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Journal articles on the topic 'Vector error correction model'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 June 2025

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1

Gonzalo, Jesùs, and Jean-Yves Pitarakis. "Specification via model selection in vector error correction models." Economics Letters 60, no. 3 (1998): 321–28. http://dx.doi.org/10.1016/s0165-1765(98)00129-3.

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2

Abusharbeh, Mohammed. "Determinants of Islamic bank financing in the Middle East: Vector Error Correction Model (VECM)." Investment Management and Financial Innovations 17, no. 4 (2020): 285–98. http://dx.doi.org/10.21511/imfi.17(4).2020.25.

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As the world has been struck with a global financial crisis, Middle Eastern countries have been affected as well. Thus, Islamic banks have expanded, and the competitive advantage has become intensive with the increased number of conventional banks in the global banking system. This manuscript is aimed to examine the impact of macroeconomic and bank-specific factors on Islamic bank financing in the Middle Eastern countries. Therefore, the Vector Error Correction Model and the Granger causality test were run from 2009 to 2018 to detect the long- and short-run relationship between the explanatory variables and Islamic bank financing. The results suggest that both inflation and profitability negatively impact Islamic bank financing in the long run. The paper also revealed bidirectional causality between the variables GDP and bank size and Islamic bank financing. It shows that GDP and bank size are highly dominant factors of Islamic bank financing in the short run. Thus, this paper provides evidence that any short-run shock in the variables of GDP, inflation, and bank size will cause a long-term relationship with Islamic bank financing. This article’s novelty is to ensure resilience within the Islamic banking system during and after the financial crisis. It provides evidence that Islamic banks can cushion their financial activities from economic volatility during the crisis. The results found can be used to predict the growth of Islamic bank financing in upcoming years in the Middle East and all emerging countries.

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3

Liao, Zhipeng, and Peter C. B. Phillips. "AUTOMATED ESTIMATION OF VECTOR ERROR CORRECTION MODELS." Econometric Theory 31, no. 3 (2015): 581–646. http://dx.doi.org/10.1017/s026646661500002x.

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Model selection and associated issues of post-model selection inference present well known challenges in empirical econometric research. These modeling issues are manifest in all applied work but they are particularly acute in multivariate time series settings such as cointegrated systems where multiple interconnected decisions can materially affect the form of the model and its interpretation. In cointegrated system modeling, empirical estimation typically proceeds in a stepwise manner that involves the determination of cointegrating rank and autoregressive lag order in a reduced rank vector autoregression followed by estimation and inference. This paper proposes an automated approach to cointegrated system modeling that uses adaptive shrinkage techniques to estimate vector error correction models with unknown cointegrating rank structure and unknown transient lag dynamic order. These methods enable simultaneous order estimation of the cointegrating rank and autoregressive order in conjunction with oracle-like efficient estimation of the cointegrating matrix and transient dynamics. As such they offer considerable advantages to the practitioner as an automated approach to the estimation of cointegrated systems. The paper develops the new methods, derives their limit theory, discusses implementation, reports simulations, and presents an empirical illustration with macroeconomic aggregates.

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Obeng, Cosmos, and Cleophas Attor. "INTERCONNECTION AMONG CRYPTOCURRENCIES: USING VECTOR ERROR CORRECTION MODEL." International Journal of Entrepreneurial Knowledge 10, no. 2 (2022): 24–41. http://dx.doi.org/10.37335/ijek.v10i2.157.

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The research paper aimed to investigate the relationship between the major popular cryptocurrencies in terms of market dominance and identify any pattern and/or causality between the short-run and long-run series. Cryptocurrency has received much attention because of media publicity and the financial returns it generates within a short time, with its associated risk level. This innovative financial research investigates for the first time by thoroughly analyzing nine top cryptocurrencies, excluding stablecoins. The study used the Vector Error Correction model to analyse how the various cryptocurrency under investigation are interconnected. The results demonstrated how concentrated the causality effect is on some specific cryptocurrencies. The study uses the top nine cryptocurrencies on the crypto markets, excluding stablecoins that have existed since October 2017. The frequency of the data is 1523 daily closing prices. The choice of the data stemmed from its availability and has existed since October 2017. The primary outcome is clear and possibly explains the dominance of Bitcoin and Ethereum as the main drivers of the prices of related or altcoins. Any movement in the price level of the two dominant cryptos affects all the altcoins on the crypto market. The research further unearths the interconnection or correlation between the major cryptocurrencies. It will assist institutional and retail investors, fund managers, and managers, with the possible mix of assets in their portfolio based on their risk appetite level in making investment decisions.

