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| ???org.dspace.app.webui.jsptag.ItemTag.dcfield??? | Value | Language |
|---|---|---|
| dc.contributor.advisor | 陳宜廷(Yi-Ting Chen) | |
| dc.contributor.author | Sheng-Kai Chou | en |
| dc.contributor.author | 周聖凱 | zh_TW |
| dc.date.accessioned | 2021-06-07T17:52:45Z | - |
| dc.date.copyright | 2012-08-20 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-20 | |
| dc.identifier.citation | Bismans, F. and R. Majetti (2012). Forecasting recessions using financial variables:
the French case, Empirical Economics, 42, 1–15. Brave, S. (2009). The Chicago Fed National Activity Index and business cycles, Federal Reserve Bank of Chicago, Chicago Fed Letter, 268. Burns, A. F. and W.C. Mitchell (1946). Measuring Business Cycles, New York: National Bureau of Economic Research Inc.. Chauvet, M. (1998). An econometric characterization of business cycle dynamics with factor structure and regime switching, International Economic Review, 39, 969–996. Chauvet, M. and S. Potter (2002). Predicting a recession: evidence from the yield curve in the presence structural breaks, Economics Letters, 77, 245–253. Chauvet, M. and S. Potter (2005). Forecasting recessions using the yield curve, Journal of Forecasting, 24, 77–103. Crone, T. M. and A. Clayton-Matthews (2005). Consistent economic indices for the 50 states, Review of Economics and Statistics, 87, 593–603. Diebold, F. X. and G. D. Rudebusch (1989). Scoring the leading indicators, Journal of Business, 62, 369–391. Diebold, F. X. and G. D. Rudebusch (1991). Forecasting output with the composite leading index: a real-time analysis, Journal of the American Statistical Association, 86, 603–610. Dueker, M. (1997). Strengthening the case for the yield curve as a predictor of U.S. recessions, Federal Reserve Bank of St. Louis Review, 79, 41–51. Estrella, A. (1998). A new measure of fit for equations with dichotomous dependent variables, Journal of Business & Economic Statistics, 16, 198–205. Estrella, A. (2008). The yield curve as a leading indicators: Frequently asked questions, available at http: // www. financeecon. com/ ycfaq. pdf , Estrella, A. and F. S. Mishkin (1998). Predicting U.S. recessions: financial variables as leading indicators, The Review of Economics and Statistics, 80, 45–61. 42 Evans, C. L., C. T. Liu, and G. Pham-Kanter (2002). The 2001 recession and the Chicago Fed National Activity Index: identifying business cycle turning points, Federal Reserve Bank of Chicago, Economic Perspectives, 26, 26–43. Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica, 57, 357–384. Hao, L. and E. C. Y. Ng (2011). Predicting Canadian recessions using dynamic probit modelling approaches, Canadian Journal of Economics, 44, 1297–1330. Harris, M., E. O. Raymond, and G. S. Pierre-Daniel (2004). Using manufacturing surveys to assess economic conditions, Federal Reserve Bank of Richmond Economic Quarterly, 90, 65–93. Kauppi, H. and P. Saikkonen (2008). Predicting U.S. recessions with dynamic binary response models, The Review of Economics and Statistics, 90, 777–791. Moore, G. H. (1961). Business Cycle Indicators Volume 1, Princeton: Princeton University Press Ng, E. C.Y. (2011). Forecasting U.S. recession with various risk factors and dynamic Probit models, Journal of Macroeconomics, 34, 112–125. Nyberg, H. (2010). Dynamic probit models and financial variables in recession forecasting, Journal of Forecasting, 29, 215–230. Stock, J. H. and M. M. Watson (1988). A probability model of the coincident economic indicators, NBER working papers Stock, J. H. and M. M. Watson (1989). New indices of coincident and leading economic indicators, in NBER Macroeconomics Annual Volume 4, 351–409. Cambridge: MIT Press Stock, J. H. and M. M. Watson (1993). A procedure for predicting recessions with leading indicators: econometric issues and recent experience, in Business Cycles, Indicators and Forecasting, 95–156, Chicago: University of Chicago Press Stock, J. H. and M. M. Watson (1999a). Business Cycle fluctuations in U.S. macroeconomic time series, in Handbook of Macroeconomics, 1, 3–64, Amsterdam: Elsevier. 