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The third illsutration for Chrysallis Counselling and Psychotherapy, this image depicts the idea of stepping out of behavioural patterns initiated in childhood.
Col busy analyzing the thousands of DNA sequences generated by the Barcode Wales project
The Barcode Wales Paper: dx.plos.org/10.1371/journal.pone.0037945
Rangeland Resources and Wildland Soils students conduct vegetation analysis on the South Spit of Humboldt Bay.
If you can, please spare the time to visit my current exhibition of drawings here on Flickr. Simply follow the link below. Thank you very much. Julian.
www.flickr.com/groups/globalworldawards/discuss/721576241...
I haven't light painted since March... I'm back in the US for a short time and decided to light paint a bit. It's so hard to light paint where I moved to so that's why I haven't done much. It's so much easier out here in the countryside where it's dark...
Detailed accommodation studies and space analysis combined with the design and fit-out of this signals training centre for Tube Lines in Stratford, London by Mansfield Monk.
Astronauts from five space agencies around the world take part in ESA’s CAVES training course– Cooperative Adventure for Valuing and Exercising human behaviour and performance Skills.
The six cavenauts of this edition of CAVES are ESA astronaut Alexander Gerst, NASA astronauts Joe Acaba and Jeanette Epps, Roscosmos’ cosmonaut Nikolai Chub, Canadian Space Agency astronaut Josh Kutryk and Japan’s space agency Takuya Onishi.
The three-week course prepares astronauts to work safely and effectively in multicultural teams in an environment where safety is critical.
As they explore caves they encounter caverns, underground lakes and strange microscopic life. They test new technology and conduct science – just as if they were living on the International Space Station.
The six astronauts have to rely on their own skills, teamwork and ground control to achieve their mission goals – the course is designed to foster effective communication, decision-making, problem-solving, leadership and team dynamics.
Credits: ESA – A. Romeo
I thought that I had a solid grasp of discourse analysis, I really did. I've never received a mark lower than an A+ on any of the discourse analyses that I've written over the years, however. Doing a presentation on the methodology and theory behind it was absolute torture. I had a mental breakdown, which triggered a mental regression that led me to play Litebrite, cry and admit that I know nothing about critical linguistics . (okay, that last part is hyperbole, I just got sidetracked by nerves).
One person said that they really liked my presentation, but it didn't matter. He has skipped, what essentially amounts to, the entire school year, so he never saw any of the good presentations. Even the bad ones were better than mine.
38-year Syncrude employee Richard Maslanko conducts a lab test at the Syncrude Research & Development Centre in Edmonton, AB. Syncrude has invested an average of $114-million over the past five years in R&D. The majority of which is spent on environmental initiatives. For more information visit www.research.syncrude.ca
Microsoft Excel 2010 - What-If Analysis icon
I often need large pictures of Microsoft Excel icons to use in my teaching and couldn't find them anywhere, so I created my own. A bit rough but hopefully it is useful to you as well.
You may be interested to know that I actually created the icon in MS Excel 2010 and then took a screen shot. The squares are rows and columns and the text at the bottom is entered in a merged cell. That is also why it isn't exactly the same as the original icon.
Researcher Phil Sharer works on AUTONOMIE, Argonne's next-generation plug-and-play software architecture for evaluating the fuel consumption benefits of both components and powertrain throughout the different phases of model-based design, from modeling to hardware implementation.
Photo by Wes Agresta / Courtesy Argonne National Laboratory.
Materials are the building blocks of all functional structures. TWI's expertise lies in understanding the complex interactions that take place when basic materials are transformed into functional shapes and joined together in different working environments.
For more information www.twi.co.uk/technologies/material-properties/
If you wish to use this image each use should be accompanied by the credit line and notice, "Courtesy of TWI Ltd".
Ordnance Survey is a partner in the CityVerve project, offering a geospatial framework. We helped visualise various use cases. This is a frame from an animation that showed how you might analyse parking trends in a city using a dashboard view.
Diana F+ (Mr. Pink), 120 Kodak Portra 800. 22 Feb 2012.
Fox Commentators talking about the Pacers and Bobcats.
a fat roll caused the light leaks.
I had been wondering how to tackle this subject and as I was ironing one of my Tee Shirts it became obvious.
The Tee Shirt lists the "By Weight" analysis of the elements that make up a typical Human Being. So by weight we are mostly Hydrocarbon and a lot of trace elements.
#110 Periodic Elements for 118 pictures in 2018
Statistics rarely give a simple view's Yes/No type answer to the question under analysis. Interpretation often comes down to the level of statistical significance applied to the numbers and often refers to the probability of a value accurately rejecting the null hypothesis (sometimes referred to as the p-value).
In this graph the black line is probability distribution for the test statistic, the critical region is the set of values to the right of the observed data point (observed value of the test statistic) and the p-value is represented by the green area.
The standard approach is to test a null hypothesis against an alternative hypothesis. A critical region is the set of values of the estimator that leads to refuting the null hypothesis. The probability of type I error is therefore the probability that the estimator belongs to the critical region given that null hypothesis is true (statistical significance) and the probability of type II error is the probability that the estimator doesn't belong to the critical region given that the alternative hypothesis is true. The statistical power of a test is the probability that it correctly rejects the null hypothesis when the null hypothesis is false.
Referring to statistical significance does not necessarily mean that the overall result is significant in real world terms. For example, in a large study of a drug it may be shown that the drug has a statistically significant but very small beneficial effect, such that the drug is unlikely to help the patient noticeably.
