<abstract xmlns="http://www.w3.org/1999/xhtml">This paper aims to estimate monthly Gross Domestic Product (GDP<xref ref-type="fn" rid="j_icas-2019-0009_fn_001_w2aab3b7c17b1b6b1ab1aaAa">1</xref>), which is an important aggregate indicator; It shows the trend of economic activity in the short term. Thus, the macroeconomic and financial risks in the short term with influences on financial markets and investor confidence (economic sentiment) can be identified and correlated. In addition, the monthly GDP series provides a condensed set of information (monthly data) needed to develop potential GDP estimating models correlated with inflation, unemployment and relevant indicators of labor market. Another applicability is quarterly GDP forecast at least two months ahead of the flash estimate published by National Institute of Statistics (NIS<xref ref-type="fn" rid="j_icas-2019-0009_fn_002_w2aab3b7c17b1b6b1ab1ab1Aa">2</xref>). This article presents a method of estimating the monthly GDP on the supply side. Gross value added has been broken down into five components: industry, construction, trade and transport, other market services, other activities, the first four of which are well interpolated with unifactorial regressions and some monthly explanatory variables. The results show a high correlation between the 4 components of supply and the additional aggregated quarterly series that are also available on a monthly basis. The highest dynamics of monthly GDP was recorded in August 2017 (+9.3%) and the lowest increase in August 2014 (+1.4%) over the period 2014-2018. Starting in January 2018, economic growth slow down, <italic>amid a pronounced base effect of the private consumption and weakening external demand</italic>.</abstract>

This paper aims to estimate monthly Gross Domestic Product (GDP1), which is an important aggregate indicator; It shows the trend of economic activity in the short term. Thus, the macroeconomic and financial risks in the short term with influences on financial markets and investor confidence (economic sentiment) can be identified and correlated. In addition, the monthly GDP series provides a condensed set of information (monthly data) needed to develop potential GDP estimating models correlated with inflation, unemployment and relevant indicators of labor market. Another applicability is quarterly GDP forecast at least two months ahead of the flash estimate published by National Institute of Statistics (NIS2). This article presents a method of estimating the monthly GDP on the supply side. Gross value added has been broken down into five components: industry, construction, trade and transport, other market services, other activities, the first four of which are well interpolated with unifactorial regressions and some monthly explanatory variables. The results show a high correlation between the 4 components of supply and the additional aggregated quarterly series that are also available on a monthly basis. The highest dynamics of monthly GDP was recorded in August 2017 (+9.3%) and the lowest increase in August 2014 (+1.4%) over the period 2014-2018. Starting in January 2018, economic growth slow down, amid a pronounced base effect of the private consumption and weakening external demand.

Modelling monthly Gross Domestic Product on the supply side. A case study for Romania

Proceedings of the International Conference on Applied Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This paper aims to estimate monthly Gross Domestic Product (GDP1), which is an important aggregate indicator; It shows the trend of economic activity in the...

Modelling monthly Gross Domestic Product on the supply side. A case study for Romania

Data publikacji: 13 lut 2020

Zakres stron: 101 - 114

DOI: https://doi.org/10.2478/icas-2019-0009

Słowa kluczowe
monthly GDP, monthly interpolation, national accounts, modelling

© 2019 Alina Mirela Bălţăţeanu, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Modelling monthly Gross Domestic Product on the supply side. A case study for Romania

Data publikacji: 13 lut 2020

Zakres stron: 101 - 114

DOI: https://doi.org/10.2478/icas-2019-0009

Słowa kluczowemonthly GDP, monthly interpolation, national accounts, modelling

© 2019 Alina Mirela Bălţăţeanu, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
monthly GDP, monthly interpolation, national accounts, modelling