Relevant bibliographies by topics / Vector error correction model (VECM)

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Academic literature on the topic 'Vector error correction model (VECM)'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Vector error correction model (VECM)"

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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 (April 23, 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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Abusharbeh, Mohammed. "Determinants of Islamic bank financing in the Middle East: Vector Error Correction Model (VECM)." Investment Management and Financial Innovations 17, no. 4 (December 9, 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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Usman, Mustofa, Luvita Loves, Edwin Russel, Muslim Ansori, Warsono Warsono, Widiarti Widiarti, and Wamiliana Wamiliana. "Analysis of Some Energy and Economics Variables by Using VECMX Model in Indonesia." International Journal of Energy Economics and Policy 12, no. 2 (March 20, 2022): 91–102. http://dx.doi.org/10.32479/ijeep.11897.

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Time series modeling analysis is one of the methods to forecast based on past data and conditions. The analytical tool that is commonly used to forecast multivariate time series data is the Vector Autoregressive (VAR) model. However, when the variables have cointegration and stationary at the first difference value, then the VAR model is modified into the Vector Error Correction Model (VECM). In VECM, all variables can be used as endogenous variables. If exogenous variables are involved in the VECM model, then the model is called as Vector Error Correction Model with Exogenous variables (VECMX). In the present study, a time series modeling analysis was used to analyze the price of gasoline, the money supply in a broad sense (M2), oil and gas exports, and consumption imports over the years from 2012 to 2020. By using information on the criteria of Akaike Information Criterion Corrected, Hannan–Quinn Criterion, Akaike Information Criterion, and Schwarz Bayesian Criterion, the best VAR(p) model is obtained with order 3, or lag 3. Based on the VAR(3) model, the cointegration test is conducted, and the result shows that there is a long-term relationship among variables, namely, there is a cointegration relationship between variables with rank = 1. Based on the cointegration rank = 1 and the smallest value of the information criteria and comparison of some candidate best models, namely, VECMX(2,1), VECMX(2,2), VECMX(3,1), VECMX(3,2), and VECMX(4,1), we found that the best model is VECMX(3,1) with lag 3 for endogenous variables and lag 1 for exogenous variables. Based on this best model, further analysis of Granger causality, Impulse Response Function (IRF), and forecasting is discussed.
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Mashabi, M., and Wasiaturrahma Wasiaturrahma. "ELECTRONIC BASED PAYMENT SYSTEMS AND ECONOMIC GROWTH IN INDONESIA." Jurnal Ilmu Ekonomi Terapan 6, no. 1 (June 26, 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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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 (December 31, 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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Sunarya, I. Wayan. "Perkembangan Makroekonomi Negara Kanada Dengan Analisa Vector Error Correction Model (VECM)." Jurnal Aplikasi Manajemen, Ekonomi dan Bisnis 6, no. 2 (April 30, 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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Shahraki, M*, and S. Ghaderi. "The Relationship between Education and Health: Vector Error Correction Model (VECM)." Journal of Health 10, no. 4 (December 1, 2019): 445–56. http://dx.doi.org/10.29252/j.health.10.4.445.

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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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Hamzah, Amir, and Mohamad Rizky. "Determinant Analysis of Company Debt Policy with Vector Error Correction Model Approach." Global Financial Accounting Journal 6, no. 1 (April 30, 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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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 (November 19, 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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Dissertations / Theses on the topic "Vector error correction model (VECM)"

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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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Meki, Brian. "Examining long-run relationships of the BRICS stock market indices to identify opportunities for implementation of statistical arbitrage strategies." Thesis, University of the Western Cape, 2012. http://hdl.handle.net/11394/4348.

