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Pradhan, Kailash. "The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in India." South East European Journal of Economics and Business 6, no. 1 (April 1, 2011): 111–23. http://dx.doi.org/10.2478/v10033-011-0010-2.
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The Hedging Effectiveness of Stock Index Futures: Evidence for the S&P CNX Nifty Index Traded in IndiaThis study evaluates optimal hedge ratios and the hedging effectiveness of stock index futures. The optimal hedge ratios are estimated from the ordinary least square (OLS) regression model, the vector autoregression model (VAR), the vector error correction model (VECM) and multivariate generalized autoregressive conditional heteroskedasticity (M-GARCH) models such as VAR-GARCH and VEC-GARCH using the S&P CNX Nifty index and its futures index. Hedging effectiveness is measured in terms of within sample and out of sample risk-return trade-off at various forecasting horizons. The analysis found that the VEC-GARCH time varying hedge ratio provides the greatest portfolio risk reduction and generates the highest portfolio returns.
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Mehrara, Mohsen, and Monire Hamldar. "Optimal Hedge Ratio for Brent Oil Market; Baysian Approach." International Letters of Social and Humanistic Sciences 37 (August 2014): 82–87. http://dx.doi.org/10.18052/www.scipress.com/ilshs.37.82.
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This paper examines the optimal hedging ratio (OHR) for the Brent Crude Oil Futures using daily data over the period 1990/17/8-2014/11/3. To gain OHR, it is employed a Vector Autoregressive (VAR) and Vector Error Correction (VEC) and Baysian Vector Autoregressive (BVAR) models. At last, the efficiency of these calculated OHR are compared through Edrington's index.
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Mugableh, Mohamed Ibrahim. "Does Monetary Policy Affect Economic Growth in Jordan? Evidence from Ordinary Least Square Models." International Business Research 12, no. 1 (December 6, 2018): 27. http://dx.doi.org/10.5539/ibr.v12n1p27.
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The main objective of this paper is to analyze equilibrium and dynamic causality relationships between monetary policy tools and economic growth in Jordan for the period (1990-2017). For this purpose, it considers the autoregressive distributed lag (ARDL) and vector error correction (VEC) models estimations. The results of ARDL approach show that monetary policy variables (i.e., real interest rate and money supply) have positive impact on economic growth in long-run and short-run except inflation rate. In addition, the results of VECM indicate bidirectional causal relationships between economic growth and monetary policy variables in long-run and short-run.
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Romyen, Arisara, Jianxu Liu, and Songsak Sriboonchitta. "Export–Output Growth Nexus Using Threshold VAR and VEC Models: Empirical Evidence from Thailand." Economies 7, no. 2 (June 18, 2019): 60. http://dx.doi.org/10.3390/economies7020060.
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This paper explores the relationship between export, import, and output for Thailand over the period from 1990 to 2017. The threshold vector autoregressive (VAR) and threshold vector error correction (VEC) models were applied. The empirical evidence confirms that the export-led growth hypothesis is valid, implying feedback within the export–output growth nexus. During business cycles, the export–output characteristics in economic cycles can be classified by the two-threshold VAR and VEC models. These relevant variables converge from the long-run equilibrium. As for the thresholds which are correlated, gross domestic product (GDP) vs. export and GDP vs. import exist as a long-run equilibrium relationship, while there does not seem to be a relationship of export vs. import. Furthermore, a five-year forecast was created (the period of 2018–2022). The export–output growth scenarios appear to swing upward continuously throughout the short-term trend. Therefore, policy-makers should highlight countercyclical macroeconomic policies at lower, medium, and upper regimes to strengthen the state of recovery and encourage the state of short recession.
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Surya, Henry Viriya, and Prastowo Cahjadi. "Komparasi Regresi Ekonometri pada Perekonomian Indonesia 2SLS, VEC, dan ARIMA." Jurnal Ekonomi dan Pembangunan Indonesia 2, no. 2 (January 1, 2002): 88–112. http://dx.doi.org/10.21002/jepi.v2i2.627.
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This paper compares three models of econometric analysis on economy, in this case the Indonesian economy. The regression models are the two stage least squares (2SLS) which has a strong support from the economic theory of aggregate expenditure, the Vector Error Correction (VEC) and Autoregressive Integrated Moving Average (ARIMA) which both comes from the time series analysis, that do not have to be economic time series. The study tries to find out which are most suitable in analyzing the time series of Indonesian economy. After all the estimation and comparison process, we finally agree that the use of those different methods must be sinchronized with the purpose of the user's study of the economic time series.
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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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Jiang, Heng, Xiao-Hua Jin, and Chunlu Liu. "The effects of the late 2000s global financial crisis on Australia’s construction demand." Construction Economics and Building 13, no. 3 (September 18, 2013): 65–79. http://dx.doi.org/10.5130/ajceb.v13i3.3602.
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An accurate measurement of the impacts of external shocks on construction demand will enable construction industry policymakers and developers to make allowances for future occurrences and advance the construction industry in a sustainable manner. This paper aims to measurethe dynamic effects of the late 2000s global financial crisis on the level of demand in the Australian construction industry. The vector error correction (VEC) model with intervention indicators is employed to estimate the external impact from the crisis on a macro-level construction economic indicator, namely construction demand. The methodology comprises six main stages to produce appropriate VEC models that describe the characteristics of the underlying process. Research findings suggestthat overall residential and non-residential construction demand were affected significantly by the recent crisis and seasonality. Non-residentialconstruction demand was disrupted more than residential construction demand at the crisis onset. The residential constructionindustry is more reactive and is able to recover faster following the crisis in comparison with the non-residential industry. The VEC model with intervention indicators developed in this study can be used as an experiment for an advanced econometric method. This can be used to analyse the effects of special eventsand factors not only on construction but also on other industries.
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Singh, Narinder Pal, and Sugandha Sharma. "Cointegration and Causality among Dollar, Oil, Gold and Sensex across Global Financial Crisis." Vision: The Journal of Business Perspective 22, no. 4 (December 2018): 365–76. http://dx.doi.org/10.1177/0972262918804336.
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Over the globe, the various financial markets are becoming integrated and the linkages among variables Gold prices, Crude Oil prices, US Dollar rate and Stock market (GODS) invite a special attention of various financial analysts and investors. For an import-dependent country like India, the interplay among these variables is vital. Thus in this study, we investigate the cointegration and causality relationship among gold, crude oil, us dollar and stock market (Sensex) across the global financial crisis of 2008. We use Johansen's cointegration technique, Vector Error Correction Model (VECM), Vector Auto Regression (VAR), VEC Granger Causality/Block Exogeneity Wald Test and Granger Causality, and Variance Decomposition to study cointegration and strength & direction of causality for three sub-periods. Johansen's cointegration test results indicate that there is long-run equilibrium relationship among the variables in the pre-crisis and the crisis periods but not in post-crisis period. VECM results report that none of four models of the variables show long-run causality in the pre-crisis period at 5% level of significance. During the crisis period, both crude oil and Sensex models show long run causality. However, in some cases short-run causality is indicated in results. Granger causality test results show that there is one-way causality from USD and Sensex to crude oil, and from gold and Sensex to USD. Thus, we conclude that the relationship among GODS is dynamic and has been affected by global financial crisis of 2008.
