forecasting
fore·cast
F0248200 (fôr′kăst′)Noun | 1. | forecasting - a statement made about the future |
单词 | forecasting | |||
释义 | forecastingfore·castF0248200 (fôr′kăst′)
forecastingforecasting[′fȯr‚kast·iŋ]forecastingthe attempt to estimate future social occurrences. Compared with the more wide-ranging, often social science based, theorizing and speculation involved in FUTUROLOGY, forecasting can be distinguished as having a more specific focus (e.g. short-term economic forecasts, political-risk analysis). However, no sharp distinction exists between the two, and general observations which apply to futurology also apply to forecasting. see also DELPHI METHOD.Forecastingthe elaboration of a forecast; in a narrow sense, special scientific research on the concrete prospects for the development of a particular phenomenon. As one of the ways in which scientific predictions regarding society are made more specific, forecasting is related to planning, programming, projecting, management, and goal selection. These interrelationships are evident in parallel studies that involve forecasting and planning, forecasting and projecting, and so forth (specific-purpose, planning, programming, projecting, and organizational forecasting). There are two main types of forecasting: exploratory (genetic, investigative, or research) and normative. The purpose of exploratory forecasting is to predict the future condition of the object of research, using observable trends that presumably will not be altered by decisions (plans and projects, for example). Normative forecasting is used to predict the ways of achieving the desired state of the object of research, on the basis of pre-established criteria, goals, and norms. Feedback between the prediction and the decision plays an important role in forecasting. It varies in intensity depending on the object of research. Theoretically, this feedback never equals zero, because in the long run, human decisions and actions will be able to change an ever-increasing range of objects of prediction. In practical terms, however, many objects of research, particularly in the natural sciences, are uncontrolled, and it is possible to make unconditional predictions only for the purpose of adapting actions to the anticipated state of an object. On the other hand, particularly in the social sciences, feedback often reaches a high degree of intensity, resulting in the self-realization or “self-destruction” of the forecast by decisions and actions based on it. For example, in the West, predictions of monetary crises often lead to panics and actually exacerbate the situation. Nonetheless, prompt intervention based on predictions makes it possible to avoid impending danger. The forecast is demolished, but the total situation is saved. Thus, in forecasting controllable (for the most part, social) phenomena, the methodology is oriented not toward unconditional prediction but toward assessing the probable state of an object of research, if observable trends continue, and the desired state of the object, based on a pre-established norm. The anticipated result of research is the use of prognostic information, which is obtained through the comparison of data from exploratory and normative forecasting, to improve the soundness of goals and decisions, including plans, programs, and projects. Branches. In the natural sciences forecasting has become established in meteorology for the prediction of atmospheric phenomena (seeFORECAST, WEATHER: AGROMETEOROLOGICAL FORECASTS); in hydrology, for the prediction of floods, high waves, tsunamis, and the freezing over and breakup of bodies of water (seeHYDROLOGIC FORECASTS); in geology (forecasts of mineral resources and of earthquakes, for example); and in astronomy (forecasts of the state of celestial bodies, gases, and radiations). In agrometeorology, forecasts are made concerning agriculture, crop yields, and the conditions for developing the yield. In biology and medicine, forecasts are used particularly in human and animal physiology and psychology. In the technical sciences, scientific and technical, technological, and engineering forecasts are made on the state of materials and on the operating conditions for mechanisms, machines, equipment, and instruments. In the social sciences, forecasting is used in the science of science to make predictions on the social aspects of the development of science, on progress in science and technology, on the prospects of particular trends in scientific research, and on the structure of science, scientific personnel, and institutions (see). Forecasting is used in the social branches of medicine to predict the prospects for the development of public health. It is used in physical culture and sports, in economic geography, in the social branches of astronomy (the prospects for studying and developing the earth and space), and in the social branches of ecology (the prospects for maintaining an equilibrium between the condition of the natural environment and human society). In addition, forecasting is important in economics (see ), in sociology (predictions regarding social structure and organization, for example), in demography (predictions of the growth and structure of the population), and in philology and ethnology (the development of language, writing, customs, and national relationships). In architecture and urban planning, forecasts are made of migration and of the development of the city, the countryside, and housing. Forecasting is also used in education, cultural affairs, ethics, government, the law (legal forecasting), foreign and domestic policy, and