A quantile vector autoregressive (VAR) model, unlike standard VAR, traces the interaction among the endogenous random variables at any quantile. Quantile forecasts are obtained by factorizing the joint distribution in a recursive structure but cannot be obtained from reduced form estimation. Identification strategies and structural quantile impulse response functions are derived as generalization of the VAR model. The model is estimated using real and financial variables for the euro area. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks.
{"title":"Forecasting and Stress Testing with Quantile Vector Autoregression","authors":"Sulkhan Chavleishvili, S. Manganelli","doi":"10.2139/ssrn.3489065","DOIUrl":"https://doi.org/10.2139/ssrn.3489065","url":null,"abstract":"A quantile vector autoregressive (VAR) model, unlike standard VAR, traces the interaction among the endogenous random variables at any quantile. Quantile forecasts are obtained by factorizing the joint distribution in a recursive structure but cannot be obtained from reduced form estimation. Identification strategies and structural quantile impulse response functions are derived as generalization of the VAR model. The model is estimated using real and financial variables for the euro area. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127305842","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}
Purpose This study aims to address the issue of prediction of inflation differences for an economy that considers either fixing its exchange rate or joining a currency union. In this setting, individual countries have limited control over their inflation, and anticipating the possible course of domestic inflation relative to inflation abroad becomes an important input in policy-making. In this context, the author compares simple forecast heuristics and econometric modeling. Design/methodology/approach The study compares two basically different approaches. The first approach of forecasting consists of simple heuristics. Various heuristics are considered that differ with respect to the economic reasoning that goes into quantifying the forecast rules. The simplest such forecasting heuristic suggests that the average over all available observations of inflation differentials should be taken as a predictor for the future. Bringing more economic insight to bear suggests a further heuristic according to which historical inflation differentials should be adjusted for changes in the nominal exchange rate. A further variant of this approach suggests that a forecast should exclusively rely on data from earlier times under a pegged exchange rate. A fundamentally different approach to prediction builds on dynamic econometric models estimated by using all available historical data independent of the currency regime. Findings The author studies three small member countries of the Eurozone, i.e. Finland, Luxembourg and Portugal. For the evaluation of the various forecasting strategies, he performs out-of-sample predictions over a horizon of five years. The comparison of the four different forecasting strategies documents that the variant of the forecast heuristic that draws on data from earlier experiences under fixed exchange rates performs better than the forecast based on the estimated econometric model. Practical implications The findings of this study provide helpful guidelines for countries considering either joining a currency union or fixing their exchange rate. The author shows that a simple forecasting heuristic gives sound advice for assessing the likely course of inflation. Originality/value This study describes how economic theory can guide the selection of historical data for assessing likely future developments. The analysis shows that using a simple heuristic based on historical analogy can lead to better forecasts than the analytically more sophisticated approach of econometric modeling.
{"title":"Heuristics versus Econometrics as a Basis For Forecasting International Inflation Differentials","authors":"Tobias F. Rötheli","doi":"10.2139/ssrn.2799750","DOIUrl":"https://doi.org/10.2139/ssrn.2799750","url":null,"abstract":"\u0000Purpose\u0000This study aims to address the issue of prediction of inflation differences for an economy that considers either fixing its exchange rate or joining a currency union. In this setting, individual countries have limited control over their inflation, and anticipating the possible course of domestic inflation relative to inflation abroad becomes an important input in policy-making. In this context, the author compares simple forecast heuristics and econometric modeling.\u0000\u0000\u0000Design/methodology/approach\u0000The study compares two basically different approaches. The first approach of forecasting consists of simple heuristics. Various heuristics are considered that differ with respect to the economic reasoning that goes into quantifying the forecast rules. The simplest such forecasting heuristic suggests that the average over all available observations of inflation differentials should be taken as a predictor for the future. Bringing more economic insight to bear suggests a further heuristic according to which historical inflation differentials should be adjusted for changes in the nominal exchange rate. A further variant of this approach suggests that a forecast should exclusively rely on data from earlier times under a pegged exchange rate. A fundamentally different approach to prediction builds on dynamic econometric models estimated by using all available historical data independent of the currency regime.