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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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Darrat, Ali F., M. Zhong, R. M. Shelor, and R. N. Dickens. "FORECASTING CORPORATE PERFORMANCE: VECM COMPARISON WITH OTHER TIME SERIES MODELS." Studies in Economics and Finance 19, no. 1/2 (January 1998): 49–61. http://dx.doi.org/10.1108/eb028752.
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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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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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Mugableh, Mohamed Ibrahim, and Mohammad Salem Oudat. "Economic Growth and Financial Development nexus in Malaysia: Dynamic Simultaneous Equations Models." Asian Journal of Finance & Accounting 10, no. 1 (April 15, 2018): 143. http://dx.doi.org/10.5296/ajfa.v10i1.12736.
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This paper estimates the equilibrium and causality relationships among gross domestic product, energy consumption, financial development, foreign direct investment inflows, and gross fixed capital formation. Different econometrics tests like descriptive statistics, ARCH, KPSS unit root, Johansen and Juselius’s co-integration, VECM Granger causality, and ARDL equilibrium relationships have been employed in Malaysia over the (1971−2013) period. The correlation matrix results indicate a linear association among variables. The null hypotheses of Heteroscedasticity and non-stationary have been rejected implying the appropriate use of VECM and ARDL approach. The VECM Granger causality findings show a long-run bidirectional among the variables. The ARDL approach results demonstrate that energy consumption, financial development, foreign direct investment inflows, and gross fixed capital formation augment gross domestic product in long-run. However, the findings of this paper add essential implications to policy makers and scholars in fields of economic, energy, and finance.
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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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Ajayi, Olaoluwa Vincent. "COMPARING MULTIVARIATE MODELS’ FORECASTS OF INFLATION FOR BRICS AND OPEC COUNTRIES." Business, Management and Education 17, no. 2 (November 8, 2019): 152–72. http://dx.doi.org/10.3846/bme.2019.10556.
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Purpose – This study identifies the most appropriately selected multivariate model for forecasting inflation in different economic environments. In specifying the multivariate models, the study test for the orders of integration of variables and for those that are nonstationary. For non-stationary variables, this study examines whether they are cointegrated. Engle and Granger (1987) establish that a cointegrating equation can be represented as an error correction model that incorporates both changes and levels of variables such that all of the elements are stationary. However, VARs estimated with cointegrated data will be misspecified if all of the data are differenced because long-run information will be omitted, and will have omitted stationarity inducing constraints if all the data are used in levels. Further, including variables in both levels and differences should sat-isfy stationarity requirements. However, they will omit cointegrating restrictions that may improve the model. Of course, these constraints will be satisfied asymptotically; but efficiency gains and improved multi-step forecasts may be achieved by imposing the constraints (Engle and Granger 1987, p. 259). Therefore, this study test for order of integration and compare inflation forecasting performance of different multivariate models for BRICS and OPEC countries. Research methodology – The following approaches were considered; the first approach is to construct a VAR model in differences (stationary form) to forecast inflation. The second approach is to construct a VECM without imposing cointegrating restrictions. The third approach is to construct a VEC that imposes cointegrating restrictions on the VECM. This will help to understand whether imposing cointegrating restrictions via a VEC improves long-run forecasts. Research limitation – The proposed multivariate models focused on differencing and cointegrating restrictions to ensure the stationarity of the data, the available variables were combined and specified based on their level of integration to forecast inflation. For instance, a VAR model is estimated based on differenced variables I(0); the same holds true for VECM and VEC models, where differenced variables and linear combinations of I(I) covariates are stationary. In future, multivariate models guided by economic theory rather than the order of integration of variables are suggested. Findings – The result shows that the forecast performance of inflation depends on the nature of the economy and whether the country experiencing higher inflation or low inflation. For instance, the model that includes long-run information in the form of a specified cointegrated equation generally improves the inflation forecasting performance for BRICS countries and one OPEC country (Saudi Arabia) that has a history of low inflation. Practical implications – This research will improve the policy makers decision on how to select appropriate model to forecast inflation over different economic environment. Originality/Value – These methods have not been used to forecast inflation for many emerging economies such as OPEC and BRICS countries despite the importance of many of these countries to the global economy. This study fills this gap by evaluating the forecasting performance of inflation using multivariate VAR and cointegrating models for OPEC and BRICS economies.
