scholarly journals The Effect of IJ-EPA to Indonesia Export: Interupted Time Series (ITS) Approach

2020 ◽  
Vol 2 (1) ◽  
pp. 128-145
Author(s):  
Yuafanda Kholfi Hartono ◽  
Sumarto Eka Putra
Keyword(s):  
Time Series ◽  
Free Trade ◽  
Free Trade Agreement ◽  
Time Series Data ◽  
Current Account Deficit ◽  
Trade Agreement ◽  
Export Market ◽  
Series Data ◽  
The Government ◽  
The Impact

Indonesia Japan Economic Partnership Agreement (IJ-EPA) is a bilateral free-trade agreement between Indonesia and Japan that has been started from July 1st, 2008. After more than a decade of its implementation, there is a question that we need to be addressed: Does liberalization of IJ-EPA make Indonesia’s export to Japan increase? This question is important since the government gives a trade-off by giving lower tariff for certain commodities agreed in agreement to increase export. Using Interrupted time series (ITS) analysis based on time-series data from Statistics Indonesia (BPS), this article found that the impact of IJ-EPA decreased for Indonesia export to Japan. Furthermore, this paper proposed some potential commodities that can increase the effectiveness of this FTA. The importance of this topic is that Indonesia will maximize the benefit in implementing of agreement that they made from the third biggest destination export of their total export value, so it will be in line with the government's goal to expand export market to solve current account deficit. In addition, the method that used in this paper can be implemented to other countries so that they can maximize the effect of Free Trade Agreement, especially for their export.

The China Factor Blunts the Cutting-Edge of the Japan-Malaysia Free Trade Agreement

2008 ◽  
Vol 8 (4) ◽  
pp. 1850152 ◽  
Author(s):  
Khondaker Mizanur Rahman ◽  
Rafiqul Islam Molla ◽  
Md. W. Murad
Keyword(s):  
Free Trade ◽  
Free Trade Agreement ◽  
Bilateral Trade ◽  
Time Series Data ◽  
Trade Agreement ◽  
Early Years ◽  
Sharp Edge ◽  
Series Data ◽  
Trade Growth ◽  
The Impact

Most industrialized and industrializing countries of the world were highly nervous about the spread effect of the surge of investment, industrialization and economic growth in China during early years of the 2000s. They were anxiously searching for ways and means to protect their economic interests from this effect. To describe this phenomenon eloquently the mass media used the term `China factor in world trade.' Against this backdrop the Japan-Malaysia free trade agreement (FTA) under an economic partnership agreement was signed in 2005 and implemented from 2006 with the expectation that it would be able to protect their bilateral trade from the sharp edge of the China factor and further enhance trade and investment relationships between the two countries. This study examines its effectiveness in influencing their bilateral trade growth in the face of this so called China factor. From analyses of the time series data on Malaysia's trade during 1986-2007 it is observed that the bilateral trade between Malaysia and Japan became stagnant during 2001-2005 with an average annual value of US$25.35 billion as a result of the impact of the China factor. However, during 2006-2007, the initial two years of its operation, the FTA was able to minimize the impacts of the China factor and revamp the growth of the bilateral trade at a modest rate. It is projected that their bilateral trade will grow marginally and reach to US$50.34 billion in 2010; but the growth rate will start declining from that year. This, in effect, indicates that the China factor's massive impact has blunted the sharp-edge of the Japan-Malaysia FTA's `tactical merit' for promoting bilateral trade growth. As a result, it is found to have only a modest and short lived influence on bilateral trade growth in the presence of China's increasing involvement in Malaysia's industrial growth. However, for a more reliable assessment a longer experience of FTA will be required.

scholarly journals A Determination Of The Trade Impacts Of The Australia-United States Free Trade Agreement

2011 ◽  
Vol 11 (1) ◽  
pp. 59
Author(s):  
P. Lynn Kennedy ◽  
Brian Hilbun
Keyword(s):  
United States ◽  
Free Trade ◽  
Free Trade Agreement ◽  
Time Series Data ◽  
Trade Flow ◽  
Trade Agreement ◽  
The United States ◽  
Series Data ◽  
Total Trade ◽  
The Impact

This paper seeks to determine the impact of the Australia-United States Free Trade Agreement (AUSFTA) on the flow of trade between Australia and the United States. To accomplish this, time series data were gathered for 10 SITC REV. 1(0-9) classifications for the years 1985-2009. These data were then sorted into three sub-classes (by direction of trade flow): 1) U.S. exports for that particular SITC class to Australia, 2) vice versa, and then 3) total trade volume for that particular sub-class between the two nations. These three classifications for each SITC class were then regressed against the explanatory variables of GDP (both Australian/U.S.), Population (both Australian/U.S.), the Relative Exchange Rate (AU$/US$), and a dummy trade agreement variable, AUSFTA. The results suggest that AUSFTA has been a greater trade creation catalyst for Australia than for the United States. In fact, for the United States, a greater level of trade diversion has been the result.

