Jurgen A Doornik
Datos Biográficos
| ID | 989464 |
|---|---|
| NOMBRE | Jurgen A Doornik |
| NOMBRES | Jurgen A |
| APELLIDO | Doornik |
| FIRMA | DOORNIK J A |
| AFILIACIONES | University of Oxford |
| ORCID | 0000-0002-0619-0955 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 11 |
| TOTAL DE CITAS | 10 |
| TOTAL COMO AUTOR | 11 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 1993 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 2 |
Forecasting Climate Change Using a Multivariate Cointegrated System
A cointegrated vector equilibrium correction model of key climate variables including sea surface temperature, ocean heat content, Arctic sea‐ice extent and sea‐level change is built, driven by radiative forcing in which a stochastic trend arises due to anthropogenic emissions of greenhouse gases. A valid and congruent statistical model requires saturation estimation to model breaks in trends, while also conditioning on natural radiative forcings…
Forecasting the UK top 1% income share in a shifting world
UK top income shares have varied hugely over the past two centuries, ranging from more than 30% to less than 7% of pre‐tax national income allocated to the top 1 percentile. We build a congruent dynamic linear regression model of the top 1% income share allowing for economic, political and social factors. Saturation estimation is used to model outliers and trend breaks, proxying underlying structural changes driving income inequality in the UK. W…
Modeling and forecasting the Covid‐19 pandemic time‐series data
Objective: We analyze the number of recorded cases and deaths of COVID-19 in many parts of the world, with the aim to understand the complexities of the data, and produce regular forecasts. Methods: The SARS-CoV-2 virus that causes COVID-19 has affected societies in all corners of the globe but with vastly differing experiences across countries. Health-care and economic systems vary significantly across countries, as do policy responses, includin…
An Omnibus Test for Univariate and Multivariate Normality
We suggest a convenient version of the omnibus test for normality, using skewness and kurtosis based on Shenton and Bowman [ Journal of the American Statistical Association (1977) Vol. 72, pp. 206–211], which controls well for size, for samples as low as 10 observations. A multivariate version is introduced. Size and power are investigated in comparison with four other tests for multivariate normality. The first power experiments consider the who…
Constructing Historical Euro‐zone Data
Existing methods of reconstructing historical Euro-zone data by aggregation of the individual countries' data raises numerous difficulties due to past exchange rate changes. The approach proposed here is designed to avoid such distortions, and aggregate exactly when exchange rates are fixed. In a simple 'Divisia-style' approach, we first compute growth rates within states, aggregate these, then cumulate this Euro-zone growth rate to obtain the ag…
Reconstructing Aggregate Euro‐zone Data
Reconstructing historical euro‐zone data by aggregation across individual countries is problematic because of past exchange rate changes. The approach here avoids such distortions, yet aggregates exactly when exchange rates are fixed. This is achieved by aggregating weighted within‐country growth rates to obtain euro‐zone growth rates, then cumulating this euro‐zone growth rate to obtain aggregate levels. The aggregate implicit deflator then coin…
The Implications for Econometric Modelling of Forecast Failure
To reconcile forecast failure with building congruent empirical models, we analyze the sources of mis‐prediction. This reveals that ex ante forecast failure is purely a function of forecast‐period events, not determinable from in‐sample information. The primary causes are unmodelled shifts in deterministic factors, rather than model mis‐specification, collinearity, or a lack of parsimony. We examine the effects of deterministic breaks on equilibr…
Stamp 5.0 Structural Time Series Analyser, Modeller and Predictor
Part 1: installation procedure for STAMP. Part 2 Tutorials on structural time series modelling: getting started on simple univariate modelling tutorial on components tutorial on interventions and explanatory variables tutorial on multivariate models applications in macroeconomics and finance. Part 3 STAMP tutorials: the basic skills tutorial on graphics tutorial on data input and output tutorial on data transformation and description tutorial on …
PcGive Professional 8.0 and PcGive Student 8.0
Journal Article PcGive Professional 8.0 and PcGive Student 8.0 Get access Guy Judge, Guy Judge University of Portsmouth Search for other works by this author on: Oxford Academic Google Scholar R. I. D. Harris R. I. D. Harris University of Portsmouth Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 105, Issue 430, 1 May 1995, Pages 776–786, https://doi.org/10.2307/2235053 Published: 01 May 1995
Modelling Linear Dynamic Econometric Systems
Econometric modeling of linear dynamic systems is considered in the light of new reasons for general to simple modeling of the joint data density. To offset the resulting modeling burden due to large numbers of variables, equations, and parameters, the authors consider PcFiml 8 as a modeling tool. Graphics allow vast amounts of information to be appraised at a glance. The demand for M1 in the United Kingdom is modeled as a system using the approa…
PcGive Version 7
Constructing Historical Euro‐zone Data
Existing methods of reconstructing historical Euro-zone data by aggregation of the individual countries' data raises numerous difficulties due to past exchange rate changes. The approach proposed here is designed to avoid such distortions, and aggregate exactly when exchange rates are fixed. In a simple 'Divisia-style' approach, we first compute growth rates within states, aggregate these, then cumulate this Euro-zone growth rate to obtain the ag…
Modeling and forecasting the Covid‐19 pandemic time‐series data
Objective: We analyze the number of recorded cases and deaths of COVID-19 in many parts of the world, with the aim to understand the complexities of the data, and produce regular forecasts. Methods: The SARS-CoV-2 virus that causes COVID-19 has affected societies in all corners of the globe but with vastly differing experiences across countries. Health-care and economic systems vary significantly across countries, as do policy responses, includin…
Modelling Linear Dynamic Econometric Systems
