form of breakdown: some capitalists go bankrupt, many lenders write off bad debts and suffer capital losses. The two types of breakdown follow paths predicted by Minsky. In the high base rate case, booms, which were nproblematic early in the simulation, become destabilizing later because of the increased debt to output ratios that develop over time. This corresponds with Minsky's predictions of a secular trend toward rising debt to equity ratios as the memory of the previous major crisis recedes, which makes the system more fragile. In the high debt sensitivity case, falling workers' share and rising bankers share (at a slightly slower rate) lead to a minor speculative boom which, occurring at a time of greatly increased debt, leads to a runaway blowout in debt. In effect, a rise in income inequality (between workers and capitalists) leads to a period of instability and then collapse, a concept explored in Minsky (1986). In both cases, a long period of apparent stability is in fact illusory, and the crisis, when it hits, is sudden—occurring too quickly to be reversible by changes to discretionary policy at the time. http://keenomics.s3.amazonaws.com/debtdeflation_media/papers/Keen1995FinanceEconomicBreakdown_JPKE_OCRed.pdf
I'm sure many people in TL are better at math than I am, I don't understand much at all this anymore. Overall, the use of models in economy is still very limited I believe.
|
On May 24 2016 08:31 WhiteDog wrote:Show nested quote +I believe I've got a general idea of what you've been talking about. You are referring to Popper and his philosophy of science. That scientific theories cannot be proven, only falsified, and that models and theories "evolve" based on the fittest (over which best advances scientific knowledge). Your argument is that, as social science theories cannot be falsified, they do not, in the Popperian sense, technically constitute a science, due to being historical in nature (I'll have to ponder this part), but they still advance scientific and human knowledge and are still essentially sciences despite not fitting the technical term. Have I gotten your viewpoint correct? It's been a long time since I last read Popper so feel free to correct me. I believe we agree for the most part, but I would like to be sure. Yes you understood me. Recent epistemology view social science as sciences oscillating from quantitative thinking (and every equal abstractions) to historical analysis (and contextualized assertions), never entirely pure. They rely on incomplete abstraction/concepts that are never entirely anhistorical nor entirely refutable. Show nested quote +As for agent-based modelling, as far as I understand, it is being talked about in economics circles because it has good potential to replace the current DSGE models if it can be greatly upscaled, with the ability to create complex and ultimately volatile systems (which were difficult to do under old DSGE modelling), which, given development, would allow for much better forecasting. Similar such models allow for greater predictions of volatility among sample groups, and better address the criticism of inaccuracies in generalized, rational actor models. Modelization in economy is largely above my head, but from my understanding it is all very limited. Agent based modelling have very weak prediction capacities, but the guys who use them tweek them each time they fail until they match reality. They are also individualist. Economists like those models because they can give good enough result with still having micro economic foundation, which is the big game since Lucas' critic. Most impressive work I've seen on models are based on differential equation inspired from meteorology (things like Lorenz's model on climate) : + Show Spoiler +Really seducing from my point as it leads to various unstable equilibriums (but that does not break down). Here is an exemple with Keen's model, based on Minsky's work on debt : http://keenomics.s3.amazonaws.com/debtdeflation_media/papers/Keen1995FinanceEconomicBreakdown_JPKE_OCRed.pdfI'm sure many people in TL are better at math than I am, I don't understand much at all this anymore. I value those model for those result.
Causal Inference researchers don't like using terms like predictions as their focus is on estimation, and not forecasting. This is due to the fact that they work primarily with messy and incomplete data with zero way of obtaining any more than mess and incomplete data. Economists can try their best to make a predictive model, but without the ability to put humans in a lab and observe them making financial transactions in a controlled manner it will never have enough total data to make the model good enough to predict. And yet, these types of things still need to be estimated because they are real world issues that needs solutions. This is true for things outside of economics as well, and even includes things in the "hard sciences" because there will always be scenarios in real life where data is limited, incomplete, and messy.
|
On May 24 2016 05:56 Lord Tolkien wrote:Show nested quote +On May 24 2016 03:20 SolaR- wrote:On May 24 2016 03:07 Lord Tolkien wrote:On May 24 2016 03:06 SolaR- wrote:On May 24 2016 02:37 Ghostcom wrote: Social Science is a Scientific Field. Woman studies is not. It is at best a sub-specialty.
