The Experts below are selected from a list of 78 Experts worldwide ranked by ideXlab platform

Scott M Weiner - One of the best experts on this subject based on the ideXlab platform.

  • modeling regional interdependencies using a global error correcting macroeconometric model
    Journal of Business & Economic Statistics, 2004
    Co-Authors: Hashem M Pesaran, Til Schuermann, Scott M Weiner
    Abstract:

    Financial institutions are ultimately exposed to macroeconomic fluctuations in the global economy. This article proposes and builds a compact global model capable of generating forecasts for a core set of macroeconomic factors (or variables) across a number of countries. The model explicitly allows for the interdependencies that exist between national and International factors. Individual region-specific vector error-correcting models are estimated in which the domestic variables are related to corresponding foreign variables constructed exclusively to match the International Trade Pattern of the country under consideration. The individual country models are then linked in a consistent and cohesive manner to generate forecasts for all of the variables in the world economy simultaneously. The global model is estimated for 25 countries grouped into 11 regions using quarterly data over 1979Q1–1999Q1. The degree of regional interdependencies is investigated via generalized impulse responses where the effects ...

  • modeling regional interdependencies using a global vector error correcting macroeconometric model
    2001
    Co-Authors: Hashem M Pesaran, Scott M Weiner, Til Schuermann
    Abstract:

    A financial institution such as a bank is ultimately exposed to macroeconomic fluctuations in the countries to which it has exposure, the most acute example being commercial lending to companies whose fortunes fluctuate with aggregate demand. It was this risk management need for financial institutions which motivated us to build a compact global macroeconometric model capable of generating (point as well as density) forecasts for a core set of macroeconomic factors for a set of regions and countries which explicitly allows for interconnections and dependencies that exist between national and International factors in a coherent and consistent manner. This paper provides such a global modeling framework by making use of recent advances in the analysis of cointegrating systems. In an unrestricted VAR model covering N countries/regions, the number of unknown parameters will be unfeasibly large (around p(4N-1)+1, where p is the order of the VAR), requiring a more parsimonious solution. We first estimate individual country (or region) specific vector error correcting models, where the domestic macroeconomic variables are related to corresponding foreign variables constructed exclusively to match the International Trade Pattern of the country under consideration. The individual country models are then combined in a consistent and cohesive manner to generate forecasts for all the variables in the world economy simultaneously. We estimate the model using quarterly data from 1979Q1 to 1999Q1 and perform contagion analysis by investigating the transmission of shocks of one variable to the rest of the world.

Hashem M Pesaran - One of the best experts on this subject based on the ideXlab platform.

  • modeling regional interdependencies using a global error correcting macroeconometric model
    Journal of Business & Economic Statistics, 2004
    Co-Authors: Hashem M Pesaran, Til Schuermann, Scott M Weiner
    Abstract:

    Financial institutions are ultimately exposed to macroeconomic fluctuations in the global economy. This article proposes and builds a compact global model capable of generating forecasts for a core set of macroeconomic factors (or variables) across a number of countries. The model explicitly allows for the interdependencies that exist between national and International factors. Individual region-specific vector error-correcting models are estimated in which the domestic variables are related to corresponding foreign variables constructed exclusively to match the International Trade Pattern of the country under consideration. The individual country models are then linked in a consistent and cohesive manner to generate forecasts for all of the variables in the world economy simultaneously. The global model is estimated for 25 countries grouped into 11 regions using quarterly data over 1979Q1–1999Q1. The degree of regional interdependencies is investigated via generalized impulse responses where the effects ...

  • modeling regional interdependencies using a global vector error correcting macroeconometric model
    2001
    Co-Authors: Hashem M Pesaran, Scott M Weiner, Til Schuermann
    Abstract:

    A financial institution such as a bank is ultimately exposed to macroeconomic fluctuations in the countries to which it has exposure, the most acute example being commercial lending to companies whose fortunes fluctuate with aggregate demand. It was this risk management need for financial institutions which motivated us to build a compact global macroeconometric model capable of generating (point as well as density) forecasts for a core set of macroeconomic factors for a set of regions and countries which explicitly allows for interconnections and dependencies that exist between national and International factors in a coherent and consistent manner. This paper provides such a global modeling framework by making use of recent advances in the analysis of cointegrating systems. In an unrestricted VAR model covering N countries/regions, the number of unknown parameters will be unfeasibly large (around p(4N-1)+1, where p is the order of the VAR), requiring a more parsimonious solution. We first estimate individual country (or region) specific vector error correcting models, where the domestic macroeconomic variables are related to corresponding foreign variables constructed exclusively to match the International Trade Pattern of the country under consideration. The individual country models are then combined in a consistent and cohesive manner to generate forecasts for all the variables in the world economy simultaneously. We estimate the model using quarterly data from 1979Q1 to 1999Q1 and perform contagion analysis by investigating the transmission of shocks of one variable to the rest of the world.

Til Schuermann - One of the best experts on this subject based on the ideXlab platform.

