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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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  1. Back to the present: Learning about the euro area through a now-casting model. (2024). Giannone, Domenico ; Modugno, Michele ; Cascaldi-Garcia, Danilo.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:40:y:2024:i:2:p:661-686.

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  2. The effect of macroeconomic news announcements on the implied volatility of commodities: The role of survey releases. (2023). Lopez, Raquel ; Fernandezperez, Adrian.
    In: Journal of Futures Markets.
    RePEc:wly:jfutmk:v:43:y:2023:i:11:p:1499-1530.

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  3. Leading indicators for the US housing market: New empirical evidence and thoughts about implications for risk managers and ESG investors. (2023). Wegener, Christoph ; Saft, Danilo ; Desmyter, Steven ; Basse, Tobias.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:89:y:2023:i:c:s1057521923002818.

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  4. Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms. (2023). Xu, Hao ; Ni, HE ; Zhang, Qin.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:122:y:2023:i:c:s0264999323000160.

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  5. Monitoring and forecasting COVID-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries. (2022). Chen, Rui ; Hu, Jihao.
    In: Current Issues in Tourism.
    RePEc:taf:rcitxx:v:25:y:2022:i:3:p:490-507.

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  6. Application of the Real-Time Tourism Data in Nowcasting the Service Consumption in Taiwan. (2022). Su, Rui-Jun ; Hsiao, Yi-Long ; Ting, Chien-Jung.
    In: Journal of Applied Finance & Banking.
    RePEc:spt:apfiba:v:12:y:2022:i:4:f:12_4_4.

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  7. Nowcasting the GDP in Taiwan and the Real-Time Tourism Data. (2022). Hsiao, Yi-Long ; Ting, Chien-Jung.
    In: Advances in Management and Applied Economics.
    RePEc:spt:admaec:v:12:y:2022:i:3:f:12_3_2.

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  8. Development Of Composite Indicators Of Cyclical Response In Business Surveys Considering The Specifics Of The ‘Covid-19 Economy’. (2021). Lipkind, Tamara ; Kitrar, Liudmila.
    In: HSE Working papers.
    RePEc:hig:wpaper:121sti2021.

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  9. Back to the Present: Learning about the Euro Area through a Now-casting Model. (2021). Modugno, Michele ; Giannone, Domenico ; Cascaldi-Garcia, Danilo ; Revil, Thiago.
    In: International Finance Discussion Papers.
    RePEc:fip:fedgif:1313.

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  10. Forecasting UK GDP growth with large survey panels. (2021). Kapetanios, George ; Kalamara, Eleni ; Anesti, Nikoleta.
    In: Bank of England working papers.
    RePEc:boe:boeewp:0923.

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  11. Mixed?frequency Bayesian predictive synthesis for economic nowcasting. (2021). McAlinn, Kenichiro.
    In: Journal of the Royal Statistical Society Series C.
    RePEc:bla:jorssc:v:70:y:2021:i:5:p:1143-1163.

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  12. Business cycle synchronization or business cycle transmission? The effect of the German slowdown on the Italian economy.. (2021). Mistretta, Alessandro.
    In: Temi di discussione (Economic working papers).
    RePEc:bdi:wptemi:td_1346_21.

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  13. Intertemporal variation in the information content of aggregate earnings and its effect on the aggregate earnings-return relation. (2020). Kim, Jaewoo ; Land, Hunter ; Wasley, Charles ; Schonberger, Bryce.
    In: Review of Accounting Studies.
    RePEc:spr:reaccs:v:25:y:2020:i:4:d:10.1007_s11142-020-09538-9.

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  14. Advance Layoff Notices and Labor Market Forecasting. (2020). Lunsford, Kurt ; Krolikowski, Pawel .
    In: Working Papers.
    RePEc:fip:fedcwq:87416.

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  15. A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth. (2020). Cheung, Calista ; Chernis, Tony ; Velasco, Gabriella.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:3:p:851-872.

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  16. Impact of manufacturing PMI on stock market index: A study on Turkey. (2020). Ozturk, Ozcan ; Osman, Asfia Binte ; Yanik, Ramazan.
    In: Journal of Administrative and Business Studies.
    RePEc:apb:jabsss:2020:p:104-108.

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  17. A PMI-Based Real GDP Tracker for the Euro Area. (2019). de Bondt, Gabe.
    In: Journal of Business Cycle Research.
    RePEc:spr:jbuscr:v:15:y:2019:i:2:d:10.1007_s41549-018-0032-2.

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  18. Macroeconomic news and market reaction: Surprise indexes meet nowcasting. (2019). Caruso, Alberto.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:35:y:2019:i:4:p:1725-1734.