While in principle the acceptable level of statistical significance may be subject to debate, the p-value is the smallest significance level that allows the test to reject the null hypothesis. This is logically equivalent to saying that the p-value is the probability, assuming the null hypothesis is true, of observing a result at least as extreme as the test statistic. Therefore, the smaller the p-value, the lower the probability of committing type I error.
Some problems are usually associated with this framework (See criticism of hypothesis testing):
A difference that is highly statistically significant can still be of no practical significance, but it is possible to properly formulate tests to account for this. One response involves going beyond reporting only the significance level to include the p-value when reporting whether a hypothesis is rejected or accepted. The p-value, however, does not indicate the size or importance of the observed effect and can also seem to exaggerate the importance of minor differences in large studies. A better and increasingly common approach is to report confidence intervals. Although these are produced from the same calculations as those of hypothesis tests or p-values, they describe both the size of the effect and the uncertainty surrounding it.
Fallacy of the transposed conditional, aka prosecutor's fallacy: criticisms arise because the hypothesis testing approach forces one hypothesis (the null hypothesis) to be favored, since what is being evaluated is probability of the observed result given the null hypothesis and not probability of the null hypothesis given the observed result. An alternative to this approach is offered by Bayesian inference, although it requires establishing a prior probability.
Rejecting the null hypothesis does not automatically prove the alternative hypothesis.
As everything in inferential statistics it relies on sample size, and therefore under fat tails p-values may be seriously mis-computed.
Working from a null hypothesis, two basic forms of error are recognized:
Type I errors where the null hypothesis is falsely rejected giving a "false positive".
Type II errors where the null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative".
Standard deviation refers to the extent to which individual observations in a sample differ from a central value, such as the sample or population mean, while Standard error refers to an estimate of difference between sample mean and population mean.
A statistical error is the amount by which an observation differs from its expected value, a residual is the amount an observation differs from the value the estimator of the expected value assumes on a given sample (also called prediction).
Mean squared error is used for obtaining efficient estimators, a widely used class of estimators. Root mean square error is simply the square root of mean squared error.
Misuse of statistics can produce subtle, but serious errors in description and interpretation—subtle in the sense that even experienced professionals make such errors, and serious in the sense that they can lead to devastating decision errors. For instance, social policy, medical practice, and the reliability of structures like bridges all rely on the proper use of statistics.
Even when statistical techniques are correctly applied, the results can be difficult to interpret for those lacking expertise. The statistical significance of a trend in the data—which measures the extent to which a trend could be caused by random variation in the sample—may or may not agree with an intuitive sense of its significance. The set of basic statistical skills (and skepticism) that people need to deal with information in their everyday lives properly is referred to as statistical literacy.
There is a general perception that statistical knowledge is all-too-frequently intentionally misused by finding ways to interpret only the data that are favorable to the presenter.[26] A mistrust and misunderstanding of statistics is associated with the quotation, "There are three kinds of lies: lies, damned lies, and statistics". Misuse of statistics can be both inadvertent and intentional, and the book How to Lie with Statistics[26] outlines a range of considerations. In an attempt to shed light on the use and misuse of statistics, reviews of statistical techniques used in particular fields are conducted (e.g. Warne, Lazo, Ramos, and Ritter (2012)).[27]
Ways to avoid misuse of statistics include using proper diagrams and avoiding bias.[28] Misuse can occur when conclusions are overgeneralized and claimed to be representative of more than they really are, often by either deliberately or unconsciously overlooking sampling bias.[29] Bar graphs are arguably the easiest diagrams to use and understand, and they can be made either by hand or with simple computer programs.[28] Unfortunately, most people do not look for bias or errors, so they are not noticed. Thus, people may often believe that something is true even if it is not well represented.[29] To make data gathered from statistics believable and accurate, the sample taken must be representative of the whole.[30] According to Huff, "The dependability of a sample can be destroyed by [bias]... allow yourself some degree of skepticism.
A least squares fit: in red the points to be fitted, in blue the fitted line.
Many statistical methods seek to minimize the residual sum of squares, and these are called "methods of least squares" in contrast to Least absolute deviations. The latter gives equal weight to small and big errors, while the former gives more weight to large errors. Residual sum of squares is also differentiable, which provides a handy property for doing regression. Least squares applied to linear regression is called ordinary least squares method and least squares applied to nonlinear regression is called non-linear least squares. Also in a linear regression model the non deterministic part of the model is called error term, disturbance or more simply noise. Both linear regression and non-linear regression are addressed in polynomial least squares, which also describes the variance in a prediction of the dependent variable (y axis) as a function of the independent variable (x axis) and the deviations (errors, noise, disturbances) from the estimated (fitted) curve.
Measurement processes that generate statistical data are also subject to error. Many of these errors are classified as random (noise) or systematic (bias), but other types of errors (e.g., blunder, such as when an analyst reports incorrect units) can also be important. The presence of missing data or censoring may result in biased estimates and specific techniques have been developed to address these problems.