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>Magister Scientiae - MSc
Purpose:This research investigates the existence of long-term equilibrium relationships among the stock market indices of Brazil, Russia, India, China and South Africa (BRICS). It further investigates cointegrated stock pairs for possible implementation of statistical arbitrage trading techniques.Design:We utilize standard multivariate time series analysis procedures to inspect unit roots to assess stationarity of the series. Thereafter, cointegration is tested by the Johansen and Juselius (1990) procedure and the variables are interpreted by a Vector Error Correction Model (VECM). Statistical arbitrage is investigated through the pairs trading technique.Findings:The five stock indices are found to be cointegrated. Analysis shows that the cointegration rank among the variables is significantly influenced by structural breaks. Two pairs of stock variables are also found to be cointegrated. This guaranteed the mean reversion property necessary for the successful execution of the pairs trading technique. Determining the optimal spread threshold also proved to be highly significant with respect to the success of this trading technique.Value:This research seeks to expand on the literature covering long-run co-movements of the volatile emerging market indices. Based on the cointegration relation shared by the BRICS, the research also seeks to encourage risk taking when investing. We achieve this by showing the potential rewards that can be realized through employing appropriate statistical arbitrage trading techniques in these markets.
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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.
Dissertation (MCom)--University of Pretoria, 2012.
Financial Management
Unrestricted
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Hadad, Junior Eli. "Um estudo econométrico do consumo e da renda agregados no Brasil." Universidade Presbiteriana Mackenzie, 2011. http://tede.mackenzie.br/jspui/handle/tede/534.

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Made available in DSpace on 2016-03-15T19:25:37Z (GMT). No. of bitstreams: 1 Eli Hadad Junior.pdf: 290403 bytes, checksum: 413b010b2b66c535b71df800b9626c61 (MD5) Previous issue date: 2011-08-10
The dissertation analyzes data of the Brazilian household consumption and income between the years 1947 and 2009. The study aims to evaluate to what extent the aggregate consumption of Brazilian household may approximate be a random walk. The dissertation uses Johansen's cointegration techniques (1988, 1991) and super exogeneity tests as proposed by Engle and Hendry et al. (1983). The dissertation attempts to evaluate whether interventions that affect consumption will impact the dynamics of aggregate income. These interventions can occur through credit policies and tax changes, among other macroeconomic shocks. Finally, a decomposition is made following the methodology proposed by Gonzalo-Granger (1995) and evaluating the importance of shocks in permanent and temporary changes in consumption.
A dissertação analisa os dados de consumo e renda das famílias brasileiras entre os anos de 1947 e 2009. O trabalho visa avaliar em que medida o consumo agregado das famílias brasileiras pode ser bem aproximando a partir de um passeio aleatório puro. O trabalho utiliza técnicas de cointegração de Johansen (1988, 1991) e testes de super exogeneidade na forma proposta por Hendry, Engle et al. (1983). A dissertação procura avaliar se intervenções que afetam o consumo das famílias geram impacto na dinâmica da renda agregada das mesmas. Tais intervenções podem ser por políticas de crédito, alterações tributárias, choque macroeconômicos entre outras. Por fim uma decomposição entre fatores permanentes e transitórios será feita pela metodologia proposta por Gonzalo-Granger (1995) com o objetivo de avaliar-se a importância dos choques permanentes e transitórios para as variações do consumo.
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Bohlandt, Florian Martin. "Single manager hedge funds - aspects of classification and diversification." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85859.

