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Relevant bibliographies by topics / Vector error correction models

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Academic literature on the topic 'Vector error correction models'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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Journal articles on the topic "Vector error correction models"

1

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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Vector error correction models"

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Sharp, Gary David. "Lag length selection for vector error correction models." Thesis, Rhodes University, 2010. http://hdl.handle.net/10962/d1002808.

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This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis of thirteen information theoretic criterion (IC), one of which is a novel derivation. The simulation exercise considers the evaluation of seven alternative error restricted vector autoregressive models with four different lag lengths. Alternative sample sizes and parameterisations are also evaluated and compared to results in the existing literature. The results of the comparative analysis provide strong support for the efficiency based criterion of Akaike and in particular the selection capability of the novel criterion, referred to as a modified corrected Akaike information criterion, demonstrates useful finite sample properties.

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Molin, Simon. "House Price Dynamics in Sweden : Vector error-correction model." Thesis, Umeå universitet, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172367.

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Movements in house prices can have effects on individuals, financial markets, and the whole economy. After the rapid increase in house prices worldwide since the mid-1990s and after the financial crisis in 2008, many studies have investigated house price dynamics. Furthermore, real house prices in Sweden have increased by more than 200 % since the mid-1990s up until today. This study takes a closer look at the fundamental determinants of house prices to investigate both the long- and short-run dynamics of Swedish house prices. The method of use includes a vector error-correction model, which exposes both long- and short-run dynamics of house prices. The long-run results show that Swedish house prices are currently not overvalued. Furthermore, in the short-run, the results suggest that house prices adjust to their equilibrium level with 7,9 % in each quarter.

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Prepic, Asmir. "Modelling and Forecast Swedish Electricity Consumption: A Comparison With Vector Error Correction Models." Thesis, Uppsala universitet, Statistiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-256875.

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Jang, Kyungho. "Three essays on structural vector error correction models with short-run and long-run restrictions." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1266069553.

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Silber, Frank. "Makroökonometrische Anpassungsanalyse im Vector-Error-Correction-Model (VECM) : Untersuchungen an ausgewählten Arbeitsmärkten /." Frankfurt am Main: Lang, 2003. http://www.gbv.de/dms/zbw/362076561.pdf.

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Tunehed, Per. "Is the Swedish housing market overvalued? : An analysis using a Vector error correction model." Thesis, Umeå universitet, Nationalekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185129.

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This thesis attempts to answer if a bubble is growing on the Swedish housing market. This is done by assessing the extent to which supply and demand – represented by fundamentals – can explain the rise on the Swedish housing market. Empirically, this is done by estimating a Vector error correction model using quarterly data stretching from Q1 2000 to Q4 2019. The model uses house prices as its dependent variable and disposable income, interest rate, construction costs, financial assets, and employment as independent variables. The study finds that there is a long-run relationship between house price and the independent variables, and that this long-run relationship can explain the increase in house prices that has been seen in Sweden over the last two decades, and that this suggests that a housing bubble is unlikely. Furthermore, the model finds that, in the long-run, house prices are positively associated with financial assets, and negatively associated with disposable income, interest rates, construction costs and employment rate.

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Nastansky, Andreas, Alexander Mehnert, and Hans Gerhard Strohe. "A vector error correction model for the relationship between public debt and inflation in Germany." Universität Potsdam, 2014. http://opus.kobv.de/ubp/volltexte/2014/5024/.

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In the paper, the interaction between public debt and inflation including mutual impulse response will be analysed. The European sovereign debt crisis brought once again the focus on the consequences of public debt in combination with an expansive monetary policy for the development of consumer prices. Public deficits can lead to inflation if the money supply is expansive. The high level of national debt, not only in the Euro-crisis countries, and the strong increase in total assets of the European Central Bank, as a result of the unconventional monetary policy, caused fears on inflating national debt. The transmission from public debt to inflation through money supply and long-term interest rate will be shown in the paper. Based on these theoretical thoughts, the variables public debt, consumer price index, money supply m3 and long-term interest rate will be analysed within a vector error correction model estimated by Johansen approach. In the empirical part of the article, quarterly data for Germany from 1991 by 2010 are to be examined.

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Mvita, Mpinda Freddy. "The impact of dividend policy on shareholders' wealth : evidence from the Vector Error Correction Model." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/31010.

