Michael P Clements
Dados Biográficos
| ID | 1082258 |
|---|---|
| NOME | Michael P Clements |
| PRENOMES | Michael P |
| SOBRENOME | Clements |
| ASSINATURA | CLEMENTS M P |
| AFILIAÇÕES | University of Warwick |
| ORCID | 0000-0001-6329-1341 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 16 |
| TOTAL DE CITAÇÕES | 7 |
| TOTAL COMO AUTOR | 16 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1995 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 2 |
Weak Exogeneity, Driving Trends and Non‐Causality Is Dynamic Adjustment Informative About Causality?
In VECMs (or CVARs), the weak exogeneity of some of the variables (for the long‐run parameters) is related to the equilibrium adjustment dynamics. This has sometimes led to the statistical concept of weak exogeneity being given a causal interpretation. This paper analyses the causal informational value of weak exogeneity, using graphical representations of causal structures, to show when such an interpretation is valid. We specifically consider t…
Inconsistent survey histograms and point forecasts revisited
Past analyses of surveys of professional forecasters’ histogram and point forecasts indicate that the two are not always consistent. The point forecasts are either systematically higher or lower than the corresponding histogram means, depending on whether we consider inflation or GDP growth. We consider whether inconsistencies are related to delayed updating of the histogram forecasts, or to the reaction of the two types of forecasts to new infor…
Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty
Macroeconomic data are subject to data revisions. Yet, the usual way of generating real‐time density forecasts from Bayesian Vector Autoregressive (BVAR) models makes no allowance for data uncertainty from future data revisions. We develop methods of allowing for data uncertainty when forecasting with BVAR models with stochastic volatility. First, the BVAR forecasting model is estimated on real‐time vintages. Second, the BVAR model is jointly est…
Individual forecaster perceptions of the persistence of shocks to GDP
We analyse individual professional forecasters' beliefs concerning the persistence of GDP shocks. Despite substantial apparent heterogeneity in perceptions, with around one half of the sample of professional forecasters believing shocks do not have permanent effects, we show that these apparent differences may be largely due to short samples and survey respondents being active at different times. When we control for these effects, using a bootstr…
Predicting Early Data Revisions to U.S. GDP and the Effects of Releases on Equity Markets
The effects of data uncertainty on real-time decision-making can be reduced by predicting data revisions to U.S. GDP growth. We show that survey forecasts efficiently predict the revision implicit in the second estimate of GDP growth, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the data revision implied by the release of the third estimate. We use forecasting models …
Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision
Model-based estimates of future uncertainty are generally based on the in-sample fit of the model, as when Box–Jenkins prediction intervals are calculated. However, this approach will generate biased uncertainty estimates in real time when there are data revisions. A simple remedy is suggested, and used to generate more accurate prediction intervals for 25 macroeconomic variables, in line with the theory. A simulation study based on an empiricall…
Forecast Uncertainty— Ex Ante and Ex Post
Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to …
Improving Real-Time Estimates of Output and Inflation Gaps With Multiple-Vintage Models
Real-time estimates of output gaps and inflation gaps differ from the values that are obtained using data available long after the event. Part of the problem is that the data on which the real-time estimates are based is subsequently revised. We show that vector-autoregressive models of data vintages provide forecasts of post-revision values of future observations and of already-released observations capable of improving estimates of output and i…
Macroeconomic Forecasting With Mixed-Frequency Data
Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to signific…
Economic Forecasting in a Changing World
This article explains the basis for a theory of economic forecasting developed over the past decade by the authors. The research has resulted in numerous articles in academic journals, two monographs, Forecasting Economic Time Series, 1998, Cambridge University Press, and Forecasting Nonstationary Economic Time Series, 1999, MIT Press, and three edited volumes, Understanding Economic Forecasts, 2001, MIT Press, A Companion to Economic Forecasting…
Evaluating the Bank of England Density Forecasts of Inflation
We consider evaluating the UK Monetary Policy Committee's inflation density forecasts using probability integral transform goodness-of-fit tests. These tests evaluate the whole forecast density. We also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated, where the ranges are chosen to be those of particular relevance to the MPC, given its remit of maintaining inflation rates in a band around per a…
Business Cycle Asymmetries
Tests for business cycle asymmetries are developed for Markov-switching autoregressive models. The tests of deepness, steepness, and sharpness are Wald statistics, which have standard asymptotics. For the standard two-regime model of expansions and contractions, deepness is shown to imply sharpness (and vice versa), whereas the process is always nonsteep. Two and three-state models of U.S. GNP growth are used to illustrate the approach, along wit…
Asymmetric output‐gap effects in Phillips Curve and mark‐up pricing models