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Jiang, Yixiao, George K. Zestos, and Zachary Timmerman. "A Vector Error Correction Model for Japanese Real Exports." Atlantic Economic Journal 48, no. 3 (2020): 297–311. http://dx.doi.org/10.1007/s11293-020-09675-1.

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Faghih, Sayed Amir Mohsen, and Hamed Kashani. "Forecasting Construction Material Prices Using Vector Error Correction Model." Journal of Construction Engineering and Management 144, no. 8 (2018): 04018075. http://dx.doi.org/10.1061/(asce)co.1943-7862.0001528.

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7

Van Gestel, Tony, Marcelo Espinoza, Bart Baesens, Johan A. K. Suykens, Carine Brasseur, and Bart De Moor. "A Bayesian nonlinear support vector machine error correction model." Journal of Forecasting 25, no. 2 (2006): 77–100. http://dx.doi.org/10.1002/for.975.

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8

Wong, James M. W., Albert P. C. Chan, and Y. H. Chiang. "Forecasting construction manpower demand: A vector error correction model." Building and Environment 42, no. 8 (2007): 3030–41. http://dx.doi.org/10.1016/j.buildenv.2006.07.024.

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9

Sung, Joo-han. "A Study on the Apartment Sale Price Decision Model Using Vector Error Correction Model (VECM): Focusing on the Housing Market in Changwon City." Housing Finance Research 5, no. 1 (2021): 27–49. http://dx.doi.org/10.52344/hfr.2021.5.1.27.

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10

Barigozzi, Matteo, Marco Lippi, and Matteo Luciani. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors." Econometrics 8, no. 1 (2020): 3. http://dx.doi.org/10.3390/econometrics8010003.

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Large-dimensional dynamic factor models and dynamic stochastic general equilibrium models, both widely used in empirical macroeconomics, deal with singular stochastic vectors, i.e., vectors of dimension r which are driven by a q-dimensional white noise, with q < r . The present paper studies cointegration and error correction representations for an I ( 1 ) singular stochastic vector y t . It is easily seen that y t is necessarily cointegrated with cointegrating rank c ≥ r − q . Our contributions are: (i) we generalize Johansen’s proof of the Granger representation theorem to I ( 1 ) singular vectors under the assumption that y t has rational spectral density; (ii) using recent results on singular vectors by Anderson and Deistler, we prove that for generic values of the parameters the autoregressive representation of y t has a finite-degree polynomial. The relationship between the cointegration of the factors and the cointegration of the observable variables in a large-dimensional factor model is also discussed.

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11

Maida, Nazira, Nanda Safarida, and Iskandar. "Pengaruh Inflasi, BI Rate dan IHSG Terhadap Nilai Aktiva Bersih Reksadana Syariah di Indonesia Periode 2015-2020." JIM: Jurnal Ilmiah Mahasiswa 4, no. 1 (2022): 57–76. http://dx.doi.org/10.32505/jim.v4i1.3921.

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Penelitian ini bertujuan untuk mengetahui pengaruh jangka pendek dan jangka panjang inflasi, BI rate dan IHSG terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia. Metode yang digunakan yaitu pendekatan kuantitatif. Penelitian ini menggunakan data sekunder yang diperoleh dari Otoritas Jasa Keuangan (OJK), Bank Indonesia (BI) dan Bursa Efek Indonesia (BEI). Data yang digunakan dalam bentuk periode per bulan mulai tahun 2015 hingga 2020 yang di publish selama 5 tahun berturut-turut. Metode analisis data menggunakan teknik analisis VAR (Vector Auto Regressive)/VECM (Vector Error Correction Model). Hasil penelitian estimasi VECM menunjukkan bahwa variabel Secara jangka pendek inflasi berpengaruh negatif dan signifikan terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia periode 2015-2020. Hal ini dibuktikan dengan hasil estimasi VECM dengan tstatistik (-2.39388) > ttabel (1.99547) dan secara jangka panjang inflasi tidak berpengaruh terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia periode 2015-2020, yang dibuktikan dari hasil estimasi VECM (Vector Error Correction Model) dengan tstatistik (-1.54214) < ttabel (1.99547). Secara jangka pendek BI Rate tidak berpengaruh terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia periode 2015-2020. Hal ini dibuktikan dari hasil estimasi VECM (Vector Error Correction Model) dengan tstatistik (-1.81465) < ttabel (1.99547) dan secara jangka panjang BI Rate berpengaruh negatif signifikan terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia periode 2015-2020. Hal ini dibuktikan dari hasil estimasi VECM (Vector Error Correction Model) dengan tstatistik (-2.57219) > ttabel (1.99547). Secara jangka pendek IHSG tidak berpengaruh terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia periode 2015-2020. Hal ini dibuktikan dari hasil estimasi VECM (Vector Error Correction Model) dengan tstatistik (-0.86317) < ttabel (1.99547) dan secara jangka panjang IHSG berpengaruh negatif signifikan terhadap Nilai Aktiva Bersih (NAB) reksadana syariah di Indonesia periode 2015-2020. Hal ini dibuktikan dari hasil estimasi VECM (Vector Error Correction Model) dengan tstatistik (-3.94995) > ttabel (1.99547).

