scholarly journals Modelling the Impact of Government Policies on Import on Domestic Price of Indian Gold Using ARIMA Intervention Method

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Jyothi Unnikrishnan ◽  
Kodakanallur Krishnaswamy Suresh
Keyword(s):  
Current Account Deficit ◽  
Moving Average ◽  
Arima Model ◽  
Trade Deficit ◽  
Government Policies ◽  
Suitable Model ◽  
Domestic Price ◽  
Gold Market ◽  
The Government ◽  
The Impact

The study attempts to determine the impact of government policies of import of gold in India on the domestic price of gold during 2013 using Autoregressive Integrated Moving Average (ARIMA) intervention model. 2013 was an amazing year for Indian gold market where the price had reached its zenith. In April 2013, to curb a record trade deficit, India imposed an import duty of 10 percent on gold and tied imports for domestic consumption to exports, creating scarce supply of the yellow metal and boosting premiums to curtail the Current Account Deficit (CAD). The objective of the paper is to model the impact of this intervention by the government on the domestic price of Indian gold. Suitable ARIMA model is fit on the preintervention period and thereafter the effects of the interventions are analysed. The results indicate that ARIMA(1,1,1)is the most suitable model during preintervention period. Intervention analysis reveals that there is significant decrease in domestic price of gold by 56% from 2013. The model may be used by policymakers to analyse the future of gold before framing regulations and policies.

scholarly journals Forecasting Monthly Gold Prices using ARIMA Model: Evidence from Indian Gold Market

2019 ◽  
Vol 8 (9S3) ◽  
pp. 1373-1376
Keyword(s):  
Moving Average ◽  
Arima Model ◽  
Gold Price ◽  
Data Series ◽  
Suitable Model ◽  
Natural Logarithm ◽  
Price Series ◽  
Gold Market ◽  
Sample Data ◽  
Augmented Dickey Fuller

In this paper an attempt has been made to give an overview of the Indian gold market so as to develop a model enabling the forecast of gold prices in India. One troy ounce is equal to 31.103 grams. The monthly sample data of gold price (in INR per troy ounce) is taken from December 1997 to December 2017.The entire data has been divided into two segments for estimation and validation sample and to find out the efficiency and accuracy of forecasting models. Since the gold price data series have shown much deviation after March 2006 the first segment of the data is taken from the time period of December 1997 to March 2006 and second segment from April 2006 to December 2017.Due to a larger value and a huge time span of the sample data, the natural logarithm of gold price has been taken to conduct the study and build an effective model to forecast future gold prices. The unit root tests of Augmented Dickey Fuller‖ and Philips Perron have been used to test the gold price series as stationary or non-stationary. It is observed that series are stationary at first difference in both the methods. At first difference the ACFs and PACFs were pattern less and statistically not significant. Box-Jenkins’s Autoregressive Integrated Moving Average of Box-Jenkins methodology has been used for developing a forecasting model of gold price in India. Different models of ARIMA have been used to obtain best suitable model for forecasting using Eviews software 10 for both time periods i.e., December 1997 to March 2006 & April 2006 to December 2017

scholarly journals Estimating COVID-19 cases in Makkah region of Saudi Arabia: Space-time ARIMA modeling

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250149
Author(s):  
Fuad A. Awwad ◽  
Moataz A. Mohamoud ◽  
Mohamed R. Abonazel
Keyword(s):  
Saudi Arabia ◽  
Moving Average ◽  
Arima Model ◽  
Daily Basis ◽  
World Health ◽  
Arima Models ◽  
Autoregressive Integrated Moving Average ◽  
First Case ◽  
Novel Coronavirus ◽  
The Impact

The novel coronavirus COVID-19 is spreading across the globe. By 30 Sep 2020, the World Health Organization (WHO) announced that the number of cases worldwide had reached 34 million with more than one million deaths. The Kingdom of Saudi Arabia (KSA) registered the first case of COVID-19 on 2 Mar 2020. Since then, the number of infections has been increasing gradually on a daily basis. On 20 Sep 2020, the KSA reported 334,605 cases, with 319,154 recoveries and 4,768 deaths. The KSA has taken several measures to control the spread of COVID-19, especially during the Umrah and Hajj events of 1441, including stopping Umrah and performing this year’s Hajj in reduced numbers from within the Kingdom, and imposing a curfew on the cities of the Kingdom from 23 Mar to 28 May 2020. In this article, two statistical models were used to measure the impact of the curfew on the spread of COVID-19 in KSA. The two models are Autoregressive Integrated Moving Average (ARIMA) model and Spatial Time-Autoregressive Integrated Moving Average (STARIMA) model. We used the data obtained from 31 May to 11 October 2020 to assess the model of STARIMA for the COVID-19 confirmation cases in (Makkah, Jeddah, and Taif) in KSA. The results show that STARIMA models are more reliable in forecasting future epidemics of COVID-19 than ARIMA models. We demonstrated the preference of STARIMA models over ARIMA models during the period in which the curfew was lifted.