43 Stock, J. H. and M. M. Watson (1999b). Forecasting inflation, Journal of Monetary Economics, 44, 293–335. Stock, J. H. and M. M. Watson (2003a). Forecasting output and inflation: The role of asset prices, Journal of Economic Literature, 41, 788–829. Stock, J. H. and M. M. Watson (2003b). How did leading indicator forecasts perform during the 2001 recession?, Federal Reserve Bank of Richmond, Economic Quarterly, 89, 71–90. Trebing, M. E. (1998). What’s happening in manufacturing, , Federal Reserve Bank of Philadelphia Business Review, 15–29. Zarnowitz, V. (1992). Business Cycles: Theory, History, Indicators, and Forecasting, Chicago: University of Chicago Press | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/15815 | - |
| dc.description.abstract | In this study, we propose a two-step method to circumvent the “announcement lag”
problem of the National Bureau of Economic Research recession dummy, which may not be suitably dealt with by existing studies on the dynamic Probit model. Specifically, we first identify the sub-sample of the recession dummy, which is unobserved because of this problem, using the information contained in certain macroeconomic indices. Then, we estimate the parameters of the dynamic Probit model based on the interest rate spread tween ten-year and three-month using the identified recession probabilities, and make the out-of-sample predictions accordingly. We show that our model is not only useful for circumventing the announcement lag problem but also for refining the performance of some alternative models. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-07T17:52:45Z (GMT). No. of bitstreams: 1 ntu-101-R99323042-1.pdf: 577157 bytes, checksum: 184ad1c22fd3a09f26639722e51cf25b (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 1 Introduction 1
2 The Existing Model 4 3 The Proposed Method 6 4 Data and Variables 9 4.1 Dependent Variable . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 4.2 Potential Explanatory Variables . . . . . . . . . . . . . . . . . . . . . 11 5 Empirical Analysis 15 5.1 Data Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 5.2 Identifying Business Conditions . . . . . . . . . . . . . . . . . . . . . 20 5.3 Predicting Business Conditions . . . . . . . . . . . . . . . . . . . . . 22 6 Conclusions 36 7 Appendix 37 | |
| dc.language.iso | en | |
| dc.subject | 最大概似法 | zh_TW |
| dc.subject | 景氣預測 | zh_TW |
| dc.subject | 指標 | zh_TW |
| dc.subject | 動態Probit | zh_TW |
| dc.subject | 迭代預測 | zh_TW |
| dc.subject | 兩階段模型 | zh_TW |
| dc.subject | Recession prediction | en |
| dc.subject | MLE | en |
| dc.subject | two-step model | en |
| dc.subject | iterative prediction | en |
| dc.subject | dynamic Probit model | en |
| dc.subject | indicator | en |
| dc.title | 以修正過之動態Probit模型認定及預測景氣狀態 | zh_TW |
| dc.title | A Modified Dynamic Probit Model for Identifying and
Predicting Recessions | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林常青(Chang-Ching Lin),徐之強(Chih-Chiang Hsu) | |
| dc.subject.keyword | 景氣預測,指標,動態Probit,迭代預測,兩階段模型,最大概似法, | zh_TW |
| dc.subject.keyword | Recession prediction,indicator,dynamic Probit model,iterative prediction,two-step model,MLE, | en |
| dc.relation.page | 44 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2012-08-20 | |
| dc.contributor.author-college | 社會科學院 | zh_TW |
| dc.contributor.author-dept | 經濟學研究所 | zh_TW |
| Appears in Collections: | 經濟學系 | |
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| File | Size | Format | |
|---|---|---|---|
| ntu-101-1.pdf Restricted Access | 563.63 kB | Adobe PDF |
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