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12

Chen, Xiaohong, Paul Wohlfarth, and Ron P. Smith. "China's money demand in a cointegrating vector error correction model." Journal of Asian Economics 75 (August 2021): 101338. http://dx.doi.org/10.1016/j.asieco.2021.101338.

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13

Rifin, A., and D. Nauly. "Vector error correction model relationship between three vegetable oil products." IOP Conference Series: Earth and Environmental Science 892, no. 1 (2021): 012062. http://dx.doi.org/10.1088/1755-1315/892/1/012062.

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Abstract International price of palm oil fluctuated frequently. It is predicted that the international price of palm oil is affected by the other vegetable oil prices. Soybean oil, rapeseed oil and palm oil are the three most important vegetable oil in the word. These commodities compete but on the other hand the world prices are moving in the same direction. This paper analyzes the relationship of these three prices in the short-run and long-run. The method utilizes in the analysis is the vector error correction model (VECM) followed by Impulse Response and Variance Decomposition. The data used is monthly data from January 2003 until December 2020. The results indicate that in the short-run, only the lag of each vegetable oil prices affects their own price. Meanwhile, in the long-run the three prices have long-run relationship or in other words the prices are cointegrated. Using variance decomposition and impulse response shows that soybean oil price has more effect on rapeseed and palm oil prices. Therefore, it can be concluded, the fluctuation of rapeseed and palm oil prices will be affected by the price fluctuation of soybean oil price

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14

Seong, Byeongchan, and Hyosang Jung. "Structural Vector Error Correction Model for Korean Labor Market Data." Korean Journal of Applied Statistics 26, no. 6 (2013): 1043–51. http://dx.doi.org/10.5351/kjas.2013.26.6.1043.

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15

Francis, Neville, and Michael T. Owyang. "Monetary Policy in a Markov-Switching Vector Error-Correction Model." Journal of Business & Economic Statistics 23, no. 3 (2005): 305–13. http://dx.doi.org/10.1198/073500104000000325.

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16

Setiawan, Setiawan, Moch Trianto Utomo, Alfira Mulya Astuti, M. Sjahid Akbar, and Imam Safawi Ahmad. "Forecasting Financial System Stability Using Vector Error Correction Model Approach." CAUCHY 6, no. 3 (2020): 109–16. http://dx.doi.org/10.18860/ca.v6i3.9811.

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Indonesia is one of the developing countries whose economic system is still very dependent on other developed countries. This reliance often becomes one of the causes of the occurrence of economic turmoil sectors that interfere with financial system stability in Indonesia. Therefore, to forecast financial system stability indicators, primarily macroeconomic variables, become essential to do to provide an accurate index value. Then, Forecasting signs of stability of the financial system in Indonesia using Vector Error Correction models (VECM) approach with financial system stability indicators used are Banking Stability Inde

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17

Anderson, Richard G., Dennis L. Hoffman, and Robert H. Rasche. "A vector error-correction forecasting model of the US economy." Journal of Macroeconomics 24, no. 4 (2002): 569–98. http://dx.doi.org/10.1016/s0164-0704(02)00067-8.

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18

Maysami, Ramin Cooper, and Tiong Sim Koh. "A vector error correction model of the Singapore stock market." International Review of Economics & Finance 9, no. 1 (2000): 79–96. http://dx.doi.org/10.1016/s1059-0560(99)00042-8.