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Guillermo, Benavides-Perales, Tellez-Leon Isela Elizabeth, and Venegas-Martinez Francisco. "The impact of banking and external sectors on Mexican agriculture in the period 1995–2015." Agricultural Economics (Zemědělská ekonomika) 64, No. 1 (January 18, 2018): 36–49. http://dx.doi.org/10.17221/193/2016-agricecon.
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Mexican agricultural production has been characterised by a lack of dynamism in recent years and is losing ground in terms of GDP. This may reflect the lack of funding from commercial and development banks. This research aims at studying the dynamics of the agriculture sector through econometric analysis using Vector Autoregressive (VAR) and Vector Error Correction (VEC) models in order to examine the short- and long-run relationships among agricultural production, terms of trade (ratio of agricultural prices and general price level), agricultural exports and lending from commercial and development banks. The main empirical findings, contrary to what was expected, is that even though there was a precarious level of funding from the banking sector, credit from commercial banking was higher than that from development banking in the last decades. Further, relative prices were found to have a negative relationship with agricultural exports, showing the importance of the external sector in agriculture.
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Hapsari, Meilina Retno, Suci Astutik, and Loekito Adi Soehono. "Relationship of Macroeconomics Variables in Indonesia Using Vector Error Correction Model." Economics Development Analysis Journal 9, no. 4 (November 6, 2020): 374–90. http://dx.doi.org/10.15294/edaj.v9i4.38662.
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This study aims to analyze the relationship between macroeconomic variables in Indonesia, namely GDP with money supply, exchange rate of rupiah to US Dollar, exports, imports and interest rates. The background problem is to analyze the best method to influence government targets or policies on economic growth by studying the relationship of macroeconomic variables. Previous studies analyzing the relationship between macroeconomic variables in Indonesia have used multiple linear regression analysis. Using VECM analysis we can find out the short-term and long-term effects on the relationship between macroeconomic variables in Indonesia. The analysis used in this study is the Vector Error Correction Model with Maximum Likelihood estimation. Based on the result, the cointegration test found that there is a long-term relationship. Based on the VECM model (3), in the short term there is a relationship between macroeconomic variables and in the long run there is a long-term causality relationship in the GDP and export models. It is expected that the Government and the Central Bank will work together cooperatively in making policies to keep control of the money supply, exchange rate of rupiah to US Dollar and interest rates to enable to stimulate the economy.
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Shah, Syed Alamdar Ali, Raditya Sukmana, and Bayu Arie Fianto. "Stage-I Shariah compliant Macaulay’s duration model testing." Journal of Islamic Accounting and Business Research 12, no. 7 (August 18, 2021): 941–64. http://dx.doi.org/10.1108/jiabr-05-2020-0158.
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Purpose The purpose of this study is to develop, test and examine econometric methodology for Sharīʿah-compliant duration models of Islamic banks. Design/methodology/approach The research evaluates all existing duration models from Sharīʿah’s perspective and develops a four-stage framework for testing Sharīʿah-compliant duration models. The econometric methodology consists of multiple regression, Johansen co-integration, error correction model, vector error correction model (VECM) and threshold vector error models (TVECM). Findings Regressions analysis suggests that returns on earning assets and interbank offered rates are significant factors for calculating the duration of earning assets, whereas returns paid on return bearing liabilities and average interbank rates of deposits are significant factors for duration of return bearing liabilities. VECM suggests that short run duration converges into long run duration and TVECM suggests that management of assets and liabilities also plays a significant role that can bring about a change of about 15% in respective durations. Practical implications Sharīʿah-compliant duration models will improve risk and Sharīʿah efficiency, which will ultimately improve market capitalization and returns stability of Islamic banks in the long run. Originality/value Sharīʿah-compliant duration models testing provides insight into how various factors, namely, rates of return, benchmark rates and managerial skills of Islamic bank risk managers impact durations of assets and liabilities. It also explains the future course of action for Sharīʿah-compliant duration model testing.
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Prayaga, Chandra, Krishna Devulapalli, Lakshmi Prayaga, and Aaron Wade. "COVID-19 Sentiments and Impact on Stock Market Prices." International Journal of Data Analytics 2, no. 2 (July 2021): 40–58. http://dx.doi.org/10.4018/ijda.2021070103.
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This paper studies the impact of sentiments expressed by tweets from Twitter on the stock market associated with COVID-19 during the critical period from December 1, 2019 to May 31, 2020. The stock prices of 30 companies on the Dow Jones Index were collected for this period. Twitter tweets were also collected, using the search phrases “COVID-19” and “Corona Virus” for the same period, and their sentiment scores were calculated. The three time series, open and close stock values, and the corresponding sentiment scores from tweets were sorted by date and combined. Multivariate time series models based on vector error correction (VEC) models were applied to this data. Forecasts for these 30 companies were made for the time series open, for the 30 days of June 2020, following the data collection period. Stock market data for the month of June was for all the companies was compared with the forecast from the model. These were found to be in excellent agreement, implying that sentiment had a significant impact or was significantly impacted by the stock market prices.
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Sakthivel, P. "Interlinkages among Asian, European and the U.S Stock Markets: A Multivariate Cointegration Analysis." Journal of Economics and Behavioral Studies 4, no. 3 (March 15, 2012): 129–41. http://dx.doi.org/10.22610/jebs.v4i3.310.
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The present study attempts to investigate the dynamic interlinkages among the Asian, European and US stock markets. Daily closing prices of twelve stock indices relating to the period from 3rd January 1998 to 30th June 2010 and are used in the analysis. Both short and long run relationships are examined through Johansen-Juselius co integration and Vector Error Correction models (VECM) and Impulse Response Function (IRF). The results of the co integration test show strong co integration relationship across international stock prices indices. The results of the Vector Error Correction model reveal that the US and some of European and Asian Stock markets lead the Indian stock market. Finally, the evidence suggests that the impact of the US market on Indian stock returns is much higher than other way round.
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Josifidis, Kosta, Emilija Beker-Pucar, Sladjana Srdic, and Gabriela Ivan. "Inflation targeting in advanced vs. emerging economies before and after the crisis." Panoeconomicus 61, no. 1 (2014): 79–106. http://dx.doi.org/10.2298/pan1401079j.
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Emerging economies have specificities which distance them compared to advanced economies in practicing inflation targeting (IT) monetary regime. One of the main differences in performing IT in advanced compared to emerging economies is ?fear of floating? problem in emerging group. However, on the road from exchange rate (ER) as a nominal anchor to IT, differences between advanced and emerging economies concerning ?fear of floating? have been more or less narrowed. In this paper we are concentrated to selected aspects of ER pass-through to prices and output, as well as (in)direct monetary policy reactions to ER shocks, trying to find out is significant difference observable between advanced and emerging IT countries in pre-crisis period and (post)crisis period. The comparison is made on the basis of forecast error variance decompositions from estimated Vector Autoregression (VAR) / Vector Error Correction (VEC) models. ?Fear of floating? phenomenon should not be exclusively applied to emerging economies, especially in the crisis period burdened with external shocks. The role of ER in IT monetary framework is strengthened with higher internal vulnerability to ER shocks, despite the level of economic development. Advanced countries more use interest rate as an indirect way to withstand ER shocks, while emerging economies more use direct way via foreign exchange interventions to withstand the ER shocks.