Econometric modeling of linear dynamic systems is considered in the light of new reasons for general to simple modeling of the joint data density. To offset the resulting modeling burden due to large numbers of variables, equations, and parameters, the authors consider PcFiml 8 as a modeling tool. Graphics allow vast amounts of information to be appraised at a glance. The demand for M1 in the United Kingdom is modeled as a system using the approa…
Reconstructing Aggregate Euro‐zone Data
Reconstructing historical euro‐zone data by aggregation across individual countries is problematic because of past exchange rate changes. The approach here avoids such distortions, yet aggregates exactly when exchange rates are fixed. This is achieved by aggregating weighted within‐country growth rates to obtain euro‐zone growth rates, then cumulating this euro‐zone growth rate to obtain aggregate levels. The aggregate implicit deflator then coin…
The Implications for Econometric Modelling of Forecast Failure
To reconcile forecast failure with building congruent empirical models, we analyze the sources of mis‐prediction. This reveals that ex ante forecast failure is purely a function of forecast‐period events, not determinable from in‐sample information. The primary causes are unmodelled shifts in deterministic factors, rather than model mis‐specification, collinearity, or a lack of parsimony. We examine the effects of deterministic breaks on equilibr…
PcGive Version 7
Modelling Linear Dynamic Econometric Systems
Econometric modeling of linear dynamic systems is considered in the light of new reasons for general to simple modeling of the joint data density. To offset the resulting modeling burden due to large numbers of variables, equations, and parameters, the authors consider PcFiml 8 as a modeling tool. Graphics allow vast amounts of information to be appraised at a glance. The demand for M1 in the United Kingdom is modeled as a system using the approa…
PcGive Professional 8.0 and PcGive Student 8.0
Journal Article PcGive Professional 8.0 and PcGive Student 8.0 Get access Guy Judge, Guy Judge University of Portsmouth Search for other works by this author on: Oxford Academic Google Scholar R. I. D. Harris R. I. D. Harris University of Portsmouth Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 105, Issue 430, 1 May 1995, Pages 776–786, https://doi.org/10.2307/2235053 Published: 01 May 1995
Stamp 5.0 Structural Time Series Analyser, Modeller and Predictor
Part 1: installation procedure for STAMP. Part 2 Tutorials on structural time series modelling: getting started on simple univariate modelling tutorial on components tutorial on interventions and explanatory variables tutorial on multivariate models applications in macroeconomics and finance. Part 3 STAMP tutorials: the basic skills tutorial on graphics tutorial on data input and output tutorial on data transformation and description tutorial on …
The Implications for Econometric Modelling of Forecast Failure
To reconcile forecast failure with building congruent empirical models, we analyze the sources of mis‐prediction. This reveals that ex ante forecast failure is purely a function of forecast‐period events, not determinable from in‐sample information. The primary causes are unmodelled shifts in deterministic factors, rather than model mis‐specification, collinearity, or a lack of parsimony. We examine the effects of deterministic breaks on equilibr…
Reconstructing Aggregate Euro‐zone Data
Reconstructing historical euro‐zone data by aggregation across individual countries is problematic because of past exchange rate changes. The approach here avoids such distortions, yet aggregates exactly when exchange rates are fixed. This is achieved by aggregating weighted within‐country growth rates to obtain euro‐zone growth rates, then cumulating this euro‐zone growth rate to obtain aggregate levels. The aggregate implicit deflator then coin…
Constructing Historical Euro‐zone Data
Existing methods of reconstructing historical Euro-zone data by aggregation of the individual countries' data raises numerous difficulties due to past exchange rate changes. The approach proposed here is designed to avoid such distortions, and aggregate exactly when exchange rates are fixed. In a simple 'Divisia-style' approach, we first compute growth rates within states, aggregate these, then cumulate this Euro-zone growth rate to obtain the ag…
An Omnibus Test for Univariate and Multivariate Normality
We suggest a convenient version of the omnibus test for normality, using skewness and kurtosis based on Shenton and Bowman [ Journal of the American Statistical Association (1977) Vol. 72, pp. 206–211], which controls well for size, for samples as low as 10 observations. A multivariate version is introduced. Size and power are investigated in comparison with four other tests for multivariate normality. The first power experiments consider the who…
Modeling and forecasting the Covid‐19 pandemic time‐series data
Objective: We analyze the number of recorded cases and deaths of COVID-19 in many parts of the world, with the aim to understand the complexities of the data, and produce regular forecasts. Methods: The SARS-CoV-2 virus that causes COVID-19 has affected societies in all corners of the globe but with vastly differing experiences across countries. Health-care and economic systems vary significantly across countries, as do policy responses, includin…
Forecasting the UK top 1% income share in a shifting world
UK top income shares have varied hugely over the past two centuries, ranging from more than 30% to less than 7% of pre‐tax national income allocated to the top 1 percentile. We build a congruent dynamic linear regression model of the top 1% income share allowing for economic, political and social factors. Saturation estimation is used to model outliers and trend breaks, proxying underlying structural changes driving income inequality in the UK. W…
Forecasting Climate Change Using a Multivariate Cointegrated System
A cointegrated vector equilibrium correction model of key climate variables including sea surface temperature, ocean heat content, Arctic sea‐ice extent and sea‐level change is built, driven by radiative forcing in which a stochastic trend arises due to anthropogenic emissions of greenhouse gases. A valid and congruent statistical model requires saturation estimation to model breaks in trends, while also conditioning on natural radiative forcings…
Econometrics (8 obras) · Economics (7 obras) · Mathematics (7 obras) · Computer Science (6 obras) · Statistics (6 obras) · Monetary Policy and Economic Impact (4 obras) · Aggregate (composite (2 obras) · Aggregate data (2 obras) · Exchange rate (2 obras) · Forecasting Techniques and Applications (2 obras)