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19

Chen, An-Sing, and Mark T. Leung. "A Bayesian vector error correction model for forecasting exchange rates." Computers & Operations Research 30, no. 6 (2003): 887–900. http://dx.doi.org/10.1016/s0305-0548(02)00041-2.

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20

Hwan Seo, Myung. "ESTIMATION OF NONLINEAR ERROR CORRECTION MODELS." Econometric Theory 27, no. 2 (2010): 201–34. http://dx.doi.org/10.1017/s026646661000023x.

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Asymptotic theory for the estimation of nonlinear vector error correction models that exhibit regime-specific short-run dynamics is developed. In particular, regimes are determined by the error correction term, and the transition between regimes is allowed to be discontinuous, as in, e.g., threshold cointegration. Several nonregular problems are resolved. First of all, consistency—square rootnconsistency for the cointegrating vectorβ—is established for the least squares estimation of this general class of models. Second, the convergence rates are obtained for the least squares of threshold cointegration, which aren3/2andnforβandγ, respectively, whereγdenotes the threshold parameter. This fast rate forβin itself is of practical relevance because, unlike in smooth transition models, the estimation error inβdoes not affect the estimation of short-run parameters. We also derive asymptotic distributions for the smoothed least squares estimation of threshold cointegration.

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21

Khera, Aastha, and Neelam Dhanda. "Empirical Relationship between Macroeconomic Variables and Stock Prices of Indian Banking Sector: A Vector Error Correction Model Approach." Review of Finance and Banking 12, no. 2 (2020): 189–98. http://dx.doi.org/10.24818/rfb.20.12.02.06.

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This existing study aims to investigate the relationship between Indian Bankingstock market prices and macroeconomic variables. The proxy for the Indian Banking stockmarket is Nifty Bank while Foreign Reserve, Exchange Rate (Indian vs US Dollar), Interestrate, and CPI are proxies of macroeconomic variables. Johansen Cointegration and VectorError Correction Model (VECM) on monthly data from January 2013 to July 2020 have beenapplied. Considering the results of cointegration, it is found that there is a long-run asso-ciation between the Indian Banking stock market and constituent macroeconomic variables.Next, the employment of VECM is done for inspecting long run and short-run causality.The result reveals long-run equilibrium in Indian commercial bankís stock prices comingfrom macroeconomic variables. This study has considerable imputations that investors candiversify their portfolio according to the ináuencing power of constituent selected macro-economic variables in the short run and the long run. Exchange rate and foreign reservesdrive the banking stock market in the short run whereas CPI and Interest rate do not createany signiÖcant impact.

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22

Guimin Huang, Guimin Huang, and Maolin Li Guimin Huang. "An Errors Correction Model for the Errors of Non-word and Real-word in English Composition." 電腦學刊 33, no. 1 (2022): 138–50. http://dx.doi.org/10.53106/199115992022023301013.

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<p>In the procedure from composing English, it is inevitable to face the phenomenon of word writing errors. In recent years, English composition automatic correcting system has attracted much attention. However, the precision of the existing word errors correcting system is vague generalization. So as to move forward the accuracy of checking and correcting word errors, this paper designs a word errors correction model based on natural language processing technology. This model designs phoneme matching method based on an improved IDM algorithm, and combined with a non-word input errors correction method based on character distance. The accuracy of correcting non-word errors in this model reached 86.5%. The study also proposes a real-word errors correction method, which is implemented basing on the real-word confusion set and combining the binary statistical model and the GloVe word vector model, improving the real-word errors correction method based on feature annotation of the real-word confusion set, with an accuracy of 77.9%. </p> <p>&nbsp;</p>

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23

Sunarya, I. Wayan. "Perkembangan Makroekonomi Negara Kanada Dengan Analisa Vector Error Correction Model (VECM)." Jurnal Aplikasi Manajemen, Ekonomi dan Bisnis 6, no. 2 (2022): 15–41. http://dx.doi.org/10.51263/jameb.v6i2.143.

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This study aims to analyze the relationship between Gross Domestic Product (GDP), Inflation (INF), Import (IMP) and Unemployment (UEM) that occurred in Canada by using Vector Error Correction Model (VECM) analysis. The data source comes from https://www.imf.org; data taken from 1980 to 2020. The analytical tool used is the Vector Error Correction Model (VECM) which aims to analyze the relationship or causality between variables both in the short and long term, where the results obtained are the relationship between variables more referring to short term causality. And to find out the impact between variables, this study uses an Impulse Response Function (IRF) analysis where the results that have a positive impact during the Covid-19 pandemic are import shocks to GDP in Canada while the results that have a negative impact are import shocks on unemployment and also Canada's unemployment rate against GDP during the COVID-19 pandemic.

