An Econometric Analysis of Markets for Pulses: A Case Study of Green Gram

2020 ◽  
pp. 559-564
Keyword(s):  
Time Series ◽  
Tamil Nadu ◽  
Time Series Data ◽  
Price Volatility ◽  
Green Gram ◽  
Series Data ◽  
Causality Test ◽  
Long Run ◽  
Adf Test ◽  
Long Run Equilibrium

Due to reduced crop area under pulses and ever-increasing domestic demand, India imports every year large chunks of a variety of pulses. The time series econometric analyses was used to estimate market integration, price transmission, and price volatility happening in the major domestic markets for one of the imported pulses namely green gram. The time-series data pertained to prices of a green gram for the major markets are sourced from 2006 to 2018 on a monthly frequency. Further, the vertical integration among the production and consumption markets were also studied using these analyses. In order to remove the non-stationarity element in the price series, the ADF test was used, which were non-stationary at levels but became stationary at the first difference. The price volatility prevailing in the green gram markets of India was estimated by GARCH (1,1) model revealed that all the markets were exhibiting consistent variability in market prices. Among these markets, there existed bi-directional causation which was confirmed by the Granger Causality test. The presence of three co-integration vectors for these markets proved the existence of a long-run equilibrium for green gram prices. Tamil Nadu market came under short-run equilibrium whereas remaining markets had long-run equilibrium estimated by VECM. Retail prices of Madurai market had bi-directional price influence with Tamil Nadu market. Hence it is suggested that better price discovery and timely market intelligence would be necessary to manage the price shocks occurring in the green gram markets in India.

scholarly journals IMPACT OF OFFICIAL DEVELOPMENT ASSISTANCE ON SUSTAINABLE DEVELOPMENT OF PAKISTAN

2021 ◽  
pp. 11-21
Keyword(s):  
Time Series ◽  
Sustainable Development ◽  
Time Series Data ◽  
Development Assistance ◽  
Official Development Assistance ◽  
Foreign Assistance ◽  
Series Data ◽  
Distributed Lag ◽  
Long Run ◽  
Adf Test

This research paper aims to find out the relationship between Official Development Assistance and sustainable development in Pakistan. Time series data was taken for the period of 42 years (1976 -2017). Sustainable Development is a dependent variable for which proxy variable of Adjusted Net Savings has been deployed. ODA (% of GNI), Inflation, Per Capita GDP and Trade (GDP %) have been used as explanatory variables. Augmented Dickey-Fuller Test has been applied to examine the nature of the data as time series data may contain unit root problems. ADF test confirms mixed order of integration for the selected variables, hence Autoregressive Distributed Lag (ARDL) Approach was applied to find out the long-run relationship among the considered variables. Estimation of Error Correction Regression resulted in a significant long-run relationship between ODA and Sustainable Development. ECM Regression also signifies the negative and significant value of the speed of adjustment term confirming that the model is stable and convergent towards the equilibrium. Overall results of this study confirm a positive and highly significant relationship between ODA and the measure of sustainable development in Pakistan. Therefore it is recommended that attention should be given to drawing on foreign assistance and it should be subject to the transparent and efficient practices applied in the Aid Allocation. It significantly improves the overall welfare of Pakistan.

scholarly journals Phillips Curve or Locus Critique: Time Series Evidence from Pakistan

2012 ◽  
Vol 4 (4) ◽  
pp. 190-193 ◽  
Author(s):  
Ihtisham Ul Haq ◽  
Alam Khan . ◽  
Ejaz Ahmed .
Keyword(s):  
Time Series ◽  
Phillips Curve ◽  
Time Series Data ◽  
Positive Association ◽  
Stationary Problem ◽  
Series Data ◽  
Significant Positive Association ◽  
Long Run ◽  
Short Run ◽  
Adf Test

Some economic problems facing by any economy are addressed such that minimum levels of these are acceptable. Inflation and unemployment are among such macroeconomic issues of which certain minimum level of both are accepted by economists. Nature of relationship between unemployment and inflation is important in economic literature. This study was performed to find this nature for a developing country. Time series data on both variables was analyzed for Pakistan from 1974 to 2010. ADF test was applied for detection of non-stationary. Problem of non-stationary was detected when variables were at level, which was eliminated by taking variables at first difference. Johansen co-integration confirmed one cointegration vector, which suggested the presence of long run relation between variables. VECM was used to find short and long run estimates. A short run relation was witnessed when unemployment worked as dependent variable and inflation as explanatory variable. This model was in equilibrium and thirty five percent disequilibria were adjusted annually as ECT value suggested. Inflation had a significant positive association with unemployment in study period. This study supported the Locus critique as opposed to Phillips curve hypothesis. Policy makers should pay special attention to this relationship between inflation and unemployment when they are going to design macroeconomic policies for Pakistan’s economy.

scholarly journals The Impact of Infrastructure on Tourism: The Case of Sri Lanka