If the statement that "every country is misogynistic" is true, then so is "every country is misandric" as males occupy the extremes when it comes to almost all applicable parameters. Painting with such a broad brush is pretty much useless. Social sciences are not true science either. In what way. Social sciences do not go through the same rigorous testing that hard sciences do. Also, in social sciences you are dealing with unquantifiable data where absolute truth cannot be obtained. Social science will never reach the precision of the hard sciences. 2+2 always equals 4. Social science is more relative. Here is a decent article on the subject: blogs.scientificamerican.com First and foremost, that is a blog (and an opinion piece) and not a published article. The argument is noted, and the blog even offers an interesting view (social engineering as opposed to social science), but the premises are flawed. First, that it presupposes that science is about finding absolute truth: the fundamental basis of western scientific epistemology is that, in no case, can any scientist claim to have discovered absolute truth, as to do so would invalidate the entirety of the epistemology (and the scientific method) they have based their research upon. The best they can claim is, under our best models and theoretical framework, and using the following data and conditionals, we arrive at X conclusion. For instance, let's use physics. Newtonian physics is fundamentally wrong. The theoretical framework that Newton's theory of gravity, and the various laws and equations that are derived from it, falls apart upon the introduction of relativity. An yet we still teach and utilize Newtownian physics, and the equations ultimately derived from an incorrect model, for remaining highly useful in the vast majority of non-relativistic cases. Meanwhile, we are still attempting to reconcile the relativistic model with quantum mechanics and string theory. Nonetheless, we still utilize these models knowing full well that they contradict (and have yet to reconcile them). Right now, it doesn't matter at all if they're true, only that they work. Secondly, he makes the claim that in the social sciences, nothing can possibly be proven because all human beings are different. This is, quite frankly, highly suspect reasoning at best, and utter hogwash in all reality. Can we not say the same thing about animals ultimately being all different and having different life experiences? Unless the argument is that humans are special and human behavior cannot be modeled like animal behavior in ecology/biology in large sample sizes, this line of reasoning is, really, highly specious. Moreover, we need simply look at string theory at fields of "hard" science for fields that almost entirely theoretical, with none/little observable basis to back up the existence of such a framework besides a lot of computers doing a lot of maths. Show nested quote +On May 24 2016 03:21 oBlade wrote:On May 24 2016 03:07 Lord Tolkien wrote:On May 24 2016 03:06 SolaR- wrote:On May 24 2016 02:37 Ghostcom wrote: Social Science is a Scientific Field. Woman studies is not. It is at best a sub-specialty.
If the statement that "every country is misogynistic" is true, then so is "every country is misandric" as males occupy the extremes when it comes to almost all applicable parameters. Painting with such a broad brush is pretty much useless. Social sciences are not true science either. In what way. Here are a couple soundbytes that capture the gist of why social science is in a different class of rigor from the natural sciences: + Show Spoiler + I am asking you to define what constitutes a "true" science, not give long out-dated soundbytes of pithy yet unproven statements and, ultimately, deflections. In essence, I'm asking you what a science is (or fundamentally, what is scientific epistemology), and, from that starting point, hope to logically derive the view that "social sciences" cannot be considered a science from it. An application of the Socratic method. Show nested quote +On May 24 2016 03:22 ticklishmusic wrote:On May 24 2016 03:14 Lord Tolkien wrote: I did not ask you to give me a strawman, Plansix. You're just detracting from what I would like to accomplish here.