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24

Kim, Yun-Yeong. "Stationary Vector Autoregressive Representation of Error Correction Models." Theoretical Economics Letters 02, no. 02 (2012): 152–56. http://dx.doi.org/10.4236/tel.2012.22027.

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Jiang, Heng, Youquan Xu, and Chunlu Liu. "Construction Price Prediction Using Vector Error Correction Models." Journal of Construction Engineering and Management 139, no. 11 (2013): 04013022. http://dx.doi.org/10.1061/(asce)co.1943-7862.0000729.

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26

Brüggemann, Ralf, Helmut Lütkepohl, and Pentti Saikkonen. "Residual autocorrelation testing for vector error correction models." Journal of Econometrics 134, no. 2 (2006): 579–604. http://dx.doi.org/10.1016/j.jeconom.2005.07.006.

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27

She, Rui, and Shiqing Ling. "Inference in heavy-tailed vector error correction models." Journal of Econometrics 214, no. 2 (2020): 433–50. http://dx.doi.org/10.1016/j.jeconom.2019.03.008.

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Hapsari, Meilina Retno, Suci Astutik, and Loekito Adi Soehono. "Relationship of Macroeconomics Variables in Indonesia Using Vector Error Correction Model." Economics Development Analysis Journal 9, no. 4 (2020): 374–90. http://dx.doi.org/10.15294/edaj.v9i4.38662.

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This study aims to analyze the relationship between macroeconomic variables in Indonesia, namely GDP with money supply, exchange rate of rupiah to US Dollar, exports, imports and interest rates. The background problem is to analyze the best method to influence government targets or policies on economic growth by studying the relationship of macroeconomic variables. Previous studies analyzing the relationship between macroeconomic variables in Indonesia have used multiple linear regression analysis. Using VECM analysis we can find out the short-term and long-term effects on the relationship between macroeconomic variables in Indonesia. The analysis used in this study is the Vector Error Correction Model with Maximum Likelihood estimation. Based on the result, the cointegration test found that there is a long-term relationship. Based on the VECM model (3), in the short term there is a relationship between macroeconomic variables and in the long run there is a long-term causality relationship in the GDP and export models. It is expected that the Government and the Central Bank will work together cooperatively in making policies to keep control of the money supply, exchange rate of rupiah to US Dollar and interest rates to enable to stimulate the economy.

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Shahraki, M*, and S. Ghaderi. "The Relationship between Education and Health: Vector Error Correction Model (VECM)." Journal of Health 10, no. 4 (2019): 445–56. http://dx.doi.org/10.29252/j.health.10.4.445.

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Ahn, Young-gyun, and Min-Kyu Lee. "The Factors Affecting World GDP Variation Using Vector Error Correction Model." Journal of Industrial Economics and Business 31, no. 6 (2018): 1925–42. http://dx.doi.org/10.22558/jieb.2018.12.31.6.1925.

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AMASSAIB, Mahmoud Ali, Mohammed Salih Adam ABDALLA, and Tarig GIBREEL. "Market Efficiency in Agricultural commodities: Vector error correction model (VECM) Approach." International Journal of Research and Innovation in Social Science 06, no. 09 (2022): 174–79. http://dx.doi.org/10.47772/ijriss.2022.6906.

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The study was conducted in Elobied Crops Market to investigate the efficiency market hypothesis (EMH) for sesame, groundnut, and Arabic gum crops. The study used Augmented-Dickey Fuller (ADF) method, Johansen multivariate approach, and Vector error correction model (VECM), and co-integration method. Data was obtained from the Elobied Crops Market database for annual prices and quantities of trading commodities from 1990 to 2017.The study concluded that there is a weak form of EMH for sesame and groundnut and a semi-strong of EMH for Arabic gum.

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32

Prasada, I. made Yoga, Moh Wahyudi Priyanto, and Yahya Shafiyuddin Hilmi. "KETAHANAN PANGAN PENDUDUK DI PULAU JAWA: PENDEKATAN VECTOR ERROR CORRECTION MODEL." Agrisocionomics: Jurnal Sosial Ekonomi Pertanian 4, no. 1 (2020): 85–95. http://dx.doi.org/10.14710/agrisocionomics.v4i1.5560.

