- Akcay, S. (2011). The Causal Relationship between Producer Price Index and Consumer Price Index: Empirical Evidence from Selected European Countries. International Journal of Economics and Finance, 3(6), 227 – 232.
- Ang, A., Bekaert. G., & Wei. M. (2006). Do macro variables, asset markets or surveys forecast inflation better? Finance and Economics Discussion Series, Divisions of Research and Statistics and Monetary Affairs, Federal Reserve Board, Washington, DC.
- Ang, A., Bekaert. G., & Wei. M. (2007). Do Macro Variables, Asset Markets, or Surveys Forecast Inflation Better? Journal of Monetary Economics, 54, 1163–1212.
- Atkeson, A., & Ohanian. L. E. (2001). Are Phillips curves useful for forecasting inflation? Federal Reserve Bank of Minneapolis Quarterly Review, 25(1), 2–11.
- Avramov, D. (2002). Stock Return Predictability and Model Uncertainty, Journal of Financial Economics, 64, 423–58.
- Aye, G., Gupta, R., Hammoudeh, SH., & Kim, W.J. (2015). Forecasting the Price of Gold Using Dynamic Model Averaging, University of Pretoria, Department of Economics Working Paper Series.
- Azevedo, J.V.e. & Pereira. A. (2010). Forecasting inflation with monetary aggregates. Economic Bulletin, Banco de Portugal; 1–18.
- Balcilar, R., Gupta, R., Eyden. R.V., Thompson, K., & Majumdar, A. (2018). Comparing the forecasting ability of financial conditions indices:The case of South Africa. The Quarterly Review of Economics and Finance, 69(C), 245-259.
- Barsoum, F., & Stankiewicz, S. (2013). Forecasting GDP Growth Using Mixed-Frequency Models with Switching Regimes. Working Paper Series, University of Konstanz, Department of Economics.
- Belmonte, M., & Koop, G. (2014). Model Switching and Model Averaging in Time-Varying Parameter Regression Models. in Ivan Jeliazkov, Dale J. Poirier (ed.) Bayesian Model Comparison (Advances in Econometrics, Volume 34) Emerald Group Publishing Limited, 45 – 69.
- Binner, JM., Tino, P., Tepper, J., Anderson, RG., Jones, B., & Kendall, G. (2010). Does money matter in inflation forecasting? Working paper series 2009-030B, Research Division, Federal Reserve Bank of St Louis.
- Bork, L. & Møller, S.V. (2014). Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection. Macroeconomic Methodology, Theory and Economic Policy (MaMTEP), Working Paper Series Department of Business & Management, 2.
- Brave, S., & Fisher, JDM. (2004). In search of a robust inflation forecast. Federal Reserve Bank of Chicago, Economic Perspectives, 28(4), 11–31.
- Buncic. D. & G-M. Frey. (2012). Forecasting commodity currencies with dynamic Bayesian Models. Working paper, Institute of Mathematics and Statistics, University of St Gallen, Switzerland.
- Buncic, D., & Moretto, C. (2015). Forecasting copper prices with dynamic averaging and selection models. North American Journal of Economics and Finance, 33, 1–38.
- Cafaie, M. & Ghassemi, H. (2012). Investigating Determinants of Iran’s Inflation, with the Use of Bayesian Averaging Approach.Journal of Economics and Modelling. 2( 7-8) ,27-58 (In Persian).
- Canova, F. (2007). G-7 inflation forecasts: random walk, Phillips Curve or what else? Macroeconomic Dynamics, 11, 1–30.
- Carnot N., Koen, V., & Tissot, B. (2005). Economic forecasting, Palgrave Macmillan.
- Cechetti, SG. (1995). Inflation indicators and inflation policy. Working paper 5161, NBER.
- Chernov, M., & Mueller, P. (2012). The term structure of inflation expectations. Journal of Financial Economics, 106(2), 367–394.
- Clark, T. E. (1995). Do Producer Prices Lead Consumer Prices?, Economic Review-Federal Reserve Bank of Kansas City, 80(3), 25 – 39.
- Cogley, T., Morozov, S. & Sargent, T. (2005). Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system. Journal of Economic Dynamics and Control, 29, 1893–1925.
- Cogley, T. & Sargent, T. (2005). Drifts and volatilities: monetary policies and outcomes in The post WWII U.S., Review of Economic Dynamics, 8, 262–302.
- Cremers, K. (2002). Stock Return Predictability: A Bayesian Model Selection Perspective, Review of Financial Studies, 15, 1223–1249.
- Cristadoro, R., Venditti, F., & Saporito, G. (2008). Forecasting inflation and tracking monetary policy in the euro area does national information help? ECB working paper series, 900.
- De Bruyn, R., Gupta, R., & van Eyden, R. (2013). Forecasting the rand–dollar and rand–pound exchange rates using dynamic model averaging. Working paper 2013-07, University of Pretoria.
- Dupasquier, C., & Ricketts, N. (1998). Non-linearities in the output–inflation relationship: some empirical results for Canada. Working paper 98-14, Bank of Canada.
- Eickmeier, S., & Ziegler, C. (2006). How good are dynamic factor models at forecasting output and inflation? A meta-analytic approach. Discussion paper, series 1: economic studies, no. 42/2006, Research Centre, Deutsche Bundesbank.
- Elliott, G., & Timmermann, A. (2013). Handbook of economic forecasting, north Holland, Handbook of Economic Forecasting, Volume 2.
