scholarly journals Vector Autoregressive X (VARX) Modeling for Indonesian Macroeconomic Indicators and Handling Different Time Variations with Cubic Spline Interpolation

2019 ◽  
pp. 175-180
Author(s):  
Ayu Septiani ◽  
I Made Sumertajaya ◽  
Muhammad Nur Aidi
Keyword(s):  
Economic Growth ◽  
Interest Rates ◽  
Time Series Data ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Cubic Spline ◽  
Series Data ◽  
Cubic Spline Interpolation ◽  
Vector Autoregressive ◽  
Time Variations

This study discusses data handling that has different time variations (for example, data available in quarterly form but the desired data is monthly) in this case the GDP variable in the quarter series, while the other five variables use monthly series, whereas in multivariate analysis the data condition must be the same, then an approach is taken to reduce monthly data from quarterly data using the interpolation method. Therefore, before conducting the VARX analysis the author interpolated GDP data from the quarter to monthly by interpolation. After the data is ready, VARX modeling of the exchange rate, economic growth (GDP), interest rates on Bank Indonesia Certificates (SBI), and inflation as endogenous variables and US interest rates (FFR) and US inflation as exogenous variables. The purpose of this study is to implement and evaluate the performance of Cubic Spline interpolation methods for time series data that have different time variations. Build VARX models and predict exchange rates, economic growth (GDP), SBI interest rates, and inflation based on US interest rates (FFR) and US inflation with the best models. Meanwhile, the interpolation method used by researchers to estimate the monthly value of the GDP variable based cubic spline interpolation. Based on the AIC value of the smallest VARX model obtained at 240.6668 so the best model obtained is the VARX (4.0) model.

scholarly journals Hypothesizing directional causality between the governance indicators and economic growth: the case of Afghanistan

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Mohammad Naim Azimi ◽  
Mohammad Musa Shafiq
Keyword(s):  
Economic Growth ◽  
Rule Of Law ◽  
Time Series Data ◽  
Political Stability ◽  
Wald Test ◽  
Series Data ◽  
Vector Autoregressive ◽  
Government Effectiveness ◽  
Governance Indicators ◽  
The Government

AbstractThis paper examines the causal relationship between governance indicators and economic growth in Afghanistan. We use a set of quarterly time series data from 2003Q1 to 2018Q4 to test our hypothesis. Following Toda and Yamamoto’s (J Econom 66(1–2):225–250, 1995. 10.1016/0304-4076(94)01616-8) vector autoregressive model and the modified Wald test, our empirical results show a unidirectional causality between the government effectiveness, rule of law, and the economic growth. Our findings exhibit significant causal relationships running from economic growth to the eradication of corruption, the establishment of the rule of law, quality of regulatory measures, government effectiveness, and political stability. More interestingly, we support the significant multidimensional causality hypothesis among the governance indicators. Overall, our findings not only reveal causality between economic growth and governance indicators, but they also show interdependencies among the governance indicators.

scholarly journals Error Analysis for a Noisy Lacunary Cubic Spline Interpolation and a Simple Noisy Cubic Spline Quasi Interpolation

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Feng-Gong Lang ◽  
Xiao-Ping Xu
Keyword(s):  
Error Analysis ◽  
Error Bounds ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Cubic Spline ◽  
The Other ◽  
Cubic Spline Interpolation ◽  
Numerical Tests ◽  
New Methods ◽  
Noisy Function

We mainly present the error analysis for two new cubic spline based methods; one is a lacunary interpolation method and the other is a very simple quasi interpolation method. The new methods are able to reconstruct a function and its first two derivatives from noisy function data. The explicit error bounds for the methods are given and proved. Numerical tests and comparisons are performed. Numerical results verify the efficiency of our methods.

Relationship between Budget Deficit and Economic Growth: Evidence from Ethiopia

2021 ◽  
Vol 2 (2) ◽  
pp. 10-15
Author(s):  
Desalegn Emana
Keyword(s):  
Economic Growth ◽  
Interest Rates ◽  
Budget Deficit ◽  
Time Series Data ◽  
Negative Impact ◽  
Positive Impact ◽  
Negative Relationship ◽  
Nominal Exchange Rate ◽  
Series Data ◽  
Long Run

This study examined the relationship between budget deficit and economic growth in Ethiopia using time series data for the period 1991 to 2019 by applying the ARDL bounds testing approach. The empirical results indicate that budget deficit and economic growth in Ethiopia have a negative relationship in the long run, and have a weak positive association in the short run. In line with this, in the long run, a one percent increase in the budget deficit causes a 1.43 percent decline in the economic growth of the country. This result is consistent with the neoclassical view which says budget deficits are bad for economic growth during stimulating periods. Moreover, in the long run, the variables trade openness and inflation have a positive impact on Ethiopian economic growth, and on the other hand, the economic growth of Ethiopia is negatively affected by the nominal exchange rate in the long run. Apart from this, in the long run, gross capital formation and lending interest rates have no significant impact on the economic growth of the country. Therefore, the study recommends the government should manage its expenditure and mobilize the resources to generate more revenue to address the negative impact of the budget deficit on economic growth.