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Food security over the past few decades has been a hot topic discussed in Indonesia. Food security can indirectly reflect the level of welfare of a household in a region. Various factors can influence the level of food security, both in the short term and in the long term. Therefore, this research was conducted with the aim to find out the factors that influence the food security of the population in the short term and in the long term. The data used in this study are secondary data sourced from the Central Bureau of Statistics (BPS) in 2008-2017, namely data on food and non-food expenditure, real per capita income, agricultural land area, real sugar prices, real beef prices, and real rice prices. The data were analyzed using the VECM (Vector Error Correction Model) model. The results showed that in the short-term the factors that influence food security are income per capita real lag 1, real sugar prices lag 1, and real beef prices lag 1, while the factors that influence food security in the long-term are per capita income 1, agricultural area lag 1, real sugar 1 lag price, real beef price lag 1, and real rice price lag 1.

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Horrace, William C. "Submodel estimation of a structural vector error correction model under cointegration." Economics Letters 59, no. 1 (1998): 23–29. http://dx.doi.org/10.1016/s0165-1765(98)00033-0.

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34

Faizin, Moh. "Penerapan Vector Error Correction Model pada Variabel Makro Ekonomi di Indonesia." Jurnal Ekonomi 25, no. 2 (2020): 287. http://dx.doi.org/10.24912/je.v25i2.671.

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In this time, the countries can be said to be in a good condition of the national economy if there are some indicators in positive economic macro, it is including the decline of inflation, the amount of money circulating is also decline, and the exchange rate strengthening against foreign currencies and reduced interest rates. The purpose of this study is to analyze the causality and cointegration relationships of economic macro variables, by using time series data for 2010-2019 and using the VECM model. The results of the study found that there is no causality relationship between inflation and the BI rate. Likewise, the variable money supply does not affect the BI rate. The exchange rate also does not affect each other on the BI rate variable. Causality test results also indicate that the money supply does not have a causality relationship to inflation, while the exchange rate variables influence each other on inflation. To exchange rates, it does not give affect in the variable amount of money in circulation each other. By explanation of the estimation results of the VECM model, it shows the long-term and short-term relationships of each variable generally.

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35

Jiang, Heng, and Chunlu Liu. "Forecasting construction demand: a vector error correction model with dummy variables." Construction Management and Economics 29, no. 9 (2011): 969–79. http://dx.doi.org/10.1080/01446193.2011.611522.

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36

Yang, Zheng, Zheng Tian, and Zixia Yuan. "GSA-based maximum likelihood estimation for threshold vector error correction model." Computational Statistics & Data Analysis 52, no. 1 (2007): 109–20. http://dx.doi.org/10.1016/j.csda.2007.06.003.

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37

Kolo, Horst, and Polia Tzanova. "Forecasting the German forest products trade: A vector error correction model." Journal of Forest Economics 26 (January 2017): 30–45. http://dx.doi.org/10.1016/j.jfe.2016.11.001.

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38

Mashabi, M., and Wasiaturrahma Wasiaturrahma. "ELECTRONIC BASED PAYMENT SYSTEMS AND ECONOMIC GROWTH IN INDONESIA." Jurnal Ilmu Ekonomi Terapan 6, no. 1 (2021): 97. http://dx.doi.org/10.20473/jiet.v6i1.26287.

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This research aims to analyze the effect of electronic payment systems based on credit cards, debit cards, and electronic money, as well as macroeconomic variables namely the money supply (M1), price level, and velocity of money towards real gross domestic product as a proxy for economic growth. The estimation carried out in this journal uses the Vector Error Correction Model (VECM) with period time series data of 2010:1-2018:12. The results of the journal show that doing debit card and electronic money-based transactions has a significant positive effect on economic growth in Indonesia in the long run.Keywords : Electronic payment systems, electronic money, credit cards, debit cards, economic growth, Vector Error Correction Model (VECM) Keywords: Electronic payment systems, electronic money, credit cards, debit cards, economic growth, Vector Error Correction Model (VECM) JEL : O470 C320

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Wu, Shan, Hongquan Han, Benwei Hou, and Kegong Diao. "Hybrid Model for Short-Term Water Demand Forecasting Based on Error Correction Using Chaotic Time Series." Water 12, no. 6 (2020): 1683. http://dx.doi.org/10.3390/w12061683.

