scholarly journals Attention to social stratification in the public discourse: An empirical study based on big data of books (1949–2008)

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jiankun Liu ◽  
Yunsong Chen
Keyword(s):  
Public Discourse ◽  
Time Series Data ◽  
Principal Component ◽  
Macro Level ◽  
Series Data ◽  
Income Disparity ◽  
Public Attention ◽  
Causality Test ◽  
Reform And Opening Up ◽  
Opening Up

AbstractUsing the Chinese corpus of Google Books Ngram in line with other macro-level socioeconomic data, this paper examines and analyzes the trend of change in public discourse about social structure in China from 1949 to 2008, as well as the mechanism that influences this trend. We find that since the reform and opening-up, the official discourse on “class,” as constructed by the official ideology, has gradually declined, while the importance of a “stratum” discourse oriented toward the mass population has increased. Using principal component analysis, we generate an index for public attention on social strata and run it through a Granger causality test along with time-series data such as macro-level economic and political indicators. The results show that since the reform and opening-up, public attention to stratum has been influenced by the general trend of the economy, income disparity, and level of political participation. Income disparity influences public attention on stratum-related topics more than macro-level economic indicators do. Official intervention on public opinions does not affect public attention on the stratum, but the former is affected by the latter.

EMPIRICAL ANALYSIS OF INDIA’S FOREIGN TRADE AND ECONOMIC GROWTH

2020 ◽  
Vol 8 (10) ◽  
pp. 105-111
Author(s):  
Khujan Singh ◽  
Anil Kumar
Keyword(s):  
Time Series Data ◽  
Unit Root Test ◽  
Series Data ◽  
Significant Implication ◽  
Causality Test ◽  
First Order ◽  
Long Run ◽  
Directional Relation ◽  
Augmented Dickey Fuller ◽  
Vecm Granger Causality

The present study is an attempt to examine long run relationship among India’s GDP, Exports and Imports for which yearly time series data from 1995 to 2018 has been collected. Data for India’s GDP has been collected from RBI website and India’s export and import data has been collected form Ministry of Commerce and Industry website. The Augmented Dickey-Fuller unit root test for stationarity found that studied variables become stationary at first order of difference. While, Johnson cointegration test revealed long run cointegration between India’s GDP, exports and imports. The results of VECM Granger causality test exhibited bi-directional relationship between India’s GDP and India’s exports, whereas uni-directional relation has been found between India’s GDP and India’s imports. These results have significant implication for India’s export import policy and to achieve a target of $5 trillion economy till 2024-2025.

scholarly journals Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States

2021 ◽  
Vol 18 (9) ◽  
pp. 4560
Author(s):  
Mostafa Abbas ◽  
Thomas B. Morland ◽  
Eric S. Hall ◽  
Yasser EL-Manzalawy
Keyword(s):  
Functional Data ◽  
Time Series Data ◽  
Principal Component ◽  
State Level ◽  
The United States ◽  
Functional Principal Component Analysis ◽  
Series Data ◽  
Dynamic Correlation ◽  
The Us ◽  
Google Search

We utilize functional data analysis techniques to investigate patterns of COVID-19 positivity and mortality in the US and their associations with Google search trends for COVID-19-related symptoms. Specifically, we represent state-level time series data for COVID-19 and Google search trends for symptoms as smoothed functional curves. Given these functional data, we explore the modes of variation in the data using functional principal component analysis (FPCA). We also apply functional clustering analysis to identify patterns of COVID-19 confirmed case and death trajectories across the US. Moreover, we quantify the associations between Google COVID-19 search trends for symptoms and COVID-19 confirmed case and death trajectories using dynamic correlation. Finally, we examine the dynamics of correlations for the top nine Google search trends of symptoms commonly associated with COVID-19 confirmed case and death trajectories. Our results reveal and characterize distinct patterns for COVID-19 spread and mortality across the US. The dynamics of these correlations suggest the feasibility of using Google queries to forecast COVID-19 cases and mortality for up to three weeks in advance. Our results and analysis framework set the stage for the development of predictive models for forecasting COVID-19 confirmed cases and deaths using historical data and Google search trends for nine symptoms associated with both outcomes.

scholarly journals Globalization Nexus Terrorism: Evidence from Pakistan

2021 ◽  
Vol 7 (1) ◽  
pp. 177-184
Author(s):  
Sabeeha Naseer ◽  
Muhammad Kamran Khan ◽  
Sami Ullah
Keyword(s):  
Foreign Direct Investment ◽  
Direct Investment ◽  
Time Series Data ◽  
Series Data ◽  
Var Model ◽  
Causality Test ◽  
Time Period ◽  
Controlling Variables ◽  
Adf Test ◽  
Auto Regression