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Shi, Ruyi, Di Wang, and Yueying Zhao. "The effect of international energy market shocks on coal price of China based on the fuzzy integrated vector auto regressive and error correction model." Journal of Intelligent & Fuzzy Systems 40, no. 4 (April 12, 2021): 8451–61. http://dx.doi.org/10.3233/jifs-189665.
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From the perspective of external market shocks, this paper proposed fuzzy integrated vector auto regression (FVAR) model that determines the long-term basis and short-term basis interactions of China’s coal price with international energy prices. The proposed FVAR preform coal price fluctuation based on long-term and short term span in six stages including unit root testing, Johansen cointegration test, vector auto regression (VAR) model construction, fuzzification of VAR model, vector error correction (VEC) model and an impulse response function(IRF). It is observed that there is a steady long-term stability and equilibrium bond between the China’s domestic coal price, international coal price and the international crude (unrefined) oil price. The international coal and international crude oil price have an opposite effect on China’s domestic coal price. In addition, the former has a stronger fuzzy price discovery function on China’s domestic coal market than the latter. In the short term, China’s domestic coal price is more complex to instability reactions and is affected by market expectations. The international energy market is more effective than domestic coal market, and there is a relatively stable price adjustment mechanism between the two, with the international coal price playing a leading role in the fuzzy guidance of China’s coal price. Therefore, in reference to international energy pricing models, the paper proposes a fuzzy pricing model for a coal futures index based on the coal futures trading price and supplemented by the premium and discount agreed to by both trading parties.
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Febriana Mk, Irma, Nurbetty Herlina Sitorus, and Rizka Malia. "Kondisi makroekonomi dan kinerja perbankan di Indonesia." Jurnal Paradigma Ekonomika 16, no. 1 (February 14, 2021): 11–28. http://dx.doi.org/10.22437/jpe.v16i1.12073.
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The purpose of this study was to see how the long-term and short-term relationship between banking performance and macroeconomic variables. The analysis method used is the vector error correction model (VECM) with the variables ROA, BOPO, LDR, industrial production index, CPI, and BI rate. The results of this study indicate that there is a significant positive relationship between ROA and industrial production index in the long run and a significant negative relationship between ROA and CPI in the long and short term. There is a significant negative relationship between BOPO and the industrial production index in the long and short term. LDR has a significant negative relationship with all macro variables in the long term whereas, in the short term, LDR has a significant negative relationship with the CPI. Keywords: Banking performance, Macroeconomic, Vector error correction models
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Assenmacher-Wesche, Katrin, and M. Hashem Pesaran. "Forecasting the Swiss economy using VECX models: An exercise in forecast combination across models and observation windows." National Institute Economic Review 203 (January 2008): 91–108. http://dx.doi.org/10.1177/0027950108089681.
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This paper uses vector error correction models of Switzerland for forecasting output, inflation and the short-term interest rate. It considers three different ways of dealing with forecast uncertainties. First, it investigates the effect on forecasting performance of averaging over forecasts from different models. Second, it considers averaging forecasts from different estimation windows. It is found that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, it examines whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of alternative weighting schemes on forecast accuracy is small in the present application.
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Singh, Narinder Pal, and Sugandha Sharma. "Phase-wise analysis of dynamic relationship among gold, crude oil, US dollar and stock market." Journal of Advances in Management Research 15, no. 4 (October 1, 2018): 480–99. http://dx.doi.org/10.1108/jamr-12-2017-0124.
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Purpose The purpose of this paper is to investigate the dynamic relationship among Gold, Crude oil, Indian Rupee-US Dollar and Stock market-Sensex (gold, oil, dollar and stock market (GODS)) in the pre-crisis, the crisis and the post-crisis periods in the Indian context. Design/methodology/approach The authors use Johansen’s cointegration technique, Vector Error Correction Model (VECM), Vector Auto Regression, VEC Granger Causality/Block Exogeneity Wald Test, and Granger Causality and Toda Yamamoto modified Granger causality to study long-run relationship and causality. Findings Johansen’s cointegration test results indicate that there is a long-run equilibrium relationship among the variables in the pre-crisis and the crisis periods but not in post-crisis period. VECM results report that none of four models of the variables show long-run causality in the pre-crisis period. During the crisis period, both crude oil and Sensex models show long-run causality. However, in some cases, results indicate short-run causality. The authors find one-way causality from USD and Sensex to crude oil, and from gold and Sensex to USD. Thus, the authors conclude that the relationship among GODS is dynamic across global financial crisis. Practical implications The research findings of this study are vital to the large group of stakeholders and participants of gold, crude oil, US dollar and stock market in emerging economies like India. The results are useful to importers, exporters, government, policy makers, corporate houses, retail investors, portfolio managers, commodity traders, treasury and fund managers, other commercial traders, etc. Originality/value This study is one of its kinds as it investigates the relationship among GODS in India in different sub-periods like before, during and after the global financial crisis of 2008. None of the studies compare phase-wise relationship among GODS in the Indian context. The study contributes to the economic theory and the body of knowledge. It highlights the need to revisit the economic theory to explain the interplay mechanism among GODS.
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Taltavull de La Paz, Paloma, and Michael White. "The sources of house price change: identifying liquidity shocks to the housing market." Journal of European Real Estate Research 9, no. 1 (May 3, 2016): 98–120. http://dx.doi.org/10.1108/jerer-11-2015-0041.
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Purpose The purpose of this paper is to examine the role of monetary liquidity in house price evolution through examining the Asset (housing) Inflation channel. It identifies the main channels of transmission affecting house prices from monetary supply channels to house price change, examining how the Asset Price channel transmits changes in M1 to housing prices in Spain and the UK. Design/methodology/approach The paper uses Vector Auto Regression (VAR) and Error Correction models to test the Asset Inflation channel in the UK and Spain from 1991 to 2013 in two steps. In the first step, the supply elasticity is estimated through the long-term relationship between house prices and stock supply. The second step estimates a Vector Error Correction (VEC) to explain house price dynamics conditioned on supply reactions. The latter is defined as a long-term inverse demand model where housing prices are controlled by fundamentals in each market. Models allow forecast testing using Choleski impulse responses methodology. Findings Several results are found. In the supply model, both countries show rapid convergence to equilibrium with a larger elasticity of supply in Spain than in the UK but with a short run effect of new supply on prices in the UK. Regarding the Asset Inflation Channel model, the paper finds evidence of the existence of a housing accelerator effect in Spain, but not in the UK where changes in liquidity fully impact house prices in one direction. Research limitations/implications Implications of findings are mainly to forecast the effects of Monetary Policy measures in different economies. Practical implications The model supports the evaluation of different impacts of monetary policy in territories. It shows that the same policy will have different impacts in different housing markets and therefore highlights the importance of examining each market separately to identify the appropriate policy interventions. Originality/value This is the first paper that estimates the impact of the Asset Inflation Channel on house prices that endogenises housing market conditions and compares effects and interrelationships in two different economies.