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 Treatment of Outlier Using Interpolation Method in Malaysia Tourist Arrivals

2018 ◽  
Vol 7 (3.7) ◽  
pp. 51
Author(s):  
Maria Elena Nor ◽  
Norsoraya Azurin Wahir ◽  
G P. Khuneswari ◽  
Mohd Saifullah Rusiman
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Performance Indicator ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Forecast Accuracy ◽  
Linear Interpolation ◽  
Negative Influence ◽  
Series Data ◽  
Missing Value

The presence of outliers is an example of aberrant data that can have huge negative influence on statistical method under the assumption of normality and it affects the estimation. This paper introduces an alternative method as outlier treatment in time series which is interpolation. It compares two interpolation methods using performance indicator. Assuming outlier as a missing value in the data allows the application of the interpolation method to interpolate the missing value, thus comparing the result using the forecast accuracy. The monthly time series data from January 1998 until December 2015 of Malaysia Tourist Arrivals were used to deal with outliers. The results found that the cubic spline interpolation method gave the best result than the linear interpolation and the improved time series data indicated better performance in forecasting rather than the original time series data of Box-Jenkins model. 

The Dynamics of Exports and Economic Growth: Assessing the Evidence from Nigeria

2018 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Clement A.U. Ighodaro ◽  
Ovenseri-Ogbomo F. O.
Keyword(s):  
Economic Growth ◽  
Social Services ◽  
Time Series Data ◽  
Positive Impact ◽  
Capital Expenditure ◽  
Impulse Response Function ◽  
Series Data ◽  
Vector Autoregressive ◽  
Long Run ◽  
Short Run

The paper empirically examines the dynamics of exports and economic growth in Nigeria using time series data for 1970 to 2017. The Vector autoregressive model (VAR) was used to investigate the long run and short run relationship between exports and economic growth as well as some selected variables. The result shows that there exists a stable long run relationship among economic growth, exports, capital expenditure on education and social services. Also, the Granger causality results reveal that export Granger causes economic growth and not the other way round. This means that an increase in economic growth may result from increase in export, but increase in economic growth does not necessarily lead to increase in exports. The Impulse Response Function (IRF) shows that a one standard innovation in exports will lead to permanent positive impact on economic growth in Nigeria. This therefore supports the exports led growth hypothesis for Nigeria.

Gait Planning of Humanoid Robot Based on ZMP and Cubic Spline Interpolation

2013 ◽  
Vol 427-429 ◽  
pp. 1394-1397 ◽  
Author(s):  
Xian Lun Wang ◽  
Ping Li ◽  
Fei Qi Yang
Keyword(s):  
Humanoid Robot ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Cubic Spline ◽  
Smooth Transition ◽  
Cubic Spline Interpolation ◽  
Gait Planning ◽  
Inverted Pendulum Model ◽  
Point Equation ◽  
The Impact

Teaching programming and manual programming are usually used to realize gait planning of humanoid robot. Many methods are lack of the adjustment of center of gravity and lead to the robot walking instability. The gait planning of humanoid robot is solved based on the Linear Inverted Pendulum Model and Zero Moment Point equation in this paper. Two feet trajectories are also planned to realize the smooth transition and overcome the impact during walking with the cubic spline interpolation method. The validation and feasibility of the method proposed in the paper are proved by the results of simulation and experiments.

scholarly journals Causality Effects among Gross Capital Formation, Unemployment and Economic Growth in South Africa

Economies ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 26 ◽  
Author(s):  
Michael Takudzwa Pasara ◽  
Rufaro Garidzirai
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Inverse Relationship ◽  
Time Series Data ◽  
Capital Formation ◽  
Series Data ◽  
Vector Autoregressive ◽  
The Third ◽  
Short Run

Stagnant economic growth, decreasing investment and high unemployment remain consistent macroeconomic challenges for South Africa. Gross Capital formation (GCF) is designed to improve employment and economic growth (GDP). This study investigates the causality effects of the three variables using time series data from 1980 to 2018 in a Vector Autoregressive (VAR) framework. Results of the first model reveal a positive long-term relationship between gross capital formation GCF and economic growth GDP. Contrariwise, the first model indicates that unemployment (UNEMP) does not influence economic growth (GDP) in the short run. The second model results reveal a significant and positive relationship between UNEMP and GCF, while the third model shows an inverse relationship between GDP and UNEMP. Based on these findings, the study therefore recommends that fiscal authorities introduce expansionary fiscal policy that stimulates economic growth, investment and employment.

Interpolation Method Research and Precision Analysis of GPS Satellite Position

2018 ◽  
Vol 6 (3) ◽  
pp. 277-288
Author(s):  
Jianmin Wang ◽  
Yabo Li ◽  
Huizhong Zhu ◽  
Tianming Ma
Keyword(s):  
Lagrange Interpolation ◽  
Hermite Interpolation ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Cubic Spline ◽  
Newton Interpolation ◽  
Cubic Spline Interpolation ◽  
Satellite Position ◽  
Precise Ephemeris ◽  
Better Than

Abstract According to the precise ephemeris has only provided satellite position that is discrete not any time, so propose that make use of interpolation method to calculate satellite position at any time. The essay take advantage of IGS precise ephemeris data to calculate satellite position at some time by using Lagrange interpolation, Newton interpolation, Hermite interpolation, Cubic spline interpolation method, Chebyshev fitting method respectively, which has a deeply analysis in the precision of five interpolations. The results show that the precision of Cubic spline interpolation method is the worst, the precision of Chebyshev fitting is better than Hermite interpolation method. Lagrange interpolation and Newton interpolation are better than other methods in precision. Newton interpolation method has the advantages of high speed and high precision. Therefore, Newton interpolation method has a certain scientific significance and practical value to get the position of the satellite quickly and accurately.

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