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.

Impacts of Government Policies, Fuel Cell Cost, and Battery Cost on Greenhouse Gas Emission of Light-Duty Vehicles

2013 ◽  
Author(s):  
Swithin S. Razu ◽  
Shun Takai
Keyword(s):  
Public Policy ◽  
Fuel Cell ◽  
Greenhouse Gas ◽  
Greenhouse Gas Emission ◽  
Ghg Emissions ◽  
Government Policies ◽  
Alternative Fuel Vehicles ◽  
Enterprise Model ◽  
The Government ◽  
The Impact

The aim of this paper is to study the impact of public government policies, fuel cell cost, and battery cost on greenhouse gas (GHG) emissions in the US transportation sector. The model includes a government model and an enterprise model. To examine the effect on GHG emissions that fuel cell and battery cost has, the optimization model includes public policy, fuel cell and battery cost, and a market mix focusing on the GHG effects of four different types of vehicles, 1) gasoline-based 2) gasoline-electric hybrid or alternative-fuel vehicles (AFVs), 3) battery-electric (BEVs) and 4) fuel-cell vehicles (FCVs). The public policies taken into consideration are infrastructure investments for hydrogen fueling stations and subsidies for purchasing AFVs. For each selection of public policy, fuel cell cost and battery cost in the government model, the enterprise model finds the optimum vehicle design that maximizes profit and updates the market mix, from which the government model can estimate GHG emissions. This paper demonstrates the model using FCV design as an illustrative example.

scholarly journals The Impact of Lengths of Time Series on the Accuracy of the ARIMA Forecasting

2019 ◽  
Vol 4 (3) ◽  
pp. 58
Author(s):  
Lu Qin ◽  
Kyle Shanks ◽  
Glenn Allen Phillips ◽  
Daphne Bernard
Keyword(s):  
Time Series ◽  
Historical Data ◽  
Moving Average ◽  
Arima Model ◽  
Forecasting Accuracy ◽  
Autoregressive Integrated Moving Average ◽  
Enrollment Forecasting ◽  
Moving Average Model ◽  
The Impact ◽  
Practical Impact

The Autoregressive Integrated Moving Average model (ARIMA) is a popular time-series model used to predict future trends in economics, energy markets, and stock markets. It has not been widely applied to enrollment forecasting in higher education. The accuracy of the ARIMA model heavily relies on the length of time series. Researchers and practitioners often utilize the most recent - to -years of historical data to predict future enrollment; however, the accuracy of enrollment projection under different lengths of time series has never been investigated and compared. A simulation and an empirical study were conducted to thoroughly investigate the accuracy of ARIMA forecasting under four different lengths of time series. When the ARIMA model completely captured the historical changing trajectories, it provided the most accurate predictions of student enrollment with 20-years of historical data and had the lowest forecasting accuracy with the shortest time series. The results of this paper contribute as a reference to studies in the enrollment projection and time-series forecasting. It provides a practical impact on enrollment strategies, budges plans, and financial aid policies at colleges and institutions across countries.

A Comparative Study on the Attitudes of Foreign Correspondents in Korea: Focusing on Their Views on North Korea

2009 ◽  
Vol 12 (2) ◽  
pp. 85-110
Author(s):  
Byung Jong Lee
Keyword(s):  
Foreign Policy ◽  
North Korea ◽  
Editorial Policy ◽  
Government Policies ◽  
Controversial Issues ◽  
Foreign Correspondents ◽  
The North ◽  
Foreign Countries ◽  
The Government ◽  
The Impact

Because newspaper readers or television viewers cannot directly experience or witness events that are happening in foreign countries, they have to rely heavily on foreign correspondents for their perspectives on the world. But the views of foreign correspondents can never be fully objective. Their views are often shaped by the government policies of the countries their companies belong to. Also, their attitudes are affected by the editorial policies of the companies they work for. Particularly for such controversial issues as North Korea, foreign correspondents' viewpoints are highly influenced by their government and company policies. The question is how foreign correspondents react when their government foreign policy is different from their company editorial policy. To examine the impact of government and company policies on the attitudes of foreign correspondents, this paper interviewed eight foreign correspondents covering North Korea. The results show government foreign policy and company editorial policy strongly influence the foreign correspondents' attitudes toward the North.

scholarly journals The Government Policies Effect on Initiation and Implementation of the Project: A Conceptual Model

2017 ◽  
Vol 2 (2) ◽  
pp. 26-37
Author(s):  
Fitria Astuti Firman ◽  
Ine Minara Ruky ◽  
Ratih Dyah Kusumastuti ◽  
Harris Turino Kurniawan
Keyword(s):  
Strategic Management ◽  
Conceptual Model ◽  
Latent Variables ◽  
Business Performance ◽  
Model Development ◽  
Project Performance ◽  
Jel Classification ◽  
Government Policies ◽  
The Government ◽  
The Impact