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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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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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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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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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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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Paulina, Paulina. "DAMPAK JANGKA PANJANG PERTUMBUHAN PENDUDUK TERHADAP INVESTASI AGREGAT PROVINSI DI INDONESIA." Jurnal Riset Manajemen dan Bisnis (JRMB) Fakultas Ekonomi UNIAT 4, no. 1 (February 28, 2019): 193–204. http://dx.doi.org/10.36226/jrmb.v4i1.258.
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This study aims to determine the causality relationship between population growth of a country / region (PG) which has an impact on the formation of investment (TINV) and economic growth (EG). This research was focused on 33 provinces in Indonesia on these 3 main variables. The data used are secondary data from 33 provinces, with observations between 2015-2017. The analysis models used are unit root and cointegration tests, VAR estimation and long-term VECM models, and panel data. The results of this study indicate: (1) there is no causal relationship between PG, TINV, and EG; (2) The cointegration test and the VAR model shows that there is a long-term relationship between endogenous and exogenous variables; (3) In the VECM model, there appears to be an influence between PG, EG on investment in the long run; (4) there are quite good investment provinces namely DKI Jakarta, and most of the eastern provinces of Indonesia experience positive investment rates.
Keywords: population growth, formation of investmen, economic growth
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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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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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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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Sutthichaimethee, Pruethsan, and Danupon Ariyasajjakorn. "Relationships between Causal Factors Affecting Future Carbon Dioxide Output from Thailand’s Transportation Sector under the Government’s Sustainability Policy: Expanding the SEM-VECM Model." Resources 7, no. 4 (December 3, 2018): 81. http://dx.doi.org/10.3390/resources7040081.
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This research aims to analyze the relationships between causal factors likely to affect future CO2 emissions from the Thai transportation sector by developing the Structural Equation Modeling-Vector Autoregressive Error Correction Mechanism Model (SEM-VECM Model). This model was created to fill information gaps of older models. In addition, the model provides the unique feature of viable model application for different sectors in various contexts. The model revealed all exogenous variables that have direct and indirect influences over changes in CO2 emissions. The variables show a direct effect at a confidence interval of 99%, including per capita GDP (), labor growth (), urbanization rate factor (), industrial structure (), energy consumption (), foreign direct investment (), oil price (), and net exports (). In addition, it was found that every variable in the SEM-VECM model has an indirect effect on changes in CO2 emissions at a confidence interval of 99%. The SEM-VECM model has the ability to adjust to the equilibrium equivalent to 39%. However, it also helps to identify the degree of direct effect that each causal factor has on the others. Specifically, labor growth () had a direct effect on per capita GDP () and energy consumption () at a confidence interval of 99%, while urbanization rate () had a direct effect on per capita GDP (), labor growth (), and net exports () at a confidence interval of 99%. Furthermore, industrial structure () had a direct effect on per capita GDP () at a confidence interval of 99%, whereas energy consumption () had a direct effect on per capita GDP () at a confidence interval of 99%. Foreign direct investment () had a direct effect on per capita GDP () at a confidence interval of 99%, while oil price () had a direct effect on industrial structure (), energy consumption (), and net exports () at a confidence interval of 99%. Lastly, net exports () had a direct effect on per capita GDP () at a confidence interval of 99%. The model eliminates the problem of heteroskedasticity, multicollinearity, and autocorrelation. In addition, it was found that the model is white noise. When the SEM-VECM Model was used for 30-year forecasting (2018–2047), it projected that CO2 emissions would increase steadily by 67.04% (2047/2018) or 123.90 Mt CO2 Eq. by 2047. The performance of the SEM-VECM Model was assessed and produced a mean absolute percentage error (MAPE) of 1.21% and root mean square error (RMSE) of 1.02%. When comparing the performance value with the values of other, older models, the SEM-VECM Model was found to be more effective and useful for future research and policy planning for Thailand’s sustainability goals.