\u0000\u0000\u0000Findings\u0000The author studies three small member countries of the Eurozone, i.e. Finland, Luxembourg and Portugal. For the evaluation of the various forecasting strategies, he performs out-of-sample predictions over a horizon of five years. The comparison of the four different forecasting strategies documents that the variant of the forecast heuristic that draws on data from earlier experiences under fixed exchange rates performs better than the forecast based on the estimated econometric model.\u0000\u0000\u0000Practical implications\u0000The findings of this study provide helpful guidelines for countries considering either joining a currency union or fixing their exchange rate. The author shows that a simple forecasting heuristic gives sound advice for assessing the likely course of inflation.\u0000\u0000\u0000Originality/value\u0000This study describes how economic theory can guide the selection of historical data for assessing likely future developments. The analysis shows that using a simple heuristic based on historical analogy can lead to better forecasts than the analytically more sophisticated approach of econometric modeling.\u0000","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123430566","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}
Italian Abstract: Ricerca sulla situazione economica italiana basata sui dati economici ufficiali; vengono analizzati e confrontati con il passato il debito pubblico, le riserve ufficiali, il PIL, l'inflazione e la disoccupazione. English Abstract: Research into the state of the Italian economy based on official economic data; the current Sovereign Debt, Official Reserves, GDP, Inflation and Unemployment situation is presented and and compared with the past.
{"title":"Italia Economia a Metà 2018 (Italy: Economy in Mid-2018)","authors":"Maurizio Mazziero, Andrew Lawford, G. Serafini","doi":"10.2139/ssrn.3252336","DOIUrl":"https://doi.org/10.2139/ssrn.3252336","url":null,"abstract":"<b>Italian Abstract:</b> Ricerca sulla situazione economica italiana basata sui dati economici ufficiali; vengono analizzati e confrontati con il passato il debito pubblico, le riserve ufficiali, il PIL, l'inflazione e la disoccupazione. <b>English Abstract:</b> Research into the state of the Italian economy based on official economic data; the current Sovereign Debt, Official Reserves, GDP, Inflation and Unemployment situation is presented and and compared with the past.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114597903","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}
This paper examines point and density forecasts of real GDP growth, inflation and unemployment from the European Central Bank?s Survey of Professional Forecasters. We present individual uncertainty measures and introduce individual point- and density-based measures of disagreement. The data indicate substantial heterogeneity and persistence in respondents? uncertainty and disagreement, with uncertainty associated with prominent respondent effects and disagreement associated with prominent time effects. We also examine the co-movement between uncertainty and disagreement and find an economically insignificant relationship that is robust to changes in the volatility of the forecasting environment. This provides further evidence that disagreement is not a reliable proxy for uncertainty.
{"title":"A Closer Look at the Behavior of Uncertainty and Disagreement: Micro Evidence from the Euro Area","authors":"Robert W. Rich, Joseph S. Tracy","doi":"10.24149/wp1811","DOIUrl":"https://doi.org/10.24149/wp1811","url":null,"abstract":"This paper examines point and density forecasts of real GDP growth, inflation and unemployment from the European Central Bank?s Survey of Professional Forecasters. We present individual uncertainty measures and introduce individual point- and density-based measures of disagreement. The data indicate substantial heterogeneity and persistence in respondents? uncertainty and disagreement, with uncertainty associated with prominent respondent effects and disagreement associated with prominent time effects. We also examine the co-movement between uncertainty and disagreement and find an economically insignificant relationship that is robust to changes in the volatility of the forecasting environment. This provides further evidence that disagreement is not a reliable proxy for uncertainty.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126102897","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}
M. Miccoli, M. Riggi, Maria Lisa Rodano, Laura Sigalotti
Assessing underlying inflation developments is crucial for a correct calibration of the monetary policy stance. To monitor the adjustment in the path of euro area inflation towards the ECB’s definition of price stability, we select a number of indicators of price dynamics in the area. We then construct a composite index summarizing the information contained in those indicators by estimating several univariate probability models. The index, which provides a synthetic measure of inflationary pressures net of the most volatile components, can be interpreted as gauging the probability of inflation returning to 1.9 per cent or over within a given time horizon. Our findings, which are based on the information available in July 2017, signal that, despite the improvement in price dynamics since the beginning of the year, the adjustment of inflation rates towards levels below, but close to, 2 per cent over the medium term is still limited and far from being sustained.