A number of studies have found an asymmetric response of consumer price index inflation to the output gap in the US in simple Phillips curve models. We consider whether there are similar asymmetries in mark‐up pricing models, that is, whether the mark‐up over producers' costs also depends upon the sign of the (adjusted) output gap. The robustness of our findings to the price series is assessed, and also whether price‐output responses in the UK ar…
Seasonality, Cointegration, and Forecasting UK Residential Energy Demand
Much of the short‐run movement in energy demand in the UK is seasonal, and the contribution of long‐run factors to short‐run forecasts is slight. Nevertheless, using a variety of techniques, including a recently developed estimation procedure that is applicable irrespective of the orders of integration of the data, we obtain a long‐run income elasticity of demand of about one third, and we are unable to reject a zero price elasticity. An economet…
Rationality and the Role of Judgement in Macroeconomic Forecasting
This paper examines the effects of judgemental adjustments on the rationality of macroeconomic forecasts. Published forecasts based on large-scale models are rarely purely model-based, but often include extensive adjustments. Forecasters' adjustments tend to improve forecast accuracy, but there is no evidence of their impact on the rationality of forecasts. Using series of revisions to forecasts we find little evidence that published forecasts ar…
Macro-Economic Forecasting and Modelling
Journal Article Macro-Economic Forecasting and Modelling Get access Michael P. Clements, Michael P. Clements Institute of Economics and Statistics, and Financial support from the UK Economic and Social Research Council under grant R000233447 is gratefully acknowledged by both authors. Neil Ericsson provided many helpful comments on an earlier draft. Search for other works by this author on: Oxford Academic Google Scholar David F. Hendry David F. …
Macro-Economic Forecasting and Modelling
Journal Article Macro-Economic Forecasting and Modelling Get access Michael P. Clements, Michael P. Clements Institute of Economics and Statistics, and Financial support from the UK Economic and Social Research Council under grant R000233447 is gratefully acknowledged by both authors. Neil Ericsson provided many helpful comments on an earlier draft. Search for other works by this author on: Oxford Academic Google Scholar David F. Hendry David F. …
Evaluating the Bank of England Density Forecasts of Inflation
We consider evaluating the UK Monetary Policy Committee's inflation density forecasts using probability integral transform goodness-of-fit tests. These tests evaluate the whole forecast density. We also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated, where the ranges are chosen to be those of particular relevance to the MPC, given its remit of maintaining inflation rates in a band around per a…
Asymmetric output‐gap effects in Phillips Curve and mark‐up pricing models
A number of studies have found an asymmetric response of consumer price index inflation to the output gap in the US in simple Phillips curve models. We consider whether there are similar asymmetries in mark‐up pricing models, that is, whether the mark‐up over producers' costs also depends upon the sign of the (adjusted) output gap. The robustness of our findings to the price series is assessed, and also whether price‐output responses in the UK ar…
Rationality and the Role of Judgement in Macroeconomic Forecasting
This paper examines the effects of judgemental adjustments on the rationality of macroeconomic forecasts. Published forecasts based on large-scale models are rarely purely model-based, but often include extensive adjustments. Forecasters' adjustments tend to improve forecast accuracy, but there is no evidence of their impact on the rationality of forecasts. Using series of revisions to forecasts we find little evidence that published forecasts ar…
Rationality and the Role of Judgement in Macroeconomic Forecasting
This paper examines the effects of judgemental adjustments on the rationality of macroeconomic forecasts. Published forecasts based on large-scale models are rarely purely model-based, but often include extensive adjustments. Forecasters' adjustments tend to improve forecast accuracy, but there is no evidence of their impact on the rationality of forecasts. Using series of revisions to forecasts we find little evidence that published forecasts ar…
Macro-Economic Forecasting and Modelling
Journal Article Macro-Economic Forecasting and Modelling Get access Michael P. Clements, Michael P. Clements Institute of Economics and Statistics, and Financial support from the UK Economic and Social Research Council under grant R000233447 is gratefully acknowledged by both authors. Neil Ericsson provided many helpful comments on an earlier draft. Search for other works by this author on: Oxford Academic Google Scholar David F. Hendry David F. …
Seasonality, Cointegration, and Forecasting UK Residential Energy Demand
Much of the short‐run movement in energy demand in the UK is seasonal, and the contribution of long‐run factors to short‐run forecasts is slight. Nevertheless, using a variety of techniques, including a recently developed estimation procedure that is applicable irrespective of the orders of integration of the data, we obtain a long‐run income elasticity of demand of about one third, and we are unable to reject a zero price elasticity. An economet…
Business Cycle Asymmetries
Tests for business cycle asymmetries are developed for Markov-switching autoregressive models. The tests of deepness, steepness, and sharpness are Wald statistics, which have standard asymptotics. For the standard two-regime model of expansions and contractions, deepness is shown to imply sharpness (and vice versa), whereas the process is always nonsteep. Two and three-state models of U.S. GNP growth are used to illustrate the approach, along wit…
