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Applies an error‐correction model to demand for money in five African economies: Congo, Côte d′Ivoire, Mauritius, Morocco and Tunisia. Attention is given to a set of opportunity cost variables including expected inflation, domestic interest rate, foreign interest rate and expected exchange‐rate depreciation. The empirical results show that the domestic interest rate plays a significant role in the demand for money functions for three of the five countries and external opportunity cost variables are significant for one of the others. The results show some diversity in money demand behaviour in the countries studied, but the error correction mechanism is always significant and in four out of five cases there is a short‐run inflation impact. The equations are subjected to a battery of tests and found to be statistically well‐behaved.

High packet error rates and variable link capacity due to harsh electric power system environments make reliable communication a challenging task for WSN in smart grid. Therefore, to increase network reliability and hence, to improve smart grid system performance, there is an urgent need for reliable communication protocols. The purpose of this paper is to propose an Adaptive Forward Error Correction (AFEC) mechanism for different smart grid environments, including 500 kV outdoor substation and underground transformer vaults, to address these challenges.

This paper presents the comparative performance evaluations of proposed AFEC mechanism for different smart grid environments. Simulation experiments have been performed by extending the ns‐2 network simulator. It also introduces existing and potential smart grid applications, research challenges, and opportunities of smart grid.

Comparative performance evaluations show that the proposed AFEC mechanism achieves high communications reliability without causing unnecessary network overhead. Also the advantages of existing smart grid applications have been presented.

The paper shows that high communications reliability without causing unnecessary network overhead has been achieved. Also comprehensive reviews of WSN smart grid applications have been presented.

The purpose of this paper is to test the overshooting effects of monetary expansion on prices of agricultural products at farm production, processing and circulation stages in China, and to investigate the heterogeneity of the overshooting mechanisms in these three links.

Empirical results are obtained through the vector error correction model and the overshooting framework proposed by Saghaian et al. (2002b). Specifically, we first apply the Dickey–Fuller generalized least squares (DF-GLS) method to test the stationarity of the key variables, and then use the Johansen’s (1991) method to conduct the cointegration test. Finally, the vector error correction model is employed to examine the overshooting hypotheses in the three stages of China’s agricultural sector.

Empirical results indicate that overshooting of prices relative to monetary expansion in China’s agricultural sector is a common phenomenon, but with significant heterogeneity. Firstly, at the stage of agricultural production, the overshooting degree and restoration rate of material price are greater than those of agricultural products price. Secondly, at the processing stage of agricultural products, both the purchase price of agricultural products and industrial producer price have an overshooting effect, but the overshooting effect of the former is more significant than the latter. Thirdly, at the circulation stage of agricultural products, the overshooting coefficient of the wholesale price index of agricultural products is the most significant, while that of the retail and purchase price of agricultural products is not significant.

The paper contributes to proposing a comprehensive framework on testing the overshooting effects for three main stages of agricultural sector in China and empirically investigating the heterogeneity of the overshooting mechanisms in different stages with time series methods.

This study aims to cover an important yet largely under-explored topic: the dynamic process of bank liquidity management in a vast developing economy by considering pool of funds hypothesis, signaling hypothesis and risk management hypothesis.

The authors apply the dynamic common correlated effect (DCCE) method with an error correction model format to a long panel datasets of 84 Indonesian banks from January 2003 to August 2019, resulting in 16,800 observations.

The authors obtain convincing evidence of dynamic liquidity management with an error correction mechanism. The time needed to adjust to a liquidity shock ranges from 2.5 to 3.5 months. The empirical results strongly support the pool of funds and signaling hypotheses, whereas risk management motive appears to have secondary importance.

The regulator should also encourage banks to diversify liquidity management to include interbank money market and off-balance-sheet instruments. The current condition shows that bank liquidity management is strongly correlated with intermediation dynamics and thus is contracyclical. Banks could end up with tight liquidity in a booming economy, which would pose a severe risk to their financial standing.

To authors’ knowledge, this study is the first to analyze bank liquidity management behavior empirically using a panel error correction mechanism. Here, the authors also try to combine a practitioner perspective with a scientific one.

Shanghai is the most important economic centre in China. It also has the nation's largest modern office market in terms of floorspace and investment values. However, as with office markets in other cities and countries, the Shanghai market displays rental volatility. This paper aims to examine this issue.

Rental volatility is examined by econometrically constructing a long‐run equilibrium relationship between rent and underlying demand and supply side factors. In order to establish the validity of this model, it is tested for the presence of a cointegrating vector. From this a short‐run dynamic adjustment model is constructed. This is an error correction mechanism that links the short‐ and long‐run models. The impact of office vacancies, foreign direct investment, and changes in the real interest rate on the office market are explicitly considered.

The results indicate that both demand (as represented by gross domestic product (GDP)) and supply (stock) are significant determinants of rents. Space demand is found to be both price and income elastic. In the short‐run model the error correction term is significant and correctly signed. In comparison to other office markets, the Shanghai market adjusts rather slowly. Foreign direct investment is found to have a positive impact on long‐run rents and the vacancy rate is found to impact on short‐term rental adjustment.