military affairs. At the beginning of the 1970’s forecasting was relatively developed only in some of the natural sciences (agrohydro-meteorology), in a number of technical sciences, in the science of science, and in demography, the economic sciences, and criminology. The classification of forecasting by branches is not yet firmly established. For example, the phrase “scientific and technological forecast” sometimes encompasses forecasting in all the natural sciences, as well as in the science of science, geography, and public health. In a broad sense, “social forecasting” means “forecasting in the social sciences,” and in a narrow sense “forecasting in sociology.” In practice, systems of interrelated forecasts are developed in particular scientific disciplines. Depending on the aim of the prognostic research, one of the branches of forecasting plays the principal role, forming the subject matter of research, while the related branches constitute a prognostic background of previously obtained data. The prognostic background includes scientific, technological, demographic, economic, sociological, and cultural data, as well as information on domestic and foreign policy. Levels. Forecasts are classified according to their time frames. In current forecasts, substantial changes are not expected in the object of study, and only particular or partial quantitative evaluations are provided. Short-term forecasts provide general quantitative evaluations; medium-term forecasts, quantitative qualitative evaluations; long-term forecasts, qualitative quantitative evaluations; and extra long-term forecasts, general qualitative evaluations. Depending on its character and goal, forecasting may deal with time frames ranging from fractions of a second (for example, in physics) to billions of years (in cosmology). In the social sciences the time frame of a forecast varies from ten years (in policy-making) to 100 or more years (in urban planning). For operational purposes, in the social sciences the forecasting levels are usually equal to the planning levels: short-term levels cover one to two years; medium-term levels, five to ten years; long-term levels, 15–20 years; and extra long-term levels, 50–100 years. In the social sciences, forecasting for the longer periods is not advisable, because the gap between the special subject of the forecast and the prognostic background becomes excessive, as does the gap between a conditional prediction and the possibility of repeated changes in the object of forecasting, owing to decisions and actions. As a result, the degree of reliability of forecasts in the social sciences declines sharply as the time frame increases. Thus, in the social sciences, scientific prediction is limited to the general laws of the development of nature and society. Methods. Unlike calculations of strictly determined phenomena (for example, solar and lunar eclipses) and nonscientific prophecies, forecasting approaches its research subjects in terms of probabilities. This approach determines the character and structure of forecasting methods, of which there were more than 100 by the beginning of the 1970’s. Forecasting methods range from general scientific methods that are valid for all the sciences (for example, analysis and synthesis, extrapolation and interpolation, induction and deduction, analogy, hypothesis, and experimentation) to interdisciplinary methods suitable for several sciences and methods restricted to only one science. In forecasting, ten to 15 general and interdisciplinary scientific methods are widely used. Among them is extrapolation, which considers the particular features of the developmental dynamics of the object of forecasting, as well as the possible deviations in a dynamic time series, under the effect of factors in the prognostic background. Other widely used methods include modeling (simulation, game, operational, network, and other models), polls of experts or of the population, historical analogy, scenario writing, and matrices of reciprocally influencing factors (“problems and solutions” and “input-output” matrices). In addition, there are forecasting methods based on the construction of graphs and “problem trees” or “goal trees” (relevance trees), as well as on the use of patents. Usually, three classes of forecasting methods are recognized: extrapolation, modeling, and polls of experts. However, this classification is hypothetical, because forecasting models presume extrapolation and expert evaluations, and the latter are the result of extrapolation and of modeling of the research object by an expert. The specific methodologies in forecasting consist of an optimum combination of several methods, depending on the goal and tasks of research. Sometimes, several methodologies are combined into a comprehensive system of forecasting (the forecasting system), forming an aggregate with systems of goal selection, planning, programming, projecting, control, and administration. An example is the FAME system (Forecasts and Appraisals for Management Evaluation), the basis for the implementation of the Apollo space research program by the USA in the 1960’s and early 1970’s. Approximately 20 forecasting systems are in use in the world. The USSR uses a comprehensive forecasting system to elaborate a forecast of scientific and technological progress and its social and economic consequences. Among the basic stages of research in the general, standard methodology of forecasting are the preforecast orientation (determining the subject matter, goal, tasks, time frame, working hypotheses, methods, structure, and organization of the