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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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Lee, Yang-Kee, and Sung-Woo Ryoo. "Analyzing the Impact of Foreign Direct Investment on Renewable Energy Production and Carbon Emissions by Using Panel VECM and VAR Models." Korea International Trade Research Institute 16, no. 6 (December 31, 2020): 13–28. http://dx.doi.org/10.16980/jitc.16.6.202012.13.
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Koondhar, Mansoor Ahmed, Noshaba Aziz, Zhixiong Tan, Shaoxiong Yang, Kashif Raza Abbasi, and Rong Kong. "Green growth of cereal food production under the constraints of agricultural carbon emissions: A new insights from ARDL and VECM models." Sustainable Energy Technologies and Assessments 47 (October 2021): 101452. http://dx.doi.org/10.1016/j.seta.2021.101452.
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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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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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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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Zhang, Qi, Peng Di, and Arash Farnoosh. "Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models." Energy 223 (May 2021): 120050. http://dx.doi.org/10.1016/j.energy.2021.120050.
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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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Purbayati, Radia. "EVALUASI PRAKTEK PERBANKAN SYARIAH DI INDONESIA : INTEREST RATE FREE?" Ekspansi: Jurnal Ekonomi, Keuangan, Perbankan dan Akuntansi 11, no. 2 (November 30, 2019): 231–50. http://dx.doi.org/10.35313/ekspansi.v11i2.1575.
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The aim of this study is to evaluate Islamic Banking practice truly interest rate free on determining funding and financing pricing. The object of this study are Islamic and Conventional Banking in Indonesia 2014-2018. Variables used in the study consists of equivalent rate (interest rate) of demand deposit, saving deposit, time deposit, working capital financing (loan) and financing (loan) in Islamic and Conventional Banking. VAR / VECM Modelling and Granger Causality Test applied on these 5 Models.
The evidence shows that at that time there are only Model 2 and Model 5 were Granger Cause at one way in the short run. On the other hand, pricing on funding and financing product at islamic banking were determined by its time lag of pricing on funding and financing products at islamic and conventional banking , vice and versa. The shocks at the short run will be adjusted as its shocks response into long run equilibrium. It means the practicing Islamic banking in Indonesia is not truly interest rate free.
Keywords : Pricing on funding and financing products, Islamic Banking, Conventional Banking, VAR/VECM Modelling, Granger Causality.
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Adelakun, Ojo Johnson, Babatunde Afolabi, and Uwasejike B. Abuh. "Macroeconomic variables and banking sector development: Evidence from Nigeria." Technium Social Sciences Journal 8 (June 2, 2020): 288–301. http://dx.doi.org/10.47577/tssj.v8i1.772.
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The study assessed the relationship between Macroeconomic Variables and Development in the Nigerian Banking Sector using annual time series data. Models were specified using Ratio of Credits to Private Sector to Gross Domestic Product (GDP) as a proxy for Banking Sector Development. At the same time, GDP growth rate, Poverty, Exchange Rate, Oil Price, Poverty, Money Supply, Inflation, and Interest rates were the selected Macroeconomic Variables used in the study. Data used were sourced from the Statistical Bulletin of Central Bank of Nigeria (CBN) for various editions and estimated using ARDL Bound Test and Vector Error Correction Mechanism (VECM). The study found that there exists a long-run relationship between Macroeconomic Variables selected and Banking Sector Development. The VECM coefficients revealed that all variables except Interest Rates have negative effects on Banking Sector Development. The VECM (-1), which showed the speed of adjustment, was rightly signed and significant, indicating a long-run causality relationship running from macroeconomic variables to banking sector development. The Impulse response from restricted VAR revealed that Banking Sector responded to the Macroeconomic Variables of which GDPGR and INT were transmitting negatively to Banking Sector Development while others were transmitting positive impulses. However, the variance decomposition found that oil price, followed by GDPGR and poverty, caused more variation in Banking Sector Development. In contrast, inflation and money supply caused the least variation in Banking Sector Development. The study, therefore, concluded that selected Macroeconomic Variables have a significant long-run relationship with Banking Sector Development. It is therefore recommended, among others that, Macroeconomic indicators should be well monitored and controlled using macroeconomic instruments promptly since when they are well managed would lead to a better developed Banking Sector in Nigeria.