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  19. Inflation expectations in India: Learning from household tendency surveys. (2019). Lahiri, Kajal ; Das, Abhiman ; Zhao, Yongchen.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:35:y:2019:i:3:p:980-993.

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  20. Extracting information on economic activity from business and consumer surveys in an emerging economy (Chile). (2019). Pedersen, Michael ; Figueroa, Camila.
    In: Journal Economía Chilena (The Chilean Economy).
    RePEc:chb:bcchec:v:22:y:2019:i:3:p:098-131.

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  21. Nowcasting Recessions using the SVM Machine Learning Algorithm. (2019). Qiao, Xiao ; Abu-Mostafa, Yaser S ; James, Alexander.
    In: Papers.
    RePEc:arx:papers:1903.03202.

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  22. Inflation Expectations in India: Learning from Household Tendency Surveys. (2018). Zhao, Yongchen ; Lahiri, Kajal ; Das, Abhiman.
    In: Working Papers.
    RePEc:tow:wpaper:2018-03.

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  23. Is PMI Useful in Quarterly GDP Growth Forecasts for India? An Exploratory Note. (2018). Coondoo, Dipankor ; Das, Sangeeta.
    In: Journal of Quantitative Economics.
    RePEc:spr:jqecon:v:16:y:2018:i:1:d:10.1007_s40953-017-0116-1.

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  24. Herding and anchoring in macroeconomic forecasts: the case of the PMI. (2018). Broughton, John B ; Lobo, Bento J.
    In: Empirical Economics.
    RePEc:spr:empeco:v:55:y:2018:i:3:d:10.1007_s00181-017-1306-6.

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  25. Improving the usefulness of the Purchasing Managers’ Index. (2018). Pelaez, Rolando F.
    In: Business Economics.
    RePEc:pal:buseco:v:53:y:2018:i:4:d:10.1057_s11369-018-0092-2.

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  26. Big Data & Macroeconomic Nowcasting: Methodological Review. (2018). Papailias, Fotis ; Kapetanios, George.
    In: Economic Statistics Centre of Excellence (ESCoE) Discussion Papers.
    RePEc:nsr:escoed:escoe-dp-2018-12.

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  27. Forecasting with Many Predictors: How Useful are National and International Confidence Data?. (2018). Rherrad, Imad ; Moran, Kevin ; Nono, Simplice Aime.
    In: Cahiers de recherche.
    RePEc:lvl:crrecr:1814.

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  28. Nowcasting with the help of foreign indicators: The case of Mexico. (2018). Caruso, Alberto.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:69:y:2018:i:c:p:160-168.

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  29. A dynamic factor model for nowcasting Canadian GDP growth. (2017). Sekkel, Rodrigo ; Chernis, Tony.
    In: Empirical Economics.
    RePEc:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-017-1254-1.

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  30. Forecasting economic activity by Bayesian bridge model averaging. (2017). Marcellino, Massimiliano ; Bencivelli, Lorenzo ; Moretti, Gianluca .
    In: Empirical Economics.
    RePEc:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-016-1199-9.

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  31. The role of indicator selection in nowcasting euro-area GDP in pseudo-real time. (2017). Golinelli, Roberto ; Girardi, Alessandro ; Pappalardo, Carmine .
    In: Empirical Economics.
    RePEc:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-016-1151-z.

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  32. Mixed-frequency models for tracking short-term economic developments in Switzerland. (2017). Scheufele, Rolf ; Hepenstrick, Christian ; Galli, Alain ; Alain, Rolf Scheufele .
    In: Working Papers.
    RePEc:snb:snbwpa:2017-02.

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  33. Macroeconomic nowcasting and forecasting with big data. (2017). Tambalotti, Andrea ; Sbordone, Argia ; Giannone, Domenico ; Bok, Brandyn ; Caratelli, Daniele.
    In: Staff Reports.
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  34. Business tendency surveys and macroeconomic fluctuations. (2017). Scheufele, Rolf ; Kaufmann, Daniel.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:33:y:2017:i:4:p:878-893.

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  35. A now-casting model for Canada: Do U.S. variables matter?. (2017). Modugno, Michele ; Bragoli, Daniela.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:33:y:2017:i:4:p:786-800.

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  36. Now-casting the Japanese economy. (2017). Bragoli, Daniela.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:33:y:2017:i:2:p:390-402.

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  37. The new MIBA model: Real-time nowcasting of French GDP using the Banque de Frances monthly business survey. (2017). Mogliani, Matteo ; Darné, Olivier ; Pluyaud, Bertrand ; Darne, Olivier.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:64:y:2017:i:c:p:26-39.

