Population growth and poverty: Another look at the Indian time series data

1985 ◽  
Vol 21 (3) ◽  
pp. 429-439 ◽  
Author(s):  
Dominique van de Walle
Keyword(s):  
Time Series ◽  
Population Growth ◽  
Time Series Data ◽  
Series Data

scholarly journals Pengaruh Pertumbuhan Ekonomi, Tingkat Inflasi, dan Pertumbuhan Penduduk terhadap Tingkat Pengangguran Terbuka di Indonesia

2019 ◽  
Vol 18 (1) ◽  
pp. 52
Author(s):  
Irma Yuni Astuti ◽  
Nanik Istiyani ◽  
Lilis Yuliati
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Population Growth ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data

This study aims to determine the effect of economic growth, inflation and population growth in open unemployment rate in Indonesia. The type of data used in this study is secondary data in the form of time series data and variable data used are annual data in the period 1986-2017 with the object of research in the country o Indonesia. The data sources used in this study were obtained from the Central Statistics Agency (BPS) Indonesia and World Bank. The analytical method used in this study is multiple linear regression analysis with the Ordinary Least Square (OLS) technique. The estimation of time series data with multiple linear regression analysis shows that the economics growth variable has a positive and not significant effect on the level of open unemployment, the inflation variable has a positive and not significant effect on the level of open unemployment, and the population growth variable has a negative and significant effect on the level of open unemployment in Indonesia. Keywords: Open Unemployment, Economic Growth, Inflation, Population Growth

scholarly journals Evaluasi wilayah unggulan pengembangan kuda Sandelwood di Kabupaten Sumba Barat Daya Provinsi Nusa Tenggara Timur

2021 ◽  
Vol 19 (2) ◽  
pp. 149
Author(s):  
Melkianus Dedimus Same Randu ◽  
Ewaldus Wera
Keyword(s):  
Time Series ◽  
Population Growth ◽  
Quantitative Method ◽  
Local Community ◽  
Time Series Data ◽  
Series Data ◽  
Mapping Data ◽  
Location Quotient ◽  
Dynamic Location ◽  
Potential Area

<p class="MDPI17abstract"><strong>Objective: </strong>The Sandalwood Horse has economic, social, and cultural advantages to the local community in Southwest Sumba Regency. However, sandalwood horse development is experiencing obstacles due to the absence of base area mapping data. This research aims to identify the potential area for the development of the Sandalwood horse in Southwest Sumba Regency.</p><p class="MDPI17abstract"><strong>Methods: </strong>Descriptive quantitative method was used in this research. Time series data (2013-2018) was collected from related stakeholders in Southwest Sumba Regency. The Location Quotient (LQ), Dynamic Location Quotient (DLQ) and a combination of both LQ and DLQ analysis were applied to identify the potential area for the development of the Sandalwood horse. If the value of LQ and DLQ is more than 1, it means that the area/district could be recommended as a potential area for the development of the Sandalwood horse.<strong></strong></p><p class="MDPI17abstract"><strong>Results</strong><strong>: </strong>The result shows that of the 11 (eleven) districts in Southwest Sumba Regency, only 5 (five) districts (Wewewa Utara, Wewewa Barat, Wewewa Selatan, Wewewa Tengah, and Kodi Bangedo) could be recommended as the potential areas for development of sandalwood horses in the future, with an average LQ value ranging from 1.01 to 1.85 and DLQ ranging from 1.27 to 78.27.<strong></strong></p><strong>Conclusions: </strong>Southwest Sumba Regency has potential districts for the development of the Sandalwood horse. The sandalwood horse in the potential districts is a leading commodity that can fulfil the local needs of each sub-district and has a population growth above the average level in Southwest Sumba Regency.

scholarly journals Relationships among Carbon Emissions, Economic Growth, Energy Consumption and Population Growth: Testing Environmental Kuznets Curve Hypothesis for Brazil, China, India and Indonesia

2019 ◽  
Author(s):  
Md. Mahmudul Alam ◽  
Wahid Murad ◽  
Abu Hanifa Md. Noman ◽  
Ilhan Ozturk
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Population Growth ◽  
Co2 Emissions ◽  
Environmental Kuznets Curve ◽  
Time Series Data ◽  
Series Data ◽  
Kuznets Curve ◽  
Long Run ◽  
Short Run

This study examines the impacts of income, energy consumption and population growth on CO2 emissions by employing an annual time series data for the period 1970-2012 for India, Indonesia, China, and Brazil. The study used the Autoregressive Distributed Lag (ARDL) bounds test approach considering both the linear and non-linear assumptions for related time series data for the top CO2 emitter emerging countries in both the short run and long run. The results show that CO2 emissions have increased statistically significantly with increases in income and energy consumption in all four countries. While the relationship between CO2 emissions and population growth was found to be statistically significant for India and Brazil, it has been statistically insignificant for China and Indonesia in both the short run and long run. Also, empirical observations from the testing of environmental Kuznets curve (EKC) hypothesis imply that in the cases of Brazil, China and Indonesia, CO2 emissions will decrease over the time when income increases. So based on the EKC findings, it can be argued that these three countries should not take any actions or policies, which might have conservative impacts on income, in order to reduce their CO2 emissions. But in the case of India, where CO2 emissions and income were found to have a positive relationship, an increase in income over the time will not reduce CO2 emissions in the country.

scholarly journals IMPACT OF FOREIGN DIRECT INVESTMENT, EXTERNAL DEBT AND POPULATION ON ECONOMIC GROWTH OF PAKISTAN: 1980-2014

2016 ◽  
Vol 55 (2) ◽  
pp. 101-114
Author(s):  
Shoukat Ali ◽  
M.Athar Hussain ◽  
Aqsa Zulqaif
Keyword(s):  
Time Series ◽  
Foreign Direct Investment ◽  
Population Growth ◽  
Direct Investment ◽  
Time Series Data ◽  
Negative Impact ◽  
External Debt ◽  
Series Data ◽  
Augmented Dickey Fuller ◽  
The Impact

This study aims to analyze the impact of Foreign Direct Investment(FDI), external debt and population growth on economic progress of Pakistan by using time series data from 1980 to 2014. It analyzes the correlation between Gross Domestic Product(GDP),FDI, external debt and population growth. Augmented Dickey Fuller test has been used to check stationarity in time series data. To evaluate the empirical results multiple regression method is used. GDP has been used as a dependent variable while FDI, external debt and population as independent variables. Findings of this paper show the positive and significant impact of FDI, and population growth on GDP but external debt has negative impact on GDP.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

Sign in / Sign up

Export Citation Format

Share Document