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Singh, Gurmeet. "Estimating Optimal Hedge Ratio and Hedging Effectiveness in the NSE Index Futures." Jindal Journal of Business Research 6, no. 2 (September 4, 2017): 108–31. http://dx.doi.org/10.1177/2278682117715358.
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This study attempts to study and suggest an optimal hedge ratio to Indian investors and traders by examining the three main indices of National Stock Exchange of India (NSE), namely, NIFTY, Bank NIFTY, and IT NIFTY, over the sample period from January 2011 to December 2015. The present study estimated the hedge ratio through six econometric models, namely, OLS, GARCH, EGARCH, TARCH, VAR, and VECM, in the minimum variance hedge ratio framework as suggested by Ederington (1979). The findings of the present study confirm the theoretical properties of Indian cash and futures market and suggest that the optimal hedge ratio estimated through EGARCH model was lowest for the NIFTY and Bank NIFTY, and that for IT NIFTY, the OLS model shows the lowest optimal hedge ratio as compared to that estimated through other models.
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Mahpudin, Endang, Disman, Nugraha, and Mayasari. "Effect of Macroeconomic Factors on Stock Prices in Indonesia." Restaurant Business 118, no. 5 (May 7, 2019): 57–61. http://dx.doi.org/10.26643/rb.v118i5.7229.
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This study aims to examine the fundamental factors that influence stock prices in Indonesia. This is academically important to test theories that have been found previously. This study uses a quantitative approach. The data of this study focus on inflation factors, exchange rates, interest rates and the money supply in Indonesia from 2004-2018, this study uses the VAR and VECM models in testing data that has been found. The results showed that from the four macroeconomic factors tested, there were no significant factors influencing stock prices in Indonesia, these findings confirmed that in emerging-market countries, there were no influential macroeconomic factors.
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Byung-Jin Yim. "An Empirical Study on the Hedge of Dubai Oil Price Risk Management by using VECM, Bivariate ECT－GARCH(1,1) and OLS Regression Models." Global Business Administration Review 9, no. 4 (December 2012): 257–70. http://dx.doi.org/10.17092/jibr.2012.9.4.257.
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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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Fonseca, Nelson Ferreira, Wagner Moura Lamounier, and Aureliano Angel Bressan. "Retornos Anormais no Ibovespa Utilizando Modelos para Dados de Alta Frequência." Brazilian Review of Finance 10, no. 2 (June 26, 2012): 243. http://dx.doi.org/10.12660/rbfin.v10n2.2012.3654.
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This article aims to identify profitable trading strategies based on the effects of leads and lags between the spot and futures equity markets in Brazil, using high frequency data. To achieve this objective and based on historical data of the Bovespa and the Bovespa Future indexes, four forecasting models have been built: ARIMA, ARFIMA, VAR, and VECM. The trading strategies tested were: net trading strategy, buy and hold strategy, and filter strategy – better than average predicted return. The period of analysis of this paper extends from August 1, 2006 to October 16, 2009. In this work, it was possible to obtain abnormal returns using trading strategies with the VAR model on the effects of leads and lags between the Bovespa index and Bovespa Future index.
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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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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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Botey Fullat, María, Pedro Arias Martín, and Silverio Alarcón. "CO2 emission allowances and their interacion with economic and energy factors in the European Union." Revista de la Facultad de Ciencias Agrarias UNCuyo 53, no. 1 (July 7, 2021): 182–95. http://dx.doi.org/10.48162/rev.39.018.
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Analysis of emission allowances prices has important environmental and political connotations. This article aimed to identifying the possible variables that may influence their behaviour and studied their relationship with fundamental factors: energy (Brent petroleum, Gas, Coal) and economy (Industrial Production Index, Baltic Dry Index, Purchasing Managers Index). With the objective of analyzing possible mutual interactions, Multivariate VAR or Error Correction Models (VECM), were applied. The information analysed derived from different sources (World Bank, Sendeco2 and various financial websites). The results obtained showed, not only the influence of past prices on the emission allowances actual price, but also the interaction with energetic and economic variables.