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. In applying statistics to, e.g., a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal." Statistics deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements. In contrast, an observational study does not involve experimental manipulation.Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation). Descriptive statistics are most often concerned with two sets of properties of a distribution (sample or population): central tendency (or location) seeks to characterize the distribution's central or typical value, while dispersion (or variability) characterizes the extent to which members of the distribution depart from its center and each other. Inferences on mathematical statistics are made under the framework of probability theory, which deals with the analysis of random phenomena.A standard statistical procedure involves the test of the relationship between two statistical data sets, or a data set and synthetic data drawn from idealized model. A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis of no relationship between two data sets. Rejecting or disproving the null hypothesis is done using statistical tests that quantify the sense in which the null can be proven false, given the data that are used in the test. Working from a null hypothesis, two basic forms of error are recognized: Type I errors (null hypothesis is falsely rejected giving a "false positive") and Type II errors (null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative"). Multiple problems have come to be associated with this framework: ranging from obtaining a sufficient sample size to specifying an adequate null hypothesis.Measurement processes that generate statistical data are also subject to error. Many of these errors are classified as random (noise) or systematic (bias), but other types of errors (e.g., blunder, such as when an analyst reports incorrect units) can also be important. The presence of missing data or censoring may result in biased estimates and specific techniques have been developed to address these problems.In applying statistics to a problem, it is common practice to start with a population or process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal".
Ideally, statisticians compile data about the entire population (an operation called census). This may be organized by governmental statistical institutes. Descriptive statistics can be used to summarize the population data. Numerical descriptors include mean and standard deviation for continuous data types (like income), while frequency and percentage are more useful in terms of describing categorical data (like race).
When a census is not feasible, a chosen subset of the population called a sample is studied. Once a sample that is representative of the population is determined, data is collected for the sample members in an observational or experimental setting. Again, descriptive statistics can be used to summarize the sample data. However, the drawing of the sample has been subject to an element of randomness, hence the established numerical descriptors from the sample are also due to uncertainty. To still draw meaningful conclusions about the entire population, inferential statistics is needed. It uses patterns in the sample data to draw inferences about the population represented, accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing), estimating numerical characteristics of the data (estimation), describing associations within the data (correlation) and modeling relationships within the data (for example, using regression analysis). Inference can extend to forecasting, prediction and estimation of unobserved values either in or associated with the population being studied; it can include extrapolation and interpolation of time series or spatial data, and can also include data mining.When full census data cannot be collected, statisticians collect sample data by developing specific experiment designs and survey samples. Statistics itself also provides tools for prediction and forecasting through statistical models. To use a sample as a guide to an entire population, it is important that it truly represents the overall population. Representative sampling assures that inferences and conclusions can safely extend from the sample to the population as a whole. A major problem lies in determining the extent that the sample chosen is actually representative. Statistics offers methods to estimate and correct for any bias within the sample and data collection procedures. There are also methods of experimental design for experiments that can lessen these issues at the outset of a study, strengthening its capability to discern truths about the population. Sampling theory is part of the mathematical discipline of probability theory. Probability is used in mathematical statistics to study the sampling distributions of sample statistics and, more generally, the properties of statistical procedures. The use of any statistical method is valid when the system or population under consideration satisfies the assumptions of the method. The difference in point of view between classic probability theory and sampling theory is, roughly, that probability theory starts from the given parameters of a total population to deduce probabilities that pertain to samples. Statistical inference, however, moves in the opposite direction—inductively inferring from samples to the parameters of a larger or total population.
The basic steps of a statistical experiment are:
Planning the research, including finding the number of replicates of the study, using the following information: preliminary estimates regarding the size of treatment effects, alternative hypotheses, and the estimated experimental variability. Consideration of the selection of experimental subjects and the ethics of research is necessary. Statisticians recommend that experiments compare (at least) one new treatment with a standard treatment or control, to allow an unbiased estimate of the difference in treatment effects.
Design of experiments, using blocking to reduce the influence of confounding variables, and randomized assignment of treatments to subjects to allow unbiased estimates of treatment effects and experimental error. At this stage, the experimenters and statisticians write the experimental protocol that will guide the performance of the experiment and which specifies the primary analysis of the experimental data.
Performing the experiment following the experimental protocol and analyzing the data following the experimental protocol.
Further examining the data set in secondary analyses, to suggest new hypotheses for future study.
Documenting and presenting the results of the study.
Experiments on human behavior have special concerns. The famous Hawthorne study examined changes to the working environment at the Hawthorne plant of the Western Electric Company. The researchers were interested in determining whether increased illumination would increase the productivity of the assembly line workers. The researchers first measured the productivity in the plant, then modified the illumination in an area of the plant and checked if the changes in illumination affected productivity. It turned out that productivity indeed improved (under the experimental conditions). However, the study is heavily criticized today for errors in experimental procedures, specifically for the lack of a control group and blindness. The Hawthorne effect refers to finding that an outcome (in this case, worker productivity) changed due to observation itself. Those in the Hawthorne study became more productive not because the lighting was changed but because they were being observed.
Observational study
An example of an observational study is one that explores the association between smoking and lung cancer. This type of study typically uses a survey to collect observations about the area of interest and then performs statistical analysis. In this case, the researchers would collect observations of both smokers and non-smokers, perhaps through a cohort study, and then look for the number of cases of lung cancer in each group.[15] A case-control study is another type of observational study in which people with and without the outcome of interest (e.g. lung cancer) are invited to participate and their exposure histories are collected.Various attempts have been made to produce a taxonomy of levels of measurement. The psychophysicist Stanley Smith Stevens defined nominal, ordinal, interval, and ratio scales. Nominal measurements do not have meaningful rank order among values, and permit any one-to-one transformation. Ordinal measurements have imprecise differences between consecutive values, but have a meaningful order to those values, and permit any order-preserving transformation. Interval measurements have meaningful distances between measurements defined, but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit), and permit any linear transformation. Ratio measurements have both a meaningful zero value and the distances between different measurements defined, and permit any rescaling transformation.
Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative variables, which can be either discrete or continuous, due to their numerical nature. Such distinctions can often be loosely correlated with data type in computer science, in that dichotomous categorical variables may be represented with the Boolean data type, polytomous categorical variables with arbitrarily assigned integers in the integral data type, and continuous variables with the real data type involving floating point computation. But the mapping of computer science data types to statistical data types depends on which categorization of the latter is being implemented.
Other categorizations have been proposed. For example, Mosteller and Tukey (1977)[distinguished grades, ranks, counted fractions, counts, amounts, and balances. Nelder (1990)[described continuous counts, continuous ratios, count ratios, and categorical modes of data. See also Chrisman (1998), van den Berg (1991). The issue of whether or not it is appropriate to apply different kinds of statistical methods to data obtained from different kinds of measurement procedures is complicated by issues concerning the transformation of variables and the precise interpretation of research questions. "The relationship between the data and what they describe merely reflects the fact that certain kinds of statistical statements may have truth values which are not invariant under some transformations. Whether or not a transformation is sensible to contemplate depends on the question one is trying to answer".Consider independent identically distributed (IID) random variables with a given probability distribution: standard statistical inference and estimation theory defines a random sample as the random vector given by the column vector of these IID variables. The population being examined is described by a probability distribution that may have unknown parameters.
A statistic is a random variable that is a function of the random sample, but not a function of unknown parameters. The probability distribution of the statistic, though, may have unknown parameters.
Consider now a function of the unknown parameter: an estimator is a statistic used to estimate such function. Commonly used estimators include sample mean, unbiased sample variance and sample covariance.
A random variable that is a function of the random sample and of the unknown parameter, but whose probability distribution does not depend on the unknown parameter is called a pivotal quantity or pivot. Widely used pivots include the z-score, the chi square statistic and Student's t-value.
Between two estimators of a given parameter, the one with lower mean squared error is said to be more efficient. Furthermore, an estimator is said to be unbiased if its expected value is equal to the true value of the unknown parameter being estimated, and asymptotically unbiased if its expected value converges at the limit to the true value of such parameter.
Other desirable properties for estimators include: UMVUE estimators that have the lowest variance for all possible values of the parameter to be estimated (this is usually an easier property to verify than efficiency) and consistent estimators which converges in probability to the true value of such parameter.
This still leaves the question of how to obtain estimators in a given situation and carry the computation, several methods have been proposed: the method of moments, the maximum likelihood method, the least squares method and the more recent method of estimating equations.
DID YOU KNOW? Many of the imaging systems used by Macroscopic Solutions are available for individuals, researchers and labs to purchase?
Products are available here: macroscopicsolutions.com/product-category/imaging-products/
Services are available here: macroscopicsolutions.com/product-category/imaging_services/
There are often many possible reasons why engineering components fail in service, and the cause and mechanisms of failure can only be determined with the right combination of analytical equipment and experienced engineers.
TWI has both the state-of-the-art facilities to carry out complex failure investigations and the critical mass to interpret the results and offer the solutions to avoid further failures in the future.
For more information www.twi.co.uk/services/failure-investigation/
If you wish to use this image each use should be accompanied by the credit line and notice, "Courtesy of TWI Ltd".
Andreas Schleicher, SDirector and Special Advisor on Education Policy to the OECD's Secretary-General.
This image is not from a statistically significant sample size--although it is from a real analysis I did (aka, the figures are not made up).
After reading any comments before yours, write 1 comment about this photograph from one of the two areas below:
Composition & Framing - this is to do with how the photographer has arranged the various elements within the photograph including their viewpoint, angle and distance. It also takes into account perspective, use of space and line.
Message & Meaning - does the image have message for the viewer? Do you see a meaning behind the work? What do you think the purpose of the image is and how does it make you feel?
IFPRI Research Fellow, Danielle Resnick introduces the speakers at the even, Donor Approaches to Political Economy Analysis.
IFPRI hosted a policy seminar titled “Donor Approaches to Political Economy Analysis” on February 5, 2015. For more information, please visit: www.ifpri.org/event/donor-approaches-political-economy-an...
©IFPRI/Xinyuan Shang
Oesterreichische Nationalbank
Logo of the Austrian National Bank
Headquarters Vienna, Austria
Central Bank of Austria
Currency€
To ISO 4217 EUR
website
Previous Austro- Hungarian Bank
List of Central Banks
Oesterreichische Nationalbank, at Otto-Wagner -Platz No. 3, Vienna
The Austrian National Bank (OeNB), Austria's central bank as an integral part of the European System of Central Banks (ESCB) and the Eurosystem. It is instrumental in the design of the economic development in Austria and in the euro area. Legally, the OeNB is a public limited company.. However, it is also subject to further enshrined in the National Bank Act regulations resulting from its separate position as a central bank. In the framework of the Eurosystem, the OeNB contributes to a stability-oriented monetary policy. At the national level, it cares about the preservation of financial stability and the money supply and manage foreign exchange reserves to hedge against the euro in times of crisis. The guideline values in terms of the tasks of the Austrian National Bank are "security, stability and trust".
