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Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences. (2014). Potter, Simon ; Peach, Richard ; onorante, luca ; Ghysels, Eric ; Alessi, Luci .
In: Staff Reports.
RePEc:fip:fednsr:680.

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  1. Out of Bounds: Do SPF Respondents Have Anchored Inflation Expectations?. (2023). Verbrugge, Randal ; Janson, Wesley ; Binder, Carola.
    In: Journal of Money, Credit and Banking.
    RePEc:wly:jmoncb:v:55:y:2023:i:2-3:p:559-576.

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  2. Censored density forecasts: Production and evaluation. (2023). Mitchell, James ; Weale, Martin.
    In: Journal of Applied Econometrics.
    RePEc:wly:japmet:v:38:y:2023:i:5:p:714-734.

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  3. Economic forecasting in a pandemic: some evidence from Singapore. (2023). Choy, Keen Meng ; Chow, Hwee Kwan.
    In: Empirical Economics.
    RePEc:spr:empeco:v:64:y:2023:i:5:d:10.1007_s00181-022-02311-8.

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  4. A snapshot of Central Bank (two year) forecasting: a mixed picture. (2023). Pradhan, Manoj ; Goodhart, C. A. E., .
    In: LSE Research Online Documents on Economics.
    RePEc:ehl:lserod:118680.

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  5. Central Bank Forecasting: A Survey. (2023). Sekkel, Rodrigo ; Binder, Carola Conces.
    In: Staff Working Papers.
    RePEc:bca:bocawp:23-18.

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  6. Evaluating the Eurosystem/ECB staff macroeconomic projections: The first 20 years. (2022). Lambrias, Kyriacos ; Kontogeorgos, G.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:41:y:2022:i:2:p:213-229.

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  7. Do expert experience and characteristics affect inflation forecasts?. (2022). Saadon, Yossi ; El-Shagi, Makram ; Benchimol, Jonathan.
    In: Journal of Economic Behavior & Organization.
    RePEc:eee:jeborg:v:201:y:2022:i:c:p:205-226.

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  8. Analyzing and forecasting Thai macroeconomic data using mixed-frequency approach. (2022). Wichitaksorn, Nuttanan.
    In: Journal of Asian Economics.
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  12. Combining shrinkage and sparsity in conjugate vector autoregressive models. (2021). Huber, Florian ; Onorante, Luca ; Hauzenberger, Niko.
    In: Journal of Applied Econometrics.
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  13. Expecting the unexpected: economic growth under stress. (2021). Ruiz, Esther ; Rodriguez-Caballero, Vladimir ; Gonzalez-Rivera, Gloria.
    In: Working Papers.
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  14. What Does Below, but Close to, 2 Percent Mean? Assessing the ECBs Reaction Function with Real-Time Data. (2021). Jalasjoki, Pirkka ; Haavio, Markus ; Paloviita, Maritta ; Kilponen, Juha.
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  15. ???????????? ?? ????????? ??????? ??? ???????? ? ????? ???????? ?????????. (2021). Telarico, Fabio Ashtar.
    In: Post-Print.
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  16. New York FED Staff Nowcasts and Reality: What Can We Learn about the Future, the Present, and the Past?. (2021). Siliverstovs, Boriss.
    In: Econometrics.
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  17. Forecasting tourism recovery amid COVID-19. (2021). Liu, Chang ; Wen, Long ; Song, Haiyan ; Zhang, Hanyuan.
    In: Annals of Tourism Research.
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  18. Expecting the unexpected: economic growth under stress. (2021). Gonzalezrivera, Gloria ; Rodriguez, Carlos Vladimir ; Ortega, Esther Ruiz.
    In: DES - Working Papers. Statistics and Econometrics. WS.
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  19. Holding the Economy by the Tail: Analysis of Short- and Long-run Macroeconomic Risks. (2021). Franta, Michal ; Libich, Jan.
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  20. The bias and efficiency of the ECB inflation projections: a State dependent analysis. (2021). Paloviita, Maritta ; Jalasjoki, Pirkka ; Granziera, Eleonora.
    In: Research Discussion Papers.
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  21. The Bias and Efficiency of the ECB Inflation Projections: a State Dependent Analysis. (2021). Jalasjoki, Pirkka ; Granziera, Eleonora ; Paloviita, Maritta.
    In: Working Paper.
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  22. Forecasting pandemic tax revenues in a small, open economy. (2021). Telarico, Fabio Ashtar.
    In: Papers.
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  23. Expecting the unexpected: economic growth under stress. (2021). Ortega, Esther Ruiz ; Rodriguez-Caballero, Carlos Vladimir ; Gonzalez-Rivera, Gloria.
    In: CREATES Research Papers.
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  24. .