Highlights
Estimation of time series interrelations through VAR models.
There is relationship of the emission allowances price with their past values.
The energy variables are factors important to also explain the behavior of the emission allowances price.
The economic variables are hardly significant except for the Dry Baltic Index.
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Nasir, Muhammad. "HINTERLAND MEDAN CITY BETWEEN BINJAI CITY: A GRAVITATION APPROACH." Jurnal Ekonomi Pembangunan 17, no. 1 (July 30, 2019): 1. http://dx.doi.org/10.22219/jep.v17i1.9119.
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Regional economy explains that there is an urban hierarchical relationship, cities that have higher hierarchy will serve cities that are below it as well as cities that are in the hierarchy undersupplying cities that are in the hierarchy above them, so there is a gravitational relationship between the two. This study aims to determine the gravitational relationship of Medan city to the hinterland of the city of Binjai. Furthermore, this study also wants to explain its influence on economic growth in both cities. This analysis tools used are descriptive statistics, gravity models, unit root test, co-integration test, optimal lag, VECM, Granger causality test, impulse response function, and variance decomposition. The results showed that the city of Medan has a gravity style greater than the gravitational style of the city of Binjai. The VECM estimation results show that the gravitational variable in the city of Binjai in lag -1 and lag-2 has a positive and significant effect on the economy of Medan city. Then the economic variable of the city of Binjai itself in lag-1, the population of the city of Medan in lag-2 and the gravity of the city of Medan in lag-2 had a positive and significant effect on the economy of Binjai city. While the variable population of Binjai city in lag -1 and residents of the city of Medan in lag -1 negatively affected the economy of Binjai city.
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Yang, Yang, Mingquan Zhou, and Michael Rehm. "Housing prices and expectations: a study of Auckland." International Journal of Housing Markets and Analysis 13, no. 4 (January 27, 2020): 601–16. http://dx.doi.org/10.1108/ijhma-12-2019-0122.
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Purpose The purpose of this paper is twofold. First, the study aims to test whether expectations are adaptive in the Auckland housing market. The second purpose is to examine the interplay between expectations and Auckland housing prices. Design/methodology/approach In this study, two vector error correction models (VECM) are built: one VECM includes survey-based expectations and another one encompasses model-based expectations with the assumption that property investors’ expectations are adaptive. The paper goes on by comparing and examining the results of Granger causality tests and impulse response analyses. Findings The findings reveal that Auckland property buyers’ expectations are adaptive. In addition, this study provides some evidence of a feedback cycle between Auckland housing prices and expectations. Research limitations/implications This study posits that Auckland property buyers’ expectations in the next 12 months are based on three-year price movements with more emphasis being placed on recent price history. This assumption may not be an accurate reflection of true expectations. Practical implications This paper helps policymakers to deepen their understanding of Auckland property buyers by showing that their expectations form through the extrapolation of the past price trend. Originality/value The study possibly marks the first attempt to test and compare the relationship between housing prices and two forms of expectations: survey-based and model-based. Additionally, this study is probably the first one that empirically examines whether there is a feedback cycle between expectations and property prices in the Auckland housing market.
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Khan, Areeba, Sulaman Hafeez Siddiqui, Shahid Hussain Bukhari, and Syed Muhammad Hashim Iqbal. "Human Development, Political Stability and Economic Growth: The way forward." Review of Economics and Development Studies 6, no. 2 (June 15, 2020): 451–61. http://dx.doi.org/10.47067/reads.v6i2.213.
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Economic growth has been known to foster human development for long term economic stability. The evidence of bi-causality in the human development and economic growth nexus is however limited. This paper builds on the reverse causality between human development and economic growth in context of Pakistan, with the moderating impact of political stability. The study applies OLS and VECM on the data collected from World Bank Database from year 2006 to 2018. Our findings exhibit empirical evidence related to endogenous growth models and a significant causal relationship between human development and economic growth, moderated by political stability. The relationship is further explained by trajectories of happiness, health and income redistribution. Our findings suggest efficient reallocation of resources towards human development to address post pandemic growth concerns.