At the moment, I would like SolaR- (or anyone else who believes something to this effect) to define, as rigorously and accurately as possible, his view of what constitutes a "true" scientific field. I would say "hard" sciences where data is quantified/collected in a very rigorous way, variables are accounted/ controlled for, hypotheses are tested, results can be replicated by using the same protocols, and with minimal reliance on frameworks. So we cannot use cell theory or germ theory, for instance, as the basis of our understanding and modeling of, say, vaccine creation? Theories and frameworks form the fundamental basis of all scientific knowledge, to exclude it as part of a definition of science, when the goal of science is to establish working theoretical models to understand phenomena (natural or human), seems dangerous. In any event, under this definition, most (if not all) social sciences fall under the category of science nowadays. Economics especially (and indeed the primary criticism of the field by the heterodox schools is that mainstream economics is far too empirically minded), but sociology. psychology, etc. all at present work empirically. Good sociological studies follow the scientific method as scrupulously as possible. Indeed, a reading of Durkheim's Suicide should dispel the notion that sociology can't readily follow scientific epistemology. It is social science (well, specific economics) departments which are currently innovating new applications of statistical approaches and analysis, after all. Honestly, all I can think of every time people make this claim is this comic: https://xkcd.com/435/I would also advise anyone who seriously considers this topic a relevant distinction to make to revisit the philosophical underpinnings of science itself, and that the basis of science and mathematics is entirely theoretical and non-observable in the physical world. EDIT: Show nested quote +On May 24 2016 05:48 Velr wrote: The problem with social science is simple, its extremly politically loaded. Findings that don't fit into the narrative are disregarded (or shouted death) and many studies seem more to be done to strenghten some agenda and not to come closer to some "truth".
I'm sure there is also tons of serious work done there (i hope so), but often it doesn't exactly look like that. Are you going to provide an example or show that this is either limited to social science as a field or that this is necessarily indicative that a field is not science?
I am not going to acknowledge everything else you said right now, I might try to respond later. I figure this argument has been beat to the ground, and I am not going to change your mind or anyone else.
However, I never claimed that the link that I posted was a published article with indisputable facts. I merely linked it because it illustrates my views on the subject. You come off as pretty presumptuous and snobby in your opening sentence.
|
On May 24 2016 08:39 Naracs_Duc wrote:Show nested quote +On May 24 2016 08:31 WhiteDog wrote:I believe I've got a general idea of what you've been talking about. You are referring to Popper and his philosophy of science. That scientific theories cannot be proven, only falsified, and that models and theories "evolve" based on the fittest (over which best advances scientific knowledge). Your argument is that, as social science theories cannot be falsified, they do not, in the Popperian sense, technically constitute a science, due to being historical in nature (I'll have to ponder this part), but they still advance scientific and human knowledge and are still essentially sciences despite not fitting the technical term. Have I gotten your viewpoint correct? It's been a long time since I last read Popper so feel free to correct me. I believe we agree for the most part, but I would like to be sure. Yes you understood me. Recent epistemology view social science as sciences oscillating from quantitative thinking (and every equal abstractions) to historical analysis (and contextualized assertions), never entirely pure. They rely on incomplete abstraction/concepts that are never entirely anhistorical nor entirely refutable. As for agent-based modelling, as far as I understand, it is being talked about in economics circles because it has good potential to replace the current DSGE models if it can be greatly upscaled, with the ability to create complex and ultimately volatile systems (which were difficult to do under old DSGE modelling), which, given development, would allow for much better forecasting. Similar such models allow for greater predictions of volatility among sample groups, and better address the criticism of inaccuracies in generalized, rational actor models. Modelization in economy is largely above my head, but from my understanding it is all very limited. Agent based modelling have very weak prediction capacities, but the guys who use them tweek them each time they fail until they match reality. They are also individualist. Economists like those models because they can give good enough result with still having micro economic foundation, which is the big game since Lucas' critic. Most impressive work I've seen on models are based on differential equation inspired from meteorology (things like Lorenz's model on climate) : + Show Spoiler +Really seducing from my point as it leads to various unstable equilibriums (but that does not break down). Here is an exemple with Keen's model, based on Minsky's work on debt : http://keenomics.s3.amazonaws.com/debtdeflation_media/papers/Keen1995FinanceEconomicBreakdown_JPKE_OCRed.pdfI'm sure many people in TL are better at math than I am, I don't understand much at all this anymore. I value those model for those result. Causal Inference researchers don't like using terms like predictions as their focus is on estimation, and not forecasting. This is due to the fact that they work primarily with messy and incomplete data with zero way of obtaining any more than mess and incomplete data. Economists can try their best to make a predictive model, but without the ability to put humans in a lab and observe them making financial transactions in a controlled manner it will never have enough total data to make the model good enough to predict. And yet, these types of things still need to be estimated because they are real world issues that needs solutions. This is true for things outside of economics as well, and even includes things in the "hard sciences" because there will always be scenarios in real life where data is limited, incomplete, and messy. Yes, there are a lot of economist that tries to do just that (creating experiments in labs to see the behavior in people before specific problems and all), but the problem is that you can't reproduce a specific historical context in a lab. You can't even reproduce an experiment, as all men are different and carries their history, incoporated in them through socialisation. Because of that, it is better to create model with specific hypothesis on the behavior of agents / groups and see if it has any help to understand reality. I believe reliable prediction in economy is very shaky at this point.