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Sahu, Tarak Nath, and Krishna Dayal Pandey. "Money Supply and Equity Price Movements During the Liberalized Period in India." Global Business Review 21, no. 1 (March 22, 2018): 108–23. http://dx.doi.org/10.1177/0972150918761084.
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This study attempts to contribute towards the prevalent understanding and the extant literatures on the effect of changes in money supply as an important monetary policy shock on the stock prices of India by using a time-varying parameter models with vector autoregressive specification during the period 1996 to 2016. The result of Johansen’s cointegration test suggests a significantly positive long-run co-movement between the growth of money supply and stock prices in India but the result of vector error correction model (VECM) does not exhibit any significant relationship in short run. Further, the error correction term of the VECM reveals a long-run unidirectional causality from money supply to stock prices. However, the Granger causality test confirms that the growth rate of money supply does not cause the stock market movement in India in short run. Finally, the variance decomposition analysis reveals that both the Indian stock markets are strongly exogenous in the sense that shocks to money supply explain only a small portion of the forecast variance error of the market indices. Again, the impulse response function analysis indicates that a positive shock in money supply has a small but persistently positive effect on stock prices in India.
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Mohd Thas Thaker, Hassanudin, Tan Siew Ee, and Sushant Vaidik. "Export-led Growth Hypothesis: Econometric Evidence from Malaysia." Journal of International Business and Economy 14, no. 2 (December 1, 2013): 94–112. http://dx.doi.org/10.51240/jibe.2013.2.5.
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The objective of this paper is to test the validity of the Export-led Growth Hypothesis (ELGH) in the Malaysian economy. Malaysia has always been considered to have attained its growth primarily through exports (Okposin, Bassey, Hamid, Halim, and Boon, 1999; Mun, 2008; Mahathir, 1990). In the past, several studies on this topic have been conducted but their analyses were limited to relationships using Bound-testing, Autoregressive –Distributed Lag (ARDL) and the Toda Yamamoto analysis. Empirical data and analysis in our paper cover a 21 – year span and quarterly time-series data (1991:Q1 – 2012:Q4) are used to test this ELG hypothesis. Also, many dynamic econometric measures including the Augmented Dickey Fuller (ADF) and Phillip – Perron (PP) unit root tests, Cointegration test as well as the Vector Error Correction model (VEC) for the long run have been applied. Based on these generic models, both real exports and capital stock (productivity) are found to have stimulated positive adjustments to economic growth in the long run whereas real exchange rate is found to have influenced economic growth negatively. Overall, our conclusion is that the ELG hypothesis seems applicable to Malaysia in the long run.
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Li, Yuanyuan, and Dietmar Bauer. "Modeling I(2) Processes Using Vector Autoregressions Where the Lag Length Increases with the Sample Size." Econometrics 8, no. 3 (September 17, 2020): 38. http://dx.doi.org/10.3390/econometrics8030038.
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In this paper the theory on the estimation of vector autoregressive (VAR) models for I(2) processes is extended to the case of long VAR approximation of more general processes. Hereby the order of the autoregression is allowed to tend to infinity at a certain rate depending on the sample size. We deal with unrestricted OLS estimators (in the model formulated in levels as well as in vector error correction form) as well as with two stage estimation (2SI2) in the vector error correction model (VECM) formulation. Our main results are analogous to the I(1) case: We show that the long VAR approximation leads to consistent estimates of the long and short run dynamics. Furthermore, tests on the autoregressive coefficients follow standard asymptotics. The pseudo likelihood ratio tests on the cointegrating ranks (using the Gaussian likelihood) used in the 2SI2 algorithm show under the null hypothesis the same distributions as in the case of data generating processes following finite order VARs. The same holds true for the asymptotic distribution of the long run dynamics both in the unrestricted VECM estimation and the reduced rank regression in the 2SI2 algorithm. Building on these results we show that if the data is generated by an invertible VARMA process, the VAR approximation can be used in order to derive a consistent initial estimator for subsequent pseudo likelihood optimization in the VARMA model.
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Bekiros, Stelios, and Christos Avdoulas. "Revisiting the Dynamic Linkages of Treasury Bond Yields for the BRICS: A Forecasting Analysis." Forecasting 2, no. 2 (May 16, 2020): 102–29. http://dx.doi.org/10.3390/forecast2020006.
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We examined the dynamic linkages among money market interest rates in the so-called “BRICS” countries (Brazil, Russia, India, China, and South Africa) by using weekly data of the overnight, one-, three-, and six- months, as well as of one year, Treasury bills rates covering the period from January 2005 to August 2019. A long-run relationship among interest rates was established by employing the Vector Error Correction modeling (VECM), which revealed the validation of the Expectation Hypothesis Theory (EH) of the term structure of interest rates, taking into account long-run deviations from equilibrium and inherent nonlinearities. We unveiled short-run dynamic adjustments for the term structure of the BRICS, subject to regime switches. We then used Markov Switching Vector Error Correction models (MS-VECM) to forecast them dynamically during an out-of-sample period of May 2016 through August 2019. The MSIH-VECM forecasts were found to be superior to the VECM approaches. The novelty of our paper is mainly due to the exploration of the possibility of parameter instability as a crucial factor, which might explain the rejection of the restricted version of the cointegration space, and on the dynamic out-of-sample forecasts of the term structure over a more recent time span in order to assess further the usefulness of our nonlinear MS-VECM characterization of the term structure, capturing the effects of the global and domestic financial crisis.
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Shafighi, Najla, Abu Hassan Shaari, Behrooz Gharleghi, Tamat Sarmidi, and Khairuddin Omar. "Financial integration via panel cointegration approaches in ASEAN+5." Journal of Economic Studies 43, no. 1 (January 11, 2016): 2–15. http://dx.doi.org/10.1108/jes-08-2014-0141.
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Purpose – The purpose of this paper is to identify whether any financial integration exists among ASEAN+5 members and some East Asian countries, including China, Japan, Korea, Hong Kong, and Taiwan, through interest rate, exchange rate, level of prices, and real output. Design/methodology/approach – Therefore, the authors intend to identify any long-term relationship among these variables utilizing the data in the most efficient manner via panel cointegration and panel unit root tests. The study likewise uses a panel-based vector error correction (panel-vec) model for comparison and also short-run relationship analysis. The long-run relationship is estimated using dynamic ordinary least square technique and a panel multi-layer perceptron (MLP) neural network. Findings – For the ten countries under consideration, the empirical result supports the long-run equilibrium relationship among real output, exchange rate, interest rate, and level of prices, and that the cointegration relationship implies unidirectional causality from exchange rate to real output. This result is favorable to a model that contains real output as a dependent variable and exchange rate, interest rate, and level of prices as explanatory variables. Panel-vec results indicate no evidence of short-run causality from exchange rate to real output. Furthermore, the comparison result of long-run equation estimation shows the superiority of neural networks over econometric models. Originality/value – This paper adds to the literature by examining the financial cointegration using a panel model that contains real exchange rate, interest rate, real output, and inflation rate in ASEAN+5. Additionally this paper applied the MLP neural network to yield a robust estimation of the long-run equation obtained among the variables.
