Nowcasting Using Mixed Frequency Methods: An Application to the Scottish Economy

Grant Allan, Gary Koop, Stuart McIntyre and Paul Smith

Sankhya B: The Indian Journal of Statistics, 2019, vol. 81, issue 1, No 2, 12-45

Abstract: 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 essential in understanding economic 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, employment, etc.). This paper nowcasts economic growth in Scotland. Nowcasting the Scottish economy is complicated because the government statistical agency treats Scotland as a region within the UK. This raises issues of data timeliness and availability. For instance, key nowcast predictors such as industrial production are 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. Similar considerations hold for other regions in other countries. Thus, we show that these models and methods can be successfully adapted for use in a regional setting, and so produce timely macroeconomic indicators for other regional economies.

Keywords: Nowcasting; Mixed frequency data; Regional economics (search for similar items in EconPapers)
JEL-codes: C13 C53 O18 P20 R11 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13571-018-0181-2

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