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  25. Nowcasting Finnish GDP growth using financial variables: a MIDAS approach. (2020). Lindblad, Annika ; Laine, Olli-Matti.
    In: BoF Economics Review.
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  26. Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors. (2020). Swanson, Norman ; Guney, Ethem I ; Cepni, Oguzhan.
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  27. Does the price of crude oil help predict the conditional distribution of aggregate equity return?. (2020). Nonejad, Nima.
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  28. Do Expert Experience and Characteristics Affect Inflation Forecasts?. (2020). Saadon, Yossi ; Benchimol, Jonathan ; El-Shagi, Makram.
    In: CFDS Discussion Paper Series.
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  29. Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them. (2020). Rossi, Barbara.
    In: CEPR Discussion Papers.
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  30. UK regional nowcasting using a mixed frequency vector auto?regressive model with entropic tilting. (2020). Mitchell, James ; McIntyre, Stuart ; Koop, Gary.
    In: Journal of the Royal Statistical Society Series A.
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  31. Forecasting in the presence of instabilities: How do we know whether models predict well and how to improve them. (2019). Rossi, Barbara.
    In: Economics Working Papers.
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  32. Consumers’ approach to the credibility of the inflation forecasts published by central banks: A new methodological solution. (2019). Tura-Gawron, Karolina.
    In: Journal of Macroeconomics.
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  33. DSGE forecasts of the lost recovery. (2019). Giannoni, Marc ; Moszkowski, Erica ; Li, Pearl ; Gupta, Abhi ; del Negro, Marco ; Cai, Michael.
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  34. Financial nowcasts and their usefulness in macroeconomic forecasting. (2019). Zaman, Saeed ; Knotek, Edward S.
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  35. An analysis of the Eurosystem/ECB projections. (2019). Lambrias, Kyriacos ; Kontogeorgos, Georgios.
    In: Working Paper Series.
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  36. On the consistency of central banks´ interest rate forecasts. (2019). Jung, Jin-Kyu ; Rlke, Jan-Christoph ; Frenkel, Michael.
    In: Economics Bulletin.
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  37. Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them. (2019). Rossi, Barbara.
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  38. The Evolution of Forecast Density Combinations in Economics. (2018). van Dijk, Herman ; Mitchell, James ; Aastveit, Knut Are ; Ravazzolo, Francesco.
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  40. Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach. (2018). Cobb, Marcus.
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  41. UK Regional Nowcasting using a Mixed Frequency Vector Autoregressive Model. (2018). Mitchell, James ; McIntyre, Stuart ; Koop, Gary.
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  42. Gold and crude oil prices after the great moderation. (2018). Sephton, Peter ; Mann, Janelle.
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  43. On the formation of inflation expectations in turbulent times: The case of the euro area. (2018). Paloviita, Maritta ; Łyziak, Tomasz.
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  44. The first twenty years of the European Central Bank: monetary policy. (2018). Hartmann, Philipp ; Smets, Frank.
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  45. The European Central Bank’s Monetary Policy during Its First 20 Years. (2018). Smets, Frank ; Hartman, Philipp.
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  46. Model uncertainty in macroeconomics: On the implications of financial frictions. (2017). Wieland, Volker ; Lieberknecht, Philipp ; Quintana, Jorge ; Binder, Michael.
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  47. What Has Publishing Inflation Forecasts Accomplished? Central Banks And Their Competitors. (2017). Siklos, Pierre.
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  48. Joint Forecast Combination of Macroeconomic Aggregates and Their Components. (2017). Cobb, Marcus.
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  49. Evidence for a Presource Curse? Oil discoveries, Elevated Expectations, and Growth Disappointments. (2017). Cust, James ; Mihalyi, David .
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  50. Forecasting GDP with global components: This time is different. (2017). Thorsrud, Leif ; Ravazzolo, Francesco ; Bjørnland, Hilde.
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  51. Model Uncertainty in Macroeconomics: On the Implications of Financial Frictions. (2017). Wieland, Volker ; Lieberknecht, Philipp ; Quintana, Jorge ; Binder, Michael.
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  52. What does “below, but close to, two percent” mean? Assessing the ECB’s reaction function with real time data. (2017). Paloviita, Maritta ; Kilponen, Juha ; Jalasjoki, Pirkka ; Haavio, Markus.
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  53. Formation of inflation expectations in turbulent times : Can ECB manage inflation expectations of professional forecasters?. (2017). Paloviita, Maritta ; Łyziak, Tomasz.
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  6. Recovering historical inflation data from postal stamps prices. (2016). Franses, Philip Hans ; Janssens, E.
    In: Econometric Institute Research Papers.
    RePEc:ems:eureir:93332.