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Short-term water demand forecasting plays an important role in smart management and real-time simulation of water distribution systems (WDSs). This paper proposes a hybrid model for the short-term forecasting in the horizon of one day with 15 min time steps, which improves the forecasting accuracy by adding an error correction module to the initial forecasting model. The initial forecasting model is firstly established based on the least square support vector machine (LSSVM), the errors time series obtained by comparing the observed values and the initial forecasted values is next transformed into chaotic time series, and then the error correction model is established by the LSSVM method to forecast errors at the next time step. The hybrid model is tested on three real-world district metering areas (DMAs) in Beijing, China, with different demand patterns. The results show that, with the help of the error correction module, the hybrid model reduced the mean absolute percentage error (MAPE) of forecasted demand from (5.64%, 4.06%, 5.84%) to (4.84%, 3.15%, 3.47%) for the three DMAs, compared with using LSSVM without error correction. Therefore, the proposed hybrid model provides a better solution for short-term water demand forecasting on the tested cases.

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Setyowati, Endang, and Algifari Algifari. "MODEL KESEIMBANGAN HUBUNGAN PENGARUH ANTARATINGKAT BUNGA, LAJU INFLASI, DAN KURS VALUTA ASING." Jurnal Riset Manajemen dan Bisnis 11, no. 2 (2017): 117. http://dx.doi.org/10.21460/jrmb.2016.112.241.

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The aims of this research is to develop unequilibrium model relationship among interest rate,inflation, and foreign exchange rate in Indonesia using monthly data from January 2011 to April2015. The results of Augmented Dickey-Fuller test shows that the data of interest rate, inflation, andforeign exchange rate in this period is not stationary at level, but stationary in first difference.Johansen Cointegration test results indicate that the interest rate, inflation, and foreign exchange rateare cointegrated. Equilibrium model that used to determine the relationship among interest rate,inflation, and foreign exchange rate is Vector Error Correction models. The results of this studyindicate that interest rate affect on inflation and foreign exchange rate in Indonesia.Keyword: Interest Rate, Inflation, Exchange Rate,Vector Error Correction Model

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Eroglu, Cuneyt, and Christian Hofer. "Inventory Types and Firm Performance: Vector Autoregressive and Vector Error Correction Models." Journal of Business Logistics 32, no. 3 (2011): 227–39. http://dx.doi.org/10.1111/j.2158-1592.2011.01019.x.

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Hodgson, Douglas J. "ADAPTIVE ESTIMATION OF ERROR CORRECTION MODELS." Econometric Theory 14, no. 1 (1998): 44–69. http://dx.doi.org/10.1017/s0266466698141026.

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This paper considers adaptive maximum likelihood estimation of reduced rank vector error correction models. It is shown that such models can be asymptotically efficiently estimated even in the absence of knowledge of the shape of the density function of the innovation sequence, provided that this density is symmetric. The construction of the estimator, involving the nonparametric kernel estimation of the unknown density using the residuals of a consistent preliminary estimator, is described, and its asymptotic distribution is derived. Asymptotic efficiency gains over the Gaussian pseudo–maximum likelihood estimator are evaluated for elliptically symmetric innovations.

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Brigadnov, Igor, Aleksandr Lutonin, and Kseniia Bogdanova. "Error State Extended Kalman Filter Localization for Underground Mining Environments." Symmetry 15, no. 2 (2023): 344. http://dx.doi.org/10.3390/sym15020344.

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The article addresses the issue of mobile robotic platform positioning in GNSS-denied environments in real-time. The proposed system relies on fusing data from an Inertial Measurement Unit (IMU), magnetometer, and encoders. To get symmetrical error gauss distribution for the measurement model and achieve better performance, the Error-state Extended Kalman Filter (ES EKF) is chosen. There are two stages of vector state determination: vector state propagation based on accelerometer and gyroscope data and correction by measurements from additional sensors. The error state vector is composed of the velocities along the x and y axes generated by combining encoder data and the orientation of the magnetometer around the axis z. The orientation angle is obtained from the magnetometer directly. The key feature of the algorithm is the IMU measurements’ isolation from additional sensor data, with its further summation in the correction step. Validation is performed by a simulation in the ROS (Robot Operating System) and the Gazebo environment on the grounds of the developed mathematical model. Trajectories for the ES EKF, Extended Kalman Filter (EKF), and Unscented Kalman Filter (UKF) algorithms are obtained. Absolute position errors for all trajectories are calculated with an EVO package. It is shown that using the simplified version of IMU’s error equations allows for the achievement of comparable position errors for the proposed algorithm, EKF and UKF.