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Kaur, Harleen, Mohammad Afshar Alam, Saleha Mariyam, Bhavya Alankar, Ritu Chauhan, Rana Muhammad Adnan, and Ozgur Kisi. "Predicting Water Availability in Water Bodies under the Influence of Precipitation and Water Management Actions Using VAR/VECM/LSTM." Climate 9, no. 9 (September 21, 2021): 144. http://dx.doi.org/10.3390/cli9090144.
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Recently, awareness about the significance of water management has risen as population growth and global warming increase, and economic activities and land use continue to stress our water resources. In addition, global water sustenance efforts are crippled by capital-intensive water treatments and water reclamation projects. In this paper, a study of water bodies to predict the amount of water in each water body using identifiable unique features and to assess the behavior of these features on others in the event of shock was undertaken. A comparative study, using a parametric model, was conducted among Vector Autoregression (VAR), the Vector Error Correction Model (VECM), and the Long Short-Term Memory (LSTM) model for determining the change in water level and water flow of water bodies. Besides, orthogonalized impulse responses (OIR) and forecast error variance decompositions (FEVD) explaining the evolution of water levels and flow rates, the study shows the significance of VAR/VECM models over LSTM. It was found that on some water bodies, the VAR model gave reliable results. In contrast, water bodies such as water springs gave mixed results of VAR/VECM.
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Nguyen, Duy Thuc, Luu Cuong Tran, Thi Ngoc Han Bui, Thi Thanh Thuy Ngo, and Thi Le Hang Nguyen. "The relationships between foreign direct investment, export and economic growth." Accounting 7, no. 6 (2021): 1371–78. http://dx.doi.org/10.5267/j.ac.2021.3.028.
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This study aims to examine the causal relationship between foreign direct investment, exports and economic growth in Dong Nai province, Vietnam from 1999 to 2019. The study uses several economic models such as Vector Auto Regression - VAR (p), Vector Error Correction Model (VECM) and Granger causality tests to evaluate relationships between research model variables. The results show that foreign direct investment and exports have the positive effects on Gross Regional Domestic Product (GRDP). Therefore, this study recommends some policy implementation to simulate the foreign direct investment. Particularly, the policy makers in Dong Nai province should be aware of the role of foreign direct investment and export incentive policies, which is an important driving force for the socio-economic development of Dong Nai province, Vietnam.
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BRAILSFORD, T. J., JACK PENM, and R. D. TERRELL. "TESTING PPP BY MEANS OF ZNZ PATTERNED VECM." International Journal of Theoretical and Applied Finance 11, no. 04 (June 2008): 345–62. http://dx.doi.org/10.1142/s021902490800483x.
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Vector error-correction models (VECM) are increasingly being used to capture dynamic relationships between financial variables. Estimation and interpretation of such models can be enhanced if zero restrictions are allowed in the coefficient matrices. Conventional use of full-order models may weaken the power of statistical inferences due to over-parameterization. The paper demonstrates the usefulness of this approach for the analysis of exchange rate relationships. Specifically, the paper examines the relationship between the money supply and the Euro and provides a test of purchasing power parity (PPP) in Japan. The latter test results shed light on the adjustment mechanisms through which PPP is achieved. In addition, it is clear that the proposed ZNZ patterned VECM modeling provides better insights from this kind of financial time-series analysis. The paper also shows that causality detection in an I(d) system can be revealed identically from the ZNZ patterned VECMs or the equivalent VAR models.
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Pereira, Marcos Vinicius Lopes, Leonardo Carneiro De Araújo, and Robert Aldo Iquiapaza. "Cointegração e previsibilidade de abordagens VECM para o Ibovespa." Brazilian Review of Finance 18, no. 2 (July 12, 2020): 82. http://dx.doi.org/10.12660/rbfin.v18n2.2020.79162.
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<p>The present research compares multivariate models applied to the IBovespa time series analysis. Macroeconomic variables, commodities and market indices are regressors suggested by the literature. The chosen approach uses a vector error correction model (VECM) alongside unit root and cointegration tests, robust under heteroskedasticity. The impact of national and international economic instability was controlled. To accomplish this, recessive cycles, in Brazil or in the United States, and the Brazilian electoral period were taken into account. In general, the evaluated models failed to meet the estimation’s assumptions, have low explanatory power and do not present significant relationship between IBOVESPA and dependent variables. However, evidence indicates that long-term relationships could exist, although this may not imply accuracy<br />in short-term predictions.</p>
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Zheng, Changjun, Probir Kumar Bhowmik, and Niluthpaul Sarker. "Industry-Specific and Macroeconomic Determinants of Non-Performing Loans: A Comparative Analysis of ARDL and VECM." Sustainability 12, no. 1 (December 31, 2019): 325. http://dx.doi.org/10.3390/su12010325.
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With the growth of an economy, the banking industry expands and the competitiveness becomes intense with the increased number of banks in the economy. The objective of this research was to discover the influence of industry-specific and macroeconomic determinants of non-performing loans (NPLs) in the entire banking system of Bangladesh. We performed an analysis for the period from 1979 to 2018 by an autoregressive distributed lag (ARDL) model and checked the robustness of the results in the vector error correction (VEC) model. The outcomes of this research suggest that both industry-specific and macroeconomic factors influence NPLs significantly. Among the industry-specific determinants, bank loan growth, net operating profit, and deposit rates negatively impact NPLs with statistical significance while bank liquidity and lending rates have a significant positive affiliation with NPLs. Gross domestic product (GDP) growth and unemployment, among the macroeconomic variables, have a negative connection with NPLs. Whereas, domestic credit and exchange rates have a significant positive association with NPLs. The contribution of this research is that the outcomes found by means of econometric models can be used for predicting and measuring NPLs in upcoming years, not only for Bangladesh but also for developing and emerging economies. Individual banks, as well as the banking sector, by and large, can get a guideline from this research.
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Loves, L., M. Usman, Warsono, Widiarti, and E. Russel. "Modeling Multivariate Time Series by Vector Error Correction Models (VECM) (Study: PT Kalbe Farma Tbk. and PT Kimia Farma (Persero) Tbk)." Journal of Physics: Conference Series 1751 (January 2021): 012013. http://dx.doi.org/10.1088/1742-6596/1751/1/012013.
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Soto, Paula Andrea, and Juan Carlos Ruilova Teran. "Arbitragem Estatística: Uma Abordagem por VECM." Brazilian Review of Finance 15, no. 4 (June 20, 2018): 537. http://dx.doi.org/10.12660/rbfin.v15n4.2017.65761.