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  7. Yet another look at MIDAS regression. (2016). Franses, Philip Hans.
    In: Econometric Institute Research Papers.
    RePEc:ems:eureir:93331.

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  8. A comparison of MIDAS and bridge equations. (2016). Schumacher, Christian.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:2:p:257-270.

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  9. Estimating dynamic equilibrium models using mixed frequency macro and financial data. (2016). van der Wel, Michel ; Posch, Olaf ; Christensen, Bent Jesper.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:194:y:2016:i:1:p:116-137.

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  10. The estimation of continuous time models with mixed frequency data. (2016). Chambers, Marcus.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:193:y:2016:i:2:p:390-404.

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  11. On the use of high frequency measures of volatility in MIDAS regressions. (2016). Andreou, Elena.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:193:y:2016:i:2:p:367-389.

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  12. Macroeconomics and the reality of mixed frequency data. (2016). Ghysels, Eric.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:193:y:2016:i:2:p:294-314.

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  13. On the use of high frequency measures of volatility in MIDAS regressions. (2016). Andreou, Elena.
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:11307.

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  14. Nowcasting in Real Time Using Popularity Priors. (2015). Monokroussos, George.
    In: MPRA Paper.
    RePEc:pra:mprapa:68594.

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  15. Benchmarking Liquidity Proxies: Accounting for Dynamics and Frequency Issues. (2015). Papanagiotou, Evangelia ; Monokroussos, George ; Langedijk, Sven.
    In: MPRA Paper.
    RePEc:pra:mprapa:61865.

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  16. Revisiting the transitional dynamics of business-cycle phases with mixed frequency data. (2015). .
    In: Post-Print.
    RePEc:hal:journl:hal-01276824.

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  17. The State and the Future of Cyprus Macroeconomic Forecasting. (2015). Andreou, Elena ; Kourtellos, Andros.
    In: Cyprus Economic Policy Review.
    RePEc:erc:cypepr:v:9:y:2015:i:1:p:73-90.

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  18. Does the Greenspan era provide evidence on leadership in the FOMC?. (2015). Jung, Alexander ; El-Shagi, Makram.
    In: Journal of Macroeconomics.
    RePEc:eee:jmacro:v:43:y:2015:i:c:p:173-190.

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  19. Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?. (2015). Mogliani, Matteo ; Bec, Frédérique.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:31:y:2015:i:4:p:1021-1042.

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  20. Do high-frequency financial data help forecast oil prices? The MIDAS touch at work. (2015). Kilian, Lutz ; Guérin, Pierre ; Baumeister, Christiane.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:31:y:2015:i:2:p:238-252.

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  21. Revisiting the transitional dynamics of business-cycle phases with mixed frequency data. (2015). .
    In: Economics Papers from University Paris Dauphine.
    RePEc:dau:papers:123456789/15246.

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  22. MIDAS regressions with time-varying parameters: An application to corporate bond spreads and GDP in the Euro area. (2014). Schumacher, Christian.
    In: Annual Conference 2014 (Hamburg): Evidence-based Economic Policy.
    RePEc:zbw:vfsc14:100289.

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  23. MIDAS and bridge equations. (2014). Schumacher, Christian.
    In: Discussion Papers.
    RePEc:zbw:bubdps:262014.

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  24. Default probabilities, CDS premiums and downgrades : A probit-MIDAS analysis. (2014). Freitag, Lennart ; Freitag L., .
    In: Research Memorandum.
    RePEc:unm:umagsb:2014038.

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  25. Testing for Cointegration with Temporally Aggregated and Mixed-frequency Time Series. (2014). Miller, J. ; Ghysels, Eric.
    In: Working Papers.
    RePEc:umc:wpaper:1307.

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  26. Forecasting Chinese GDP Growth with Mixed Frequency Data. (2014). Mikosch, Heiner ; Zhang, Ying.
    In: KOF Working papers.
    RePEc:kof:wpskof:14-359.

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  27. Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences. (2014). Potter, Simon ; Peach, Richard ; onorante, luca ; Ghysels, Eric ; Alessi, Luci .
    In: Staff Reports.
    RePEc:fip:fednsr:680.

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  28. Forecasting inflation using commodity price aggregates. (2014). Turnovsky, Stephen J ; Zivot, Eric ; Chen, Yu-Chin .
    In: Journal of Econometrics.
    RePEc:eee:econom:v:183:y:2014:i:1:p:117-134.

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  29. Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences. (2014). Potter, Simon ; Peach, Richard ; onorante, luca ; Alessi, Lucia ; Ghysels, Eric.
    In: Working Paper Series.
    RePEc:ecb:ecbwps:20141688.

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  30. Variable Selection in Predictive MIDAS Models. (2014). Marsilli, Clément.
    In: Working papers.
    RePEc:bfr:banfra:520.