Contents
1 History
1.1 1816 to 1818
1.2 1818 to 1878
1.3 1878 to 1922
1.4 1922 to 1938
1.5 1938 to 1945
1.6 1945 to 1998
1.7 From 1999
2 The OeNB as a modern central bank
3 Legal form and organs
3.1 Legal framework
3.2 organs
3.2.1 General
3.2.2 General
3.2.3 Board of Directors
4 Tasks
4.1 Monetary policy strategies and monetary policy decision-making process
4.1.1 Economic analysis
4.1.2 Production of statistical information
4.1.3 Contribute to international organizations
4.2 Implementation of monetary policy
4.2.1 use of monetary policy instruments
4.2.2 Reserve Management
4.2.3 Money Supply
4.3 Communication of monetary policy
4.4 ensure financial stability
4.4.1 Financial Stability
4.4.2 Payment System Stability and payments
5 The OeNB in the European System of National Banks
6 President / Governors
7 See also
8 Literature
9 links
10 Notes and references
History
1816-1818
As long as 50 years before the founding of the National Bank the Habsburgs carried out first experiments with securities in the form of paper money. Finally, in the 18th Century the issue of banknotes transferred to a state independent institution, while the issue of paper money called "Banco notes," founded in 1705 by the "Vienna City Bank" took place in 1762.
In wartime governance took back control of the money issue, so there was an inflation of Banco-Zettel 1796-1810. The state ordered the forced acceptance of paper money in private transport, which led to a fast-growing discount on bills in the market. 1799 was therefore one for 100 guilders paper money only 92 guilders in silver coins, and at the end of 1810 the value of the paper florin had fallen to 15 % of the nominal value of the Banco-Zettel. Later, the Habsburgs declared a devaluation of the Banco-Zettel in the ratio of 5:1. This act was considered by the business community as a sovereign default, which the paper money experienced a rapid devaluation.
At the end of the Napoleonic wars the Habsburg multinational state ( → Habsburg Monarchy) faced a new challenge: the restoration of a European balance. Church, the nobility, the army and the bureaucracy as elements in the Ancien Régime were not sufficient to solve this problem, a well -founded economic situation was needed. Moreover, one could not ignore readily the laws of supply and demand.
In this regard, were the first June 1816 by Emperor Francis I two patents issued (later to distinguish the "main patent" or "bank patent"), the "privileged Austrian National Bank", conceived as a public company, had to constitute itself as soon a possible, propose the emperor three of its directors for selection of the governor and take up their activity provisionally on 1 July 1816.
The National Bank had henceforth a monopoly on the issuance of paper money, which led to a slowdown in the Austrian monetary system and an increase in the value of paper money. The economy was again a solid source of money keeping constant the value of money regardless of the spending plans of the State. The equity of the Bank justified this by share issues.
Initially comprised the activities of the bank - under temporary management - the redemption of paper money and the issuance of shares. The full effectiveness attained the National Bank until after the issue of 1,000 shares and the associated possibility of shareholders to set the management themselves.
1818-1878
On 15 July 1817 recieved the National Bank as the "first Bankprivilegium" the exclusive right to unrestricted issue of banknotes and in this context a special position in terms of Rediskontgeschäfts (rediscount business). Beginning of 1818 the definitive bank management was ready. Part of it were among leading figures of Viennese society, including the banker Johann Heinrich von Geymüller and Bernard of Eskeles. From 1830 to 1837 the Office of the Governor was held by Adrian Nicholas Baron Barbier.
In the countries of the Habsburg Monarchy, which were characterized in large part by an agricultural oriented activity pattern, some regions showed a lively commercial-industrial growth. The goal now was to create a system of economic exchange between these areas. Successively established the National Bank branch network and thus guaranteed a uniform money and credit supply. From its headquarters in Vienna this network extended over early industrial areas and commercial centers in Eastern and Central Europe to the northern Mediterranean.
Trade bills and coins were preferred assets of the National Bank, less the supply of money to the state. With the exchange transactions, the National Bank supported the economic growth of the monarchy and secured at the same time the supply of silver coins in the event that the need for these increases in exchange for bank notes, contrary to expectations. 1818 was the National Bank, however, by increasing public debt, due to high spending in times of crisis, not spared to make an increase in the government debt positions on the asset side of its balance sheet.
The patent provisions of the founding of the National Bank not sufficiently secured against the autonomy of governance. At the center of the struggle for independence, this was the question of the extent to which the issue of banknotes must be made on the basis of government bonds. In 1841, a renewal of Bankprivilegiums got a weakening of the independence by pushing back the influence of the shareholders in favor of the state administration. During the revolution of 1848/49 followers of constitutional goals received great support from senior figures in the National Bank. For about a hundred years, the Austrian branch of the Rothschild bank (from which from 1855, the "Royal Privileged Austrian Credit-Institute for Commerce and Industry", the later Creditanstalt, was born) was playing a leading role in the banking center of Vienna. Salomon Mayer von Rothschild was involved during the pre-March in all major transactions of the National Bank for the rehabilitation of the state budget.
Special focus the National Bank was putting on the development of the premium that was payable at the exchange of banknotes into silver money in business dealings. The increase, which corresponded to a depreciation of the notes issued by the Bank should be prevented. From an overall state perspective, the increase of the silver premium means a deterioration in terms of the exchange ratio towards foreign countries, influencing the price competitiveness of the Austrian foreign trade adversely. The stabilization of the premium were set some limits. Although the height of the emission activitiy was depending on the Bank, but also the price of silver and the potential effects of increased government debt materially affected the silver premium. Especially the 1848 revolution and conflicts in the following years caused an increasement of the silver premium.