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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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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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Mumo, Muinde Patrick. "Effects of Macroeconomic Volatility on Stock Prices in Kenya: A Cointegration Evidence from the Nairobi Securities Exchange (NSE)." International Journal of Economics and Finance 9, no. 2 (January 11, 2017): 1. http://dx.doi.org/10.5539/ijef.v9n2p1.
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This study examined the effects of macroeconomic volatility on stock prices via selected macro variables using the Johansen co-integration methodology. Time series data was obtained from the Kenya National Bureau of Statistics (KNBS) and the Central Bank of Kenya (CBK) for the period 1998-2015. Macro variables studied include inflation, money supply, exchange rates and interest rates against the NSE 20 share index. The study exploits the presence of unit roots of order 1(1) on the data set to apply the Johansen procedure and the Vector Error Correction Model (VECM) for data analysis. The study finds both a long-run equilibrium relationship between stock prices and the macroeconomic variables and between inflation and other macro variables. Specifically, and contrary to earlier evidence on the Kenyan market, the results suggest a negative long-run equilibrium relationship between money supply and stock prices. Inflation shows negative but insignificant relationship. Exchange rates and interest rates show a positive relationship. The short-term dynamics from the VECM support earlier documented evidence, implying the earlier evidence reflect short-run and not long-run dynamics.The study concludes that the effects of inflation seem to outweigh any possible gains from money supply on aggregate firm output in the long-run. Also, the study adduces evidence of possible spurious problems on earlier documented evidence from the reviewed studies that could be attributable to non stochastic processes in the models used. A robustness check using a multivariate approach points to this and confirms the co-integration results.
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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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Kuzmenko, Elena, Luboš Smutka, Mikhail Pankov, and Nadezhda Efimova. "The Success of Economic Policies in Russia: Dependence on Crude Oil vs. Export Diversification." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 65, no. 1 (2017): 299–310. http://dx.doi.org/10.11118/actaun201765010299.
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In the light of numerous debates around Russia’s dependence on crude oil and the necessity to diversify the Russian economy, the present paper investigates how closely federal budget revenues, structure of export basket and GDP growth in Russia are tied up with crude oil prices (POIL) on the one hand and the real effective exchange rate of ruble (REER) on the other. The study covers the period from 2000:Q1 till 2014:Q4 and employs index analysis along with vector error correction model (VECM) based on Johansen co‑integration technique. The calculated REER revealed its significant appreciation, that together with a high share of mineral products in total Russian exports points to Dutch disease presence. The constructed econometric models revealed the existence of long‑run relationships among the analyzed indicators. Post‑estimation tests proved the validity of the VECMs. According to the obtained results, in order to stimulate “non‑oil” exports monetary authorities should depreciate national currency, whilst fiscal burden should be mild towards “non oil” producers. However, the observed dynamics of macroeconomic indicators points to the fact that the Russian economy is still substantially influenced by POIL and this influence is much more stronger than it is exerted by fiscal and monetary regulators. It allows us to conclude that crude oil will continue to play, at least in foreseeable future, a dominant role in further development of the Russian economy.
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Doszyń, Mariusz. "Econometric Analysis of the Impact of Propensities on Economic Occurrences: A Macroeconomic Perspective." Folia Oeconomica Stetinensia 10, no. 2 (January 1, 2012): 138–54. http://dx.doi.org/10.2478/v10031-011-0021-2.
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Econometric Analysis of the Impact of Propensities on Economic Occurrences: A Macroeconomic PerspectiveThe main aim of this article was the specification of problems connected with analysis of impact of human propensities on economic occurrences and also a proposition of econometric tools enabling the identification of this impact. According to the meaning of propensities in economics the current state of knowledge is mostly an effect of considerations presented by J.M. Keynes in his famous book "The General Theory of Employment, Interest and Money" where J.M. Keynes proposed such economic categories as the average and marginal propensities. One of the goals of the presented deliberations was to specify problems related with economic theory of propensities. Such propensities as a propensity to consume, to save, to invest and thesaurisation were particularly carefully analysed. The impact of these propensities on basic macroeconomic variables was considered with respect to the classical model, the neoclassical Solow-Swan model and theIS-LMscheme. In case of spatial data the effects of the impact of propensities could be analysed by means of models with dummy variables showing presence of given propensities. A procedure enabling the construction of such variables was proposed. In case of time series, conceptions delivered by the integration and cointegration theory could be applied. Especially such models as VAR and VECM could be useful. Models for panel data enable direct (models with fixed effects) or indirect (models with random effects) consideration of the impact of propensities on the analysed processes.
