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Journal articles on the topic 'Economic forecasting'

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Published: 4 June 2021
Last updated: 3 March 2023

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1

Clark, Mary E. "Economic Forecasting." Science 246, no. 4926 (October 6, 1989): 10. http://dx.doi.org/10.1126/science.246.4926.10.b.

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2

Lieberman, Bernhardt. "Economic Forecasting." Science 246, no. 4926 (October 6, 1989): 10. http://dx.doi.org/10.1126/science.246.4926.10.a.

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3

CLARK, M. E. "Economic Forecasting." Science 246, no. 4926 (October 6, 1989): 10. http://dx.doi.org/10.1126/science.246.4926.10-a.

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4

Vogelsang, Timothy J. "Economic Forecasting." Journal of the American Statistical Association 96, no. 453 (March 2001): 339–55. http://dx.doi.org/10.1198/jasa.2001.s386.

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5

Elliott, Graham, and Allan Timmermann. "Economic Forecasting." Journal of Economic Literature 46, no. 1 (February 1, 2008): 3–56. http://dx.doi.org/10.1257/jel.46.1.3.

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Forecasts guide decisions in all areas of economics and finance and their value can only be understood in relation to, and in the context of, such decisions. We discuss the central role of the loss function in helping determine the forecaster's objectives. Decision theory provides a framework for both the construction and evaluation of forecasts. This framework allows an understanding of the challenges that arise from the explosion in the sheer volume of predictor variables under consideration and the forecaster's ability to entertain an endless array of forecasting models and time-varying specifications, none of which may coincide with the “true” model. We show this along with reviewing methods for comparing the forecasting performance of pairs of models or evaluating the ability of the best of many models to beat a benchmark specification.
6

Суворов, Anatoliy Suvorov, Ивантер, Viktor Ivantyer, Сутягин, and Valyeriy Sutyagin. "The Main Objectives and Principles of Socio-Economic Forecasting." Administration 3, no. 1 (March 17, 2015): 8–17. http://dx.doi.org/10.12737/8785.

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The methodological foundations of socio-economic forecasting are considered in this paper. The forecasting’s definition is given; the forecasting’s role and place in national economy regulation are considered. Forecasts types’ classification and the forecasting’s basic principles have been presented. Forecasting models’ structure and classification, as well as socio-economic forecasts’ elements and development stages have been considered.
7

Clements, Michael P., and David F. Hendry. "Forecasting economic processes." International Journal of Forecasting 14, no. 1 (March 1998): 111–31. http://dx.doi.org/10.1016/s0169-2070(97)00057-5.

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8

Bradley, M. E. "Forecasting Oilfield Economic Performance." Journal of Petroleum Technology 46, no. 11 (November 1, 1994): 965–71. http://dx.doi.org/10.2118/26054-pa.

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9

Hall, Stephen G., K. Holden, D. A. Peel, and J. L. Thompson. "Economic Forecasting: An Introduction." Economica 59, no. 233 (February 1992): 132. http://dx.doi.org/10.2307/2555081.

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10

Swanson, Norman R., Michael P. Clements, and David F. Hendry. "Forecasting Economic Time Series." Journal of the American Statistical Association 95, no. 450 (June 2000): 687. http://dx.doi.org/10.2307/2669429.

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11

Teguh, Muhammad, and Abdul Bashir. "Indonesia’s Economic Growth Forecasting." SRIWIJAYA INTERNATIONAL JOURNAL OF DYNAMIC ECONOMICS AND BUSINESS 3, no. 2 (July 10, 2019): 134. http://dx.doi.org/10.29259/sijdeb.v3i2.134-145.