The current study investigates nexuses between globalization and terrorism in context of Pakistan. Time series data utilized for time period 1981 to 2017. The data has been taken from the World Governance Indicator (WGI) and Swiss global index (KOF). Augmented Dicky fuller (ADF) test was applied to check out stationary of all variables such as terrorism, globalization, remittances, foreign direct investment and trade. The results of ADF test indicated that all variables were stationary at first difference. For empirical analysis Johnson co-integration and VAR model under causality were applied. The co-integration result shows all variables terrorism, globalization, FDI, remittances and trade are not co-integrated. Vector Auto Regression (VAR) Model under causality test shows that Globalization is causing factor of terrorism. While, other controlling variables such as remittances cause globalization, foreign direct investment and trade.

scholarly journals The Nexus between Export and Economic Growth in Tanzania

2019 ◽  
Vol 1 (2) ◽  
pp. p95
Author(s):  
Romanus L. Dimoso (PhD, Economics) ◽  
UTONGA, Dickson (MSc. Economics)
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Series Data ◽  
Test Results ◽  
Causality Test ◽  
Goods And Services ◽  
Long Run ◽  
Causality Tests ◽  
The Government ◽  
Econometrics Analysis

This study explored the causal relationship between exports and economic growth in Tanzania. It analyzed time series data for the period of 1980 to 2015. Economic growth is measured in terms of growth per cent while exports are measured in percentage change of goods and services sold abroad. Econometrics analysis was employed in the due course. Such procedures as testing for the presence of unit root, co-integration and causality were done. Furthermore, the Johansen co-integration and Granger causality tests were employed to examine the long-run relationship among variables. The results of co-integration indicate the existence of one co-integrating equation. The causality test results exhibited causality which runs from economic growth to exports. The results conclude that, in the long run, there is a relationship between exports and economic growth in Tanzania. This study recommends the Government to make efforts to improve exports and eventually, in the long-run, rejuvenating the economy.

scholarly journals Islamic Finance and Economic Growth Nexus: An Econometric Analysis

2019 ◽  
Vol 2 (1) ◽  
pp. 11-22
Author(s):  
Kashif Raza ◽  
Rashid Ahmad ◽  
Muhammad Abdul Rehman Shah ◽  
Muhammad Umar
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Trade Openness ◽  
Unit Root Test ◽  
Least Square ◽  
Series Data ◽  
Islamic Finance ◽  
Causality Test ◽  
Economic Agents ◽  
Fixed Capital Formation

Researchers have written chain of research papers about the dynamics of financial development and economic growth. The financial capital plays a productive role when it delivers to economic agents who are facing shortage or excess of funds.  This study explores the linkages among Islamic financing and economic growth for Pakistan, by using annual time series data from 2005-2018. Islamic banks’ financing funds used as a proxy of Islamic financing, Gross Domestic Product (GDP), Gross Fixed Capital Formation (GFCF), labor force (LF),Broad money(M) and Trade openness (TO) to presents real sector of an economy. For the exploration, the unit root test, Ordinary least square technique and Granger causality test are applied. The results validate a substantial causal relationship of Islamic financing and GDP, which supports the Schumpeter’s supply-leading view. The results indicate that Islamic finance contributed towards economic growth.  

scholarly journals COINTEGRATING RELATION BETWEEN EXCHANGE RATE AND GOLD PRICE

2017 ◽  
Vol 5 (10) ◽  
pp. 263-269
Author(s):  
Ranjusha ◽  
Devasia ◽  
Nandakumar
Keyword(s):  
Exchange Rate ◽  
Time Series Data ◽  
Unit Root Test ◽  
Gold Price ◽  
Series Data ◽  
Annual Data ◽  
Causality Test ◽  
Long Run ◽  
Integration Test ◽  
The Relationship

The very purpose of this paper is to analyse the relationship between gold price and Rupee – Dollar exchange rate in India. The study utilises the annual data of exchange Rate (ER) and Gold Price (GP) from 1970 to 2015 to determine the relationship. Different econometric tools like Unit root test, Johansen co integration test, Vector error correction model, Granger causality test are used for detecting the long run relation, if any between the mentioned variables. The result shows that there exists a long run cointegrating relation between the variables. That is we can stabilise the Gold Price movement by controlling the exchange rate fluctuations. Likewise it also shows that Exchange rate doesn’t Granger cause to Gold price and vice versa. It means that the time series data of one vasriable cannot be used to predict another.

