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Journal articles on the topic 'Error correction vector model'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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1

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

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2

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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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

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4

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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5

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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6

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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7

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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8

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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9

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 v

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10

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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11

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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12

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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13

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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14

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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15

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

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16

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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17

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 ) singula

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18

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 coi

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19

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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20

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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21

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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22

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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23

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 bet

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24

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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25

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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26

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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27

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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28

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 a

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29

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,

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30

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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31

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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32

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

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33

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

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34

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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35

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–maximu

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36

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

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37

Fisher, Lance A., and Hyeon-seung Huh. "IDENTIFICATION METHODS IN VECTOR-ERROR CORRECTION MODELS: EQUIVALENCE RESULTS." Journal of Economic Surveys 28, no. 1 (2012): 1–16. http://dx.doi.org/10.1111/j.1467-6419.2012.00734.x.

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38

Hansen, Gerd, Jeong-Ryeol Kim, and Stefan Mittnik. "Testing cointegrating coefficients in vector autoregressive error correction models." Economics Letters 58, no. 1 (1998): 1–5. http://dx.doi.org/10.1016/s0165-1765(97)00199-7.

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39

Shahandashti, S. M., and B. Ashuri. "Highway Construction Cost Forecasting Using Vector Error Correction Models." Journal of Management in Engineering 32, no. 2 (2016): 04015040. http://dx.doi.org/10.1061/(asce)me.1943-5479.0000404.

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40

Liang, Chong, and Melanie Schienle. "Determination of vector error correction models in high dimensions." Journal of Econometrics 208, no. 2 (2019): 418–41. http://dx.doi.org/10.1016/j.jeconom.2018.09.018.

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41

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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42

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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43

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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44

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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45

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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46

Koo, Tay T. R., David T. Tan, and David Timothy Duval. "Direct air transport and demand interaction: A vector error-correction model approach." Journal of Air Transport Management 28 (May 2013): 14–19. http://dx.doi.org/10.1016/j.jairtraman.2012.12.005.

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47

Pippenger, Michael K. "Testing price-exchange rate noncausality: Results from a vector error correction model." Atlantic Economic Journal 23, no. 4 (1995): 255–66. http://dx.doi.org/10.1007/bf02298762.

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48

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

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49

Cancino, Susan Elsa, and Giovanni Orlando Cancino-Escalante. "Estimation of peach supply response in Colombia using a Vector Error Correction Model." Entramado 17, no. 1 (2021): 250–60. http://dx.doi.org/10.18041/1900-3803/entramado.1.7243.

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An empirical study of peach supply response to own-price and yield in Colombia using time series data from 2000 to 2018 was undertaken. A quantitative, correlational and non-experimental research design was selected and the Johansen´s co-integration as well as the vector error correction framework were employed. The Augmented Dickey-Fuller test showed that the time series were integrated of order one and the Johansen´s co-integration confirmed the existence of a long-term relationship between the variables. Moreover, the short and long run coefficients for own-price and yield were statisticall

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50

Awe, Olushina Olawale, Damola M. Akinlana, and Sherifat Omolola Adesunkanmi. "Foreign Trade-Foreign Exchange Nexus in Nigeria: A Vector Error Correction Modelling Approach." Binus Business Review 7, no. 1 (2016): 1. http://dx.doi.org/10.21512/bbr.v7i1.1427.

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This study investigates trade foreign exchange nexus in Nigeria. This study is also done with a view to detecting the kind of relationship that exists between the two and also to investigate their co-integration. Annual time series data for the period 1996 – 2010 was used for the study. The Vector Correction Model (VECM) approach was employed to determine both the short and long run relationships. Results showed that the series becomes stationary after second difference. The co – integration test reveals five co – integrating vectors in the model, implying that the variables have the same stoc

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