{"title":"A Composite Index of Inflation Tendencies in the Euro Area","authors":"M. Miccoli, M. Riggi, Maria Lisa Rodano, Laura Sigalotti","doi":"10.2139/ssrn.3056283","DOIUrl":"https://doi.org/10.2139/ssrn.3056283","url":null,"abstract":"Assessing underlying inflation developments is crucial for a correct calibration of the monetary policy stance. To monitor the adjustment in the path of euro area inflation towards the ECB’s definition of price stability, we select a number of indicators of price dynamics in the area. We then construct a composite index summarizing the information contained in those indicators by estimating several univariate probability models. The index, which provides a synthetic measure of inflationary pressures net of the most volatile components, can be interpreted as gauging the probability of inflation returning to 1.9 per cent or over within a given time horizon. Our findings, which are based on the information available in July 2017, signal that, despite the improvement in price dynamics since the beginning of the year, the adjustment of inflation rates towards levels below, but close to, 2 per cent over the medium term is still limited and far from being sustained.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121568972","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}
This article characterises the level of uncertainty in the Spanish economy. Various indicators are analysed, distinguishing their source: financial market volatility, degree of disagreement between agents on the economic situation and economic policy uncertainty. Aggregate uncertainty in the Spanish economy increased in 2016, although it remained at levels below the average for the 2008-2013 recession. The changes in uncertainty captured by financial indicators are shown to have a higher impact on economic activity, and particularly on investment. Finally, it is illustrated how a significant part of the macroeconomic effect of the heightened uncertainty in the past year originated outside the Spanish economy.
{"title":"Macroeconomic Uncertainty: Measurement and Impact on the Spanish Economy","authors":"M. Gil, Javier J. Pérez, A. Urtasun","doi":"10.2139/ssrn.2910373","DOIUrl":"https://doi.org/10.2139/ssrn.2910373","url":null,"abstract":"This article characterises the level of uncertainty in the Spanish economy. Various indicators are analysed, distinguishing their source: financial market volatility, degree of disagreement between agents on the economic situation and economic policy uncertainty. Aggregate uncertainty in the Spanish economy increased in 2016, although it remained at levels below the average for the 2008-2013 recession. The changes in uncertainty captured by financial indicators are shown to have a higher impact on economic activity, and particularly on investment. Finally, it is illustrated how a significant part of the macroeconomic effect of the heightened uncertainty in the past year originated outside the Spanish economy.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124498460","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}
This paper assesses the contribution of confidence - or sentiment - data in predicting Canadian economic slowdowns. A probit framework is specified and applied to an indicator on the status of the Canadian business cycle produced by the OECD. Explanatory variables include all available Canadian data on sentiment (which arise from four different surveys) as well as various macroeconomic and financial data. The model is estimated via maximum likelihood and sentiment data are introduced either as individual variables, as simple averages (such as confidence indices) and as confidence factors extracted, via principal components' decompositions, from a larger dataset in which all available sentiment data have been collected. Our findings indicate that the full potential of sentiment data for forecasting future business cycles in Canada is attained when all data are used through the use of factor models.