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This work develops a statistical arbitrage model which was tested on the Brazilian stock market. Prices were modeled using VECM (Vector Error Correction Models) to create a self-financing, market-neutral, long/short trading strategy. In this strategy, deviations in the long-term equilibrium of prices are identified in order to create buy and sell signals. Portfolios with common trends were selected by means of Principal Component Analysis. The viability of this strategy was empirically addressed using simulations on these portfolios. Its performance was also compared to other long/short trading strategies and were all analyzed in terms of returns, volatility and statistical arbitrage opportunities. The methodology used in this paper shows good results for modeling prices, and though all trading strategies offer considerable gains for the investor, the proposed strategy stands out by presenting statistical arbitrage.
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Huy Hoang, Nguyen, Nguyen Van Phong, and Nguyen Trung Dong. "Examining the relationship between public spending and some socioeconomic indicators of Ho Chi Minh city using time series models." Science & Technology Development Journal - Economics - Law and Management 3, no. 1 (June 12, 2019): 68–84. http://dx.doi.org/10.32508/stdjelm.v3i1.542.
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This paper used multiple time series regression models namely VAR(p) — (Vector Autoregression ) and VECM (Vector Error Correction Model) to study the relationship between public spending and some socioeconomic indicators of Ho Chi Minh City (HCMC) such as — gross Domestic Product; FDI — Foreign Direct Investment..., the topic that has received a special interest of both economists and governmental authorities. With the main contents include introducing the economic geography of Ho Chi Minh City, we expect the empirical results to aim to find the relationship public spending and some socioeconomic indicators of Ho Chi Minh City. Through analyzing research methods and pointing out a suitable model, it helps managers adjust policies, so that public spending brings the highest efficiency to the economic leader of the country, Ho Chi Minh City. This model helps us consider the long-term relationship of variables (time series). The results of the model are read through Granger causality tests, Graph of impulse response function. The table decomposes variance and co-integration equations... They are so useful to show the effectiveness of applying econometric models in the analysis of economic and financial problems.
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Amizuar, Sabilil Hakimi, Anny Ratnawati, and Trias Andati. "The Integration of International Capital Market from Indonesian Investors’ Perspective: Do Integration Still Give Diversification Benefit." International Journal of Economics and Finance 9, no. 9 (August 23, 2017): 157. http://dx.doi.org/10.5539/ijef.v9n9p157.
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The objective of this study is to analyze whether, despite the international equity liberalization and growing world financial integration, Indonesian investors can be beneficial from international diversification. The study covers both emerging markets (Indonesia, Philippines, Malaysia, Thailand, Korea, China, and Taiwan) and developed markets (USA, UK, Japan, Singapore, and Australia) over the period of January 1st, 2007 to April 30st, 2017. It uses several state-of-the-art techniques: multivariate cointegration and vector error correction models (VECM) with the analysis of impulse response function (IRF) and forecast error variance decomposition (FEVD) to analyze the long-term level of integration and time-varying correlations with the Dynamic Conditional Correlation (DCC) aproach to analyze short term level of integration. The analysis provides the evidence of integration berween Indonesian market and international markets. The findings suggest that Indonesian investors have more chance to gain international diversification benefit from developed markets rather than emerging markets as the Indonesian market has low level of integration compared to developed markets.
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ALI, Mostafa. "Dynamic Relation Between Economic Growth, Stock Market Depth and Macroeconomic Variables of Bangladesh." Eurasian Journal of Business and Economics 13, no. 26 (November 30, 2020): 45–63. http://dx.doi.org/10.17015/ejbe.2020.026.03.
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This study explores the dynamic relation between economic growth and stock market depth in the presence of three more macroeconomic indicators such as exchange rate, inflation and interest rate of Bangladesh. We use Johansen and Juselius (1990) test of co-integration and Vector Error Correction Model (VECM) to detect the possible short-run and long-run causal relation among the selected economic forces. The results of the study evidence that the lagged error-correct term of GDP (i.e., the proxy of economic growth) is found statistically significant in all three models. This manifest that GDP tends to converge to its long-run equilibrium path in response to changes in its regressors. But we find a complex network of causal linkage between the variables in the short-run. The findings of this study are of particular interest and importance to policymakers, financial managers, financial analysts and investors dealing with the Bangladesh economy and the Bangladesh stock market.
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Su, Yong, Jacob Cherian, Muhammad Safdar Sial, Alina Badulescu, Phung Anh Thu, Daniel Badulescu, and Sarminah Samad. "Does Tourism Affect Economic Growth of China? A Panel Granger Causality Approach." Sustainability 13, no. 3 (January 28, 2021): 1349. http://dx.doi.org/10.3390/su13031349.
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The main purpose of the current study is to investigate if tourism affects economic growth of China. The data set has been acquired from the Beijing Municipal Bureau of Statistics, and the time span of the data set takes into account a 20-year time period, from 2000 to 2019. To determine the strength of the above-mentioned relationship previous models that have been used for this research are mainly VAR (vector auto-regression) and VECM (vector error correction) models. The VAR and VECM models have been conducted together with the Granger causality test. The internal revenue generated from tourism-related activities is taken as being the main indicator for the tourism industry, while economic growth is determined by GDP (gross domestic product). We support the above-mentioned notion, as we found that a strong relationship exists between the development of the tourism industry and economic growth. Moreover, our analysis also indicates that this industry has a major impact on long-term economic growth in the region as well. This study thus provides further support to the existing literature on the topic of tourism and the impact that tourism-related activities have upon economic development and growth. The existence and the impact of tourism-related activities upon long-term economic growth were confirmed by the results of the VAR models. At the same time, the unidirectional results of VECM models have confirmed the existence of economic growth in the short term. In our case, the cardinal relationship between the development of the tourism industry and the economic growth in the Beijing region of China have managed to provide strong empirical support to the earlier stated notions and to the literature alike.
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Putri, Selly Febriana. "HUBUNGAN PEMBANGUNAN EKONOMI TERHADAP KUALITAS LINGKUNGAN HIDUP DI PROVINSI JAWA TIMUR." JURNAL DINAMIKA EKONOMI PEMBANGUNAN 2, no. 2 (January 2, 2020): 58. http://dx.doi.org/10.14710/jdep.2.2.58-70.
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Penelitian ini bertujuan untuk mengetahui seberapa besar hubungan pembangunan ekonomi yang difokuskan pada sisi laju pertumbuhan Sektor Pertanian, Industri, dan Transportasi terhadap Kualitas Lingkungan Hidup di Provinsi Jawa Timur. Metode analisis yang digunakan dalam penelitian ini adalah analisis data panel dengan menggabungkan data cross section dan time series. Model yang digunakan dalam penelitian ini adalah Vector Error Correction Models (VECM) dan metode yang dipilih dalam penelitian ini adalah Granger Causality. Hasil penelitian dari metode analisis Granger Causality menunjukkan bahwa hubungan kausal antara laju pertumbuhan sektor Industri terhadap Indeks Kualitas Lingkungan Hidup sebesar 0.0470 signifikan dalam taraf 5%. Sektor Transportasi memiliki hubungan kausal sebesar 0.0000 terhadap Indeks Kualitas Lingkungan Hidup signifikan dalam taraf 5%. Sektor Pertanian memiliki hubungan kausal terhadap Indeks Kualitas Lingkungan Hidup signifikan dalam taraf 5%. Hipotesis Environmental Kuznet Curve terbukti di Jawa Timur berbentuk U-terbalik yang melandai.