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Thesis (PhD)--Stellenbosch University, 2013.
A persistent problem for hedge fund researchers presents itself in the form of inconsistent and diverse style classifications within and across database providers. For this paper, single-manager hedge funds from the Hedge Fund Research (HFR) and Hedgefund.Net (HFN) databases were classified on the basis of a common factor, extracted using the factor axis methodology. It was assumed that the returns of all sample hedge funds are attributable to a common factor that is shared across hedge funds within one classification, and a specific factor that is unique to a particular hedge fund. In contrast to earlier research and the application of principal component analysis, factor axis has sought to determine how much of the covariance in the dataset is due to common factors (communality). Factor axis largely ignores the diagonal elements of the covariance matrix and orthogonal factor rotation maximises the covariance between hedge fund return series. In an iterative framework, common factors were extracted until all return series were described by one common and one specific factor. Prior to factor extraction, the series was tested for autoregressive moving-average processes and the residuals of such models were used in further analysis to improve upon squared correlations as initial factor estimates. The methodology was applied to 120 ten-year rolling estimation windows in the July 1990 to June 2010 timeframe. The results indicate that the number of distinct style classifications is reduced in comparison to the arbitrary self-selected classifications of the databases. Single manager hedge funds were grouped in portfolios on the basis of the common factor they share. In contrast to other classification methodologies, these common factor portfolios (CFPs) assume that some unspecified individual component of the hedge fund constituents’ returns is diversified away and that single manager hedge funds should be classified according to their common return components. From the CFPs of single manager hedge funds, pure style indices were created to be entered in a multivariate autoregressive framework. For each style index, a Vector Error Correction model (VECM) was estimated to determine the short-term as well as co-integrating relationship of the hedge fund series with the index level series of a stock, bond and commodity proxy. It was postulated that a) in a well-diversified portfolio, the current level of the hedge fund index is independent of the lagged observations from the other asset indices; and b) if the assumptions of the Efficient Market Hypothesis (EMH) hold, it is expected that the predictive power of the model will be low. The analysis was conducted for the July 2000 - June 2010 period. Impulse response tests and variance decomposition revealed that changes in hedge fund index levels are partially induced by changes in the stock, bond and currency markets. Investors are therefore cautioned not to overemphasise the diversification benefits of hedge fund investments. Commodity trading advisors (CTAs) / managed futures, on the other hand, deliver diversification benefits when integrated with an existing portfolio. The results indicated that single manager hedge funds can be reliably classified using the principal factor axis methodology. Continuously re-balanced pure style index representations of these classifications could be used in further analysis. Extensive multivariate analysis revealed that CTAs and macro hedge funds offer superior diversification benefits in the context of existing portfolios. The empirical results are of interest not only to academic researchers, but also practitioners seeking to replicate the methodologies presented.
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Louw, Riëtte. "Forecasting tourism demand for South Africa / Louw R." Thesis, North-West University, 2011. http://hdl.handle.net/10394/7607.