research) and the prognostic background (the assembling of available data on related branches of forecasting). Also among the main stages in the general methodology of forecasting are the initial or base model (a system of indexes and parameters depicting the character and structure of the object of research) and the exploratory model (a projection of the status of the system of indexes in the initial model as of the prediction date, based on observable trends and taking into consideration the factors in the prognostic background). For controllable phenomena, a normative model is also worked out (a projection into the future of the system of indexes in the initial model, in conformity with goals and norms established according to particular criteria). The basic stages in the general methodology of forecasting also include an evaluation of the degree of reliability (verification) and an adjustment of the preliminary models, using parallel control methods, usually the questioning of experts. Finally, based on a comparison of the prognostic models, recommendations are made to optimize the decision-making process in planning and administration. Experience shows that observing the requirements of forecasting methodology makes it possible to elaborate forecasts with a relatively high degree of reliability, accuracy, and time depth. For controllable phenomena, following the methodology of forecasting makes it possible to provide valuable scientific information in advance and to improve the level of objectivity and consequently the level of soundness of goals, plans, programs, designs, and decisions. However, forecasting theory is not sufficiently developed. Many difficulties in forecasting have not yet been overcome, and in a number of instances, the quality of forecasts does not correspond to rising needs. Historical survey. The term “forecasting” gained currency in the 1960’s, when a special theory of elaborating forecasts for controllable phenomena developed (see). However, forecasting has a long history. For many centuries, forecasting was not applied to society, because religious, Utopian, and idealistic philosophical and historical approaches completely dominated the understanding of society’s future. Marxism-Leninism marked the beginning of the history of the consistent, scientific prediction of the future of society. The experience of national economic planning in the USSR in the 1920’s and early 1930’s provided a new impetus to social forecasting, because it revealed the necessity of preplanning forecasts. In the natural sciences, however, the second half of the 19th century and the first half of the 20th were marked by the development of specific types of forecasts (for example, of the weather, diseases, and minerals). Increasingly, these scientific forecasts replaced customary predictions based on omens. During World War II (1939–45) forecasting was sharply curtailed, and it was not resumed until the 1950’s. In the 1960 s the scientific and technological revolution gave rise to a worldwide “forecasting boom.” Forecasting methods and techniques used under socialism and capitalism share certain features. At the same time, there are fundamental differences between the methodologies and characters of research on the future from the standpoint of Marxism-Leninism and from that of bourgeois futurology. In the capitalist countries forecasting, which is based on diverse, contradictory methodological concepts of bourgeois philosophy and sociology, serves the purposes of state-monopoly capitalism. In the developed capitalist countries forecasting is used by state institutions and private firms to improve the effectiveness of decision-making. In the socialist countries, including the USSR, as well as Bulgaria, Hungary, the German Democratic Republic (GDR), Poland, Rumania, Czechoslovakia, and Yugoslavia, forecasting is closely associated with national economic planning. In the Soviet Union problems in forecasting are the concern of special departments in many scientific institutions, of the Academy of Sciences of the USSR, of the State Planning Committee (Gosplan of the USSR), of the State Committee for Science and Technology, of the State Committee for Construction (Gosstroi), and of the Central Board of the Hydrometeorological Service of the Council of Ministers of the USSR. There are analogous departments in Bulgaria, Czechoslovakia, the GDR, Hungary, Poland, Rumania, and Yugoslavia. In Bulgaria, forecasting research is coordinated by the Commission for Forecasting of the Central Committee of the Bulgarian Communist Party; in the GDR, by the Strategic Study Group of the Politburo of the Central Committee of the Socialist Unity Party of Germany; in Hungary, by the Commission on Future Research of the Hungarian Academy of Sciences; in Poland, by the Committee on Poland in the Year 2000 of the Polish Academy of Sciences; and in Rumania, by the International Center of Methodology for Future and Development Studies. Since 1967 annual conferences on forecasting have been organized by the members of the Council for Mutual Economic Assistance (COMECON). In the developed capitalist countries many institutions are engaged in forecasting. In the USA the most important of them are the RAND Corporation, the Hudson Institute, the Institute for the Future, and the Commission on the Year 2000 of the American Academy of Arts and Sciences. In Great Britain the most important institution engaged in forecasting is the Next 30 Years Committee, which is subordinate to the Social Science Research Council. In France forecasting is handled primarily by the 1985 