Economic statistics

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Economic statistics is a topic in applied statistics that concerns the collection, processing, compilation, dissemination, and analysis of economic data. It is also common to call the data themselves 'economic statistics', but for this usage see economic data. The data of concern to economic statistics may include those of an economy within a region, country, or group of countries. Economic statistics may also refer to a subtopic of official statistics for data produced by official organizations (e.g. national statistical services, intergovernmental organizations such as United Nations, European Union or OECD, central banks, ministries, etc.). Analyses within economic statistics both make use of and provide the empirical data needed in economic research, whether descriptive or econometric. They are a key input for decision making as to economic policy. The subject includes statistical analysis of topics and problems in microeconomics, macroeconomics, business, finance, [1] forecasting, data quality, and policy evaluation. [2] [3] It also includes such considerations as what data to collect in order to quantify some particular aspect of an economy and of how best to collect in any given instance.

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Econometrics is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships". The first known use of the term "econometrics" was by Polish economist Paweł Ciompa in 1910. Jan Tinbergen is considered by many to be one of the founding fathers of econometrics. Ragnar Frisch is credited with coining the term in the sense in which it is used today.

Economic data or economic statistics are data describing an actual economy, past or present. These are typically found in time-series form, that is, covering more than one time period or in cross-sectional data in one time period. Data may also be collected from surveys of for example individuals and firms or aggregated to sectors and industries of a single economy or for the international economy. A collection of such data in table form comprises a data set.

Clive Granger

Sir Clive William John Granger was a British econometrician known for his contributions to non-linear time series. He taught in Britain, at the University of Nottingham and in the United States, at the University of California, San Diego. During his university he was a member of Claymore. Granger was awarded the Nobel Memorial Prize in Economic Sciences in 2003 in recognition of the contributions that he and his co-winner, Robert F. Engle, had made to the analysis of time series data. This work fundamentally changed the way in which economists analyse financial and macroeconomic data.

Heteroscedasticity

In statistics, a vector of random variables is heteroscedastic if the variability of the random disturbance is different across elements of the vector. Here, variability could be quantified by the variance or any other measure of statistical dispersion. Thus heteroscedasticity is the absence of homoscedasticity. A typical example is the set of observations of income in different cities.

Agricultural economics is an applied field of economics concerned with the application of economic theory in optimizing the production and distribution of food and fiber. Agricultural economics began as a branch of economics that specifically dealt with land usage, it focused on maximizing the crop yield while maintaining a good soil ecosystem. Throughout the 20th century the discipline expanded and the current scope of the discipline is much broader. Agricultural economics today includes a variety of applied areas, having considerable overlap with conventional economics. Agricultural economists have made substantial contributions to research in economics, econometrics, development economics, and environmental economics. Agricultural economics influences food policy, agricultural policy, and environmental policy.

Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit—or at a more disaggregated level, for specific sectors of the economy or even specific firms.Economic forecasting is a measure to find out the future prosperity of a pattern of investment and is the key activity in economic analysis.

National accounts Accounting for nations

National accounts or national account systems (NAS) are the implementation of complete and consistent accounting techniques for measuring the economic activity of a nation. These include detailed underlying measures that rely on double-entry accounting. By design, such accounting makes the totals on both sides of an account equal even though they each measure different characteristics, for example production and the income from it. As a method, the subject is termed national accounting or, more generally, social accounting. Stated otherwise, national accounts as systems may be distinguished from the economic data associated with those systems. While sharing many common principles with business accounting, national accounts are based on economic concepts. One conceptual construct for representing flows of all economic transactions that take place in an economy is a social accounting matrix with accounts in each respective row-column entry.

Computational economics is a research discipline at the interface of computer science, economics, and management science. This subject encompasses computational modeling of economic systems, whether agent-based, general-equilibrium, macroeconomic, or rational-expectations, computational econometrics and statistics, computational finance, computational tools for the design of automated internet markets, programming tool specifically designed for computational economics and the teaching of computational economics. Some of these areas are unique, while others extend traditional areas of economics by solving problems that are tedious to study without computers and associated numerical methods.

The Journal of Business & Economic Statistics is a quarterly peer-reviewed academic journal published by the American Statistical Association. The journal covers a broad range of applied problems in business and economic statistics, including forecasting, seasonal adjustment, applied demand and cost analysis, applied econometric modeling, empirical finance, analysis of survey and longitudinal data related to business and economic problems, the impact of discrimination on wages and productivity, the returns to education and training, the effects of unionization, and applications of stochastic control theory to business and economic problems.

Arnold Zellner was an American economist and statistician specializing in the fields of Bayesian probability and econometrics. Zellner contributed pioneering work in the field of Bayesian analysis and econometric modeling.

William A. Barnett American economist

William Arnold Barnett is an American economist, whose current work is in the fields of chaos, bifurcation, and nonlinear dynamics in socioeconomic contexts, econometric modeling of consumption and production, and the study of the aggregation problem and the challenges of measurement in economics.

Official statistics

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Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation of probability, as opposed to a relative-frequency interpretation.

Jan Kmenta

Jan Kmenta was a Czech-American economist. He was the Professor Emeritus of Economics and Statistics at the University of Michigan and Visiting Professor at CERGE-EI in Prague, until summer 2016.

The methodology of econometrics is the study of the range of differing approaches to undertaking econometric analysis.

Edward Emory Leamer is a professor of economics and statistics at UCLA. He is Chauncey J. Medberry Professor of Management and director of the UCLA Anderson Forecast.

Causation in economics has a long history with Adam Smith explicitly acknowledging its importance via his (1776) An Inquiry into the Nature and Causes of the Wealth of Nations and David Hume and John Stuart Mill (1848) both offering important contributions with more philosophical discussions. Hoover (2006) suggests that a useful way of classifying approaches to causation in economics might be to distinguish between approaches that emphasize structure and those that emphasise process and to add to this a distinction between approaches that adopt a priori reasoning and those that seek to infer causation from the evidence provided by data. He represented by this little table which useful identifies key works in each of the four categories.

John Maron Abowd is the Associate director for research and methodology and chief scientist of the US Census Bureau, where he serves on leave from his position as the Edmund Ezra Day Professor of Economics, professor of information science, and member of the Department of Statistical Science at Cornell University.

Agustín Maravall

Agustín Maravall Herrero is a Spanish economist known for his contributions in statistics and econometrics time series analysis, in particular seasonal adjustment and in the estimation of signals in economic time series. He has completed a methodology and several computer programs that are used throughout the world by analysts, researchers, and data producers. An important use is official production of series adjusted for seasonality and (perhaps) other undesirable effects such as noise, outliers, or missing observations. Maravall has received several awards and distinctions and retired in December 2014 from the Bank of Spain.

References

Citations

  1. Journal of Business and Economic Statistics, Aims and Scope. [ permanent dead link ]
  2. "Journal of Business & Economic Statistics, American Statistical Association."
  3. • Charles J. Bullock, 1919. "Prefatory Statement," Review of Economic Statistics, 1(1), [unnumbered page].
      Arnold Zellner, 1983. "Editorial Statement," Journal of Business and Economic Statistics, 1(1), pp. 1-4.
      Eric Ghysels and Alastair Hall, 2002. "Editors' Introduction to Twentieth Anniversary Commemorative Issue," Journal of Business and Economic Statistics, 20(1), pp. 1-4.

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