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The high economic growth is very important for Indonesia to accelerate the development process at this period. Although, the growth rate was reached at 5.17 % in 2018 is likely high enough, some domestic economists even point out, it really can be raised to a higher level. This research tries to investigate and formulate again Indonesia’s economic growth rate in 2018 and forecast it for 2019. By doing analysis recent real GDP data by industrial origin and by type of expenditures, and also consider all of the available potential economic resources, this research shows that Indonesia’s economic growth rate could stand at 6.03 % in 2018 and also at 6.03 % in 2019. Anyway, the government need a good economic plan and consistently performing appropriate strategies which are suited to targets in order to have rapid and stable economic growth rate
12

Suiter, Mary C., and Diego Mendez-Carbajo. "FREDcast: Economic forecasting game." Journal of Economic Education 49, no. 3 (June 7, 2018): 296. http://dx.doi.org/10.1080/00220485.2018.1464988.

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13

FKIRIN, M. A., and I. A. AL-TURKI. "FORECASTING AGRICULTURAL ECONOMIC SYSTEMS." Cybernetics and Systems 22, no. 1 (January 1991): 17–24. http://dx.doi.org/10.1080/01969729108902268.

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14

Schorfheide, Frank. "FORECASTING ECONOMIC TIME SERIES." Econometric Theory 16, no. 3 (June 2000): 441–50. http://dx.doi.org/10.1017/s0266466600003066.

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The prediction of future events and developments is an exciting and perhaps mysterious task, often associated with the aura of prophets and seers instead of probabilistic models and computer screens. The reality of macroeconomic forecasting, however, is quite mundane. Predictions of macroeconomic aggregates play an important role in the decision making of private enterprises, central banks, and governments. In general, forecasts become less popular if they turn out to be inaccurate ex post, and the postwar history of macroeconomic forecasting has had its share of disappointments. For instance, in the early 1980's, economists tested inflation forecasts taken over the previous 20 years and found that the forecasts were poor, partly as a result of the oil price shocks in the 1970's. A recent study (Croushore, 1998) with data up to 1996 provides a more favorable assessment of the quality of inflation forecasts.
15

Kunst, Robert M., and Martin Wagner. "Economic forecasting: editors’ introduction." Empirical Economics 58, no. 1 (January 2020): 1–5. http://dx.doi.org/10.1007/s00181-019-01820-3.

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16

Silver, Stephen. "Economic forecasting for business." International Journal of Forecasting 4, no. 3 (January 1988): 499–500. http://dx.doi.org/10.1016/0169-2070(88)90118-5.

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17

Koehler, Anne B. "Forecasting economic time series." International Journal of Forecasting 5, no. 1 (January 1989): 137–38. http://dx.doi.org/10.1016/0169-2070(89)90073-3.

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18

Fisher, Paul. "Economic forecasting: an introduction." International Journal of Forecasting 7, no. 3 (November 1991): 388–89. http://dx.doi.org/10.1016/0169-2070(91)90014-m.

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19

Briscoe, G., and R. Wilson. "Forecasting economic activity rates." International Journal of Forecasting 8, no. 2 (October 1992): 201–17. http://dx.doi.org/10.1016/0169-2070(92)90119-t.

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20

Allen, P. Geoffrey. "Economic forecasting in agriculture." International Journal of Forecasting 10, no. 1 (June 1994): 81–135. http://dx.doi.org/10.1016/0169-2070(94)90052-3.

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21

Bullard, Peter, K. Holden, D. A. Peel, and J. L. Thompson. "Economic Forecasting: An Introduction." Statistician 42, no. 1 (1993): 79. http://dx.doi.org/10.2307/2348126.

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22

Pliskin, Jeffrey, C. W. J. Granger, and Paul Newbold. "Forecasting Economic Time Series." Journal of the American Statistical Association 83, no. 402 (June 1988): 574. http://dx.doi.org/10.2307/2288897.

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23

Focardi, Sergio M., and Frank J. Fabozzi. "Economics: An Empirical Science Capable of Forecasting Economic Events?" Journal of Portfolio Management 41, no. 4 (July 31, 2015): 145–51. http://dx.doi.org/10.3905/jpm.2015.41.4.145.