|
On May 24 2016 08:42 WhiteDog wrote:Show nested quote +On May 24 2016 08:39 Naracs_Duc wrote:On May 24 2016 08:31 WhiteDog wrote:I believe I've got a general idea of what you've been talking about. You are referring to Popper and his philosophy of science. That scientific theories cannot be proven, only falsified, and that models and theories "evolve" based on the fittest (over which best advances scientific knowledge). Your argument is that, as social science theories cannot be falsified, they do not, in the Popperian sense, technically constitute a science, due to being historical in nature (I'll have to ponder this part), but they still advance scientific and human knowledge and are still essentially sciences despite not fitting the technical term. Have I gotten your viewpoint correct? It's been a long time since I last read Popper so feel free to correct me. I believe we agree for the most part, but I would like to be sure. Yes you understood me. Recent epistemology view social science as sciences oscillating from quantitative thinking (and every equal abstractions) to historical analysis (and contextualized assertions), never entirely pure. They rely on incomplete abstraction/concepts that are never entirely anhistorical nor entirely refutable. As for agent-based modelling, as far as I understand, it is being talked about in economics circles because it has good potential to replace the current DSGE models if it can be greatly upscaled, with the ability to create complex and ultimately volatile systems (which were difficult to do under old DSGE modelling), which, given development, would allow for much better forecasting. Similar such models allow for greater predictions of volatility among sample groups, and better address the criticism of inaccuracies in generalized, rational actor models. Modelization in economy is largely above my head, but from my understanding it is all very limited. Agent based modelling have very weak prediction capacities, but the guys who use them tweek them each time they fail until they match reality. They are also individualist. Economists like those models because they can give good enough result with still having micro economic foundation, which is the big game since Lucas' critic. Most impressive work I've seen on models are based on differential equation inspired from meteorology (things like Lorenz's model on climate) : + Show Spoiler +Really seducing from my point as it leads to various unstable equilibriums (but that does not break down). Here is an exemple with Keen's model, based on Minsky's work on debt : http://keenomics.s3.amazonaws.com/debtdeflation_media/papers/Keen1995FinanceEconomicBreakdown_JPKE_OCRed.pdfI'm sure many people in TL are better at math than I am, I don't understand much at all this anymore. I value those model for those result. Causal Inference researchers don't like using terms like predictions as their focus is on estimation, and not forecasting. This is due to the fact that they work primarily with messy and incomplete data with zero way of obtaining any more than mess and incomplete data. Economists can try their best to make a predictive model, but without the ability to put humans in a lab and observe them making financial transactions in a controlled manner it will never have enough total data to make the model good enough to predict. And yet, these types of things still need to be estimated because they are real world issues that needs solutions. This is true for things outside of economics as well, and even includes things in the "hard sciences" because there will always be scenarios in real life where data is limited, incomplete, and messy. Yes, there are a lot of economist that tries to do just that (creating experiments in labs to see the behavior in people before specific problems and all), but the problem is that you can't reproduce a specific historical context in a lab. Because of that, it is better to create model with specific hypothesis on the behavior of agents / groups and see if it has any help to understand reality. I believe reliable prediction in economy is very shaky at this point.