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Dividend policy is widely researched in financial management, but determining whether it affects the market price per share is difficult. There has been much published on the subject, which presented theories such as the Modigliani, Miller, Gordon, Lintner, Walter and Richardson propositions and the relevance and irrelevance theories. However, little research has been done on the impact of dividend policy on shareholders’ wealth while considering the short- and long-run effects. The Vector Error Correction Model (VECM) was used to describe the short-run and long-run dynamics or the adjustment of the cointegrated variables towards their equilibrium values in South Africa. This study attempts to explain the effect of dividend policy on the market price per share. A sample of 46 companies listed on the Johannesburg Securities Exchange (JSE) was selected for the period 1995-2010. Three variables were used, namely the market price per share, the dividend per share and the earnings per share. The market price per share was used as a proxy in measuring shareholders’ wealth and the dividend per share was used as a proxy in measuring the dividend policy. Fixed and random effects models were applied to panel data to determine the relation between dividend policy and market price per share. The fixed effects method was used to control the stable characteristics of the companies over a fixed period. The random effects model was applied when the companies’ characteristics differed. Results for both models indicated that dividend yield is positively related to market price per share, while earnings per share do not have a significant impact on the market price per share. To test the strength of the long-run relationship, the VECM was applied. The coefficient for dividend per share in the co-integrating equation was positive, while the coefficient for earnings per share was negative. This confirms previous research findings. The results suggest that there is a long-run relationship between dividend per share and market price per share. The Granger causality test indicates there is bi-directional Granger causality between market price per share and dividend per share in South Africa. Therefore dividend policy does have a significant long-run impact on the share price and therefore provides a signal about the company’s financial success.<br>Dissertation (MCom)--University of Pretoria, 2012.<br>Financial Management<br>Unrestricted

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Persson, Rickard. "The short and long-term interdependencies between stock prices and dividends: A panel vector error correction approach." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-255666.

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This paper examines the short and long-term interdependencies between stock prices and dividends. I utilize firm level data from FTSE ALL SHARE from 1990-2014 and apply panel vector error correction model estimated with Engle & Grangers (1987) two-step procedure. The results show that there is a bi-directional long-term relationship between stock prices and dividends, i.e. an adjustment process is at work when a disequilibrium occurs. I also find a bi-directional short-term relationship. This paper also shows that Lintners model and the present value model are relevant frameworks in stock valuations.

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Behar, Alberto. "Estimating elasticities of demand and supply for South African manufactured exports using a vector error correction model." Master's thesis, University of Cape Town, 2002. http://hdl.handle.net/11427/10118.

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Bibliography: leaves 82-83.<br>Elasticities of demand and supply for South African manufactured exports are estimated using the co-integrating vector autoregression / vector error correction model approach in order toaddress simultaneity and non-stationarity issues. Demand is highly price-elastic, ranging from-3 to -6. The price elasticity of supply is 1. Competitors' prices and world income are an important determinant of demand, but domestic capacity utilization is not an important determinant of export supply.

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Books on the topic "Vector error correction models"

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Makroökonometrische Anpassungsanalyse im Vector-Error-Correction-Model (VECM): Untersuchungen an ausgewählten Arbeitsmarkten. P. Lang, 2003.

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Anderson, Richard G. Analysis of panel vector error correction models using maximum likelihood, the bootstrap, and canonical-correlation estimators. Federal Reserve Bank of St. Louis, 2006.

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S, Madheswaran, and Institute for Social and Economic Change, eds. Casuality between energy consumption and output growth in Indian cement industry: An application of panel vector error correction model. Institute for Social and Economic Change, 2010.

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Lloyd, Tim. Testing a capital pricing model of land values: Cointegration and error correction in a vector auto-regression. Department of Economics, University of Nottingham, 1992.

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Babeshko, Lyudmila, and Irina Orlova. Econometrics and econometric modeling in Excel and R. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1079837.

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The textbook includes topics of modern econometrics, often used in economic research. Some aspects of multiple regression models related to the problem of multicollinearity and models with a discrete dependent variable are considered, including methods for their estimation, analysis, and application. A significant place is given to the analysis of models of one-dimensional and multidimensional time series. Modern ideas about the deterministic and stochastic nature of the trend are considered. Methods of statistical identification of the trend type are studied. Attention is paid to the evaluation, analysis, and practical implementation of Box — Jenkins stationary time series models, as well as multidimensional time series models: vector autoregressive models and vector error correction models. It includes basic econometric models for panel data that have been widely used in recent decades, as well as formal tests for selecting models based on their hierarchical structure. Each section provides examples of evaluating, analyzing, and testing models in the R software environment. Meets the requirements of the Federal state educational standards of higher education of the latest generation.  It is addressed to master's students studying in the Field of Economics, the curriculum of which includes the disciplines Econometrics (advanced course)", "Econometric modeling", "Econometric research", and graduate students."

