{"title":"Estimating DSGE Models with Unknown Data Persistence","authors":"Gianluca Moretti, G. Nicoletti","doi":"10.2139/ssrn.1670091","DOIUrl":"https://doi.org/10.2139/ssrn.1670091","url":null,"abstract":"Recent empirical literature shows that key macro variables such as GDP and productivity display long memory dynamics. For DSGE models, we propose a i?½Generalizedi?½ Kalman Filter to deal effectively with this problem: our method connects to and innovates upon data-filtering techniques already used in the DSGE literature. We show our method produces more plausible estimates of the deep parameters as well as more accurate out-of-sample forecasts of macroeconomic data.","PeriodicalId":291338,"journal":{"name":"ERN: Forecasting & Simulation (Production) (Topic)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125490841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal Monetary Policy with Durable Consumption Goods and Factor Demand Linkages","authors":"Ivan Petrella, E. Santoro","doi":"10.2139/ssrn.1690189","DOIUrl":"https://doi.org/10.2139/ssrn.1690189","url":null,"abstract":"This paper deals with the implications of factor demand linkages for monetary policy design. We consider a dynamic general equilibrium model with two sectors that produce durable and non-durable goods, respectively. Part of the output of each sector serves as a production input in both sectors, in accordance with a realistic input-output structure. Strategic complementarities induced by factor demand linkages significantly alter the transmission of exogenous shocks and amplify the loss of social welfare under optimal monetary policy, compared to what is observed in standard two-sector models. The distinction between value added and gross output that naturally arises in this context is of key importance to explore the welfare properties of the model economy. A flexible inflation targeting regime is close to optimal only if the central bank balances inflation and value added variability. Otherwise, targeting gross output variability entails a substantial increase in the loss of welfare.","PeriodicalId":291338,"journal":{"name":"ERN: Forecasting & Simulation (Production) (Topic)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133569555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Challenges for Estimating and Forecasting Macroeconomic Trends During Financial Crises: Implications for Counter-Cyclical Policies","authors":"Pingfan Hong","doi":"10.2139/ssrn.1453009","DOIUrl":"https://doi.org/10.2139/ssrn.1453009","url":null,"abstract":"The short article is focused on four issues associated with challenges in estimating and forecasting economic trends during financial crises: difficulties in forecasting the eruption of a large-scaled financial crisis, evaluation of some high-frequency modeling techniques, comparison of two quarterly GDP indicators in their value for defining the turning point, and discussion of how to estimate potential output.","PeriodicalId":291338,"journal":{"name":"ERN: Forecasting & Simulation (Production) (Topic)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115377357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karim Barhoumi, Szilárd Benk, Riccardo Cristadoro, Ard H. J. den Reijer, A. Jakaitienė, P. Jelonek, A. Rúa, Gerhard Rünstler, Karsten Ruth, C. V. Nieuwenhuyze
{"title":"Short-Term Forecasting of GDP Using Large Monthly Datasets – A Pseudo Real-Time Forecast Evaluation Exercise","authors":"Karim Barhoumi, Szilárd Benk, Riccardo Cristadoro, Ard H. J. den Reijer, A. Jakaitienė, P. Jelonek, A. Rúa, Gerhard Rünstler, Karsten Ruth, C. V. Nieuwenhuyze","doi":"10.2139/ssrn.1685265","DOIUrl":"https://doi.org/10.2139/ssrn.1685265","url":null,"abstract":"This paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best.","PeriodicalId":291338,"journal":{"name":"ERN: Forecasting & Simulation (Production) (Topic)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127991824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Oil and the U.S. Macroeconomy: An Update and a Simple Forecasting Exercise","authors":"Kevin L. Kliesen","doi":"10.2139/ssrn.1124028","DOIUrl":"https://doi.org/10.2139/ssrn.1124028","url":null,"abstract":"Recently, some analysts and economists had warned that the U.S. economy faces a much higher risk of falling into a recession should the price of oil rise to $100 per barrel or more. In February 2008, spot crude oil prices closed above $100 per barrel for the first time ever, and they have since climbed even further. Meanwhile, according to some surveys of economists, there is a high probability that a recession in the United States began in late 2007 or early 2008. Although the findings in this paper are consistent with the view that the U.S. economy has become much less sensitive to large changes in oil prices, a simple forecasting exercise reveals that a permanent increase in the price of crude oil to $150-per barrel-by the end of 2008 would have a significant negative effect on the growth rate of real GDP in the short run. However, the exercise also predicts such an increase in oil prices would have minimal effect on future inflation.","PeriodicalId":291338,"journal":{"name":"ERN: Forecasting & Simulation (Production) (Topic)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121837314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}