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Tourism is currently the third largest industry within South Africa. Many African countries, including South Africa, have the potential to achieve increased economic growth and development with the aid of the tourism sector. As tourism is a great earner of foreign exchange and also creates employment opportunities, especially low–skilled employment, it is identified as a sector that can aid developing countries to increase economic growth and development. Accurate forecasting of tourism demand is important due to the perishable nature of tourism products and services. Little research on forecasting tourism demand in South Africa can be found. The aim of this study is to forecast tourism demand (international tourist arrivals) to South Africa by making use of different causal models and to compare the forecasting accuracy of the causal models used. Accurate forecasts of tourism demand may assist policy–makers and business concerns with decisions regarding future investment and employment. An overview of South African tourism trends indicates that although domestic arrivals surpass foreign arrivals in terms of volume, foreign arrivals spend more in South Africa than domestic tourists. It was also established that tourist arrivals from Africa (including the Middle East), form the largest market of international tourist arrivals to South Africa. Africa is, however, not included in the empirical analysis mainly due to data limitations. All the other markets namely Asia, Australasia, Europe, North America, South America and the United Kingdom are included as origin markets for the empirical analysis and this study therefore focuses on intercontinental tourism demand for South Africa. A review of the literature identified several determinants of tourist arrivals, including income, relative prices, transport cost, climate, supply–side factors, health risks, political stability as well as terrorism and crime. Most researchers used tourist arrivals/departures or tourist spending/receipts as dependent variables in empirical tourism demand studies. The first approach used to forecast tourism demand is a single equation approach, more specifically an Autoregressive Distributed Lag Model. This relationship between the explanatory variables and the dependent variable was then used to ex post forecast tourism demand for South Africa from the six markets identified earlier. Secondly, a system of equation approach, more specifically a Vector Autoregressive Model and Vector Error Correction Model were estimated for each of the identified six markets. An impulse response analysis was undertaken to determine the effect of shocks in the explanatory variables on tourism demand using the Vector Error Correction Model. It was established that it takes on average three years for the effect on tourism demand to disappear. A variance decomposition analysis was also done using the Vector Error Correction Model to determine how each variable affects the percentage forecast variance of a certain variable. It was found that income plays an important role in explaining the percentage forecast variance of almost every variable. The Vector Autoregressive Model was used to estimate the short–run relationship between the variables and to ex post forecast tourism demand to South Africa from the six identified markets. The results showed that enhanced marketing can be done in origin markets with a growing GDP in order to attract more arrivals from those areas due to the high elasticity of the real GDP per capita in the long run and its positive impact on tourist arrivals. It is mainly up to the origin countries to increase their income per capita. Focussing on infrastructure development and maintenance could contribute to an increase in future tourist arrivals. It is evident that arrivals from Europe might have a negative relationship with the number of hotel rooms available since tourists from this region might prefer accommodation with a safari atmosphere such as bush lodges. Investment in such accommodation facilities and the marketing of such facilities to Europeans may contribute to an increase in arrivals from Europe. The real exchange rate also plays a role in the price competitiveness of the destination country. Therefore, in order for South Africa to be more price competitive, inflation rate control can be a way to increase price competitiveness rather than to have a fixed exchange rate. Forecasting accuracy was tested by estimating the Mean Absolute Percentage Error, Root Mean Square Error and Theil’s U of each model. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was estimated for each origin market as a benchmark model to determine forecasting accuracy against this univariate time series approach. The results showed that the Seasonal Autoregressive Integrated Moving Average model achieved more accurate predictions whereas the Vector Autoregressive model forecasts were more accurate than the Autoregressive Distributed Lag Model forecasts. Policy–makers can use both the SARIMA and VAR model, which may generate more accurate forecast results in order to provide better policy recommendations.
Thesis (M.Com. (Economics))--North-West University, Potchefstroom Campus, 2011.
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Bentivoglio, Deborah. "Analisi della Sostenibilità Socio-economica ed Ambientale dei Biocarburanti nel Contesto Europeo e Brasiliano." Doctoral thesis, Università Politecnica delle Marche, 2015. http://hdl.handle.net/11566/243058.