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Urbain, Jean-Pierre. Exogeneity in error correction models. Springer-Verlag, 1993.

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Urbain, Jean-Pierre. Exogeneity in Error Correction Models. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-95706-2.

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Alogoskoufis, George S. On error correction models: Specification, interpretation, estimation. Birkbeck College, 1990.

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Cipollini, Fabrizio. Vector multiplicative error models: Representation and inference. National Bureau of Economic Research, 2006.

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Kurniyati, Yuli. Alokasi dan distribusi anggaran pemerintah daerah Tingkat II untuk sektor pendidikan serta pengaruhnya terhadap pertumbuhan ekonomi regional: Aplikasi Vector Error Correction Model pada kabupaten dan kota di Propinsi Daerah Istimewa Yogyakarta, 1990-2006 : laporan penelitian dosen muda. Fakultas Ekonomi, Universitas Proklamasi 45, 2008.

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Book chapters on the topic "Vector error correction models"

1

Lütkepohl, Helmut. "Vector Error Correction Models." In New Introduction to Multiple Time Series Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-27752-1_6.

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Lütkepohl, Helmut. "Estimation of Vector Error Correction Models." In New Introduction to Multiple Time Series Analysis. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-27752-1_7.

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Thasnimol, C. M., and R. Rajathy. "Vector Error Correction Model for Distribution Dynamic State Estimation." In Control Applications in Modern Power System. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8815-0_2.

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Chen, Jun, Xiaoqi Peng, and Xiuming Tang. "Error Correction of Support Vector Regression Model for Copper-Matte Converting Process." In Proceedings of the 2015 Chinese Intelligent Automation Conference. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46466-3_13.

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Yamaka, Woraphon, Pathairat Pastpipatkul, and Songsak Sriboonchitta. "Business Cycle of International Tourism Demand in Thailand: A Markov-Switching Bayesian Vector Error Correction Model." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25135-6_38.

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Thongkairat, Sukrit, Woraphon Yamaka, and Songsak Sriboonchitta. "A Regime Switching Vector Error Correction Model of Analysis of Cointegration in Oil, Gold, Stock Markets." In Structural Changes and their Econometric Modeling. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04263-9_40.

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Ogah, Odey Moses, Jenny Essien, and Emmanuel Hakuri Gidado. "Cereal Crops Yield, Food Security and Agricultural Growth in Nigeria: A Vector Error Correction Model Approach." In Agricultural Transformation in Africa. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19527-3_7.

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Kuiper, Erno W., and Matthew T. G. Meulenberg. "A Structural Vector Error-Correction Model of Price Time Series to Detect Bottleneck Stages within a Marketing Channel." In Contributions to Economics. Physica-Verlag HD, 1999. http://dx.doi.org/10.1007/978-3-642-48765-1_8.

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Ao, Zou. "Dynamic Impacts of Social Expectation and Macroeconomic Factor on Shanghai Stock Market: An Application of Vector Error Correction Model." In Springer Proceedings in Mathematics & Statistics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_47.

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Beenstock, Michael, and Daniel Felsenstein. "Spatial Vector Error Correction." In Advances in Spatial Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03614-0_9.

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Conference papers on the topic "Vector error correction models"

1

Ellett, Scott A., John F. Walkup, and Thomas F. Krile. "Encoding for error correction in optical computing." In OSA Annual Meeting. Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.ft3.

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Optical processors can perform complex calculations in parallel at high speeds. They commonly suffer, however, from low accuracy, which currently hinders their widespread use. Various models for the noise in optical processors have been developed.1 In addition, various techniques have been developed to improve their accuracy. One technique involves the use of error-detection and correction codes to improve the accuracy of optical linear algebra processors.2 This allows some of the errors that occur during computation to be detected and possibly corrected. These codes, developed earlier for data transmission and fault tolerance in electronic processors, can thus be used to improve accuracy. Many of the required encoding and decoding operations can be performed optically. Computer simulations of optical matrix-vector multipliers employing various error codes will be presented. They indicate that a significant improvement in accuracy can be obtained when they are compared with processors not employing error codes.