Asymmetric output‐gap effects in Phillips Curve and mark‐up pricing models
A number of studies have found an asymmetric response of consumer price index inflation to the output gap in the US in simple Phillips curve models. We consider whether there are similar asymmetries in mark‐up pricing models, that is, whether the mark‐up over producers' costs also depends upon the sign of the (adjusted) output gap. The robustness of our findings to the price series is assessed, and also whether price‐output responses in the UK ar…
Evaluating the Bank of England Density Forecasts of Inflation
We consider evaluating the UK Monetary Policy Committee's inflation density forecasts using probability integral transform goodness-of-fit tests. These tests evaluate the whole forecast density. We also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated, where the ranges are chosen to be those of particular relevance to the MPC, given its remit of maintaining inflation rates in a band around per a…
Macroeconomic Forecasting With Mixed-Frequency Data
Many macroeconomic series, such as U.S. real output growth, are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS specification used in the comparison uses a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to signific…
Economic Forecasting in a Changing World
This article explains the basis for a theory of economic forecasting developed over the past decade by the authors. The research has resulted in numerous articles in academic journals, two monographs, Forecasting Economic Time Series, 1998, Cambridge University Press, and Forecasting Nonstationary Economic Time Series, 1999, MIT Press, and three edited volumes, Understanding Economic Forecasts, 2001, MIT Press, A Companion to Economic Forecasting…
Improving Real-Time Estimates of Output and Inflation Gaps With Multiple-Vintage Models
Real-time estimates of output gaps and inflation gaps differ from the values that are obtained using data available long after the event. Part of the problem is that the data on which the real-time estimates are based is subsequently revised. We show that vector-autoregressive models of data vintages provide forecasts of post-revision values of future observations and of already-released observations capable of improving estimates of output and i…
Forecast Uncertainty— Ex Ante and Ex Post
Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to …
Predicting Early Data Revisions to U.S. GDP and the Effects of Releases on Equity Markets
The effects of data uncertainty on real-time decision-making can be reduced by predicting data revisions to U.S. GDP growth. We show that survey forecasts efficiently predict the revision implicit in the second estimate of GDP growth, but that forecasting models incorporating monthly economic indicators and daily equity returns provide superior forecasts of the data revision implied by the release of the third estimate. We use forecasting models …
Assessing Macro Uncertainty in Real-Time When Data Are Subject To Revision
Model-based estimates of future uncertainty are generally based on the in-sample fit of the model, as when Box–Jenkins prediction intervals are calculated. However, this approach will generate biased uncertainty estimates in real time when there are data revisions. A simple remedy is suggested, and used to generate more accurate prediction intervals for 25 macroeconomic variables, in line with the theory. A simulation study based on an empiricall…
Individual forecaster perceptions of the persistence of shocks to GDP
We analyse individual professional forecasters' beliefs concerning the persistence of GDP shocks. Despite substantial apparent heterogeneity in perceptions, with around one half of the sample of professional forecasters believing shocks do not have permanent effects, we show that these apparent differences may be largely due to short samples and survey respondents being active at different times. When we control for these effects, using a bootstr…
Density forecasting with Bayesian Vector Autoregressive models under macroeconomic data uncertainty
Macroeconomic data are subject to data revisions. Yet, the usual way of generating real‐time density forecasts from Bayesian Vector Autoregressive (BVAR) models makes no allowance for data uncertainty from future data revisions. We develop methods of allowing for data uncertainty when forecasting with BVAR models with stochastic volatility. First, the BVAR forecasting model is estimated on real‐time vintages. Second, the BVAR model is jointly est…
Inconsistent survey histograms and point forecasts revisited
Past analyses of surveys of professional forecasters’ histogram and point forecasts indicate that the two are not always consistent. The point forecasts are either systematically higher or lower than the corresponding histogram means, depending on whether we consider inflation or GDP growth. We consider whether inconsistencies are related to delayed updating of the histogram forecasts, or to the reaction of the two types of forecasts to new infor…
Weak Exogeneity, Driving Trends and Non‐Causality Is Dynamic Adjustment Informative About Causality?
In VECMs (or CVARs), the weak exogeneity of some of the variables (for the long‐run parameters) is related to the equilibrium adjustment dynamics. This has sometimes led to the statistical concept of weak exogeneity being given a causal interpretation. This paper analyses the causal informational value of weak exogeneity, using graphical representations of causal structures, to show when such an interpretation is valid. We specifically consider t…
Econometrics (15 obras) · Economics (14 obras) · Monetary Policy and Economic Impact (13 obras) · Market Dynamics and Volatility (10 obras) · Computer Science (8 obras) · Mathematics (8 obras) · Statistics (5 obras) · Autoregressive model (4 obras) · Macroeconomics (4 obras) · Monetary policy (4 obras)