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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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Dzingirai, Canicio, and Nixon S. Chekenya. "Longevity swaps for longevity risk management in life insurance products." Journal of Risk Finance 21, no. 3 (June 27, 2020): 253–69. http://dx.doi.org/10.1108/jrf-05-2019-0085.
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Purpose The life insurance industry has been exposed to high levels of longevity risk born from the mismatch between realized mortality trends and anticipated forecast. Annuity providers are exposed to extended periods of annuity payments. There are no immediate instruments in the market to counter the risk directly. This paper aims to develop appropriate instruments for hedging longevity risk and providing an insight on how existing products can be tailor-made to effectively immunize portfolios consisting of life insurance using a cointegration vector error correction model with regime-switching (RS-VECM), which enables both short-term fluctuations, through the autoregressive structure [AR(1)] and long-run equilibria using a cointegration relationship. The authors also develop synthetic products that can be used to effectively hedge longevity risk faced by life insurance and annuity providers who actively hold portfolios of life insurance products. Models are derived using South African data. The authors also derive closed-form expressions for hedge ratios associated with synthetic products written on life insurance contracts as this will provide a natural way of immunizing the associated portfolios. The authors further show how to address the current liquidity challenges in the longevity market by devising longevity swaps and develop pricing and hedging algorithms for longevity-linked securities. The use of a cointergrating relationship improves the model fitting process, as all the VECMs and RS-VECMs yield greater criteria values than their vector autoregressive model (VAR) and regime-switching vector autoregressive model (RS-VAR) counterpart’s, even though there are accruing parameters involved. Design/methodology/approach The market model adopted from Ngai and Sherris (2011) is a cointegration RS-VECM for this enables both short-term fluctuations, through the AR(1) and long-run equilibria using a cointegration relationship (Johansen, 1988, 1995a, 1995b), with a heteroskedasticity through the use of regime-switching. The RS-VECM is seen to have the best fit for Australian data under various model selection criteria by Sherris and Zhang (2009). Harris (1997) (Sajjad et al., 2008) also fits a regime-switching VAR model using Australian (UK and US) data to four key macroeconomic variables (market stock indices), showing that regime-switching is a significant improvement over autoregressive conditional heteroscedasticity (ARCH) and generalised autoregressive conditional heteroscedasticity (GARCH) processes in the account for volatility, evidence similar to that of Sherris and Zhang (2009) in the case of Exponential Regressive Conditional Heteroscedasticity (ERCH). Ngai and Sherris (2011) and Sherris and Zhang (2009) also fit a VAR model to Australian data with simultaneous regime-switching across many economic and financial series. Findings The authors develop a longevity swap using nighttime data instead of usual income measures as it yields statistically accurate results. The authors also develop longevity derivatives and annuities including variable annuities with guaranteed lifetime withdrawal benefit (GLWB) and inflation-indexed annuities. Improved market and mortality models are developed and estimated using South African data to model the underlying risks. Macroeconomic variables dependence is modeled using a cointegrating VECM as used in Ngai and Sherris (2011), which enables both short-run dependence and long-run equilibrium. Longevity swaps provide protection against longevity risk and benefit the most from hedging longevity risk. Longevity bonds are also effective as a hedging instrument in life annuities. The cost of hedging, as reflected in the price of longevity risk, has a statistically significant effect on the effectiveness of hedging options. Research limitations/implications This study relied on secondary data partly reported by independent institutions and the government, which may be biased because of smoothening, interpolation or extrapolation processes. Practical implications An examination of South Africa’s mortality based on industry experience in comparison to population mortality would demand confirmation of the analysis in this paper based on Belgian data as well as other less developed economies. This study shows that to provide inflation-indexed life annuities, there is a need for an active market for hedging inflation in South Africa. This would demand the South African Government through the help of Actuarial Society of South Africa (ASSA) to issue inflation-indexed securities which will help annuities and insurance providers immunize their portfolios from longevity risk. Social implications In South Africa, there is an infant market for inflation hedging and no market for longevity swaps. The effect of not being able to hedge inflation is guaranteed, and longevity swaps in annuity products is revealed to be useful and significant, particularly using developing or emerging economies as a laboratory. This study has shown that government issuance or allowing issuance, of longevity swaps, can enable insurers to manage longevity risk. If the South African Government, through ASSA, is to develop a projected mortality reference index for South Africa, this would allow the development of mortality-linked securities and longevity swaps which ultimately maximize the social welfare of life assurance policy holders. Originality/value The paper proposes longevity swaps and static hedging because they are simple, less costly and practical with feasible applications to the South African market, an economy of over 50 million people. As the market for MLS develops further, dynamic hedging should become possible.