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Suharsono, Agus, Auliya Aziza, and Wara Pramesti. "Comparison of vector autoregressive (VAR) and vector error correction models (VECM) for index of ASEAN stock price." In INTERNATIONAL CONFERENCE AND WORKSHOP ON MATHEMATICAL ANALYSIS AND ITS APPLICATIONS (ICWOMAA 2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5016666.

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Arce, Paola, Jonathan Antognini, Werner Kristjanpoller, and Luis Salinas. "An Online Vector Error Correction Model for Exchange Rates Forecasting." In International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005205901930200.

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Zhao, Ziping, and Daniel P. Palomar. "Robust maximum likelihood estimation of sparse vector error correction model." In 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2017. http://dx.doi.org/10.1109/globalsip.2017.8309093.

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Kong, Feng, and Xiaojuan Wu. "Time Series Forecasting Model with Error Correction by Structure Adaptive Support Vector Machine." In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.88.

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Baniya, Jeevan. "Linkages between Real Sector and Financial Sector in Nepal: A Vector Error Correction Model." In 5th International Conference on New Ideas in Management, Economics and Accounting. Acavent, 2018. http://dx.doi.org/10.33422/5imea.2018.02.57.

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Chengli Zheng and Ting He. "Investor sentiment and stock index: A test of causality based on vector error correction model." In 2010 2nd International Conference on Information Science and Engineering (ICISE). IEEE, 2010. http://dx.doi.org/10.1109/icise.2010.5690893.

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Lestari, Reni. "Analysis of Stock Market Integration Among ASEAN Countries by Using Vector Error Correction Model (VECM) Approach." In Japan International Business and Management Research Conference. RSF Press & RESEARCH SYNERGY FOUNDATION, 2020. http://dx.doi.org/10.31098/jibm.v1i1.220.

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Globalization has driven the economy of countries to relate to each other. It brings relationships in the capital among countries in the world, especially in ASEAN region countries. This study aimed to analyze the integration of the stock market among countries in the ASEAN region. The stock market was analyzed are the Indonesia Stock Exchange, Malaysia Stock Exchange, Singapore Stock Exchange, Thailand Stock Exchange, Vietnam Stock Exchange, and Philippine Stock Exchange. This study using the Vector Error Correction Model (VECM) as the method. The result of this study shows that, in the long term Singapore Stock Index (STI), Malaysia Stock Index (KLSE), Philippines (PSEi), and Indonesia Stock Index (JKSE) are positively correlated. This means the change of stock index price in one country will affect other related countries in the long term. In the short term of VECM estimation, found the Vietnam Stock Index (VNI), Singapore Stock Exchange (STI), Philippine (PSEi) are positively correlated and negatively correlated with Thailand Stock Exchange (SET). For the managerial implication, the result of this study is expected as a reference or basis of consideration of investment decisions. This because long-term stock market movements are important because they impact international portfolio management and risk diversification.

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Shi, Yufeng, and Wei Dong. "The Interaction between Economic Level and Pipeline Logistics in China - Based on Vector Error Correction Model." In The 10th International Symposium on Project Management, China. Aussino Academic Publishing House, 2022. http://dx.doi.org/10.52202/065147-0157.

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Xiong Jiping and Wu Ping. "An Analysis of Forecasting Model of Crude Oil Demand Based on Cointegration and Vector Error Correction Model (VEC)." In 2008 International Seminar on Business and Information Management (ISBIM 2008). IEEE, 2008. http://dx.doi.org/10.1109/isbim.2008.97.

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Reports on the topic "Vector error correction models"

1

Anderson, Richard G., Dennis Hoffman, and Robert H. Rasche. A Vector Error-Correction Forecasting Model of the U.S. Economy. Federal Reserve Bank of St. Louis, 1998. http://dx.doi.org/10.20955/wp.1998.008.

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Anderson, Richard G., Hailong Qian, and Robert H. Rasche. Analysis of Panel Vector Error Correction Models Using Maximum Likelihood, the Bootstrap, and Canonical Correlation Estimators. Federal Reserve Bank of St. Louis, 2006. http://dx.doi.org/10.20955/wp.2006.050.

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Hoffman, Dennis, and Robert H. Rasche. STLS/US-VECM 6.1: A Vector Error-Correction Forecasting Model of the US Economy. Federal Reserve Bank of St. Louis, 1997. http://dx.doi.org/10.20955/wp.1997.008.

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Salazar-Díaz, Andrea, Aaron Levi Garavito Acosta, Sergio Restrepo-Ángel, and Leidy Viviana Arcila-Agudelo. Real Equilibrium Exchange Rate in Colombia: Thousands of VEC Models Approach. Banco de la República Colombia, 2022. http://dx.doi.org/10.32468/be.1221.