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Negli ultimi anni la produzione e il consumo dei biocarburanti sono aumentati a livello globale. Tale incremento è stato incentivato soprattutto grazie al supporto e agli incentivi adottati dai vari Paesi promotori finalizzati alla riduzione delle emissioni di gas serra e alla sicurezza energetica. Ad oggi il mercato globale è dominato dall’etanolo (79%) e dal biodiesel (21%). In particolare, l'Unione Europea domina il mercato del biodiesel mentre il Brasile è il più grande produttore ed esportatore mondiale di zucchero, nonché il più grande produttore al mondo e consumatore di etanolo da canna da zucchero per il settore del trasporto. Tuttavia, recentemente, sono state sollevate incertezze relative alla reale sostenibilità dei biocombustibili, sia dal punto di vista ambientale che socio-economico. Accanto ai dubbi relativi alle loro performance in termini di riduzione di emissioni di GHG rispetto ai combustibili fossili, sono emerse critiche relative all’impatto che tali biocarburanti hanno sull’utilizzo del suolo (ILUC), sulla perdita di biodiversità e sull’aumento dei prezzi dei mercati delle commodities agricole usate come materie prime per la loro produzione. A tal proposito, la ricerca condotta si inserisce a pieno all’interno di tale dibattito e si pone l’obiettivo di valutare la sostenibilità ambientale e le implicazioni socio-economiche della produzione di biocombustibili nel contesto europeo che in quello brasiliano, soffermandosi in particolare sull’analisi econometrica dei prezzi delle commodities agricole utilizzate come materie prime di origine. Al fine di valutare la sostenibilità ambientale è stata applicata un’analisi multicriteriale grazie all’applicazione di uno studio meta-analitico volto ad identificare i criteri ambientali per la stima dell’impatto della filiera biodiesel. Lo scopo è stata quello di individuare l’alternativa migliore tra le diverse tipologie di biomassa utilizzata per la produzione del biodiesel in Europa (olio di colza, di girasole, di palma e di soia). La valutazione della sostenibilità socio-economica è stata invece effettuata tramite l’analisi delle serie storiche e la successiva applicazione di un modello a correzione di errore (VECM) al fine di verificare se i prezzi delle commodities agricole, (olio di colza nel contesto europeo e zucchero nel contesto brasiliano) siano influenzati dai prezzi dei biocombustibili di riferimento, quali biodiesel ed etanolo, e viceversa. Tale relazione è stata studiata anche in relazione al combustibile fossile di riferimento, ossia la benzina (o gasolina) per il Brasile e il diesel per l’Europa. Sintetizzando i risultati, per quanto riguarda l’impatto ambientale, dall’applicazione multicriteria, si evince che nel caso in cui si considerino prioritari i criteri di sostenibilità ambientale, la soluzione migliore a livello europeo sarebbe quella del biodiesel da olio di girasole. Tale soluzione risulterebbe molto interessante per l’Europa e in particolar modo per l’Italia. Tuttavia la filiera del girasole risulta inaccessibile dal punto di vista economico aziendale. Va da sé che nell’ipotesi in cui si consideri prioritario il criterio economico, la produzione di biodiesel da olio di palma, di derivazione estera, risulterebbe la soluzione migliore, creando squilibri dal punto di vista ambientale e in particolare di cambiamento di uso del suolo (ILUC). I risultati dello studio socio-economico tramite l’analisi delle serie storiche indica, ceteris paribus, che i prezzi dei biocarburanti sono influenzati soprattutto dai prezzi delle materie prime anche se emerge con chiarezza che le variazioni dei prezzi dei biocarburanti non influenzano in misura sostanziale i prezzi degli alimenti.
The last decade has seen a rapid increase in the production and consumption of biofuels at global level. This development has been especially stimulated by policy as a means to promote energy security and to reduce the emissions of greenhouse gases. Nowadays, world biofuel markets are dominated by ethanol (79%) and biodiesel (21%). In particular, Biodiesel market is dominated by the European Union, at the same time Brazil is the world’s biggest sugar producer and exporter, as well as the world’s largest producer and consumer of sugarcane ethanol as a transportation fuel. However, several authors have recently raised concerns about the environmental benefits and social-economic implications of biofuels production such as underlying uncertainties over the life cycle emissions of greenhouse gas emissions (GHG), possible deforestation for feedstock production, degradation of soil (ILUC) and air quality, increased water consumption, possible loss of biodiversity, possible competition with food production, and other potential social imbalances. The aim of this work is to investigate the impacts of biofuels on the environmental aspects and food prices in the European and Brazilian context. In order to assess the environmental performance this work aims to identify environmental criteria in order to evaluate the impact of the entire biodiesel production chain thought an exploratory meta-analysis of international scientific research. The information from the meta-analysis enabled the design and implementation of a multi-criteria methodology to define the best alternative between different agricultural raw materials used for biodiesel production (rapeseed oil, sunflower oil and palm oil) according to the principles of sustainability expressed by current EU policy. In order to explore relationship between food commodity and biofuel prices a time series models is used. In particular, both the impact of EU biodiesel prices on diesel and rapeseed oil prices and Brazilian ethanol prices on sugar and gasoline prices are investigated using a vector error corrections model (VECM). The multi-criteria shows that from an environmental perspective the best solution at European level is biodiesel production based on sunflower oil. This solution would be very interesting for Europe and especially for Italy. However, the sunflower chain is not feasible from the economic point of view, especially for the biodiesel company. In fact, if the economic aspect is priority, the palm oil from Malaysia is the best alternative. Finally, the results from the time series analysis suggest that biofuels prices are mainly affected by feedstock prices, but there is no strong evidence that changes in biofuels prices affect food prices, for the market and time period considered.
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Tao, Juan. "A re-examination of the relationship between FTSE100 index and futures prices." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/8071.