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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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Iqbal, Muhammad Nadeem, Muhammad Zia ur Rehman, and Kashif Saleem. "Impact of Macroeconomic Variables on Stock Markets: Evidence from Frontier Markets like Pakistan Stock Exchange (PSX)." Global Social Sciences Review III, no. III (September 30, 2018): 595–610. http://dx.doi.org/10.31703/gssr.2018(iii-iii).35.
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The macroeconomic version of the APT is of great significance in examining the return on assets. It analyzes the estimated security return with reference to various macroeconomic variables. Despite availability of research studies related to the developed and emerging stock markets of the world, still a research gap exists for exploring the frontier markets like equity market of Pakistan. The study examines the long and short term impact of macroeconomic variables on the KSE 100 index for the period of July 1996 - June 2015. Cointegration technique and VECM models have been applied. Among these variables, GDP, inflation, exchange rate, unemployment rate, labor force cost and stock market of US were found significant for explanation of effects on return of stock market of Pakistan. The study findings have potential implications for both policymakers and investors pertaining to macroeconomic factors and stock market volatility.
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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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Rehman, Naqeeb Ur. "FDI and economic growth: empirical evidence from Pakistan." Journal of Economic and Administrative Sciences 32, no. 1 (May 16, 2016): 63–76. http://dx.doi.org/10.1108/jeas-12-2014-0035.
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Purpose – The purpose of this paper is to investigate the relationship between FDI and economic growth. Two models have been used to analyse the time series data on Pakistan from 1970 to 2012. This paper contributes to the existing literature by examining the different empirical methods to estimate the relationship between FDI and economic growth. The vector error correction model (VECM) results suggest that FDI depends on the economic growth but this relationship is not true vice versa. The second model showed that FDI, human capital and exports are important factors of economic growth. However, the negative relationship between interactive variables (FDI and human capital) and economic growth indicates that low level of human capital affect the economic growth of Pakistan. Design/methodology/approach – Used time series data (1970-2012) for empirical analysis. Findings – The VECM results suggest that FDI depends on the economic growth but this relationship is not true vice versa. The second model showed that FDI, human capital and exports are important factors of economic growth. However, the negative relationship between interactive variables (FDI and human capital) and economic growth indicates that low level of human capital affect the economic growth of Pakistan. Research limitations/implications – The limitations of this empirical paper are as follows: it would be better to use secondary school enrolment (per cent) to measure human capital instead adult literacy rate. Similarly, the non-availability of R & D data on Pakistan limited the scope of the paper to measure the role of absorptive capacity of domestic and its relationship with FDI. The results of this paper are specifically related to Pakistan and cannot be generalized to other countries. Practical implications – This empirical study implies that Pakistan should improve its economic growth. The robust policies are required to increase the literacy rate of the country. Higher human capital will attract more FDI into the economy and may reduce the unemployment. This would increase the national output of the country and their national income level. Presently, Pakistan is going through war on terror and foreign firms are reluctant to invest. A stable and secure business environment will ultimately inject foreign direct investment into Pakistan. Originality/value – This paper is first time analyse the time series data to explore the relationship between FDI and economic growth. A new approach has been used called VECM.