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24

Ramatov, Jumaniyoz, Sharofat Rakhmanova, and Nasiba Sh. Yunusova. "Philosophical Analysis of Socio-Economic Forecasting of the Future." International Journal of Psychosocial Rehabilitation 24, Special Issue 1 (February 28, 2020): 991–99. http://dx.doi.org/10.37200/ijpr/v24sp1/pr201244.

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25

Amoroso, Nicola, Loredana Bellantuono, Alfonso Monaco, Francesco De Nicolò, Ernesto Somma, and Roberto Bellotti. "Economic Interplay Forecasting Business Success." Complexity 2021 (March 19, 2021): 1–12. http://dx.doi.org/10.1155/2021/8861267.

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A startup ecosystem is a dynamic environment in which several actors, such as investors, venture capitalists, angels, and facilitators, are the protagonists of a complex interplay. Most of these interactions involve the flow of capital whose size and direction help to map the intricate system of relationships. This quantity is also considered a good proxy of economic success. Given the complexity of such systems, it would be more desirable to supplement this information with other informative features, and a natural choice is to adopt mathematical measures. In this work, we will specifically consider network centrality measures, borrowed by network theory. In particular, using the largest publicly available dataset for startups, the Crunchbase dataset, we show how centrality measures highlight the importance of particular players, such as angels and accelerators, whose role could be underestimated by focusing on collected funds only. We also provide a quantitative criterion to establish which firms should be considered strategic and rank them. Finally, as funding is a widespread measure for success in economic settings, we investigate to which extent this measure is in agreement with network metrics; the model accurately forecasts which firms will receive the highest funding in future years.
26

Ericsson, Neil R., and Jaime R. Marquez. "A Framework for Economic Forecasting." International Finance Discussion Paper 1998, no. 626 (October 1998): 1–48. http://dx.doi.org/10.17016/ifdp.1998.626.

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27

Ericsson, Neil R. "Predictable Uncertainty in Economic Forecasting." International Finance Discussion Paper 2000, no. 695 (December 2000): 1–30. http://dx.doi.org/10.17016/ifdp.2000.695.

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28

Greszta, Michał, and Wojciech Maciejewski. "Combined Economic Forecasting in Poland." Gospodarka Narodowa 200, no. 5-6 (June 30, 2005): 49–61. http://dx.doi.org/10.33119/gn/101524.

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29

Smaghi, Lorenzo Bini. "Economic Forecasting and Monetary Policy." Vierteljahrshefte zur Wirtschaftsforschung 75, no. 2 (April 2006): 54–64. http://dx.doi.org/10.3790/vjh.75.2.54.

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30

Clements, Michael P., and David F. Hendry. "Macro-Economic Forecasting and Modelling." Economic Journal 105, no. 431 (July 1995): 1001. http://dx.doi.org/10.2307/2235166.

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31

Cai, Zongwu, Yongmiao Hong, and Shouyang Wang. "Econometric Modeling and Economic Forecasting." Journal of Management Science and Engineering 3, no. 4 (December 2018): 178–82. http://dx.doi.org/10.3724/sp.j.1383.304010.

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32

Ericsson, Neil R., and Jaime Marquez. "A framework for economic forecasting." Econometrics Journal 1, no. 1 (June 1, 1998): C228—C266. http://dx.doi.org/10.1111/1368-423x.00011.

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33

Donihue, Michael R. "Teaching Economic Forecasting to Undergraduates." Journal of Economic Education 26, no. 2 (April 1995): 113–21. http://dx.doi.org/10.1080/00220485.1995.10844863.

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34

Degiannakis, Stavros, and George Filis. "Forecasting European economic policy uncertainty." Scottish Journal of Political Economy 66, no. 1 (January 3, 2019): 94–114. http://dx.doi.org/10.1111/sjpe.12174.