Group of the Council of Ministers and by the Center of Forecasting Research; in the Federal Republic of Germany (FRG), by the Wickert Institute for Economic Research on the Future; and in Italy, by the Institute for Applied Economic Research. Centers for research on the future have also been established in West Berlin and under the governments of many countries, including Sweden, Denmark, Norway, Belgium, the Netherlands, and Switzerland. Centers for research in forecasting have been organized in a number of developing countries, including India, Iran, Argentina, Venezuela, and Mexico. In virtually all of the Western European countries and in the USA there are national scientific societies of forecasting specialists. Three of the national societies are also international, with branches in various countries (the Association Internationale Futuribles [France], the World Future Society [USA], and Mankind 2000 [Great Britain]). The World Future Studies Federation was established in 1973. Four world conferences for research on the future have been held (Oslo, 1967; Kyoto, 1970; Bucharest, 1972; and Paris, 1974). Many specialists are working on problems in forecasting: in the USSR, A. N. Efimov, N. P. Fedorenko, V. M. Glushkov, D. M. Gvishiani, N. N. Nekrasov, and V. I. Siforov; in the USA, D. Bell, J. Bright, J. Forrester, T. Gordon, O. Helmer, H. Khan, and J. McHale; and in France, B. de Jouvenel. Also among the authorities working on problems in forecasting are F. Baade (FRG), D. Gabor (Great Britain), R. Jungk (Austria), F. Polak (the Netherlands), and J. G. Haltung (Norway). In the USSR a number of journals publish articles on problems in forecasting: Mirovaia ekonomika i mezhdunarodnye otnosheniia (World Economics and International Relations), Voprosy ekonomiki (Problems of Economics), Ekonomika i matematicheskie metody (Economics and Mathematical Methods), Voprosy filosofii (Problems of Philosophy), and Sotsiologicheskie issledovaniia (Sociological Research). Many foreign periodicals focus on problems in forecasting, including Analysen und Prognosen (West Berlin, since 1968), 2000 (Paris, since 1967), Futures (Guildford, since 1968), Futuribili (Rome, since 1967), Futuribles (Paris, since 1975), Futurist (Washington, D.C., since 1967), Futurum (Meisenheim-Munich, since 1968), and the Newsletter of Social and Human Forecasting (Rome, since 1971). Other foreign periodicals that specialize in forecasting include Polska 2000 (Warsaw, since 1970), Prognosen—Pläne—Perspektiven (Vienna, since 1967), Prognosztika (Budapest, since 1969), Technological Forecasting and Social Change (New York, since 1969), Trend (Prague, since 1969), and Trendek—Prognozisok (Budapest, since 1968). REFERENCESDobrov, G. M. Prognozirovanie nauki i lekhniki. Moscow, 1969.Bestuzhev-Lada, I. V. Okno v budushchee: Sovremennye problemy sotsial’nogo prognozirovaniia. Moscow, 1970. Lisichkin, V. A. Otraslevoe nauchno-tekhnicheskoe prognozirovanie. Moscow, 1971. Nauchnye osnovy ekonomicheskogo prognoza. Moscow, 1971. Prognozirovanie kapitalisticheskoi ekonomiki. Moscow, 1970. Avanesov, G. A. Teoriia i metodologiia kriminologicheskogo prognozirovaniia. Moscow, 1972. Bednyi, M. S. Demograficheskie protsessy i prognozy zdorov’ia naseleniia. Moscow, 1972. Anchishkin, A. I. Prognozirovanie rosta sotsialisticheskoi ekonomiki. Moscow, 1973. Jantsch, E. Prognozirovanie nauchno-tekhnicheskogo progressa, 2nd ed. Moscow, 1974. (Translated from English.) Zykov, Iu. A. Ekonomicheskoe prognozirovanie nauchno-tekhnicheskogo progressa. Moscow, 1975. Martino, J. Technological Forecasting for Decision-making. New York, 1972. A Guide to Practical Technological Forecasting. Englewood Cliffs, N. J., 1973. I. V. BESTUZHEV-LADA BIBLIOGRAPHYNauchnoe predvidenie i ekonomicheskoe prognozirovanie: Bibliograficheskii ukazatel’, vols. 1–6. Moscow, 1967–74.Ekonomicheskoe prognozirovanie v kapitalisticheskikh stranakh, vols. 1–2. Moscow, 1967–71. ForecastingForecastingForecastingforecastingsee SALES FORECASTING, TECHNOLOGICAL FORECASTING.ForecastingThe process of making predictions about future general economic and market conditions as a basis for decision-making by government and business. Various forecasting methods can be used to estimate future economic conditions, varying greatly in terms of their subjectivity, sophistication, data requirements and cost:
then use past data to estimate the regression coefficients d, b and c (see REGRESSION ANALYSIS). Econometric models may consist of just one equation like this, but often in complex economic situations the independent variables in one equation are themselves influenced by other variables, so that many equations may be necessary to represent all the causal relationships involved. For example, the macroeconomic forecasting model used by the British Treasury to predict future economic activity levels has over 600 equations. No forecasting method will generate completely accurate predictions, so when making any forecast we must allow for a margin of error in that forecast. In the situation illustrated in Fig. 75, we cannot make a precise estimate of the future value of an economic variable; rather, we must allow that there is a range of possible future outcomes centred on the forecast value, showing a range of values with their associated probability distribution. Consequently, forecasters need to exercise judgement in predicting future economic conditions, both in choosing which forecasting methods to use and in combining information from different forecasts. See FCT forecasting
Synonyms for forecasting
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