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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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Rahman, Mohammed Mizanur, Munni Begum, Badar Nadeem Ashraf, and Md Abdul Kaium Masud. "Does Trade Openness Affect Bank Risk-Taking Behavior? Evidence from BRICS Countries." Economies 8, no. 3 (September 14, 2020): 75. http://dx.doi.org/10.3390/economies8030075.
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In this paper, we examine the impact of trade openness on bank risk-taking behavior employing a panel dataset of 899 banks from the BRICS (i.e., Brazil, Russia, India, China, and South Africa) countries over the period 2000–2017. We find that higher trade openness lowers bank risk-taking. Our results are robust when we use alternative proxies of trade openness and bank risk-taking, estimate country-wise regressions, or use alternative estimation methods such as system Generalized Methods of Moments (GMM), fixed effects, pooled Ordinary Least Square (OLS), and Vector Error Correction Model (VECM) models. We also observe higher trade openness decreases bank risk-taking in both the short and long run. Moreover, banks in more open countries perform relatively better during the crisis period further signifying the diversification benefits of openness. Together, our findings imply the beneficial impact of trade openness for financial sector stability.
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Dogan, Aydan, and Timo Bettendorf. "Revisiting real exchange rate volatility: non-traded goods and cointegrated TFP shocks." Oxford Economic Papers 72, no. 1 (April 9, 2019): 80–100. http://dx.doi.org/10.1093/oep/gpz029.
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Abstract International real business cycle (IRBC) models predict a real exchange rate volatility that is much lower than the levels observed in the data. In this paper, we build a two-country IRBC model with both a traded and a non-traded goods sector, and calibrate it to UK-euro area (EA) data. We provide evidence on the existence of a cointegrating relationship between UK and EA traded sector total factor productivity (TFP) by estimating a vector error correction model (VECM). To account for this relationship, we incorporate non-stationary technology shocks in the traded sectors in our model, and show that then the model is able to match the observed volatility of the UK–EA real exchange rate. Our analysis points out that both the presence of non-traded sectors and non-stationary technology shocks are necessary to account for the observed volatility in the real exchange rate.
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Latief, Rashid, Yusheng Kong, Sohail Ahmad Javeed, and Usman Sattar. "Carbon Emissions in the SAARC Countries with Causal Effects of FDI, Economic Growth and Other Economic Factors: Evidence from Dynamic Simultaneous Equation Models." International Journal of Environmental Research and Public Health 18, no. 9 (April 27, 2021): 4605. http://dx.doi.org/10.3390/ijerph18094605.
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South Asian Association for Regional Cooperation (SAARC) countries like other developing countries are the major destination for foreign investors. At the same time, these countries are facing different climate change challenges. This study aims to inspect the economic determinants of carbon emissions (CE) and dynamic causal interaction of CE with foreign direct investment (FDI), economic growth (EG), and other economic factors using panel cointegration test, dynamic ordinary least squares (DOLS) and vector error correction model (VECM) for the SAARC countries. To make the homogenous analysis, we examined the association among variables for the individual country and as a group for the period 1990 to 2016. The panel results of this study confirmed the presence of the unidirectional causal association of EG with CE. The panel results of other economic factors confirmed the causality of urban population (UP) and energy consumption (EC) with CE. Moreover, the panel results of domestic capital (DS) and inflation rate (INF) confirmed the causal association with EG. Finally, the panel results of DS revealed a causality with FDI. Based on the above results, some policy guidelines are proposed.
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Makhoba,, Bongumusa Prince, and Irrshad Kaseeram. "The Contribution of Foreign Direct Investment (FDI) To Domestic Employment Levels in South Africa: A Vector Autoregressive Approach." Journal of Economics and Behavioral Studies 11, no. 1(J) (March 10, 2019): 110–21. http://dx.doi.org/10.22610/jebs.v11i1(j).2752.
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Several empirical works have yielded mixed and controversial results with regard to the effects of FDI on employment and economic growth. The primary focus of this study is to investigate the contribution of FDI to domestic employment levels in the context of the South African economy. The analyses of the study were carried out using the annual time series data from 1980 to 2015. The macroeconomic variables employed in the empirical investigation include employment, FDI, GDP, inflation, trade openness and unit labour costs. The study used secondary data from the South African Reserve Bank and Statistics South Africa database. The study estimated a Vector Autoregressive/ Vector Error Correction Mechanism (VAR/VECM) approach to conduct empirical analysis. However, the study also employed single equation estimation techniques, including the Ordinary Least Squares (OLS), Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS) and Canonical Cointegrating Regression (CCR) models as supporting tools to verify the VAR/VECM results. This study provides strong evidence of a significant negative relationship between FDI and employment levels in the South African economy. Empirical analysis of the study suggests that the effect of economic growth on employment is highly positive and significant in South Africa’s economy. The study recommends that policymakers ought to invest more in productive sectors that aim to promote economic growth and development to boost employment opportunities in South Africa.
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Tsuji, Chikashi. "Dynamic Relations of Consumer Prices: A Case Study of Recent Effects on the Japanese Headline CPI." Journal of Social Science Studies 3, no. 2 (February 7, 2016): 28. http://dx.doi.org/10.5296/jsss.v3i2.8991.
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<p>This study attempts to empirically examine the relations between the headline consumer price index (CPI) and several other CPIs in Japan by applying the vector error correction models (VECMs). Our investigations derive the following interesting findings. First, we reveal that as to our four combinations of the CPIs tested in this paper, 1) all variable coefficients in the cointegrating equations are statistically significant in our VECM models and the statistical significance is very strong. Thus, we understand that our four bivariate combinations of the CPIs tested in this paper are all strongly cointegrated and the VECM approach is very effective to capture the time-series effects of the categorized CPIs on the Japanese headline CPI. Further, we also find that 2) as far as judging by the results of our impulse response analyses, for the period from May 2011 to June 2015, the headline CPI for Japan is weakly or little affected by the CPI of energy and the CPI of food for Japan. We further clarify that 3) according to the results of our impulse response analyses, the Japanese headline CPI is positively affected by both the CPI of utilities for Japan and the CPI of transportation and communication expenses for Japan.</p>
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Akinkunmi, Mustapha A. "Dynamic Analysis of Structural Shifts of Fiscal Revenue in Nigeria, 1999-2016." International Journal of Economics and Finance 8, no. 11 (October 26, 2016): 96. http://dx.doi.org/10.5539/ijef.v8n11p96.
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The oil sector that eased the financial constraint of Nigerian government in the 1970s is presently acting as the source of financial constraints to the country due to a continuous decline in government revenue, arising from the recent drastic fall in world crude oil prices. This calls for the government to diversify its revenue base through improving taxation. This study examined the influence of economic performance on the government revenue as well as the various sources of tax revenues in Nigeria. Monthly data spanning 1999 to 2016 were utilized to estimate vector error correction models (VECM) for five sources of government tax revenues based on data availability. Empirical results revealed that there is a significant relationship between real GDP and real company income tax revenues, and between real GDP and real excise duty revenues in the long run. However, in the short run, the one-year lag of tax revenue varieties poses a significant influence on the various sources of tax revenues.