Mid-century, the private banking and wholesale houses were no longer able to cope with the rapidly growing financial intermediation of the Habsburg monarchy. New forms of capital formation were required. From an initiative of the House of Rothschild, the first by the government approved and private joint-stock bank was created. This formation was followed in 1863 and 1864 by two other joint-stock banks, whose major shareholders included important personalities of the aristocracy, who possessed large liquid funds. Overall, grew with these banks the money creation potential of the "financial center of Vienna".
The central bank faced another difficult task: with its limited resources it had to secure sufficient liquidity on the one hand and on the other hand prevent the inflationary expansion of the money supply. Through close contacts with the shareholders of Vienna was a financial center (informal) ballot, especially in times of crisis, easily dealt out. In contrast, it gave differences of opinion in the Fed Board, which required enforcement of decisions.
In 1861, Friedrich Schey Koromla became director of the National Bank. On 27 December 1862 experienced the Bankprivilegium another innovation. The independence of the National Bank of the State was restored and anchored. Furthermore, was introduced the direct allocation of banknotes in circulation by the system of "Peel'schen Bank Act", which states that the fixed budget of 200 million guilders exceeding circulation of banknotes must be covered by silver coins. In 1866, when the German war ended in defeat for Austria, the compliance of the system was no longer met. The state felt itself forced to pay compensation for breach of privilege. This balance was supported by a law of 1872, after the National Bank may issue notes up to a maximum of 200 million guilders and each additional payment must be fully backed by gold or silver.
1873 the economic boom of the Habsburg monarchy was represented in a long-lasting rise in the share price. A now to be expecting break could by the behavior of the Vienna Stock not be intercepted, so it came to the "Great Crash of 1873". The in 1872 fixed restrictions of the circulation of notes for a short time have been suspended. Contrary to expectations, the money supply in crisis peak but only outgrew by nearly 1% the prescribed limit in the bank acts. The banks and the industrial and commercial companies survived the crash without major losses, although the share prices significantly lay below the initial level.
The years with high growth were followed by a period of stagnation.
1878-1922
As part of the compensation negotiations between Austria and Hungary in 1867, the National Bank was able to exercise fully their Privilegialrechte, the Kingdom of Hungary but now had the certified right, every ten years exercisable, to found an own central bank (bank note). As resulted from the first 10 -year period that furthermore none of the two parts of the monarchy wanted to build an independent money-issuing bank (Zettelbank), was built on 28 June 1878, initially to 31 December 1887 limited, an Austro-Hungarian Bank, and equipped with the Fed privilege. The first privilege of the new bank was a compromise in which on the one hand, regulations on liability for national debts as well as regulations limiting the influence of the government on banking businesses were included. 1878 Gustav Leonhardt was Secretary of the Bank.
The General Assembly and the General Council formed the unit of the bank management. Two directorates and major institutions - in Vienna and Budapest - represented the dual nature of the bank. 1892-1900 followed a long discussion finally the currency conversion from guilders (silver currency) to the crown (gold standard) with "Gold Crown" said coins.
Since the new banknotes were very popular in the public, now many gold coins piled up in the vaults of the Austro-Hungarian Bank. This period was characterized by a balanced combination of price growth and damping, the "per capita national product" grew while prices remained mostly stable. Against this background, it was easy for the Fed to encourage a new wave of industrialization.
With a third privilege in 1899 conditions were established under which the bank could be put into the financial services of the two countries, on the other hand there have been important innovations that paved a good exchange policy. By 1914, the exchange ratio of the Austro-Hungarian currency was unchanged with only minor fluctuations. In contrast, was the by conflicts marked political development.
The expansive foreign policy quickly led to high costs from which had to be shouldered by the central bank a significant part. The stability of the currency was in danger. Shortly after the beginning of World War I in 1914, laid down the Military Command to indemnify any seized property with double the price. There was an increasing scarcity of goods, connected with an ongoing expansion of the money supply and finally the increase in the price level on the 16-fold.
The resulting cost of the war of the Dual Monarchy were covered to 40% on central bank loans and 60% through war bonds. Over the duration of the war, the power force built up in recent decades has been frozen at the end of the conflict in 1918, the real income of the workers had fallen to one-fifth of the last year of peace.
With the end of the war the end for the old order had come, too. The decay of Cisleithania and Transleithania caused in several successor states, despite the efforts of the central bank to maintain the order, a currency separation (see Crown Currency in the decay of the monarchy, successor states). First, a separate "Austrian management" of the bank was introduced. It was encouraged to shoulder the shortcomings of the state budget of the Republic of Austria founded in 1918.
The new South Slav state began in January 1919 stamping its crown banknotes. The newly founded Czechoslovak Republic retained the crown currency (to date), but their printed banknotes in circulation as of February 1919 with indications that now these ar Czechoslovak crowns. (The country could an inflation as experienced by Austria avoide.) In March 1919, German Austria began to stamp its crown banknotes.
The Treaty of Saint-Germain-en-Laye of 10 September 1919, by Austria on 25 October 1919 ratified and which on 16 July 1920 came into force, determined the cancellation and replacement of all crown banknotes of all successor states of Austria-Hungary as well as the complete liquidation of the Austro-Hungarian Bank under the supervision of the war winners. The last meetings of the Bank took place mid 1921 and at the end of 1922.
After a period of overvaluation of the crown the dollar rate rose from 1919 again. 1921, had to be paid over 5,000 Austrian crowns per dollar. In addition to the significant drop in the external value existed in Austria rising inflation. End of 1922 was ultimately a rehabilitation program with foreign assistance - the "Geneva Protocol" - passed which slowed down the inflation.