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35

FOURIE, F. C. v. N. "Second Thoughts on Economic Forecasting." South African Journal of Economics 54, no. 3 (September 1986): 196–202. http://dx.doi.org/10.1111/j.1813-6982.1986.tb00880.x.

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36

Wennberg, Karl, and Bjorn Nykvist. "The psychology of economic forecasting." Global Business and Economics Review 9, no. 2/3 (2007): 211. http://dx.doi.org/10.1504/gber.2007.013702.

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37

Sherman, Howard J. "Forecasting Financial and Economic Cycles." Journal of Economic Issues 29, no. 3 (September 1995): 956–57. http://dx.doi.org/10.1080/00213624.1995.11505725.

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38

Loomis, David G., and James E. Cox. "Principles for Teaching Economic Forecasting." International Review of Economics Education 2, no. 1 (2003): 69–79. http://dx.doi.org/10.1016/s1477-3880(15)30151-1.

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39

Breece, James H. "Business forecasting and economic cycles." International Journal of Forecasting 7, no. 4 (March 1992): 533–35. http://dx.doi.org/10.1016/0169-2070(92)90038-b.

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40

Chen, Dean T. "Economic forecasting in agriculture: Comment." International Journal of Forecasting 10, no. 4 (December 1994): 597–99. http://dx.doi.org/10.1016/0169-2070(94)90027-2.

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41

Alien, P. Geoffrey. "Economic forecasting in agriculture: Reply." International Journal of Forecasting 10, no. 4 (December 1994): 601–2. http://dx.doi.org/10.1016/0169-2070(94)90028-0.

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42

Bessler, David A. "Economic forecasting in agriculture: Discussion." International Journal of Forecasting 10, no. 1 (June 1994): 137–38. http://dx.doi.org/10.1016/0169-2070(94)90053-1.

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43

Tomek, William G. "Economic forecasting in agriculture: Comment." International Journal of Forecasting 10, no. 1 (June 1994): 143–45. http://dx.doi.org/10.1016/0169-2070(94)90055-8.

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44

Mullineux, Andy W. "Forecasting financial and economic cycles." International Journal of Forecasting 11, no. 1 (March 1995): 191–92. http://dx.doi.org/10.1016/0169-2070(95)90023-3.

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45

Donihue, Michael R. "Teaching Economic Forecasting to Undergraduates." Journal of Economic Education 26, no. 2 (1995): 113. http://dx.doi.org/10.2307/1183366.

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46

FKIRIN, M. A., and F. A. AL-TURKI. "Forecasting of economic dynamic systems." International Journal of Systems Science 22, no. 12 (December 1991): 2685–89. http://dx.doi.org/10.1080/00207729108910826.

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47

Kenneth Alexander. "The uncertainties of economic forecasting." Futures 20, no. 3 (June 1988): 307–12. http://dx.doi.org/10.1016/0016-3287(88)90083-3.

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48

Holden, Kenneth. "Centre for economic forecasting, economic and financial review." International Journal of Forecasting 4, no. 2 (January 1988): 290–91. http://dx.doi.org/10.1016/0169-2070(88)90084-2.

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49

HOLLY, SEAN. "Economic Viewpoint: Economic Models and Economic Forecasting: Ptolemaic or Copernican?" Economic Outlook 15, no. 9 (June 1991): 32–38. http://dx.doi.org/10.1111/j.1468-0319.1991.tb00647.x.

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50

Liao, Yun. "Machine Learning in Macro-Economic Series Forecasting." International Journal of Economics and Finance 9, no. 12 (November 13, 2017): 71. http://dx.doi.org/10.5539/ijef.v9n12p71.

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Abstract:
In this paper I conducted a simple experiment to using Artificial Neural Network in time-series forecasting, by combining First order Markov Switching Model and K-means algorithms, the forecasting performance of machine learning has outperformed the benchmark of time-series inflation rate forecasting. The paper reveal the potential of ANN forecasting, also provide future direction of research.
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