Combining high-resolution gross domestic product data with home and personal care product market research data to generate a subnational emission inventory for Asia

2013 ◽  
Vol 10 (2) ◽  
pp. 237-246 ◽  
Author(s):  
Juliet Elizabeth Natasha Hodges ◽  
Raghu Vamshi ◽  
Christopher Holmes ◽  
Matthew Rowson ◽  
Taqmina Miah ◽  
...  
Keyword(s):  
High Resolution ◽  
Gross Domestic Product ◽  
Market Research ◽  
Emission Inventory ◽  
Product Market ◽  
Research Data ◽  
Domestic Product ◽  
Personal Care ◽  
Product Data ◽  
Personal Care Product

scholarly journals Methodological Features of GDP Formation Within the Framework of the System of National Accounts

2020 ◽  
Vol 17 (2) ◽  
pp. 10-17
Author(s):  
K. A. Alekseev
Keyword(s):  
Gross Domestic Product ◽  
Production Method ◽  
Product Formation ◽  
Standard System ◽  
Domestic Product ◽  
National Accounts ◽  
Product Data ◽  
International Standard ◽  
System Of National Accounts ◽  
The International Monetary Fund

Purpose of the study. The aim of this work is to examine methodological approaches to the formation of gross domestic product on an annual and quarterly basis within the framework of the System of National Accounts, using the example of 189 countries. The work is based on a dynamic and structural analysis of statistical information of gross domestic product published on the official websites of statistical agencies and the International Monetary Fund.Materials and methods. The information base of the study is the official statistical data of countries published on the website of the International Monetary Fund, as well as methodological provisions for the formation of gross domestic product. The research methodological base is represented by statistical methods of information analysis and empirical research.Results. The analysis of data and methodological approaches to gross domestic product formation in different countries has been carried out, as a result of which the main problems of a number of countries regarding the accuracy and relevance of gross domestic product data have been identified. These problems are grouped into six key criteria based on practical macroeconomic approaches, in particular gross domestic product: updating of the base year, annual and quarterly gross domestic product data, timeliness of reporting gross domestic product data, method of compiling gross domestic product (production, expenditure, income), use of the international standard “System of national accounts, 2008”.Conclusion. Despite a rather large volume of macroeconomic indicators, one of the main indicators is gross domestic product, the dynamics of which reflects the development of the economy. Therefore, reliable data on gross domestic product play a key role in the analysis of macroeconomic and financial policies, as well as in the analysis and accuracy of forecasting the development of the country’s economy. The study revealed that 50% of the countries surveyed had acceptable base years, meaning that the transition to the new base year did not exceed 10 years. Virtually all countries generate annual gross domestic product data, while quarterly estimates of gross domestic product form about 65% of countries. The timeliness of data dissemination also varies from country to country, and many do not publish date information. 72% surveyed countries provide annual gross domestic product data in a timely manner, while 55% surveyed countries provide quarterly gross domestic product data in a timely manner. The production method is the most common of the three methods of calculating gross domestic product (the production method, the method of using income and the generation of gross domestic product by source of income). Gross domestic product formation in accordance with the current version of the international standard “System of National Accounts, 2008” is applied in 52% of countries, and in most other countries the previous version of the international standard “System of National Accounts, 1993” is used.

scholarly journals Modeling Agricultural Gross Domestic Product of Kenyan Economy Using Time Series

2018 ◽  
pp. 1-12
Author(s):  
Musyoki M. Ngungu ◽  
Ong'ala Jacob ◽  
Wawire Noah
Keyword(s):  
Time Series ◽  
Gross Domestic Product ◽  
Significant Role ◽  
Domestic Product ◽  
Time Series Modeling ◽  
Product Data ◽  
Agriculture Sector ◽  
Modeling Approach

The agriculture sector is the mainstay of the Kenyan economy. Thus, the sector has a significant role and contribution to GDP. In this study, Box-Jenkins seasonal ARIMA time series modeling approach is used to develop a model that best describes the quarterly agricultural gross domestic product of Kenyan economy. Agricultural gross domestic product data collected quarterly from 2000-2014 at constant 2001 prices is used for modeling. From the analysis, SARIMA(1, 0, 0)(1, 1, 0)4 was found to be the best model describing the quarterly agricultural gross domestic product of Kenyan economy.

scholarly journals ARIMA Model for Gross Domestic Product (GDP): Evidence from Nigeria

2020 ◽  
pp. 49-61
Author(s):  
Atanu, Enebi Yahaya ◽  
Ette, Harrison Etuk ◽  
Nwuju, Kingdom ◽  
Nwaoha, William Chimee
Keyword(s):  
Gross Domestic Product ◽  
Arima Model ◽  
Research Data ◽  
Domestic Product ◽  
Annual Data ◽  
Important Index ◽  
Sample Data ◽  
Out Of Sample

A nation’s GDP is an important index reflecting development in economy and incomes. This paper uses the annual data of Nigeria’s GDP from 1981 to 2019 as the research data. An Augmented Dick Fuller test was used to test for stationarity of the data and was seen to be stationary at the second differencing. ARIMA (1, 2, 1) was identified as an appropriate model using Eviews 11 software after comparing the AIC values. The Ljung-Box test of the Residual satisfied that the model was adequate and was used to forecast the out of sample data. And with a Theil inequality of 0.022008, the model forecasting ability is deemed be a good.

scholarly journals Spatially explicit global gross domestic product (GDP) data set consistent with the Shared Socioeconomic Pathways

2021 ◽  
Author(s):  
Tingting Wang ◽  
Fubao Sun
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Gross Domestic Product ◽  
Socioeconomic Development ◽  
Domestic Product ◽  
Spatially Explicit ◽  
Historical Period ◽  
Data Set ◽  
Climate Change Research ◽  
Fixed Base

Abstract. The increasing demand of ScenarioMIP is calling for GDP projections of high resolution for the future Shared Socioeconomic Pathways (SSPs) in both socioeconomic development and in climate change of adaption and mitigation research. While to date the global GDP projections for five SSPs are mainly provided at national scales, and the gridded data set are very limited. Meanwhile, the historical GDP can be disaggregated using nighttime light (NTL) images but the results are not open accessed, making it cumbersome in climate change impact and socioeconomic risk assessments across research disciplines. To this end, we produce a set of spatially explicit global Gross Domestic Product (GDP) that presents substantial long-term changes of economic activities for both historical period (2005 as representative) and for future projections under all five SSPs with a spatial resolution of 30 arc-seconds. Chinese population in SSP database were first replaced by the projections under the two-children policy implemented since 2016 and then used to spatialize global GDP using NTL images and gridded population together as fixed base map, which outperformed at subnational scales. The GDP data are consistent with projections from the SSPs and are freely available at http://doi.org/10.5281/zenodo.4350027 (Wang and Sun, 2020). We also provide another set of spatially explicit GDP using the global LandScan population as fixed base map, which is recommended at county or even smaller scales where NTL images are limited. Our results highlight the necessity and availability of using gridded GDP projections with high resolution for scenario-based climate change research and socioeconomic development that are consistent with all five SSPs.

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