{"title":"Using Confidence Data to Forecast the Canadian Business Cycle","authors":"Kevin Moran, Nono Simplice Aime, Imad Rherrad","doi":"10.2139/ssrn.3149094","DOIUrl":"https://doi.org/10.2139/ssrn.3149094","url":null,"abstract":"This paper assesses the contribution of confidence - or sentiment - data in predicting Canadian economic slowdowns. A probit framework is specified and applied to an indicator on the status of the Canadian business cycle produced by the OECD. Explanatory variables include all available Canadian data on sentiment (which arise from four different surveys) as well as various macroeconomic and financial data. The model is estimated via maximum likelihood and sentiment data are introduced either as individual variables, as simple averages (such as confidence indices) and as confidence factors extracted, via principal components' decompositions, from a larger dataset in which all available sentiment data have been collected. Our findings indicate that the full potential of sentiment data for forecasting future business cycles in Canada is attained when all data are used through the use of factor models.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124265004","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}
The research article aims to create a general fundamental theory on the Digital DNA of the modern digital creative economy of the scale and scope. In the frames of our theory, we define the Digital DNA of the modern digital creative economy of the scale and scope, making the following theoretical assumptions: 1) Digital DNA exists in the modern digital creative economy of the scale and scope; 2) Digital DNA consists of a chain of the knowledge with all the information on the modern digital creative economy of the scale and scope; 3) the Digital DNA uniquely identifies and accurately characterizes the modern digital creative economy of the scale and scope in the time, scale, frequency domains; 4) the Digital DNA represents a genetic key, which may help us to better understand the generation of the discrete-time digital business cycles with the different amplitudes, frequencies, shapes and powers in the modern digital creative economy of the scale and scope in the time, scale, frequency domains. In this innovative advanced research, we investigate the following research problems: 1) the existing damaging mechanisms of the Digital DNA’s complex knowledge base structure in the modern digital creative economies of the scales and scopes in the time, scale, frequency domains; 2) the possible repairing mechanisms of the Digital DNA’s complex knowledge base structure in the modern digital creative economies of the scales and scopes in the time, scale, frequency domains; 3) the specific influences by the damaged/repaired Digital DNA on the discrete-time digital business cycles generation/propagation in the modern digital creative economies of the scales and scopes in the time, scale, frequency domains. In addition, the innovative advanced research aims: 1) to perform the computer modeling on the Digital DNA’s complex knowledge base structure in the modern digital creative economy of the scale and scope; 2) to decode the Digital DNA’s complex knowledge base structure in the modern digital creative economy of the scale and scope.
{"title":"Digital DNA of Economy of Scale and Scope","authors":"D. Ledenyov, Viktor O. Ledenyov","doi":"10.2139/ssrn.2718931","DOIUrl":"https://doi.org/10.2139/ssrn.2718931","url":null,"abstract":"The research article aims to create a general fundamental theory on the Digital DNA of the modern digital creative economy of the scale and scope. In the frames of our theory, we define the Digital DNA of the modern digital creative economy of the scale and scope, making the following theoretical assumptions: 1) Digital DNA exists in the modern digital creative economy of the scale and scope; 2) Digital DNA consists of a chain of the knowledge with all the information on the modern digital creative economy of the scale and scope; 3) the Digital DNA uniquely identifies and accurately characterizes the modern digital creative economy of the scale and scope in the time, scale, frequency domains; 4) the Digital DNA represents a genetic key, which may help us to better understand the generation of the discrete-time digital business cycles with the different amplitudes, frequencies, shapes and powers in the modern digital creative economy of the scale and scope in the time, scale, frequency domains. In this innovative advanced research, we investigate the following research problems: 1) the existing damaging mechanisms of the Digital DNA’s complex knowledge base structure in the modern digital creative economies of the scales and scopes in the time, scale, frequency domains; 2) the possible repairing mechanisms of the Digital DNA’s complex knowledge base structure in the modern digital creative economies of the scales and scopes in the time, scale, frequency domains; 3) the specific influences by the damaged/repaired Digital DNA on the discrete-time digital business cycles generation/propagation in the modern digital creative economies of the scales and scopes in the time, scale, frequency domains. In addition, the innovative advanced research aims: 1) to perform the computer modeling on the Digital DNA’s complex knowledge base structure in the modern digital creative economy of the scale and scope; 2) to decode the Digital DNA’s complex knowledge base structure in the modern digital creative economy of the scale and scope.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122842380","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}
Private equity (PE) funds operate at the interface of private and public capital markets. This paper investigates whether PE fund managers have private information about the valuations of publicly traded securities. Using a dataset of cash flows from 941 buyout and venture funds, I show that PE funds' distribution patterns predict returns of public securities in the industries of the funds' specialization, but fund managers tend to sell at the market peaks only when they have performance fees to harvest. I find that the cost of this agency tension increases in the manager's survival risk and that the managers' knowledge pertains to the public firms' future earnings rather than the discount-rates. My tests distinguish market-timing from reactions to the variation in risk premia and spillover effects of PE activity on public firms. The results help better understand PE performance and have strong implications for PE manager selection. It follows that PE activity embeds private information into the prices of public securities.