scholarly journals Financial Structure, Misery Index, and Economic Growth: Time Series Empirics from Pakistan

2019 ◽  
Vol 12 (2) ◽  
pp. 100 ◽  
Author(s):  
Nianyong Wang ◽  
Muhammad Haroon Shah ◽  
Kishwar Ali ◽  
Shah Abbas ◽  
Sami Ullah
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Trade Openness ◽  
Financial Structure ◽  
Series Data ◽  
Growth Time ◽  
Misery Index ◽  
The Government ◽  
The Impact

This study empirically analyzes the impact of the financial structure and misery index on economic growth in Pakistan. We adopted Autoregressive-Distributed Lag (ARDL) for a co-integration approach to the data analysis and used time series data from 1989 to 2017. We used GDP as the dependent variable; the Financial Development index (FDI) and misery index as the explanatory variables; and remittances, real interest, and trade openness as the control variables. The empirical results indicate the existence of a long-term relationship among the included variables in the model and the FD index, misery index, interest rate, trade openness, and remittances as the main affecting variables of GDP in the long run. The government needs appropriate reform in the financial sector and external sector in order to achieve a desirable level of economic growth in Pakistan. The misery index is constructed based on unemployment and inflation, which has a negative implication on the economic growth, and the government needs policies to reduce unemployment and inflation.

scholarly journals Impact of National Debt on Economic Growth in Tanzania: 1980-2019

2021 ◽  
pp. 85-96
Author(s):  
Lemada Lesamana Lelya ◽  
Deus D. Ngaruko
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
National Bureau ◽  
Validity And Reliability ◽  
Long Run ◽  
Domestic Debt ◽  
The Government ◽  
The Impact

This paper is based on the study that examined the impact of external and domestic debt on economic growth of Tanzania over the period 1980-2019. The study’s specific objectives were; to examine trends of external and domestic debts from 1980 to 2019, to determine long run relationship between external debt stock and economic growth in Tanzania from 1980 to 2019, and to examine the long run relationship between domestic debt and economic growth in Tanzania from 1980 to 2019. The study used time series data of Tanzania collected from the Bank of Tanzania (BOT), National Bureau of Statistics (NBS) and the World Bank indicators. The study used Vector error correction model (VECM) for estimation of the time series since all the variables’ data were stationary in first difference I (1), and there was cointegration within the variables. To ensure the validity and reliability of the data; the study carried out normality test, multicollinearity, heteroscedasticity, and unit root tests. The empirical findings reveal that both   external and domestic debt significantly affects the economic growth of Tanzania.  The study recommends that the government should promote moderate levels of domestic borrowing which can be sustained as it promotes economic growth if used in productive and efficient avenues. The study further recommends that policymakers should efficiently allocate and develop constraints that will ensure the external borrowing is utilized on more productive and  development expenditures, so that the finance is a source of increase in net investment in the country.

scholarly journals Vietnam’s Meat Import Market Under Impacts Of The European -Vietnam Free Trade Agreement And Quality Management Demand

Management ◽  
2021 ◽  
Vol 25 (1) ◽  
pp. 99-117
Author(s):  
Doan Nguyen Minh ◽  
Le Thi Viet Nga ◽  
Dinh Tran Ngoc Huy ◽  
Pham Minh Dat
Keyword(s):  
Quality Management ◽  
Free Trade ◽  
Free Trade Agreement ◽  
Trade Agreement ◽  
Global Competitiveness ◽  
The Social ◽  
Huge Impact ◽  
The Government ◽  
The Impact ◽  
Good Food

Abstract The impact of Free Trade Agreement (FTA) on commercial business of the member could be assessed by the potential and tangible effects. This paper is adopted by Partial equilibrium theory and SMART tool to measure the impact of EVFTA on the Vietnamese meat import (HS code 02). The result of this model is claimed that EVFTA has a huge impact on boosting the meat import from EU to Vietnam. However, the value of import in this category from European nations in each country and good fluctuated significantly. This study also proposes some measures for domestic businesses and the government to ensure the benefits on Vietnam’s livestock industry. Last but not least, meat quality management is one of vital issues under EFVTA and global competitiveness to meet higher expectation of consumers. Good food (meat) manufacturing practices need to be applied. That is the social contribution value of this paper.

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.

