"Comparative Analysis of Age Effect, Period Effect, and Cohort Effect through Time Series Data Analysis - Focus on Changes in Consumer Perception of Corporate Social Responsibility"

2021 ◽  
Vol 32 (1) ◽  
pp. 49-73
Author(s):  
Hyewon Lee ◽  
Rando Kim
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Time Series Data ◽  
Cohort Effect ◽  
Age Effect ◽  
Consumer Perception ◽  
Series Data ◽  
Period Effect ◽  
Corporate Social ◽  
Time Series Data Analysis

scholarly journals The Forecast of the Number of Soldiers in the Saudi Arabian Army in Terms of Military Security

2021 ◽  
Vol 50 ◽  
pp. 1-10
Author(s):  
Bartosz Kozicki ◽  
◽  
Jarosław Zelkowski ◽  
Szymon Mitkow ◽  
Mariusz Gontarczyk ◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Comparative Analysis ◽  
Time Series Data ◽  
Saudi Arabian ◽  
Series Data ◽  
Middle East Countries ◽  
Military Security ◽  
Time Series Data Analysis ◽  
Klein’S Model ◽  
The Impact

The study concerns forecasting the number of soldiers in the Saudi Arabian army based on information obtained from the website: https://data.worldbank.org (The World Bank, 9.03.2020). The research began with a comparative analysis of the number of soldiers in the armies of Saudi Arabia and Russia. The idea for a comparative analysis of the number of armies of Saudi Arabia and the Russian Federation arises from Russian policy in the region of the Middle East countries, including the impact on world oil prices. The comparative analysis showed the similarities and differences in the dynamics of changes in the number of both armies dynamically. Subsequently, the primary time series data analysis on the number of Saudi Arabian troops was performed. The study selected methods for predicting raw data: Holt’s exponential smoothing and Klein’s model for the future. The next stage of the research was forecasting and the analysis and evaluation of the obtained forecasts. Klein’s model was the best forecasting model. The forecast of the number of soldiers in the Saudi Arabian army for 2020 is 251454, and for 2021, it has increased to 251006. The study ends with a summary and conclusions.

Examining the Long Run Effects of Export, Import and FDI Inflows on the FDI Outflows from India: A Causality Analysis

2009 ◽  
Vol 10 (1) ◽  
pp. 65-88
Author(s):  
Nandita Dasgupta
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Driving Force ◽  
Time Series Data ◽  
Series Data ◽  
Causality Analysis ◽  
Fdi Inflows ◽  
Long Run ◽  
Time Series Data Analysis ◽  
Trade And Investment

The objective of this paper is to examine the effects of international trade and investment related macro economic variables, namely, exports, imports and FDI inflows on the outflows of FDI from India over 1970 through 2005. Using time series data analysis, the empirical part of the paper finds unidirectional Granger Causality from export and import to FDI outflows but no such causality exists from FDI inflows to the corresponding outflows from India. Results confirm the assumption that lagged imports and exports are a driving force of ing front.

scholarly journals Periodic Time Series Data Analysis by Deep Learning Methodology

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223078-223088
Author(s):  
Haolong Zhang ◽  
Haoye Lu ◽  
Amiya Nayak
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Periodic Time Series ◽  
Time Series Data Analysis

Democratic peace: Does ethnic inclusiveness reduce interstate conflict?

2019 ◽  
pp. 019251211988473
Author(s):  
Seung-Whan Choi ◽  
Henry Noll
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Estimation Method ◽  
Interstate Conflict ◽  
Model Specification ◽  
Series Data ◽  
Democratic Peace ◽  
Interstate Disputes ◽  
Time Series Data Analysis ◽  
Cross National

In this study, we argue that ethnic inclusiveness is an important democratic norm that fosters interstate peace. When two states are socialized into the notion of ethnic tolerance, they acquire the ability to reach cooperative arrangements in time of crisis. Based on cross-national time-series data analysis covering the period 1950–2001, we illustrate how two states that are inclusive of their politically relevant ethnic groups are less likely to experience interstate disputes than states that remain exclusive. This finding was robust, regardless of sample size, intensity of the dispute, model specification, or estimation method. Therefore, we believe in the existence of ethnic peace: ethnic inclusiveness represents an unambiguous force for democratic peace.

Robust Extrema Features for Time-Series Data Analysis

2013 ◽  
Vol 35 (6) ◽  
pp. 1464-1479 ◽  
Author(s):  
Pramod K. Vemulapalli ◽  
Vishal Monga ◽  
Sean N. Brennan
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Time Series Data Analysis
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