Regional nowcasting: an illustration using the Scottish economy

Research output: Contribution to journalArticle

Abstract

The delays in the release of key economic variables mean that policymakers do not know their current values. Quickly produced, high frequency, indicators are essen- tial in understanding regional performance in a timely fashion. Thus, there is a need for nowcasts, which are estimates of the current values of such variables (e.g. GDP, employ- ment, etc.). This paper nowcasts growth in a regional economy, taking Scotland, UK, as our example. Regional nowcasting is complicated due to issues around data timeliness and availability. For instance, key nowcast predictors such as industrial production are often unavailable at the sub-national level. Accordingly, we use data on some non-traditional variables and investigate whether UK aggregates, and indicators for neighbouring regions of the UK, can help nowcast Scottish GDP growth. We show that these models and methods can be successfully adapted for use in a regional setting, and so produce timely macroeconomic indicators for the regional economy.
LanguageEnglish
Pages1-25
Number of pages25
JournalSankhya B
Publication statusAccepted/In press - 14 Oct 2018

Fingerprint

Nowcasting
Regional economy
Timeliness
GDP growth
Industrial production
Macroeconomic indicators
Economic variables
Nontraditional
Scotland
Politicians
Predictors

Keywords

  • nowcasting
  • mixed frequency data
  • regional economics

Cite this

@article{b279d0c29bed41cd81e93bbcd655713d,
title = "Regional nowcasting: an illustration using the Scottish economy",
abstract = "The delays in the release of key economic variables mean that policymakers do not know their current values. Quickly produced, high frequency, indicators are essen- tial in understanding regional performance in a timely fashion. Thus, there is a need for nowcasts, which are estimates of the current values of such variables (e.g. GDP, employ- ment, etc.). This paper nowcasts growth in a regional economy, taking Scotland, UK, as our example. Regional nowcasting is complicated due to issues around data timeliness and availability. For instance, key nowcast predictors such as industrial production are often unavailable at the sub-national level. Accordingly, we use data on some non-traditional variables and investigate whether UK aggregates, and indicators for neighbouring regions of the UK, can help nowcast Scottish GDP growth. We show that these models and methods can be successfully adapted for use in a regional setting, and so produce timely macroeconomic indicators for the regional economy.",
keywords = "nowcasting, mixed frequency data, regional economics",
author = "Gary Koop and Stuart McIntyre and Grant Allan and Paul Smith",
note = "This is a post-peer-review, pre-copyedit version of an article published in Sankhya B. The final authenticated version is available online at: https://link.springer.com/journal/13571.",
year = "2018",
month = "10",
day = "14",
language = "English",
pages = "1--25",

}

Regional nowcasting : an illustration using the Scottish economy. / Koop, Gary; McIntyre, Stuart; Allan, Grant; Smith, Paul.

14.10.2018, p. 1-25.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Regional nowcasting

T2 - an illustration using the Scottish economy

AU - Koop, Gary

AU - McIntyre, Stuart

AU - Allan, Grant

AU - Smith, Paul

N1 - This is a post-peer-review, pre-copyedit version of an article published in Sankhya B. The final authenticated version is available online at: https://link.springer.com/journal/13571.

PY - 2018/10/14

Y1 - 2018/10/14

N2 - The delays in the release of key economic variables mean that policymakers do not know their current values. Quickly produced, high frequency, indicators are essen- tial in understanding regional performance in a timely fashion. Thus, there is a need for nowcasts, which are estimates of the current values of such variables (e.g. GDP, employ- ment, etc.). This paper nowcasts growth in a regional economy, taking Scotland, UK, as our example. Regional nowcasting is complicated due to issues around data timeliness and availability. For instance, key nowcast predictors such as industrial production are often unavailable at the sub-national level. Accordingly, we use data on some non-traditional variables and investigate whether UK aggregates, and indicators for neighbouring regions of the UK, can help nowcast Scottish GDP growth. We show that these models and methods can be successfully adapted for use in a regional setting, and so produce timely macroeconomic indicators for the regional economy.

AB - The delays in the release of key economic variables mean that policymakers do not know their current values. Quickly produced, high frequency, indicators are essen- tial in understanding regional performance in a timely fashion. Thus, there is a need for nowcasts, which are estimates of the current values of such variables (e.g. GDP, employ- ment, etc.). This paper nowcasts growth in a regional economy, taking Scotland, UK, as our example. Regional nowcasting is complicated due to issues around data timeliness and availability. For instance, key nowcast predictors such as industrial production are often unavailable at the sub-national level. Accordingly, we use data on some non-traditional variables and investigate whether UK aggregates, and indicators for neighbouring regions of the UK, can help nowcast Scottish GDP growth. We show that these models and methods can be successfully adapted for use in a regional setting, and so produce timely macroeconomic indicators for the regional economy.

KW - nowcasting

KW - mixed frequency data

KW - regional economics

UR - https://link.springer.com/journal/13571

M3 - Article

SP - 1

EP - 25

ER -