scholarly journals INDIKATOR MAKROEKONOMI DAN RETURN SAHAM SYARIAH DI INDONESIA

2013 ◽  
Vol 2 (2) ◽  
Author(s):  
Utami Baroroh
Keyword(s):  
Exchange Rate ◽  
Discount Rate ◽  
Stock Return ◽  
Time Series Data ◽  
Empirical Test ◽  
Cointegration Test ◽  
Series Data ◽  
Causality Test ◽  
Us Dollar

The objectives of this study are to examine empirical test the long term equilibrium and simulteneous relationship between macroeconomics variables to stock return in Indonesia and to observe stock return response because shock/innovation of inflation, SBI discount rate and exchange rate Rupiah to US dollar. The data sample used in this study are monthly time series data from 2003.1 – 2010.6. Those data are SBI discount rate, inflation (CPI), exchange rate Rupiah to US dollar, money supply and stock return (IHSG). A method of analysis in this study are Granger Causality Test and Cointegration test. The empirical results shows that SBI discount rate, inflation (CPI), and exchange rate Rupiah to US dollar have causality relationship to stock return.. The cointegration test indicates that among research variables there is long term equilibrium and simultaneous relationshipDOI: 10.15408/sjie.v2i2.2421

scholarly journals A Study on Estimation and Prediction of Vector Time Series Model Using Financial Big Data (Interest Rates)

2021 ◽  
Vol 12 (5) ◽  
pp. 309-316
Author(s):  
Jae-Hyun Kim, Chang-Ho An
Keyword(s):  
Time Series ◽  
Interest Rate ◽  
Prediction Model ◽  
Interest Rates ◽  
Time Series Data ◽  
Information Criteria ◽  
Series Data ◽  
Call Rate ◽  
Causality Test ◽  
Vector Autoregressive

Due to the global economic downturn, the Korean economy continues to slump. Hereupon the Bank of Korea implemented a monetary policy of cutting the base rate to actively respond to the economic slowdown and low prices. Economists have been trying to predict and analyze interest rate hikes and cuts. Therefore, in this study, a prediction model was estimated and evaluated using vector autoregressive model with time series data of long- and short-term interest rates. The data used for this purpose were call rate (1 day), loan interest rate, and Treasury rate (3 years) between January 2002 and December 2019, which were extracted monthly from the Bank of Korea database and used as variables, and a vector autoregressive (VAR) model was used as a research model. The stationarity test of variables was confirmed by the ADF-unit root test. Bidirectional linear dependency relationship between variables was confirmed by the Granger causality test. For the model identification, AICC, SBC, and HQC statistics, which were the minimum information criteria, were used. The significance of the parameters was confirmed through t-tests, and the fitness of the estimated prediction model was confirmed by the significance test of the cross-correlation matrix and the multivariate Portmanteau test. As a result of predicting call rate, loan interest rate, and Treasury rate using the prediction model presented in this study, it is predicted that interest rates will continue to drop.

scholarly journals AN ANALYTICAL STUDY OF TOTAL FDI INFLOW, OUTFLOW AND NET FDI OF FIVE SOUTH ASIAN COUNTRIES OVER THE PERIOD 1992–2019

2021 ◽  
pp. 417-435
Author(s):  
Sushanta Kumar Tarai ◽  
Prof. Sudhakar Patra
Keyword(s):  
Sri Lanka ◽  
South Asian ◽  
Analytical Study ◽  
Time Series Data ◽  
Secondary Data ◽  
Series Data ◽  
Asian Countries ◽  
Causality Test ◽  
Development Indicators ◽  
The World Bank

This present research aims to analyze the total FDI inflow, outflow and net FDI of five South Asian countries over the period 1992–2019.This study is based on 28years Time series data taken from the World Bank Development Indicators. In order to compare the FDI inflow, outflow and net FDI inflow of India, Pakistan, Sri Lanka, Bangladesh, Nepal over the period 1992–2019,both descriptive and inferential statistical tools such as correlation test, paired t test, the familiar linear regression model, Granger-Causality test, percentage analysis and tables, are used for analysis, hypothesis testing and interpretation of data. This study used various secondary data. Economic development of the developing countries like India, Pakistan, Sri Lanka, Bangladesh, and Nepal largely rely on FDI. However, the study also reveals that in the last two decades, India received 23 times more FDI than Bangladesh, Pakistan, Sri Lanka and Nepal. For attracting more FDI, these nations require to create more congenial and favorable atmosphere towards the foreign investors. It is also concluded that the after implementing make in India campaign investing countries in total FDI inflow are increased. KEYWORDS: FDI inflow, FDI outflow, GDP growth.

Sign in / Sign up

Export Citation Format

Share Document