I don't disagree. But estimation (not really prediction) is something economist first got from epidemiologists who primarily got it from spatial statisticians who primarily got it from etc....
Its the same thing that limits medical research--primarily because its hard to just grab a bunch of humans and do experiments on them without there being some amount of variables that can't really be taken into account (people act differently when they know they're in an experiment for example while molecules and objects don't)
But I think we are in agreement on this for the most part.
|
On May 24 2016 08:50 Naracs_Duc wrote:Show nested quote +On May 24 2016 08:42 WhiteDog wrote:On May 24 2016 08:39 Naracs_Duc wrote:On May 24 2016 08:31 WhiteDog wrote:I believe I've got a general idea of what you've been talking about. You are referring to Popper and his philosophy of science. That scientific theories cannot be proven, only falsified, and that models and theories "evolve" based on the fittest (over which best advances scientific knowledge). Your argument is that, as social science theories cannot be falsified, they do not, in the Popperian sense, technically constitute a science, due to being historical in nature (I'll have to ponder this part), but they still advance scientific and human knowledge and are still essentially sciences despite not fitting the technical term. Have I gotten your viewpoint correct? It's been a long time since I last read Popper so feel free to correct me. I believe we agree for the most part, but I would like to be sure. Yes you understood me. Recent epistemology view social science as sciences oscillating from quantitative thinking (and every equal abstractions) to historical analysis (and contextualized assertions), never entirely pure. They rely on incomplete abstraction/concepts that are never entirely anhistorical nor entirely refutable. As for agent-based modelling, as far as I understand, it is being talked about in economics circles because it has good potential to replace the current DSGE models if it can be greatly upscaled, with the ability to create complex and ultimately volatile systems (which were difficult to do under old DSGE modelling), which, given development, would allow for much better forecasting. Similar such models allow for greater predictions of volatility among sample groups, and better address the criticism of inaccuracies in generalized, rational actor models. Modelization in economy is largely above my head, but from my understanding it is all very limited. Agent based modelling have very weak prediction capacities, but the guys who use them tweek them each time they fail until they match reality. They are also individualist. Economists like those models because they can give good enough result with still having micro economic foundation, which is the big game since Lucas' critic. Most impressive work I've seen on models are based on differential equation inspired from meteorology (things like Lorenz's model on climate) : + Show Spoiler +Really seducing from my point as it leads to various unstable equilibriums (but that does not break down). Here is an exemple with Keen's model, based on Minsky's work on debt : http://keenomics.s3.amazonaws.com/debtdeflation_media/papers/Keen1995FinanceEconomicBreakdown_JPKE_OCRed.pdfI'm sure many people in TL are better at math than I am, I don't understand much at all this anymore. I value those model for those result. Causal Inference researchers don't like using terms like predictions as their focus is on estimation, and not forecasting. This is due to the fact that they work primarily with messy and incomplete data with zero way of obtaining any more than mess and incomplete data. Economists can try their best to make a predictive model, but without the ability to put humans in a lab and observe them making financial transactions in a controlled manner it will never have enough total data to make the model good enough to predict. And yet, these types of things still need to be estimated because they are real world issues that needs solutions. This is true for things outside of economics as well, and even includes things in the "hard sciences" because there will always be scenarios in real life where data is limited, incomplete, and messy. Yes, there are a lot of economist that tries to do just that (creating experiments in labs to see the behavior in people before specific problems and all), but the problem is that you can't reproduce a specific historical context in a lab. Because of that, it is better to create model with specific hypothesis on the behavior of agents / groups and see if it has any help to understand reality. I believe reliable prediction in economy is very shaky at this point. I don't disagree. But estimation (not really prediction) is something economist first got from epidemiologists who primarily got it from spatial statisticians who primarily got it from etc.... Its the same thing that limits medical research--primarily because its hard to just grab a bunch of humans and do experiments on them without there being some amount of variables that can't really be taken into account (people act differently when they know they're in an experiment for example while molecules and objects don't) But I think we are in agreement on this for the most part. But most economist who came from a math background (like Keynes) believed estimations had very limited use for economy due to the radical uncertainty of economic phenomena. In modern economy, this leads to various mathematical tools : the evaluation of the skewness of datas to evaluate the lack of symmetry of the distribution ; the evaluation of the kurtosis to see if the datas are light tail or heavy tail (especially in regards to finance ; for exemple, we used to believe, for almost a hundred years, that price in finance followed a normal distribution, only to see that it actually vary a lot more than that) ; the idea that some phenomena are completly impossible to evaluate from a statiscal point of view (what economists call knightian uncertainty), etc.