  • modeling regional interdependencies using a global error correcting macroeconometric model
    Journal of Business & Economic Statistics, 2004
    Co-Authors: Hashem M Pesaran, Til Schuermann, Scott M Weiner
    Abstract:

    Financial institutions are ultimately exposed to macroeconomic fluctuations in the global economy. This article proposes and builds a compact global model capable of generating forecasts for a core set of macroeconomic factors (or variables) across a number of countries. The model explicitly allows for the interdependencies that exist between national and International factors. Individual region-specific vector error-correcting models are estimated in which the domestic variables are related to corresponding foreign variables constructed exclusively to match the International Trade Pattern of the country under consideration. The individual country models are then linked in a consistent and cohesive manner to generate forecasts for all of the variables in the world economy simultaneously. The global model is estimated for 25 countries grouped into 11 regions using quarterly data over 1979Q1–1999Q1. The degree of regional interdependencies is investigated via generalized impulse responses where the effects ...

  • modeling regional interdependencies using a global vector error correcting macroeconometric model
    2001
    Co-Authors: Hashem M Pesaran, Scott M Weiner, Til Schuermann
    Abstract:

    A financial institution such as a bank is ultimately exposed to macroeconomic fluctuations in the countries to which it has exposure, the most acute example being commercial lending to companies whose fortunes fluctuate with aggregate demand. It was this risk management need for financial institutions which motivated us to build a compact global macroeconometric model capable of generating (point as well as density) forecasts for a core set of macroeconomic factors for a set of regions and countries which explicitly allows for interconnections and dependencies that exist between national and International factors in a coherent and consistent manner. This paper provides such a global modeling framework by making use of recent advances in the analysis of cointegrating systems. In an unrestricted VAR model covering N countries/regions, the number of unknown parameters will be unfeasibly large (around p(4N-1)+1, where p is the order of the VAR), requiring a more parsimonious solution. We first estimate individual country (or region) specific vector error correcting models, where the domestic macroeconomic variables are related to corresponding foreign variables constructed exclusively to match the International Trade Pattern of the country under consideration. The individual country models are then combined in a consistent and cohesive manner to generate forecasts for all the variables in the world economy simultaneously. We estimate the model using quarterly data from 1979Q1 to 1999Q1 and perform contagion analysis by investigating the transmission of shocks of one variable to the rest of the world.

Qi Hai - One of the best experts on this subject based on the ideXlab platform.

  • Evolution of Fossil Energy International Trade Pattern Based on Complex Network
    Energy Procedia, 2014
    Co-Authors: Hao Xiaoqing, An Haizhong, Qi Hai
    Abstract:

    Abstract Energy is basis for national economic development and power products, and its imports and exports play a primary role for economic cooperation between countries. The energy International Trade network is formed through the energy imports and exports among countries. From the characteristics of the network we can know the changes in energy Trade Patterns. According to the International energy Trade data which include crude oil, coal and natural gas data published by The United Nations Statistics Division from 1996 to 2012, with the state as the node and the energy flows of Trade for the side, this article constructed directed energy International Trade complex network with out-weighted edges. This article calculated such complex network properties as node degree, network structure entropy, average clustering coefficient, and average nearest neighbor degree of the energy International Trade complex network. Based on these characteristics, this article analyzed the degree distribution, heterogeneity, clustering, and vertex intensity correlation of the energy International Trade complex network. We find that countries increased tightness and strengthened interdependence when they carry out the International energy Trade. Transportation costs and customs tax, etc. will not have much impact on the import and export of fossil fuels. It will be more frequently trading with each other among countries’ partner who have smaller population or lower economic strength. Small countries tend to make energy Trade relations with regional hubs in local area. Global trading countries have a lot of partners around the world. If energy war, crisis or other issues occur in these countries, it is likely to spread to other countries, so that the global fossil energy Trade will be affected.

Hao Xiaoqing - One of the best experts on this subject based on the ideXlab platform.

  • Evolution of Fossil Energy International Trade Pattern Based on Complex Network
    Energy Procedia, 2014
    Co-Authors: Hao Xiaoqing, An Haizhong, Qi Hai
    Abstract:

    Abstract Energy is basis for national economic development and power products, and its imports and exports play a primary role for economic cooperation between countries. The energy International Trade network is formed through the energy imports and exports among countries. From the characteristics of the network we can know the changes in energy Trade Patterns. According to the International energy Trade data which include crude oil, coal and natural gas data published by The United Nations Statistics Division from 1996 to 2012, with the state as the node and the energy flows of Trade for the side, this article constructed directed energy International Trade complex network with out-weighted edges. This article calculated such complex network properties as node degree, network structure entropy, average clustering coefficient, and average nearest neighbor degree of the energy International Trade complex network. Based on these characteristics, this article analyzed the degree distribution, heterogeneity, clustering, and vertex intensity correlation of the energy International Trade complex network. We find that countries increased tightness and strengthened interdependence when they carry out the International energy Trade. Transportation costs and customs tax, etc. will not have much impact on the import and export of fossil fuels. It will be more frequently trading with each other among countries’ partner who have smaller population or lower economic strength. Small countries tend to make energy Trade relations with regional hubs in local area. Global trading countries have a lot of partners around the world. If energy war, crisis or other issues occur in these countries, it is likely to spread to other countries, so that the global fossil energy Trade will be affected.