{"title":"Market-Timing and Agency Costs: Evidence from Private Equity","authors":"Oleg R. Gredil","doi":"10.2139/ssrn.2410257","DOIUrl":"https://doi.org/10.2139/ssrn.2410257","url":null,"abstract":"Private equity (PE) funds operate at the interface of private and public capital markets. This paper investigates whether PE fund managers have private information about the valuations of publicly traded securities. Using a dataset of cash flows from 941 buyout and venture funds, I show that PE funds' distribution patterns predict returns of public securities in the industries of the funds' specialization, but fund managers tend to sell at the market peaks only when they have performance fees to harvest. I find that the cost of this agency tension increases in the manager's survival risk and that the managers' knowledge pertains to the public firms' future earnings rather than the discount-rates. My tests distinguish market-timing from reactions to the variation in risk premia and spillover effects of PE activity on public firms. The results help better understand PE performance and have strong implications for PE manager selection. It follows that PE activity embeds private information into the prices of public securities.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131247868","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}
N. Fawcett, Lena Korber, Riccardo M. Masolo, Matt Waldron
This paper investigates the real-time forecast performance of the Bank of England’s main DSGE model, COMPASS, before, during and after the financial crisis with reference to statistical and judgemental benchmarks. A general finding is that COMPASS’s relative forecast performance improves as the forecast horizon is extended (as does that of the Statistical Suite of forecasting models). The performance of forecasts from all three sources deteriorates substantially following the financial crisis. The deterioration is particularly marked for the DSGE model’s GDP forecasts. One possible explanation for that, and a key difference between DSGE models and judgemental forecasts, is that judgemental forecasts are implicitly conditioned on a broader information set, including faster-moving indicators that may be particularly informative when the state of the economy is evolving rapidly, as in periods of financial distress. Consistent with that interpretation, GDP forecasts from a version of the DSGE model augmented to include a survey measure of short-term GDP growth expectations are competitive with the judgemental forecasts at all horizons in the post-crisis period. More generally, a key theme of the paper is that both the type of off-model information and the method used to apply it are key determinants of DSGE model forecast accuracy.
{"title":"Evaluating UK Point and Density Forecasts from an Estimated DSGE Model: The Role of Off-Model Information Over the Financial Crisis","authors":"N. Fawcett, Lena Korber, Riccardo M. Masolo, Matt Waldron","doi":"10.2139/ssrn.2639055","DOIUrl":"https://doi.org/10.2139/ssrn.2639055","url":null,"abstract":"This paper investigates the real-time forecast performance of the Bank of England’s main DSGE model, COMPASS, before, during and after the financial crisis with reference to statistical and judgemental benchmarks. A general finding is that COMPASS’s relative forecast performance improves as the forecast horizon is extended (as does that of the Statistical Suite of forecasting models). The performance of forecasts from all three sources deteriorates substantially following the financial crisis. The deterioration is particularly marked for the DSGE model’s GDP forecasts. One possible explanation for that, and a key difference between DSGE models and judgemental forecasts, is that judgemental forecasts are implicitly conditioned on a broader information set, including faster-moving indicators that may be particularly informative when the state of the economy is evolving rapidly, as in periods of financial distress. Consistent with that interpretation, GDP forecasts from a version of the DSGE model augmented to include a survey measure of short-term GDP growth expectations are competitive with the judgemental forecasts at all horizons in the post-crisis period. More generally, a key theme of the paper is that both the type of off-model information and the method used to apply it are key determinants of DSGE model forecast accuracy.","PeriodicalId":108782,"journal":{"name":"ERN: Outlooks & Forecasting (Topic)","volume":"82 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879111","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：