Objective - An urgency to investigate the impact of government policies on project performance through strategic management perspective is motivated by the gap of knowledge on a relationship between government policies and project. This paper proposes a conceptual model for further empirical research in the future. Six latent variables and ten hypotheses are developed through reviewing some literature in three following research avenues: Entrepreneurship, Strategic Management, and Project Management. Methodology - In order to observe a logical fitness of model development on government policies influences to firm activities, a specific context is chosen, namely the Indonesian renewable energy power generation. The last research avenue is strongly related to the research context. Further empirical study is required, and a discussion on it is presented in this paper. Findings – This paper emphasizes that project activities should be strategically managed since those support the achievement of business performance. Novelty - The study will bring benefits to the three following aspects: theoretical, managerial and regulatory aspects. Type of Paper - Review Keywords: Capability; Entrepreneurial orientation; Government policies; Project performance; Resource orchestration JEL Classification: H11, M21

scholarly journals The Impact of Political Activities on PSX: The Evidence from Pakistan

2018 ◽  
Vol III (II) ◽  
pp. 55-66
Author(s):  
Sami Ur Rahman ◽  
Ihtesham Khan ◽  
Muhammad Faizan Malik
Keyword(s):  
Stock Exchange ◽  
Moving Average ◽  
Abnormal Returns ◽  
Government Policies ◽  
Political Activities ◽  
Government Organizations ◽  
Political Events ◽  
And Behavior ◽  
The Impact ◽  
The Relationship

The aim of this research study is to find the association between political events in Pakistan and Pakistans stock exchange. The study considered 10 most big political events in Pakistan in the duration of 2012 to 2017. To calculate the results, the study used moving average method for calculating expected and abnormal returns. Further, t-statistics is used to explore the relationship between political events and behavior of PSX (100). The study has explored in results that political events, on which investor believes some change in Government policies do have impact on PSX. Investors respond positively when government organizations look strong and free from political pressure. The study recommended that government should make strong their organization, rather than alter government policies frequently.

scholarly journals Forecast Foreign Exchange Rate: The Case Study of PKR/USD

2020 ◽  
Vol 11 (4) ◽  
pp. 129
Author(s):  
Muhammad Asadullah ◽  
Nawaz Ahmad ◽  
Maria José Palma Lampreia Dos-Santos
Keyword(s):  
Exchange Rate ◽  
Arima Model ◽  
Future Trend ◽  
Suitable Model ◽  
The Future ◽  
The Exchange Rate ◽  
The Difference ◽  
The Government ◽  
Future Exchange

The main aim of this paper is to forecast the future values of the exchange rate of the USD. Dollar (USD) and Pakistani Rupee (PR). For this purpose was used the ARIMA model to forecast the future exchange rates, because the time series was stationary at first difference.  Data reported to five years ranging from the first day of April 2014 to 31st March 2019. The results proved that ARIMA (1,1,9) is the most suitable model to forecast the exchange rate. The difference between the forecasted values and actual values are less than 1%; therefore, it was found that the ARIMA is robust and this model will be helpful for the government functionaries, monetary policymakers, economists and other stakeholders to identify and forecast the future trend of the exchange rate and make their policies accordingly.

scholarly journals Assessment of the Impact of COVID-19 pandemic on population level interest in Skincare: Evidence from a google trends-based Infodemiology study

2020 ◽  
Author(s):  
Hasan Symum ◽  
Md. F. Islam ◽  
Habsa K. Hiya ◽  
Kh M. Ali Sagor
Keyword(s):  
Time Series ◽  
Moving Average ◽  
Arima Model ◽  
Population Level ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Search Volume ◽  
Quasi Experimental ◽  
Relative Search Volume ◽  
The Impact

AbstractBackgroundCOVID-19 pandemic created an unprecedented disruption of daily life including the pattern of skin related treatments in healthcare settings by issuing stay-at-home orders and newly coronaphobia around the world.ObjectiveThis study aimed to evaluate whether there are any significant changes in population interest for skincare during the COVID-19 pandemic.MethodsFor the skincare, weekly RSV data were extracted for worldwide and 23 counties between August 1, 2016, and August 31, 2020. Interrupted time-series analysis was conducted as the quasi-experimental approach to evaluate the longitudinal effects of COVID-19 skincare related search queries. For each country, autoregressive integrated moving average (ARIMA) model relative search volume (RSV) time series and then testing multiple periods simultaneously to examine the magnitude of the interruption. Multivariate linear regression was used to estimate the correlation between countries’ relative changes in RSV with COVID-19 confirmed cases/ per 10000 patients and lockdown measures.ResultsOut of 23 included countries in our study, 17 showed significantly increased (p<0.01) RSVs during the lockdown period compared with the ARIMA forecasted data. The highest percentage of increments occurs in May and June 2020 in most countries. There was also a significant correlation between lockdown measures and the number of COVID-19 cases with relatives changes in population interests for skincare.ConclusionUnderstanding the trend and changes in skincare public interest during COVID-19 may assist health authorities to promote accessible educational information and preventive initiatives regarding skin problems.

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