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This thesis examines the validity of the cost of carry model for pricing FTSE100 futures contracts and the relationship between FTSE100 spot and futures markets during two sub-periods characterised by different market trading systems employed by the LSE and LIFFE. The empirical work is carried out using three approaches to econometric modeling: a basic VECM for spot and futures prices, a VECM extended with a DCCTGARCH framework to account for the conditional variance-covariance structure for spot and futures prices and a threshold VECM to capture regime-dependent spot-futures price dynamics. Overall, both the basic VECM and the DCC-TGARCH analysis suggest that there are deviations from the cost of carry relationship in the first sub-sample when transactions costs in both markets are relatively high but that the cost of carry relationship tends to be valid in the second sub-sample when transactions costs are lower. This is further confirmed by the evidence of higher conditional correlations between the two markets in the second sub-sample as compared with the first, using the DCC-TGARCH analysis. This implies that the no-arbitrage cost of carry relationship between spot and futures markets is more effectively maintained by index arbitrageurs in the second period when market conditions are closer to perfect market assumptions, and hence the cost of carry model could be more reasonably used as a benchmark for pricing stock index futures. The threshold VECM analysis depicts regime-dependent price dynamics between FTSE100 spot and futures markets and leads to some interesting and important findings: arbitrage may not be practicable under some market conditions, either because it is difficult to find counterparties for the arbitrage transactions, or because there is significant risk associated with arbitrage; as a result, the cost of carry model may not always be suitable for pricing stock index futures. Furthermore, the threshold values yielded from estimating the threshold VECM reflect the average transaction costs for most arbitrageurs that are more reliable and fair than subjective estimations.
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Ramanauskaitė, Giedrė. "Stress testing in credit risk analysis." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080620_110415-38466.

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The supervising institutions do not give to commercial banks indications what models have to be used for stress testing. This research was done in order to find out which mathematical/statistical models are and can be used in credit risk stress testing. Credit risk is one of the biggest financial risks that every bank faces. Stress testing is a tool of credit risk assessment that helps to estimate the consequences of the events that have really small probability to happen but if they occur, banks can have significant losses. This study determined that the most plausible event is adverse macroeconomic conditions. For this reason, models that include macroeconomic impact were presented. Vector autoregression and vector error correction model were tested using the empirical data received from Swedish central bank, Swedish statistics and Eurostat. For financial stability it is worth using vector autoregression or vector error correction model as they describe the macroeconomic environment in the most suitable way and they are appropriate for shock analysis by showing how the impact of any factor can change the whole system. Structure: introduction, main part (credit risk, methods and empirical analysis), publication, conclusions, references. Thesis consists of: 50 p. text without appendices, 13 pictures, 11 tables, 26 bibliographical entries. Appendices included.
Kredito įstaigų priežiūros institucijos nepateikia komerciniams bankams kokius metodus jie turėtų naudoti testavime nepalankiomis sąlygomis. Tiriamasis darbas buvo atliktas tuo tikslu, kad būtų išsiaiškinta kokie matematiniai ir statistiniai metodai yra ir gali būti naudojami kredito rizikos vertinime testuojant nepalankiomis sąlygomis. Kredito rizika yra viena iš didžiausių finansinių rizikų su kuria bankai susiduria. Testavimas nepalankiomis sąlygomis yra kredito rizikos vertinimo įrankis, padedantis nustatyti įvykių, kurių realizavimosi tikimybės yra mažos, tačiau jiems įvykus, bankai patirtų reikšmingus nuostolius, pasekmes. Šis tyrimas nustatė, jog labiausiai tikėtinas įvykis gali būti ypatingai nepalankios ekonominės sąlygos. Dėl šios priežasties darbe yra pristatyti metodai, kurie įvertina makroekonominių veiksnių įtaką. Vektorinė autoregresija ir vektorinis paklaidų korekcijos modelis buvo patikrinti naudojant Švedijos centrinio banko, Švedijos statistikos departamento ir Eurostat empirinius duomenis. Finansinio stabilumo įvertinimui vertėtų naudoti vektorinį autoregresijos ar vektorinį paklaidų korekcijos modelius, nes šie modeliai geriausiai aprašo ekonominę aplinką bei yra labai tinkami šokų analizei, kadangi įvertina bet kurio veiksnio įtaką visai sistemai. Struktūra: įvadas, pagrindinė dalis (kredito rizika, metodai ir empirinė analizė), publikacija, išvados, literatūros sąrašas. Tiriamasis darbas sudarytas iš: 50 psl. teksto be priedų, 13 paveikslų, 11... [toliau žr. visą tekstą]
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Raksong, Saranya. "The stability of money demand and monetary transmission mechanism in Thailand." Thesis, Curtin University, 2010. http://hdl.handle.net/20.500.11937/612.