1922-1938
With Federal Law of 24 July 1922 the Minister of Finance was commissioned to build a central bank, which had to take over the entire note circulation plus current liabilities of the Austrian management of the Austro-Hungarian Bank. With Federal Law of 14 November 1922, certain provisions of the law were amended and promulgated the statutes of the Austrian National Bank. By order of the Federal Government Seipel I 29 December 1922, the Board of the Austrian Austro-Hungarian Bank issued authorization for the central bank union activity with 1 January 1923 have been declared extinct and was made known the commencement of operations of the Oesterreichische Nationalbank this day.
The statutes of the Austrian National Bank (OeNB) secured the independence from the state, the independence of the Bank under exclusion of external influences and the corresponding equity. First, the stabilization of the Austrian currency was at the forefront. With the Schilling Act of 20 December 1924 was the schilling currency (First Republic) with 1 Introduced in March 1925, it replaced the crown currency. For 10,000 crowns now you got a shilling.
As an important personality in terms of the order of the state budget, Dr. Victor Kienböck has to be mentioned. He was in the time from 1922 to 1924 and from 1926 to 1929 finance minister of the First Republic and from 1932 to 1938 President of the Austrian National Bank. Through his work remained the Austrian Schilling, also beyound the global economy crisis, stable. Under this condition, the Fed was able to cope with the large number of bank failures of the past.
1938-1945
According to the on 13th March issued Anschlussgesetz (annexation law) , the Reichsmark with order of the Fuehrer and Chancellor of 17 was March 1938 introduced in the country Austria and determines the course: A Reichsmark is equal to one shilling fifty pence. On the same day, the Chancellor ordered that the management of the to be liquidated National Bank was transferred to the Reichsbank.
With regulation of three ministers of the German Reich of 23 April 1938, the National Bank was established as a property of the Reichsbank and its banknotes the quality as legal tender by 25 April 1938 withdrawn; public funds had Schilling banknotes until 15th of may in 1938 to accept. All the gold and foreign exchange reserves were transferred to Berlin.
The Second World War weakened the Austrian economy to a great extent, the production force after the war corresponded to only 40% of that of 1937 (see also air raids on Austria). To finance the war, the Reichsbank brought to a high degree banknotes in circulation, which only a great victory of the kingdom (Reich) actual values would have been opposable. Since prices were strictly regulated, inflation virtually could be "banned" during the war.
1945-1998
In occupied postwar Austria about 10 billion shillings by Allied military occupying powers were initially printed, which contributed to significant price increases.
With the re-establishment of the Republic of Austria by the Austrian declaration of independence of 27 April 1945, it came to the resumption of activities of the Oesterreichische Nationalbank. By the "Fed Transition Act" of July 1945 preliminary legal regulations for the operations of the Bank have been established. The restoration of the Austrian currency was their first big job. The goal was the summary of all currencies, which at the time were in circulation, and their secondment to a new Austrian currency. The "Schilling Act" of November 1945, the basis for the re-introduction of the Schilling (Second Republic) as legal tender in Austria. The next step was to reduce excess liquidity to make necessary funds for new business investment available and to make the external value of the shilling for the development of the economy competitive. First, however, less changed the inflationary situation and also the shilling was still significantly undervalued in relation to other currencies.
The "Currency Protection Act" of 1947 brought a significant change in the monetary overhang. Some deposits have been deleted without replacement, others converted into claims against the Federal Treasury. The following exchange operations also significantly reduced the amount of cash: banknotes from 1945 were canceled and exchanged for new schilling notes in the ratio 1:3. Only 150 shillings per person could go 1-1.
To control inflation, the social partners came to the foreground. The associations of employers and employees set in 1947 prices for supplies, wages were also raised. This was the first of the five "wage-price agreements" of the social partners. In 1952, inflation was held back by limiting the use of monetary policy instruments by the National Bank. Also, the external sector slowly relaxed after the end of the Korean War.
In 1955, the Austrian National Bank was re-established by the new National Bank Act as a corporation and the by the National Bank Transition of Authorities Act (Nationalbank-Überleitungsgesetz) established provisional arragement abolished. The National Bank Act stipulated that each half of the capital should be situated at the federal government and private shareholders. In addition to the independence of bank loans of the state, the new National Bank Act also contained an order that the central bank must watch within their monetary and credit policies on the economic policies of the federal government. From now on also included within the instruments of the National Bank were the areas open market and minimum reserve policy.
The Austrian economy increasingly stabilized, through good fiscal and monetary policy a high growth could be attained, with low inflation and long-term maintenance of external equilibrium.
1960, Austria joined the European Free Trade Association and participated in the European integration.
In the sixties came the international monetary system based on gold-dollar convertibility into currency fluctuations and political reforms were necessary. First, the loosening of exchange rate adjustments between several states was an option. However, U.S. balance of payments problems brought with it restrictions on capital movements, and then the Euro-Dollar market was born. In 1971, the convertibility of the U.S. dollar was lifted.
1975 interrupted a recession increasing growth time. International unbalanced ayments caused very extensive foreign exchange movements, whereby the intervention force of Austrian monetary policy has been strongly challenged. Their task now was to control the effect of foreign exchange on domestic economic activities to stabilize the shilling in the context of constantly shifting exchange rates and to control the price rise appropriately. Since the inflow of foreign funds reached to high proportions, so that the economic stability has been compromised, the policy went the way of the independent course design in a pool of selected European currencies.