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  38. Measuring real business condition in China. (2017). Hueng, C. ; Liu, Ping.
    In: China Economic Review.
    RePEc:eee:chieco:v:46:y:2017:i:c:p:261-274.

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  39. A Dynamic Factor Model for Nowcasting Canadian GDP Growth. (2017). Chernis, Tony ; Sekkel, Rodrigo.
    In: Staff Working Papers.
    RePEc:bca:bocawp:17-2.

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  40. Determinants of Consumer Sentiment over Business Cycles: Evidence from the U.S. Surveys of Consumers. (2016). Zhao, Yongchen ; Lahiri, Kajal.
    In: Working Papers.
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  41. Determinants of Consumer Sentiment Over Business Cycles: Evidence from the US Surveys of Consumers. (2016). Zhao, Yongchen ; Lahiri, Kajal.
    In: Journal of Business Cycle Research.
    RePEc:spr:jbuscr:v:12:y:2016:i:2:d:10.1007_s41549-016-0010-5.

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  42. Foreign PMIs: A reliable indicator for exports?. (2016). Scheufele, Rolf ; Hanslin Grossmann, Sandra.
    In: Working Papers.
    RePEc:snb:snbwpa:2016-01.

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  43. PMI Thresholds for GDP Growth. (2016). Yücel, Mustafa ; Kilinc, Zubeyir.
    In: MPRA Paper.
    RePEc:pra:mprapa:70929.

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  44. A Nowcasting Model for Canada: Do U.S. Variables Matter?. (2016). Modugno, Michele ; Bragoli, Daniela.
    In: Finance and Economics Discussion Series.
    RePEc:fip:fedgfe:2016-36.

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  45. Nowcasting GDP in Greece: The impact of data revisions and forecast origin on model selection and performance. (2016). Lamprou, Dimitra .
    In: The Journal of Economic Asymmetries.
    RePEc:eee:joecas:v:14:y:2016:i:pa:p:93-102.

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  46. Forecasting and nowcasting economic growth in the euro area using factor models. (2016). Koopman, Siem Jan ; de Winter, Jasper ; Hindrayanto, Irma.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:32:y:2016:i:4:p:1284-1305.

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  47. Nowcasting Czech GDP in real time. (2016). Rusnák, Marek ; Rusnak, Marek .
    In: Economic Modelling.
    RePEc:eee:ecmode:v:54:y:2016:i:c:p:26-39.

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  48. Improving model-based near-term GDP forecasts by subjective forecasts: A real-time exercise for the G7 countries. (2016). Jansen, W. Jos ; de Winter, Jasper.
    In: DNB Working Papers.
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  49. Foreign PMIs: A reliable indicator for Swiss exports. (2015). Scheufele, Rolf ; Hanslin Grossmann, Sandra.
    In: Annual Conference 2015 (Muenster): Economic Development - Theory and Policy.
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  50. Forecasting Consumption: The Role of Consumer Confidence in Real Time with many Predictors. (2015). Zhao, Yongchen ; Monokroussos, George ; Lahiri, Kajal.
    In: Working Papers.
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  51. Business tendency surveys and macroeconomic fluctuations. (2015). Scheufele, Rolf ; Kaufmann, Daniel.
    In: KOF Working papers.
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  52. Nowcasting Business Cycles: a Bayesian Approach to Dynamic Heterogeneous Factor Models. (2015). Modugno, Michele ; Lenza, Michele ; Giannone, Domenico ; D'Agostino, Antonello.
    In: Finance and Economics Discussion Series.
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  53. Shaping the manufacturing industry performance: MIDAS approach. (2015). Sensoy, Ahmet ; Turhan, Ibrahim M ; Hacihasanoglu, Erk.
    In: Chaos, Solitons & Fractals.
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  54. Confidence Matters for Current Economic Growth: Empirical Evidence for the Euro Area and the United States. (2015). de Bondt, Gabe ; Schiaffi, Stefano .
    In: Social Science Quarterly.
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  55. A multi-country approach to forecasting output growth using PMIs. (2014). Pesaran, M ; Chudik, Alexander ; Grossman, Valerie.
    In: Globalization Institute Working Papers.
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  56. Real-time GDP forecasting for Japan: A dynamic factor model approach. (2014). Urasawa, Satoshi.
    In: Journal of the Japanese and International Economies.
    RePEc:eee:jjieco:v:34:y:2014:i:c:p:116-134.

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  57. A Multi-Country Approach to Forecasting Output Growth Using PMIs. (2014). Pesaran, M ; Chudik, Alexander ; Grossman, Valerie.
    In: CESifo Working Paper Series.
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    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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