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The major objective of this thesis is to investigate whether there exists a stable long run and short run equilibrium relationship between real money balances (M1 or M2) and their determinants in Thailand. A cointegration analysis and the Vector Error Correction Model (VECM) are conducted on quarterly data over two data set periods, 1980Q1 to 2007Q1 and 1993Q1 to 2007Q1. The results indicate that there exists a long run equilibrium relationship between real money demand (both M1 and M2) and its determinants: real income, price level, exchange rates, and external interest rates.The thesis also used the Vector Autoregression model (VAR) to test the monetary transmission mechanism in Thailand in three different channels of monetary policy: the interest rate channel, the credit channel, and the exchange rate channel. The results find that a change in the M1 money demand has more effect on economic growth while a change in M2 has a stronger effect on the price level. In addition, the results also show that the M1 money demand is responsive to the transmission mechanism in all channels tested in the thesis.
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Books on the topic "Vector error correction model (VECM)"

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

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

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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. Bangalore: Institute for Social and Economic Change, 2010.

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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. Yogyakarta: Fakultas Ekonomi, Universitas Proklamasi 45, 2008.

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5

Pevehouse, Jon, and Jason D. Brozek. Time‐Series Analysis. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0019.

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This article discusses time-series methods such as simple time-series regressions, ARIMA models, vector autoregression (VAR) models, and unit root and error correction models (ECM). It specifically presents a brief history of time-series analysis before moving to a review of the basic time-series model. It then describes the stationary models in univariate and multivariate analyses. The nonstationary models of each type are addressed. In addition, various issues regarding the analysis of time series including data aggregation and temporal stability are considered. Before concluding, the article briefly reports the time-series techniques in the context of panel data. In general, time-series analysis can help improve the understanding of the political world.
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Book chapters on the topic "Vector error correction model (VECM)"

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Labuschagne, Coenraad C. A., Niel Oberholzer, and Pierre J. Venter. "A Vector Error Correction Model (VECM) of FTSE/JSE SA Listed Property Index and FTSE/JSE SA Capped Property Index." In Advances in Panel Data Analysis in Applied Economic Research, 95–111. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70055-7_8.

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Sah, Hemant Kumar, and Gyanendra Singh Sisodia. "Exploring the Relationship Among Economic Growth, Energy Consumption, Carbon Emission and Trade: A Panel Vector Error Correction Model (VECM) Analyses." In Energy Transition, 249–65. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3540-4_9.

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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, 15–27. Singapore: 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, 117–27. Berlin, Heidelberg: 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, 415–27. Cham: 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, 514–24. Cham: 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, 69–85. Cham: 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, 129–41. Heidelberg: 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, 489–96. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08377-3_47.