|
On May 24 2016 09:05 WhiteDog wrote:Show nested quote +On May 24 2016 08:50 Naracs_Duc wrote:On May 24 2016 08:42 WhiteDog wrote:On May 24 2016 08:39 Naracs_Duc wrote:On May 24 2016 08:31 WhiteDog wrote:I believe I've got a general idea of what you've been talking about. You are referring to Popper and his philosophy of science. That scientific theories cannot be proven, only falsified, and that models and theories "evolve" based on the fittest (over which best advances scientific knowledge). Your argument is that, as social science theories cannot be falsified, they do not, in the Popperian sense, technically constitute a science, due to being historical in nature (I'll have to ponder this part), but they still advance scientific and human knowledge and are still essentially sciences despite not fitting the technical term. Have I gotten your viewpoint correct? It's been a long time since I last read Popper so feel free to correct me. I believe we agree for the most part, but I would like to be sure. Yes you understood me. Recent epistemology view social science as sciences oscillating from quantitative thinking (and every equal abstractions) to historical analysis (and contextualized assertions), never entirely pure. They rely on incomplete abstraction/concepts that are never entirely anhistorical nor entirely refutable. As for agent-based modelling, as far as I understand, it is being talked about in economics circles because it has good potential to replace the current DSGE models if it can be greatly upscaled, with the ability to create complex and ultimately volatile systems (which were difficult to do under old DSGE modelling), which, given development, would allow for much better forecasting. Similar such models allow for greater predictions of volatility among sample groups, and better address the criticism of inaccuracies in generalized, rational actor models. Modelization in economy is largely above my head, but from my understanding it is all very limited. Agent based modelling have very weak prediction capacities, but the guys who use them tweek them each time they fail until they match reality. They are also individualist. Economists like those models because they can give good enough result with still having micro economic foundation, which is the big game since Lucas' critic. Most impressive work I've seen on models are based on differential equation inspired from meteorology (things like Lorenz's model on climate) : + Show Spoiler +Really seducing from my point as it leads to various unstable equilibriums (but that does not break down). Here is an exemple with Keen's model, based on Minsky's work on debt : http://keenomics.s3.amazonaws.com/debtdeflation_media/papers/Keen1995FinanceEconomicBreakdown_JPKE_OCRed.pdfI'm sure many people in TL are better at math than I am, I don't understand much at all this anymore. I value those model for those result. Causal Inference researchers don't like using terms like predictions as their focus is on estimation, and not forecasting. This is due to the fact that they work primarily with messy and incomplete data with zero way of obtaining any more than mess and incomplete data. Economists can try their best to make a predictive model, but without the ability to put humans in a lab and observe them making financial transactions in a controlled manner it will never have enough total data to make the model good enough to predict. And yet, these types of things still need to be estimated because they are real world issues that needs solutions. This is true for things outside of economics as well, and even includes things in the "hard sciences" because there will always be scenarios in real life where data is limited, incomplete, and messy. Yes, there are a lot of economist that tries to do just that (creating experiments in labs to see the behavior in people before specific problems and all), but the problem is that you can't reproduce a specific historical context in a lab. Because of that, it is better to create model with specific hypothesis on the behavior of agents / groups and see if it has any help to understand reality. I believe reliable prediction in economy is very shaky at this point. I don't disagree. But estimation (not really prediction) is something economist first got from epidemiologists who primarily got it from spatial statisticians who primarily got it from etc.... Its the same thing that limits medical research--primarily because its hard to just grab a bunch of humans and do experiments on them without there being some amount of variables that can't really be taken into account (people act differently when they know they're in an experiment for example while molecules and objects don't) But I think we are in agreement on this for the most part. But most economist who came from a math background (like Keynes) believed estimations had very limited use for economy due to the radical uncertainty of economic phenomena. In modern economy, this leads to various mathematical tools : the evaluation of the skewness of datas to evaluate the lack of symmetry of the distribution ; the evaluation of the kurtosis to see if the datas are fat tail or heavy tail (especially in regards to finance ; for exemple, we used to believe, for hundred years, that price in finance followed a normal distribution, only to see that it actually vary a lot more than that) ; the idea that some phenomena are completly impossible to evaluate from a statiscal point of view (what economists call knightian uncertainty), etc.