- Ferreira, D., & Palma, A. (2015). Forecasting Inflation with the Phillips Curve: A Dynamic Model Averaging Approach for Brazil, Revista Brasileira de Economia, 69(4), 451-465.
- Filippo, D.G. (2015). Dynamic Model Averaging and CPI Inflation Forecasts: A Comparison between the Euro Area and the United States. Journal of Forecasting, 34(8), 619–648.
- Fisher, JDM., Liu, CT., & Zhou, R. ( 2002). When can we forecast inflation?, Economic Perspectives, 26(1), 32–44.
- Gonzalo, C-M., & Kapetanios, G. (2005). Forecasting euro area inflation using dynamic factor measures of underlying inflation, Journal of Forecasting, 24(7), 491–503.
- Grassi, S., & De Magistris, P.S. (2015). It's all about volatility (of volatility): Evidence from a two-factor stochastic volatility model
, Journal of Empirical Finance, 60, 62-78.
- Groen, J., Paap, R., & Ravazzolo, F. (2010). Real-time Inflation Forecasting in a Changing World, Federal Reserve Bank of New York Staff Report Number 388.
- Hofmann, B. (2008). Do monetary indicators lead euro area inflation?, ECB working paper 867.
- Holden, K., Peel, D.A., & Thompson, J.L. (1999). Economic forecasting: an introduction, Cambridge University Press.
- Huang, J-z., & Grishchenko, OV. (2011).Inflation risk premium: evidence from the TIPS market. Finance and Economics Discussion, Federal Reserve Board.
- Kim, C-J., & Nelson, CR. (1998). State-Space Models with Regime-Switching: Classical and Gibbs-Sampling Approaches with Applications. MIT Press: Cambridge, MA.
- Klein, L. (1950). Economic Fluctuations in the United States: 1921-1941, New York: Wiley.
- Koop, G., & Korobilis, D. (2011). UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so?. Economic Modelling, 28, 2307–2318.
- Koop, G., & Korobilis, D. (2012). Forecasting Inflation Using Dynamic Model Averaging, International Economic Review, 53(3), 867-886.
- Koop, G., & Potter, S. (2004). Forecasting in dynamic factor models using Bayesian model averaging. The Econometrics Journal, 7, 550–565.
- Koop, G., & Tole, L. (2012). Forecasting the European carbon market. Journal of the Royal Statistical Society, Series A, 176(3), 723–741.
- Lansing, KJ. (2002). Can the Phillips curve help forecast inflation? Economic Letter No. 2002-29, Federal Reserve Bank of San Francisco.
- Lenza, M. (2006). Does money help to forecast inflation in the euro area? Working paper, European Central Bank.
- Meyler, A., Kenny, G., & Quinn, T. (1998). Forecasting Irish inflation using ARIMA models. Central Bank and Financial Services Authority of Ireland Technical Paper Series, 3/RT/98: 1–48.
- Naser, H. & Alaali, F. (2018). Can Oil Prices Help Predict US Stock Market Returns: An Evidence Using a DMA Approach? Empirical Economics, 55(4), 1757-1777.
- Nicoletti, G., & Passaro, R. (2012). Sometimes it helps: the evolving predictive power of spreads on GDP dynamics. ECB working paper series 1447.
- Orphanides, A., & van Norden, S. (2005). The reliability of inflation forecast based on output gap estimates in real time. Journal of Money, Credit, and Banking, 37(3), 583–600.
- Pesaran, M. H., & Timmermann, A. (2000). A Recursive Modelling Approach to Predicting UK Stock Returns, The Economic Journal, 110, 159–91.
- Primiceri, G. (2005). Time Varying Structural Autoregressions and Monetary Policy. Review of Economic Studies, 72, 821-852.
- Raftery, A., Karny, M., Andrysek. J., & Ettler, P. (2007). Online prediction under model uncertainty via dynamic model averaging: application to a cold rolling mill. Technical report, 525. Department of Statistics, University of Washington.
- Raftery, A., Karny, M., & Ettler, P. (2010). Online prediction under model uncertainty via dynamic model averaging: application to a cold rolling mill. Technometrics, 52(1), 52–66.
- Stock, J. & Watson, M. (1999). Forecasting Inflation, Journal of Monetary Economics, 44, 293–335.
- Stock, JH., & Watson, MW. (2003). Forecasting output and inflation: the role of asset prices. Journal of Economic Literature, 41(3), 788–829.
- Stock, JH., & Watson, MW. (2007). Why has US inflation become harder to forecast? Journal of Money, Credit, and Banking 39(Suppl. 1), 3–33.
- Stock, JH., & Watson, MW. (2008). Phillips Curve Inflation Forecasts, NBER Working Paper No. 14322.
- Tinbergen, J. (1939). Business Cycles in the United States: 1912–1932. League of Nations.
- Tiwari, A. K., Mutascu, M. & Andries, M. A. (2012). An Empirical Investigation of Causality between Producers' Price and Consumers' Price Indices in Australia in Frequency Domain. Economic Modelling, 29(5), 1571 – 1578.
- Tobias, A., & Wu, H. (2010). The term structure of inflation expectations. Staff report no. 362, Federal Reserve Bank of New York.
- Wright, JH. (2009). Forecasting US inflation by Bayesian model averaging. Journal of Forecasting, 28(2), 131–144.
- Yazdani, M. & Pirpour, H. (2016).The Determinants of Export of Technical and Engineering Services in Iran: Seasonal Co-integration Approach.Quarterly Journal of Quantitative Economics. 12(4), 91-118(In Persian).
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