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Hamzah, Amir, and Mohamad Rizky. "Determinant Analysis of Company Debt Policy with Vector Error Correction Model Approach." Global Financial Accounting Journal 6, no. 1 (2022): 154. http://dx.doi.org/10.37253/gfa.v6i1.6547.

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Purpose- This study uses a VECM model that aims to see the short-run and long-term effects of managerial ownership, sales growth, free cash flow, and asset structure against debt policy. Vector Error Correction Model (VECM) is a model that can be used for time series data that is not stationary but has a cointegration relationship where in the model included stationary exogenous variables as additional regressors. Research Method- The sample used in this research is quantitative data with a purposive sampling technique. Based on the criteria, the number of samples collected is 32 samples in the period 2013-2021.The data analysis techniques in this study use Vector Error Correlation Model (VECM) analysis, several stages that researchers must go through before determining the right model, namely data stationarity test, optimal lag length test, co-integration test, VAR model stability test, granger causality analysis, VAR/VECM empirical model, Impulse Response Function analysis and Variance Decomposition analysis. Findings- The results of the analysis show that in the short term only sales growth and asset structure have a significant influence on debt policy. Meanwhile, in the long-term free cash flow, asset structure and sales growth have a significant influence on debt policy, while managerial ownership has an insignificant effect on debt policy. Implication- For the company should reduce the proportion of funding from debt in the implementation of its operations so as to reduce financial distress, because funding from corporate debt causes financial distress and agency costs greater than tax savings from debt interest expense, as a result of which the company is very vulnerable to economic turmoil. For creditors who provide sources of debt funding, pay more attention to aspects of the company's asset structure to be used as collateral for debt, because the company usually uses loan funds for high-risk projects. For investors should take deeper considerations to invest in companies that have large free cash flow because companies that have large free cash flow tend to show good cash flow for the future.

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Ambler, Steve. "Does Money Matter in Canada? Evidence from a Vector Error Correction Model." Review of Economics and Statistics 71, no. 4 (1989): 651. http://dx.doi.org/10.2307/1928107.

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Faizin, Moh. "Penerapan Vector Error Correction Model pada Hubungan Kurs, Inflasi dan Suku Bunga." e-Journal Ekonomi Bisnis dan Akuntansi 8, no. 1 (2021): 33. http://dx.doi.org/10.19184/ejeba.v8i1.18810.

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Kondisi stabil dan tidaknya suatu negara tercermin dari stabilnya nilai tukar mata uang tersebut serta dengan memperhatikan tingkat laju inflasi dan suku bunga acuan. Tujuan penelitian ini menganalisis hubungan jangka pendek dan jangka panjang antara variabel kurs, inflasi dan suku bunga di Indonesia. Penelitian ini menggunakan model VECM data sekunder time series untuk periode 2011-2019. Hasil menunjukkan bahwa hubungan jangka pendek terjadi hanya pada variabel inflasi yang mempengaruhi kurs, sementara variabel yang lain tidak siknifikan. Hasil juga menunjukkan bahwa dari ketiga variabel kurs, inflasi dan suku bunga terdapat hubungan timbal balik jangka panjang.

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Dhakal, Basanta. "Investigating Nepal’s Gross Domestic Product from Tourism: Vector Error Correction Model Approach." American Journal of Theoretical and Applied Statistics 5, no. 5 (2016): 311. http://dx.doi.org/10.11648/j.ajtas.20160505.20.

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Kim, Ki-Ho. "US inflation and the dollar exchange rate: a vector error correction model." Applied Economics 30, no. 5 (1998): 613–19. http://dx.doi.org/10.1080/000368498325606.

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Swanson, Norman R. "Comments on ‘A vector error-correction forecasting model of the US economy’." Journal of Macroeconomics 24, no. 4 (2002): 599–606. http://dx.doi.org/10.1016/s0164-0704(02)00068-x.

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Lastrapes, William D. "Comments on ‘A vector error-correction forecasting model of the US economy’." Journal of Macroeconomics 24, no. 4 (2002): 607–11. http://dx.doi.org/10.1016/s0164-0704(02)00069-1.

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