Transport infrastructure of the Rostov Oblast: Problems and prospects for development in the context of national projects implementation

2020 ◽  
Vol 19 (6) ◽  
pp. 1015-1034
Author(s):  
O.Yu. Patrakeeva
Keyword(s):  
Time Series Data ◽  
Mutual Influence ◽  
Rostov Oblast ◽  
Transport Infrastructure ◽  
Series Data ◽  
Cointegration Tests ◽  
Level Of Economic Development ◽  
Short Run ◽  
The Government ◽  
The Impact

Subject. The paper considers national projects in the field of transport infrastructure, i.e. Safe and High-quality Roads and Comprehensive Plan for Modernization and Expansion of Trunk Infrastructure, and the specifics of their implementation in the Rostov Oblast. Objectives. The aim is to conduct a statistical assessment of the impact of transport infrastructure on the region’s economic performance and define prospects for and risks of the implementation of national infrastructure projects in conditions of a shrinking economy. Methods. I use available statistics and apply methods and approaches with time-series data, namely stationarity and cointegration tests, vector autoregression models. Results. The level of economic development has an impact on transport infrastructure in the short run. However, the mutual influence has not been statistically confirmed. The paper revealed that investments in the sphere of transport reduce risk of accidents on the roads of the Rostov Oblast. Improving the quality of roads with high traffic flow by reducing investments in the maintenance of subsidiary roads enables to decrease accident rate on the whole. Conclusions. In conditions of economy shrinking caused by the complex epidemiological situation and measures aimed at minimizing the spread of coronavirus, it is crucial to create a solid foundation for further economic recovery. At the government level, it is decided to continue implementing national projects as significant tools for recovery growth.

Assessing the Impact of the Australia-United States Free Trade Agreement (AUSFTA) on Australian and Global Medicines Policy

2005 ◽  
Author(s):  
Thomas Alured Faunce ◽  
Evan Doran ◽  
David Henry ◽  
Peter Drahos ◽  
Andrew Searles ◽  
...  
Keyword(s):  
United States ◽  
Free Trade ◽  
Free Trade Agreement ◽  
Trade Agreement ◽  
The Impact

EFFECTS OF TREND AND PERIODICITY ON THE CORRELATION DIMENSION AND THE LYAPUNOV EXPONENTS

2008 ◽  
Vol 18 (12) ◽  
pp. 3679-3687 ◽  
Author(s):  
AYDIN A. CECEN ◽  
CAHIT ERKAL
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Lyapunov Exponents ◽  
Correlation Dimension ◽  
Time Series Data ◽  
Logistic Map ◽  
Model Identification ◽  
Series Data ◽  
Largest Lyapunov Exponent ◽  
The Impact

We present a critical remark on the pitfalls of calculating the correlation dimension and the largest Lyapunov exponent from time series data when trend and periodicity exist. We consider a special case where a time series Zi can be expressed as the sum of two subsystems so that Zi = Xi + Yi and at least one of the subsystems is deterministic. We show that if the trend and periodicity are not properly removed, correlation dimension and Lyapunov exponent estimations yield misleading results, which can severely compromise the results of diagnostic tests and model identification. We also establish an analytic relationship between the largest Lyapunov exponents of the subsystems and that of the whole system. In addition, the impact of a periodic parameter perturbation on the Lyapunov exponent for the logistic map and the Lorenz system is discussed.

scholarly journals A Comparison of Time-Series Predictions for Healthcare Emergency Department Indicators and the Impact of COVID-19

2021 ◽  
Vol 11 (8) ◽  
pp. 3561
Author(s):  
Diego Duarte ◽  
Chris Walshaw ◽  
Nadarajah Ramesh
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
General Regression Neural Network ◽  
Series Data ◽  
Machine Learning Model ◽  
Hospital Patients ◽  
Major Incidents ◽  
General Regression ◽  
The Impact

Across the world, healthcare systems are under stress and this has been hugely exacerbated by the COVID pandemic. Key Performance Indicators (KPIs), usually in the form of time-series data, are used to help manage that stress. Making reliable predictions of these indicators, particularly for emergency departments (ED), can facilitate acute unit planning, enhance quality of care and optimise resources. This motivates models that can forecast relevant KPIs and this paper addresses that need by comparing the Autoregressive Integrated Moving Average (ARIMA) method, a purely statistical model, to Prophet, a decomposable forecasting model based on trend, seasonality and holidays variables, and to the General Regression Neural Network (GRNN), a machine learning model. The dataset analysed is formed of four hourly valued indicators from a UK hospital: Patients in Department; Number of Attendances; Unallocated Patients with a DTA (Decision to Admit); Medically Fit for Discharge. Typically, the data exhibit regular patterns and seasonal trends and can be impacted by external factors such as the weather or major incidents. The COVID pandemic is an extreme instance of the latter and the behaviour of sample data changed dramatically. The capacity to quickly adapt to these changes is crucial and is a factor that shows better results for GRNN in both accuracy and reliability.

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