The collapse of the economy forced the policy makers to a new course with active mutual credit control, subdued wage growth, financial impulses in supply and demand, and interest rates are kept low. This system of regulation, however, kept back the need for structural change, so it had to be given up in 1979. In the same year a fire destroyed large parts of the main building of the Austrian National Bank in Vienna. The repairs lasted until 1985.
Target in the eighties was to strengthen the economic performance using a competitive power comparison. The findings from the seventies stimulated the Austrian monetary policy to align the Schilling course at the Deutsche Mark to ensure price stability in the country. In addition, the structural change was initiated by inclusion in a large area. Stable, if not necessarily comfortable environment of monetary policy was a prerequisite, to secure the companies long-term productivity gains and thus safeguard their position in the economy.
Initially, this development stood a high level of unemployment in the way. Growth until the second half of the decade increased, at the same time increased the competitiveness and current accounts could be kept in balance.
In the nineties, the annexation of Austria took place in the European Community. 1995 Austria became a member of the European Union (EU) and joined the exchange rate mechanism of the European Monetary System. In 1998, the Central Banks (ESCB) have established the independence of institutions or bodies of the European Community and the governments of the EU Member States through an amendment to the National Bank Act of the Austrian National Bank to implement the goals and tasks of the European System. Thus, the legal basis for the participation of Austria in the third stage of Economic and Monetary Union (EMU) was created in 1999.
As of 1999
The Austrian National Bank, and other national central banks including the European Central Bank ( ECB), belongs to the European System of Central Banks.
On 1 January 1999 was introduced in the third stage of Economic and Monetary Union in Austria and ten other EU Member States, the euro as a common currency. The European Central Bank is henceforth responsible for monetary and currency policy, decisions in this regard will be taken in accordance with the Council of the European Central Bank.
Since May 2010, the OeNB is in full possession of the Republic of Austria, after originally lobbies, banks and insurance companies were involved with 50 % of the share capital in it. In 2011, the National Bank Act was adapted by an amendment (Federal Law Gazette I No. 50 /2011) in this circumstance, a renewed privatization is thus excluded by law.
The OeNB as a modern central bank
With the withdrawal from the retail business in the sixties as well as the first major internationalization and implementation of a strategic management in the seventies, the OeNB went on the way to a future-oriented central bank. Another major reform of banking began at the end of the eighties.
In terms of global development, the OeNB established in 1988 as a service company and expanded its guiding values - "security, stability and trust" - to the principles of " fficiency" and "cost-consciousness". The business center was optimized and strategic business experienced through targeted improvements a reinforcement. Be mentioned as examples are intensifying domestic cooperation in the area of payments by encouraging the creation of the Society for the Study co-payments (STUZZA), the liberalization of capital movements, the professional management of foreign exchange reserves, the improvement of the supply of money through the construction of the money center and the internationalization of business activities through the establishment of representative offices in Brussels (European Union), Paris (OECD) and the financial center of New York.
After Austria's accession to the EU in 1995, the OeNB participated in the European Monetary System (EMS ) and its Exchange Rate Mechanism. The integration in the third stage of Economic and Monetary Union (EMU) was the next step towards further development of policy stability. Since the conclusion of the Maastricht Treaty, the Austrian National Bank has very fully considered its role in the ESCB and created a basis for inclusion in the community. The profound economic and monetary policy of Austria was also a reference that qualified the OeNB to actively participate in the monetary future of Europe, a greater harmonization of the statistical framework and monetary policy instruments with a view to the euro system, the preparation of the issue of European banknotes, and the establishment of operational processes and organizational integration of business processes within the ESCB being specific objectives of the OeNB.
In the following, it came, inter alia, to the establishement of an economic study department, of an education or training initiative and to strengthen the position of payment transactions through the TARGET system.
A in 1996 created "OeNB master plan" provided important points for the upcoming transition to the euro.
In May 1998, a new pension system came into force, by which new employees were incorporated into a two-pillar model.
1999, Austria's participation in the third stage of EMU was manifest. The Austrian National Bank - as part of the ESCB - became the owner of the European Central Bank and received new powers in this context in the sense of participation in the monetary policy decision-making at the level of the European Community. With the introduction of the euro, monetary policy functions of the General Council have been transferred to the Governing Council. However, the implementation remains the responsibility of national central banks.
Activities of the Oesterreichische Nationalbank were or are, for example, the further professionalization of asset management, the expansion of the network of representative offices by opening a representative office in the financial center of London, preparation of the smooth introduction of euro cash in 2002 and the participation of the OeNB on the creation of the "A-SIT" (Center for secure Information Technology Center - Austria) and the "A-Trust" (society of electronic security systems in traffic GmbH ) in order to promote security in information technology.
de.wikipedia.org/wiki/Oesterreichische_Nationalbank
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I'm guessing about the authors of these three pieces of graffiti written on a ventilation shaft of the MTR at Kowloon Tong station: there were three teenage, female, native English speakers, who shared the same felt tip pen while waiting for a bus. One or more was smoking a cigarette (because it's hidden from street view). The thoughts are interesting/sensitive, but they didn't finish one of them because their bus had arrived. I note the same mistake of a dotted "i" while the rest of the letters are capitalized. However, the mistake was probably made by different authors suggesting they are in the same class at school, and were taught the same mistake/were not corrected. The writing is delicate, suggesting the authors were female, but the "quiet hope" sentence was written with a heavier hand, suggesting either confidence or possibly a male author. There is some inconsistency about the dots at the end of each sentence, with most placing three, one four and one five.