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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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Shanthi, A., and R. Thamilselvan. "Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India." Restaurant Business 118, no. 3 (March 11, 2019): 137–52. http://dx.doi.org/10.26643/rb.v118i3.7637.
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The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets
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Marcal, Emerson F., and Pedro L. Valls Pereira. "Evaluating the existence of structural change in the Brazilian term structure of interest rate: evidence based on Hansens cointegration models with structural break." São Paulo Journal of Mathematical Sciences 8, no. 2 (December 12, 2014): 211. http://dx.doi.org/10.11606/issn.2316-9028.v8i2p211-239.
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This paper investigates whether there is evidence of struc- tural change in the Brazilian term structure of interest rates. Multivari- ate cointegration techniques are used to verify this evidence. An econo- metric model is estimated which is a Vector Autoregressive Model with Error Correction Mechanism (VECM) with abrupt structural change formulated by Hansen [13]. Two datasets were analysed. The rst one contains a nominal interest rate with maturity up to three years. The second data set focuses on maturity up to one year. The rst data set focuses on a sample period from 1995 to 2010 and the second from 1998 to 2010. The frequency is monthly. The estimated models suggest the existence of structural change in the Brazilian term structure. It was possible to document the existence of multiple regimes using the tech- nique for both databases. The risk premium for dierent spreads varied considerably during the earliest period of both samples and seemed to converge to stable and lower values at the end of the sample period. Long-term risk premiums seemed to converge to international stand- ards, although the Brazilian term structure is still subject to liquidity problems for longer maturities.
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Kharbanda, Varuna, and Archana Singh. "Hedging and effectiveness of Indian currency futures market." Journal of Asia Business Studies 14, no. 5 (February 14, 2020): 581–97. http://dx.doi.org/10.1108/jabs-10-2018-0279.
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Purpose The purpose of this paper is to measure the effectiveness of the hedging with futures currency contracts. Measuring the effectiveness of hedging has become mandatory for Indian companies as the new Indian accounting standards, Ind-AS, specify that the effectiveness of hedges taken by the companies should be evaluated using quantitative methods but leaves it to the company to choose a method of evaluation. Design/methodology/approach The paper compares three models for evaluating the effectiveness of hedge – ordinary least square (OLS), vector error correction model (VECM) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH) model. The OLS and VECM are the static models, whereas DCC-MGARCH is a dynamic model. Findings The overall results of the study show that dynamic model (DCC-MGARCH) is a better model for calculating the hedge effectiveness as it outperforms OLS and VECM models. Practical implications The new Indian accounting standards (Ind-AS) mandates the calculation of hedge effectiveness. The results of this study are useful for the treasurers in identifying appropriate method for evaluation of hedge effectiveness. Similarly, policymakers and auditors are benefitted as the study provides clarity on different methods of evaluation of hedging effectiveness. Originality/value Many previous studies have evaluated the efficiency of the Indian currency futures market, but with rising importance of hedging in the Indian companies, Reserve Bank of India’s initiatives and encouragement for the use of futures for hedging the currency risk and now the mandatory accounting requirement for measuring hedging effectiveness, it has become more relevant to evaluate the effectiveness of hedge. To the authors’ best knowledge, this is one of the first few papers which evaluate the effectiveness of the currency future hedging.
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Sung, Joo-han. "A Study on the Apartment Sale Price Decision Model Using Vector Error Correction Model (VECM): Focusing on the Housing Market in Changwon City." Housing Finance Research 5, no. 1 (June 2021): 27–49. http://dx.doi.org/10.52344/hfr.2021.5.1.27.
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Ma, Yanli, Jieyu Zhu, Gaofeng Gu, and Ke Chen. "Freight Transportation and Economic Growth for Zones: Sustainability and Development Strategy in China." Sustainability 12, no. 24 (December 14, 2020): 10450. http://dx.doi.org/10.3390/su122410450.
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The causal relationship between zonal freight turnover and gross domestic product (GDP) are receiving increasing attention to coordinate the balanced development of freight transportation and zonal economic level effectively. However, studies on the causality direction between freight transportation and economic have so far been in debate. To understand the relationship of causality direction between transportation and economic development for different zones which can provide decision support for public policies, econometrics is used to analyze the relationship between them. This paper investigates the relationship between GDP and freight turnover for economic zones of stationary series and non-stationary sequences using the vector autoregressive (VAR) and the vector error correction models (VECM). The impulse response analysis and variance decomposition are conducted to verify the effectiveness of the models. The Granger causality test is exploited to discover the relationship between transportation and economic development in each economic zone. The data on freight transportation and GDP in China from 2003 to 2018 is used. Results show that the relationship between freight turnover and GDP in the Northeast economic zone is bidirectional. A unidirectional relationship exists between freight turnover and GDP in the Circum Bohai-Sea, the Pearl River, Middle Part, Southwest, and Northwest zone. And the Granger causality is not obvious in the Yangtze River economic zone. In addition, suggestions for the zonal development of transportation and economic systems are provided. This study can provide a basis to adopt relevant policies and measures of sustainable development between transportation and economic growth for different zones.
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Singh, Amanjot, and Manjit Singh. "A revisit to how linkages fuel dependent economic policy initiatives." International Journal of Law and Management 59, no. 6 (November 13, 2017): 1068–108. http://dx.doi.org/10.1108/ijlma-08-2016-0074.
Full textAbstract:
Purpose The authors aim to report empirical linkages between the US and Brazil, Russia, India and China (BRIC) financial stress indices catalyzing catalyzing dependent economic policy initiatives (an extended version of Singh and Singh, 2017a). Design/methodology/approach Initially, the study develops financial stress indices for the respective BRIC financial markets. Later, it captures linkages among the said US-BRIC indices by using Johansen cointegration, vector autoregression/vector error correction models (VECM), generalized impulse response functions, Toda–Yamamoto Granger causality, variance decomposition analyses and bivariate generalized autoregressive conditional heteroskedasticity (GARCH) model under constant conditional correlation framework, in general. Markov regime switching and efficient causality tests proposed by Hill (2007) are also used. Findings Overall, there are both short-run and long-run dynamic interactions observed between the US and Indian financial stress indices. For rest of the markets, only short-run interactions are found to be in existence. The time-varying co-movement coefficients report financial contagion impact of the US financial crisis on Russian and Indian financial systems only. Contrary to this, Brazilian and Chinese financial systems are largely exhibiting interdependence with the US financial system. Efficient causality tests report indirect impact of the Russian financial system on Brazilian via auxiliary Indian financial system. Originality/value The present study is the first of its kind capturing linkages among the US-BRIC financial stress indices by using diverse econometric models. The results support different market participants and policymakers in understanding effectiveness and implementation of economic policies while considering their cross-market interactions as well.