2019 ◽  
Vol 15 (7) ◽  
pp. 174 ◽  
Author(s):  
A. M. M. Mustafa
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Time Series Data ◽  
Positive Impact ◽  
Series Data ◽  
Long Run ◽  
Short Run ◽  
The Government ◽  
The Impact ◽  
Adf Test

This study examines the impact of infrastructure on tourism development in Sri Lanka with greater emphasis on road network. The time period used in this study are ranging from year 2005 to year 2017. The annual time series data are analyzed by using statistical package, E-Views 10 after the preliminary calculations by using Microsoft Excel. The unit root of the variables is tested by ADF test to test the stationarity of the time series data used in the model of this study. Co-integration is tested with the use of Engle–Granger. The relationship of causality between the variables is found by test of Granger Causality. The results show that infrastructure has significant short run as well long run positive impact on tourism. Two-way causal relationship is found between tourism sector and infrastructure. Further, this study recommends that the government should play its role in improving the infrastructure facilities to increase tourist’s arrival in Sri Lanka.

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 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 Consequences of Capital formation, Trade Liberalization on the Economic Growth: Pakistan’s Experience

2015 ◽  
Vol 2 (1) ◽  
pp. 1-4
Author(s):  
Nadia Bukhari ◽  
Anjum Iqbal
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Trade Openness ◽  
Capital Formation ◽  
Vital Role ◽  
Series Data ◽  
Distributed Lag ◽  
Long Run ◽  
Auto Regressive ◽  
Adf Test

This study considers the long run relationship between the liberalization of trade, capital formation and the economic growth of Pakistan by using the time series data from 1975-2013. The main aim of this study is to examine that how much liberalization of trade and capital formation affects the economic growth of Pakistan in long run. The approach that has been used for empirical analysis is Auto Regressive Distributed Lag (ARDL) model. Under the ADF test capital formation (CF) is stationary at its first level but the trade openness (TO) and GDP is stationary at its first difference. Moreover, the granger casualty test is evident that there become a casual relationship between the trade openness and GDP. The result of this study shows that both the trade openness and the capital formation determined the economic growth in long run and they both have statistically significant effect on the GDP. Furthermore it has has been depicted from the study that the trade has a vital role to influence the economic growth.

scholarly journals Political Stability and its Impact on Economic Growth of Pakistan (1988-2018): A Time Series Analysis

2020 ◽  
Vol 6 (1) ◽  
pp. 273-282
Author(s):  
Majid Hussain Phul ◽  
Muhammad Saleem Rahpoto ◽  
Ghulam Muhammad Mangnejo
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Political Stability ◽  
Series Data ◽  
Explanatory Variables ◽  
Long Run ◽  
Short Run ◽  
The Impact ◽  
Positive Effect

This research paper empirically investigates the outcome of Political stability on economic growth (EG) of Pakistan for the period of 1988 to 2018. Political stability (PS), gross fixed capital formation (GFCF), total labor force (TLF) and Inflation (INF) are important explanatory variables. Whereas for model selection GDPr is used as the dependent variable. To check the stationary of time series data Augmented Dickey Fuller (ADF) unit root (UR) test has been used,  and whereas to find out the long run relationship among variables, OLS method has been used. The analysis the impact of PS on EG (EG) in the short run, VAR model has been used. The outcomes show that all the variables (PS, GFCF, TLF and INF) have a significantly positive effect on the EG of Pakistan in the long run period. But the effect of PS on GDP is smaller. Further, in this research we are trying to see the short run relationship between GDP and other explanatory variables. The outcomes show that PS does not have such effect on GDP in the short run analysis. While GFCF, TLF and INF have significantly positive effect on GDP of Pakistan in the short run period.

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 How applicable is export-led growth and import-led growth hypotheses to South African economy?

2015 ◽  
Vol 4 (2) ◽  
pp. 15-24
Author(s):  
Ntebogang Dinah Moroke ◽  
Molebogeng Manoto
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Adverse Effect ◽  
Time Series ◽  
South African ◽  
Time Series Data ◽  
Series Data ◽  
Long Run ◽  
Reserve Bank ◽  
Equilibrium Relationship

This paper investigated exports, imports and the economic growth nexus in the context of South Africa. The paper sets out to examine if long-run and causal relationships exist between these variables. Quarterly time series data ranging between 1998 and 2013 obtained from the South African Reserve Bank and Quantec databases was employed. Initial data analysis proved that the variables are integrated at their levels. The results further indicated that exports, imports and economic growth are co-integrated, confirming an existence of a long-run equilibrium relationship. Granger causal results were shown running from exports and imports to GDP and from imports to exports, validating export-led and import-led growth hypotheses in South Africa. A significant causality running from imports to exports, suggests that South Africa imported finished goods in excess. If this is not avoided, lots of problems could be caused. A suggestion was made to avoid such problematic issues as they may lead to replaced domestic output and displacement of employees. Another dreadful ramification may be an adverse effect on the economy which may further be experienced in the long-run.

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