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  31. Do High-Frequency Financial Data Help Forecast Oil Prices? The MIDAS Touch at Work. (2014). Kilian, Lutz ; Guérin, Pierre ; Baumeister, Christiane ; Guerin, Pierre .
    In: Staff Working Papers.
    RePEc:bca:bocawp:14-11.

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  32. Do high-frequency financial data help forecast oil prices? The MIDAS touch at work. (2013). Kilian, Lutz ; Guérin, Pierre ; Baumeister, Christiane.
    In: CFS Working Paper Series.
    RePEc:zbw:cfswop:201322.

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  33. Importance of the macroeconomic variables for variance prediction A GARCH-MIDAS approach. (2013). Asgharian, Hossein ; Hou, Aijun ; Javed, Farrukh .
    In: Knut Wicksell Working Paper Series.
    RePEc:hhs:luwick:2013_004.

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  34. Nowcasting US GDP: The role of ISM business surveys. (2013). Monokroussos, George ; Lahiri, Kajal.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:29:y:2013:i:4:p:644-658.

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  35. Changes in predictive ability with mixed frequency data. (2013). Galvão, Ana ; Galvo, Ana Beatriz.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:29:y:2013:i:3:p:395-410.

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  36. Advances in Forecasting under Instability. (2013). Rossi, Barbara.
    In: Handbook of Economic Forecasting.
    RePEc:eee:ecofch:2-1203.

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  37. Nowcasting GDP: Electronic Payments, Data Vintages and the Timing of Data Releases. (2013). Tkacz, Greg ; Galbraith, John.
    In: CIRANO Working Papers.
    RePEc:cir:cirwor:2013s-25.

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  38. Real-Time Forecast Density Combinations (Forecasting US GDP Growth Using Mixed-Frequency Data). (2012). Urbain, Jean-Pierre ; Hecq, Alain ; Götz, Thomas ; Gotz Thomas B., .
    In: Research Memorandum.
    RePEc:unm:umamet:2012021.

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  39. Forecasting Mixed Frequency Time Series with ECM-MIDAS Models. (2012). Urbain, Jean-Pierre ; Hecq, Alain ; Götz, Thomas.
    In: Research Memorandum.
    RePEc:unm:umamet:2012012.

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  40. Mixed-frequency Cointegrating Regressions with Parsimonious Distributed Lag Structures. (2012). Miller, J..
    In: Working Papers.
    RePEc:umc:wpaper:1211.

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  41. Predicting quarterly aggregates with monthly indicators. (2012). Winkelried, Diego.
    In: Working Papers.
    RePEc:rbp:wpaper:2012-023.

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  42. Testing the functional constraints on parameters in regressions with variables of different frequency. (2012). Zemlys, Vaidotas ; Kvedaras, Virmantas.
    In: Economics Letters.
    RePEc:eee:ecolet:v:116:y:2012:i:2:p:250-254.

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  43. U-MIDAS: MIDAS regressions with unrestricted lag polynomials. (2011). Schumacher, Christian ; Marcellino, Massimiliano ; Foroni, Claudia.
    In: Discussion Paper Series 1: Economic Studies.
    RePEc:zbw:bubdp1:201135.

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  44. Estimating VARs sampled at mixed or irregular spaced frequencies : a Bayesian approach. (2011). Kim, Tae Bong ; Foerster, Andrew ; Chiu, Ching-Wai (Jeremy) ; Seoane, Hernan D. ; Eraker, Bjorn .
    In: Research Working Paper.
    RePEc:fip:fedkrw:rwp11-11.

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  45. Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models. (2011). Chevallier, Julien.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:28:y:2011:i:6:p:2634-2656.

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  46. Advances in Forecasting Under Instability. (2011). Rossi, Barbara.
    In: Working Papers.
    RePEc:duk:dukeec:11-20.

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  47. Growth and chronic poverty: Evidence from rural communities in Ethiopia. (2011). Hoddinott, John ; Dercon, Stefan ; Woldehanna, Tassew.
    In: CSAE Working Paper Series.
    RePEc:csa:wpaper:2011-18.

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  48. Vector autoregression with varied frequency data. (2010). Qian, Hang.
    In: MPRA Paper.
    RePEc:pra:mprapa:34682.

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  49. Linear regression using both temporally aggregated and temporally disaggregated data: Revisited. (2010). Qian, Hang.
    In: MPRA Paper.
    RePEc:pra:mprapa:32686.

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  50. MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area. (2009). Schumacher, Christian ; Marcellino, Massimiliano ; Kuzin, Vladimir .
    In: CEPR Discussion Papers.
    RePEc:cpr:ceprdp:7445.

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