The Shanghai office market is the most important in China. However, it has displayed significant rental volatility. This paper is the first to examine explicitly the rental adjustment process in this office market. The results suggest a market that is performing as expected by economic theory but which nevertheless displays relatively slow adjustment to market imbalances.

This paper looks into the dynamics of private housing prices in Singapore from the first quarter of 1985 to the fourth quarter of 1995. Employing the cointegration analysis, the paper shows that overall private housing price is cointegrated with real gross domestic product, prime lending rate and private housing starts. An error‐correction mechanism is also incorporated in the estimation of changes in the overall private housing price to account for the short‐run deviations from the equilibrium relationship among these variables.

The purpose of this paper is to investigate asymmetric cointegration and causality effects between financial development and economic growth for South African data spanning over the period of 1992-2013.

This study makes the use of the momentum threshold autoregressive (M-TAR) approach which allows for threshold error-correction (TEC) modeling and Granger causality analysis between the variables. In carrying out an empirical analysis, the author uses six measures of the financial development variables against gross domestic per capita, that is, three measures which proxy banking activity and another three proxies for stock market development.

The empirical results generally indicate an abrupt asymmetric cointegration relationship between banking activity and economic growth, on the one hand, and a smooth cointegration relationship between stock market activity and economic growth, on the other hand. Moreover, causality analysis generally reveals that while banking activity tends to Granger cause economic growth, stock market activity is, however, caused by economic growth increase.

This study contributes to the literature by examining asymmetries in the cointegration and causality relations by using both banking and stock market proxies against economic growth for the South African economy.

This study examines the impact of expectations on the market share mechanism. The dynamic strategic pricing behaviors in the short‐run and the long‐run are also explored. The exchange rate expectations are incorporated into a switching cost model via the method of exchange rate pass‐through on product‐specific and country‐specific approach. By using the time series techniques, the results of the system estimations prove that the market share mechanisms are weakened by exchange rate expectations in open economies. Furthermore, not only is the degree of exchange rate pass‐through higher in the short‐run than in the long‐run but also many cases of pair‐wise rivalry are found. An improved understanding of the effects of exchange rate movements on foreign exporters pricing and pass‐through relations from this study may enhance competition in international markets.

The aims of the paper are to investigate IT software and service export function for India. First, cointegration tests have been used to investigate the long-run equilibrium relationship of the given variables. Second, long-run coefficients and associated error correction mechanism are estimated.

Annual time series data on IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index have been used for the present study during the period 1980–2017. The data are collected from the National Association of Software and Service Companies (NASSCOM), Planning Commission of India, University Grants Commission (UGC) of India, real effective exchange rate (REER) database and World Bank development indicators. Auto regressive distributed lag (ARDL) model is used to analyze both short-run and long-run dynamic behaviour of economic variables with appropriate asymptotic inferences.

Results of the analysis show the stable long-run equilibrium relationship among the given variables. It is found that external demand, exchange rate, human capital and openness index have a substantial long-run impact on the IT software and service exports. We also found that the coefficient of error correction term is negative and significant at 1% of the level of significance, which confirms the existence of stable long-run relationship which means adjustment will take place when there is a short-run deviation to its long-run equilibrium after a shock.

There may be other determinants of software and service exports apart from those considered by the present study. Due to the non-availability of data, the study considers only important determinants that determine the software and service exports in India. The IT exports are an emerging and dynamic field of economic activity and the rate of change is so rapid that the relevance of individual factors may change over time. The study period is also limited to available data.

The paper has implications for achieving sustainability in IT software and service exports growth. It is recommended that policies directed at improving the performance of IT software and service exports should largely consider the long-run behaviour of these variables.

This paper focuses on originality in the analysis of the relationship among the given variables including IT software and service exports, human capital, exchange rate, investment in IT, external demand and openness index in India. All the work has been done in original by the authors, and the work used has been acknowledged properly.

The purpose of this paper is to investigate the causal relationship between the prices of rice, crude oil, wheat, corn and soybean in China and estimate the long-run and short-run price relationships.

Using monthly price date over the period of January 1998-December 2013 in China, this paper employs an autoregressive distributed lag (ARDL) bounds test to explore the cointegration relationship among the price variables and estimate the ARDL long-run price relationship and the short-run error correction process (ARDL-EC).

The empirical results indicate that crude oil, as one of the forcing variables along with wheat, corn, and soybean prices, is effecting rice price in China. Both the long-run and short-run price transmission elasticity estimates suggest the importance of crude oil price on the formation of rice prices. Furthermore, the adjustment speed coefficient is found to be statistically significant, supporting the notion that there is an error correction mechanism for maintaining the long-run price relationship facing short-run shocks.

This paper adopts four types of commodity food prices to explore the relationships with crude oil price. The evidence of market integration, including the degree of price transmission and the speed of adjustment, remains a crucial step to proceed with the government intervention.