Its a fairly recent trend I've been noticing talking to Phd Grads from the past 2ish years or so. Now that they're trying to integrate economics theory into public health and agro-economics, the shift into the importance of estimations (other than predictions) has been growing. This is primarily because of the nature of the domains--really hard to predict if correlative variables results in health/yield results is causal or not especially with how messy that data is. But yes, when it comes to economics, the biggest barrier is that economists and statisticians have a vastly different way they want to tackle producing models for the industry they usually end up in (finance) who cares more about predictions than estimations.
I'm really enjoying this chat but I think people would rather we yell about Bernie or Hillary.
|
|
A US appeals court on Monday reinstated a civil lawsuit accusing 16 major banks of conspiring to manipulate the Libor benchmark interest rate. The ruling, which overturns a 2013 decision, could bankrupt the institutions, the judges warned.
A lower court judge erred in dismissing the antitrust portion of private litigation against Barclays, Bank of America, Deutsche Bank, HSBC, UBS and others on the ground that the investors failed to allege harm to competition, according to the US circuit court of appeals in Manhattan.
Libor, or the London interbank offered rate, underpins hundreds of trillions of dollars of transactions and is used to set rates on credit cards, student loans and mortgages. It is calculated based on submissions by banks that sit on panels.
In litigation that began in 2011, investors accused big banks of suppressing Libor during the financial crisis in order to boost earnings or make their finances appear healthier.
Back in early 2013, Manhattan federal district court judge Naomi Reice Buchwald dismissed the claims filed by private plaintiffs. According to her 161-page decision, the banks did not violate antitrust laws when they colluded to manipulate the Libor benchmark interest rate and that the plaintiffs failed to prove harm from such collusion.
Buchwald’s 2013 decision surprised some, as at the time Barclays, UBS and Royal Bank of Scotland had already settled cases with more than $2.5bn in penalties. Since then penalties in Libor-rigging probes have climbed to roughly $9bn, including a penalty of $2.5bn against Deutsche Bank.
Source
|
On May 24 2016 10:16 {CC}StealthBlue wrote:Show nested quote +A US appeals court on Monday reinstated a civil lawsuit accusing 16 major banks of conspiring to manipulate the Libor benchmark interest rate. The ruling, which overturns a 2013 decision, could bankrupt the institutions, the judges warned.
A lower court judge erred in dismissing the antitrust portion of private litigation against Barclays, Bank of America, Deutsche Bank, HSBC, UBS and others on the ground that the investors failed to allege harm to competition, according to the US circuit court of appeals in Manhattan.
Libor, or the London interbank offered rate, underpins hundreds of trillions of dollars of transactions and is used to set rates on credit cards, student loans and mortgages. It is calculated based on submissions by banks that sit on panels.
In litigation that began in 2011, investors accused big banks of suppressing Libor during the financial crisis in order to boost earnings or make their finances appear healthier.
Back in early 2013, Manhattan federal district court judge Naomi Reice Buchwald dismissed the claims filed by private plaintiffs. According to her 161-page decision, the banks did not violate antitrust laws when they colluded to manipulate the Libor benchmark interest rate and that the plaintiffs failed to prove harm from such collusion.