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Behavioral Equilibrium Exchange Rate (BEER) models suggest many variables as potential drivers of equilibrium real exchange rates (ERER). This gives rise to model uncertainty issues, as ERER depends and varies, often drastically, on a particular set of chosen variables. We address this issue by estimating thousands of Vector Error Correction (VEC) specifications for Colombian data between 2000Q1-2019Q4. According to an extensive literature review, we employ thirty-five proxies categorized among five fixed groups of economic fundamentals that underlie the ERER: Indebtedness, Fiscal sector, Productivity, Terms-of-Trade, and Interest Rate Differentials. Our approach derives an empirical distribution of ERER that allows us to state with greater certainty, among hundreds of plausible economic specifications, whether the real exchange rate is either misaligned or in equilibrium.

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Ahwireng-Obeng, Asabea Shirley, and Frederick Ahwireng-Obeng. Private Philanthropic Cross-Border Flows and Sustainable Development in Africa. Centre on African Philanthropy and Social Investment, 2011. http://dx.doi.org/10.47019/2021.ra1.

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The paper examines the simultaneous impact of private philanthropic cross-border funding from international foundations on the economic, social, and environmental dimensions of sustainable development in Africa. The vector error correction model (VECM) was used, and contrary to expectations drawn from past studies, funding from this source improves economic growth, advances human development, and enhances environmental quality. Causality test results also disconfirmed the assumption that interactions among the three dimensions were positive and complementary in the long term. The environment variable was found to be noncomplementary. Based on these unique results, theoretical propositions are made with an underlying mechanism of action. Practical and policy implications, limitations, and directions for future research are discussed.

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Cipollini, Fabrizio, Robert Engle, and Giampiero Gallo. Vector Multiplicative Error Models: Representation and Inference. National Bureau of Economic Research, 2006. http://dx.doi.org/10.3386/t0331.

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Cipollini, Fabrizio, Robert Engle, and Giampiero Gallo. Vector Multiplicative Error Models: Representation and Inference. National Bureau of Economic Research, 2006. http://dx.doi.org/10.3386/w12690.

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Sayyar-Rodsari, Bijan, and Carl Schweiger. Optimal Model-Based Fault Estimation and Correction for Particle Accelerators and Industrial Plants Using Combined Support Vector Machines and First Principles Models. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/992983.

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Dassanayake, Wajira, Xiaoming Li, and Klaus Buhr. A Revisit of Price Discovery Dynamics Across Australia and New Zealand. Unitec ePress, 2015. http://dx.doi.org/10.34074/rsrp.039.

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This study re-investigates the price discovery dynamics of selected stocks cross-listed on the Australian Stock Exchange (ASX) and the New Zealand Stock Exchange (NZX) during a bear trading phase from January 2008 to December 2011. A differing price discovery dynamic in a bear market versus a bull market may occur because of variations in investor sentiments and disparities in the role of the stock prices. Using intraday data, we employ the vector error correction mechanism, Hasbrouck’s (1995) information share and Grammig et al.’s (2005) conditional information share methods. Consistent with previous research, we find that price discovery takes place mostly on the home market for the Australian firms and for all but one of the New Zealand firms. However, not seen in existing studies, we show that the NZX has grown in importance for both the Australian and New Zealand firms. This suggests that the NZX is deviating from being a pure satellite market.

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Dassanayake, Wajira, Xiaoming Li, and Klaus Buhr. A Revisit of Price Discovery Dynamics Across Australia and New Zealand. Unitec ePress, 2015. http://dx.doi.org/10.34074/rsrp.039.

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Abstract:

This study re-investigates the price discovery dynamics of selected stocks cross-listed on the Australian Stock Exchange (ASX) and the New Zealand Stock Exchange (NZX) during a bear trading phase from January 2008 to December 2011. A differing price discovery dynamic in a bear market versus a bull market may occur because of variations in investor sentiments and disparities in the role of the stock prices. Using intraday data, we employ the vector error correction mechanism, Hasbrouck’s (1995) information share and Grammig et al.’s (2005) conditional information share methods. Consistent with previous research, we find that price discovery takes place mostly on the home market for the Australian firms and for all but one of the New Zealand firms. However, not seen in existing studies, we show that the NZX has grown in importance for both the Australian and New Zealand firms. This suggests that the NZX is deviating from being a pure satellite market.

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