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Dghais, Amel Abdoullah, and Mohd Tahir Ismail. "Modeling Relationship Between Stock Market of UK and MENA Countries: A Wavelet Transform and Markov Switching Vector Error Correction Model Approach." In Proceedings of the International Conference on Computing, Mathematics and Statistics (iCMS 2015), 165–73. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2772-7_17.

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Conference papers on the topic "Vector error correction model (VECM)"

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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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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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Mehmetaj, Nevila. "Relationship between Exchange Rate and Trade Balance Pre and after COVID-19 – Albania Case Study." In ERAZ: KNOWLEDGE BASED SUSTAINABLE DEVELOPMENT. Association of Economists and Managers of the Balkans – Belgrade, Serbia, 2022. http://dx.doi.org/10.31410/eraz.2022.23.

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This study attempts to identify the relationship between the real exchange rate and trade balance in Albania with its major trading partner Italy. Due to the severe lockdown and restrictions policies in response to Covid-19 measures, there were important effects on the evolution of trade. Quarterly data from 2008 to 2022 are used in several econometric methods such as unit root tests, cointegration techniques, Granger test, and vector error correction model (VECM). The main findings of this study are that domestic income and exchange rate show a long-run positive relationship to the trade balances. Devaluation of the domestic currency will improve the trade balance in the long run, consistent with the Marshall-Lerner condition.
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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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Karn, Arodh Lal, and Rakshha Kumari Karna. "Supply line engineering on importation and exportation: bimstec perspective." In Contemporary Issues in Business, Management and Economics Engineering. Vilnius Gediminas Technical University, 2019. http://dx.doi.org/10.3846/cibmee.2019.016.

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Purpose – the purpose of this paper is to investigate whether supply line engineering strategies of goods and service exports, exports transport services and export time have a significant impact on GDP growth of BIMSTEC countries or not. Research methodology – the study employed a panel vector error correction model (VECM) instead of loose VAR to examine the short and long-run relationship among the selected indicators and GDP growth. Findings – in the long-run, the time of export negatively and suggestively associate with GDP. Conversely, VECM based Granger causality test signposted that in short-run only unidirectional causality running from goods and service exports (GSE), trade duration like exports time (ET) toward GDP and for the rest of the variables no causality found. Research limitations – this study is contextualized only on Bangladesh, Bhutan, India, Myanmar, Nepal, Sri Lanka and Thailand. Practical implications – to investigate the current position of the link between supply line logistics strategies and economic growth by using annual data for the period of 1980 to 2014 and possible weaknesses and logistics presence. Originality/Value – this paper is an attempt, first of its kind, to fill up this shortfall, to estimate the relationship of exports transport services, exports time, and goods and services exports with GDP growth of BIMSTEC countries.
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Algan, Neşe, Başak Gül Aktakas, and İpek Tekin. "The Relationship between Corruption and Economic Growth as a Social Issue: A Case Study on Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.00996.

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The present study aims to investigate the relationship between corruption and economic growth by taking the driving force of education into account. A significant contribution of the education level to the reduction process of corruption is expected to occur. For this reason, the number of those who are convicted of corruption offenses depending on their educational status for Turkey are to be taken into account, whereas the effect of education being a separate variable on growth and corruption will not be considered. In this regard, Vector Error Correction (VECM) model will be used as a method for the years between 1980-2011 and the relationship between corruption and economic growth will be analyzed. The contribution of the study to the literature is to reveal the impact of those who cause corruption depending on their education level on growth by undertaking the education levels separately. According to the empirical findings, considering corruption convicts who are literate but not graduated from a school and those having graduated from primary and secondary education, it was observed that corruption affects growth in a negative way. In contrast, given the corruption crimes which were committed by the graduates of both high school and vocational school at high school level and higher education, it was determined that there is a positive relationship between corruption and economic growth.
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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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Reports on the topic "Vector error correction model (VECM)"

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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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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, August 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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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, December 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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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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