Buchwald’s 2013 decision surprised some, as at the time Barclays, UBS and Royal Bank of Scotland had already settled cases with more than $2.5bn in penalties. Since then penalties in Libor-rigging probes have climbed to roughly $9bn, including a penalty of $2.5bn against Deutsche Bank. Source
I'd love to see bankers explain to people in prison for stealing things or running schemes why billion dollar fines make sense for bankers and prison makes sense for them.
|

More than one-third of North America’s 1,154 native bird species are at high risk of extinction due to climate change and other manmade factors, a new report found.
Thirty-seven percent of the continent’s bird species across 10 different habitat types need “urgent conservation action,” the North American Bird Conservation Initiative said in its annual “State of the Birds” report released Sunday. Forty-nine percent were identified as having moderate risk, while just 14 percent were marked as low risk.
Researchers categorized bird species based on their population size, population trends, population distribution and threats to both breeding and non-breeding members of the species.
The decline of bird species is most pronounced in ocean and tropical forest habitats, where more than half were identified as having a high risk of extinction and are on the organization’s “Watch List.”
“The outlook for oceanic birds — including seabirds and a group of landbirds found only on islands off the Mexican coast — is the bleakest of any North American bird group,” with 57 percent of species in the “high risk” category, the report found. “Small and declining seabird populations are severely threatened by invasive predators on nesting islands and accidental bycatch by commercial fishing vessels, as well as overfishing of forage fish stocks, pollution, and climate change.”
Some of the most threatened oceanic species include the Black-capped Petrel, the Fea’s Petrel and the Bermuda Petrel.
J.D. Bergeron, the executive director of International Bird Rescue, said these findings were consistent with his organization’s observations.
Source
|
On May 24 2016 07:59 Introvert wrote:Show nested quote +On May 24 2016 07:14 LegalLord wrote:On May 24 2016 06:13 Plansix wrote:On May 24 2016 06:10 GreenHorizons wrote: I'm not sure amuses me more, when people here get in a math/science tizzy or when they try to discuss women. When they manage to discuss both at the same time it's pure awesome though Your comment about everyone on TL being a huge math nerd and pouncing on the topic like the only girl at the party hold true to this day. And the discussions about women/sexism always start and end in the exact same place, no matter how many times we go over the same points. And the women's studies meme continues to be a thing. Secretly I'm hoping Trump will say something provocative enough in the next few hours that this discussion becomes sidelined in the process. We could joke that the Virginia gov moved to give voting rights back to felons because he knew he'd be joining them. I wonder how long it will take for Trump to incorporate this into the Crooked Hillary narrative? McAuliffe is basically inseparable from the Clintons.
|
edit: miss-post. got my dates wrong :x
|
The New York city council is poised to pass a series of criminal justice reforms that would sharply curtail the punishments for low-level offenses such as littering and peeing in public, an overhaul intended to help unclog the courts and jails of the nation’s largest city.
The Criminal Justice Reform Act would alter the penalties for certain offenses, including possessing an open container of alcohol in public. Though the offenses would remain illegal, the legislation would steer them to civil court rather than criminal court.
Public urination and most offenses in public parks would be downgraded from misdemeanors to violations, and the council’s plan would reduce the available jail penalties to just one day for violations. Currently, jail time could stretch up to 90 days for such offenses.
The package of bills was unveiled by city council speaker Melissa Mark-Viverito on Monday and will be voted upon by the entire city council on Wednesday, when it’s expected to pass.
“For too long, New York’s criminal justice system has been broken – it’s time we fix it,” Mark-Viverito, a Democrat, said in a statement. “The Criminal Justice Reform Act is going to continue to keep New Yorkers safe while also creating a more fair and just system that will ensure the penalties fit the crime.”
The plan has the support of the New York police department and first-term Democratic mayor Bill de Blasio, who is expected to sign it into law in the coming weeks.
Council staffers estimate that the plan would divert more than 100,000 cases from the criminal court system every year, avoid the issuance of 50,000 warrants annually, and prevent nearly 10,000 people annually from having permanent criminal records. There are currently 1.5m open warrants in the city, which has about 8.5 million residents.
Source
|
Is... is that a good thing overall?
|
On May 24 2016 12:00 SK.Testie wrote: Is... is that a good thing overall?
as long as there's not a sharp increase in public urination it seems to be a good thing
|
|
|
|