Fiscal policyIn economics and political science, fiscal policy is the use of government revenue collection (taxes or tax cuts) and expenditure to influence a country's economy. The use of government revenue expenditures to influence macroeconomic variables developed in reaction to the Great Depression of the 1930s, when the previous laissez-faire approach to economic management became unworkable.
New Keynesian economicsNew Keynesian economics is a school of macroeconomics that strives to provide microeconomic foundations for Keynesian economics. It developed partly as a response to criticisms of Keynesian macroeconomics by adherents of new classical macroeconomics. Two main assumptions define the New Keynesian approach to macroeconomics. Like the New Classical approach, New Keynesian macroeconomic analysis usually assumes that households and firms have rational expectations.
Keynesian economicsKeynesian economics (ˈkeɪnziən ; sometimes Keynesianism, named after British economist John Maynard Keynes) are the various macroeconomic theories and models of how aggregate demand (total spending in the economy) strongly influences economic output and inflation. In the Keynesian view, aggregate demand does not necessarily equal the productive capacity of the economy. Instead, it is influenced by a host of factors – sometimes behaving erratically – affecting production, employment, and inflation.
Consumption (economics)Consumption is the act of using resources to satisfy current needs and wants. It is seen in contrast to investing, which is spending for acquisition of future income. Consumption is a major concept in economics and is also studied in many other social sciences. Different schools of economists define consumption differently. According to mainstream economists, only the final purchase of newly produced goods and services by individuals for immediate use constitutes consumption, while other types of expenditure — in particular, fixed investment, intermediate consumption, and government spending — are placed in separate categories (see consumer choice).
Monetary policyMonetary policy is the policy adopted by the monetary authority of a nation to affect monetary and other financial conditions to accomplish broader objectives like high employment and price stability (normally interpreted as a low and stable rate of inflation). Further purposes of a monetary policy may be to contribute to economic stability or to maintain predictable exchange rates with other currencies.
Consumption functionIn economics, the consumption function describes a relationship between consumption and disposable income. The concept is believed to have been introduced into macroeconomics by John Maynard Keynes in 1936, who used it to develop the notion of a government spending multiplier. Its simplest form is the linear consumption function used frequently in simple Keynesian models: where is the autonomous consumption that is independent of disposable income; in other words, consumption when disposable income is zero.
Neoclassical synthesisThe neoclassical synthesis (NCS), neoclassical–Keynesian synthesis, or just neo-Keynesianism was a neoclassical economics academic movement and paradigm in economics that worked towards reconciling the macroeconomic thought of John Maynard Keynes in his book The General Theory of Employment, Interest and Money (1936). It was formulated most notably by John Hicks (1937), Franco Modigliani (1944), and Paul Samuelson (1948), who dominated economics in the post-war period and formed the mainstream of macroeconomic thought in the 1950s, 60s, and 70s.
Numerical analysisNumerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). It is the study of numerical methods that attempt at finding approximate solutions of problems rather than the exact ones. Numerical analysis finds application in all fields of engineering and the physical sciences, and in the 21st century also the life and social sciences, medicine, business and even the arts.
New classical macroeconomicsNew classical macroeconomics, sometimes simply called new classical economics, is a school of thought in macroeconomics that builds its analysis entirely on a neoclassical framework. Specifically, it emphasizes the importance of rigorous foundations based on microeconomics, especially rational expectations. New classical macroeconomics strives to provide neoclassical microeconomic foundations for macroeconomic analysis.
Numerical integrationIn analysis, numerical integration comprises a broad family of algorithms for calculating the numerical value of a definite integral, and by extension, the term is also sometimes used to describe the numerical solution of differential equations. This article focuses on calculation of definite integrals. The term numerical quadrature (often abbreviated to quadrature) is more or less a synonym for numerical integration, especially as applied to one-dimensional integrals.
Fiscal conservatismFiscal conservatism or economic conservatism is a political and economic philosophy regarding fiscal policy and fiscal responsibility with an ideological basis in capitalism, individualism, limited government, and laissez-faire economics. Fiscal conservatives advocate tax cuts, reduced government spending, free markets, deregulation, privatization, free trade, and minimal government debt. Fiscal conservatism follows the same philosophical outlook of classical liberalism. This concept is derived from economic liberalism.
Keynesian RevolutionThe Keynesian Revolution was a fundamental reworking of economic theory concerning the factors determining employment levels in the overall economy. The revolution was set against the then orthodox economic framework, namely neoclassical economics. The early stage of the Keynesian Revolution took place in the years following the publication of John Maynard Keynes' General Theory in 1936. It saw the neoclassical understanding of employment replaced with Keynes' view that demand, and not supply, is the driving factor determining levels of employment.
Numerical methods for ordinary differential equationsNumerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals. Many differential equations cannot be solved exactly. For practical purposes, however – such as in engineering – a numeric approximation to the solution is often sufficient. The algorithms studied here can be used to compute such an approximation.
Numerical methods for partial differential equationsNumerical methods for partial differential equations is the branch of numerical analysis that studies the numerical solution of partial differential equations (PDEs). In principle, specialized methods for hyperbolic, parabolic or elliptic partial differential equations exist. Finite difference method In this method, functions are represented by their values at certain grid points and derivatives are approximated through differences in these values.
Monetary economicsMonetary economics is the branch of economics that studies the different theories of money: it provides a framework for analyzing money and considers its functions (such as medium of exchange, store of value, and unit of account), and it considers how money can gain acceptance purely because of its convenience as a public good. The discipline has historically prefigured, and remains integrally linked to, macroeconomics. This branch also examines the effects of monetary systems, including regulation of money and associated financial institutions and international aspects.
ParameterA parameter (), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when identifying the system, or when evaluating its performance, status, condition, etc. Parameter has more specific meanings within various disciplines, including mathematics, computer programming, engineering, statistics, logic, linguistics, and electronic musical composition.
Statistical parameterIn statistics, as opposed to its general use in mathematics, a parameter is any measured quantity of a statistical population that summarises or describes an aspect of the population, such as a mean or a standard deviation. If a population exactly follows a known and defined distribution, for example the normal distribution, then a small set of parameters can be measured which completely describes the population, and can be considered to define a probability distribution for the purposes of extracting samples from this population.
CT scanA computed tomography scan (usually abbreviated to CT scan; formerly called computed axial tomography scan or CAT scan) is a medical imaging technique used to obtain detailed internal images of the body. The personnel that perform CT scans are called radiographers or radiology technologists. CT scanners use a rotating X-ray tube and a row of detectors placed in a gantry to measure X-ray attenuations by different tissues inside the body.
PET-CTPositron emission tomography–computed tomography (better known as PET-CT or PET/CT) is a nuclear medicine technique which combines, in a single gantry, a positron emission tomography (PET) scanner and an x-ray computed tomography (CT) scanner, to acquire sequential images from both devices in the same session, which are combined into a single superposed () image. Thus, functional imaging obtained by PET, which depicts the spatial distribution of metabolic or biochemical activity in the body can be more precisely aligned or correlated with anatomic imaging obtained by CT scanning.
Scale parameterIn probability theory and statistics, a scale parameter is a special kind of numerical parameter of a parametric family of probability distributions. The larger the scale parameter, the more spread out the distribution. If a family of probability distributions is such that there is a parameter s (and other parameters θ) for which the cumulative distribution function satisfies then s is called a scale parameter, since its value determines the "scale" or statistical dispersion of the probability distribution.
