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The purpose of this paper is to examine the performance of the vector error‐correction (VEC) econometric modelling technique in predicting short‐ to medium‐term construction manpower demand.

The VEC modelling technique is evaluated with two conventional forecasting methods: the Box‐Jenkins approach and the multiple regression analysis, based on the forecasting accuracy on construction manpower demand.

While the forecasting reliability of the VEC modelling technique is slightly inferior to the multiple log‐linear regression analysis in terms of forecasting accuracy, the error correction econometric modelling technique outperformed the Box‐Jenkins approach. The VEC and the multiple linear regression analysis in forecasting can better capture the causal relationship between the construction manpower demand and the associated factors.

Accurate predictions of the level of manpower demand are important for the formulation of successful policy to minimise possible future skill mismatch.

The accuracy of econometric modelling technique has not been evaluated empirically in construction manpower forecasting. This paper unveils the predictability of the prevailing manpower demand forecasting modelling techniques. Additionally, economic indicators that are significantly related to construction manpower demand are identified to facilitate human resource planning, and policy simulation and formulation in construction.

It is widely documented that while contemporaneous spot and forward financial prices trace each other extremely closely, their difference is often highly persistent and the conventional cointegration tests may suggest lack of cointegration. This chapter studies the possibility of having cointegrated errors that are characterized simultaneously by high persistence (near-unit root behavior) and very small (near zero) variance. The proposed dual parameterization induces the cointegration error process to be stochastically bounded which prevents the variables in the cointegrating system from drifting apart over a reasonably long horizon. More specifically, this chapter develops the appropriate asymptotic theory (rate of convergence and asymptotic distribution) for the estimators in unconditional and conditional vector error correction models (VECM) when the error correction term is parameterized as a dampened near-unit root process (local-to-unity process with local-to-zero variance). The important differences in the limiting behavior of the estimators and their implications for empirical analysis are discussed. Simulation results and an empirical analysis of the forward premium regressions are also provided.

This study aims to establish the dynamic relationship between international crude oil prices and Indian stock prices represented by the Bombay Stock Exchange (BSE) energy index.

Using Johansen’s cointegration test, vector error correction (VEC) model, impulse response function and variance decomposition test the study tries to ascertain the short-term and long-term dynamic association between the oil price shock and the movement of stock price and Granger causality test is applied to find out the nature of causality.

Considering vector autoregression estimation, the present study analyzes the relationship between the variables and tries to make a valid conclusion. The result of the co-integration test exhibits the presence of a long-term association between these two macro-economic variables during the period under study. Also, in the short-run VEC Granger causality result reveals that the movement of international crude oil price significantly influences the Indian stock price.

To get a more robust result the study can be further extended by taking a longer time period with data of shorter time-frequency such as daily or weekly and further by using more sophisticated econometric and statistical tools. Further, the study can be extended to firm-level investigation considering the forward trading concentration with the Indian oil basket.

In today’s globalized era, forecasting of share price movement helps investors in predicting the market and invest accordingly. Through this liquidity of the markets enhance and markets become more active in the global arena.

This study represents fresh findings in the changing time period the linkage between crude oil prices and stock prices which are of value to the academicians, researchers, policymakers, investors, market regulators, etc.

The purpose of this paper is to investigate firm strategies and the exertion of market power in the brewing sector in Brazil following a merger between the two largest brewers (Brahma and Antarctica) that created Ambev and given that the existing literature is inconclusive on this subject

In this study the authors apply cointegration analysis to price series of beer brands. The authors use the reduced form vector error correction (VEC) model to measure the price responses of beer brands in terms of direction, magnitude and speed. The authors use monthly retail prices for the primary brands of beer in the city of São Paulo, Brazil's largest consumer market. Specifically, the authors use two sets of retail prices, one from bars (the main point of beer sales, with roughly 50% of market share) and another from supermarkets. The series range from 1994 to 2014, depending on the brand.

This study indicates that Ambev's two major brands (Skol and Brahma) behave as market leaders, while its third brand (Antarctica) has been used to challenge the low-price competitor (Nova Schin). The authors also found evidence that the pricing policies of Brahma and Antarctica have changed toward cooperation following the creation of Ambev.

The main limitation of this article is that the authors only had access to retailer data. As the merger involved brewers, the authors would ideally use manufacturer beer prices in their econometric analysis. However, the consistency of our results suggests that retailers have been passively transmitting brand strategies launched at a manufacturer level.

As the dominant firm created following the merger of the two largest brewers appears to use one of its brand to restrict entry of competitors and the premium brands to enjoy high profits, consumers tend to be harmed by high beer prices and lack of options. Furthermore, small and medium-size companies cannot grow due to entry barriers created by the dominant firm.

This paper is the first to apply cointegration analysis to examine the effect of mergers on pricing strategies. The robustness of this study suggests that this approach could be used for antitrust agencies to monitor post-merger strategies.

This study adds to the ongoing analysis of the long‐term impact of Asian financial crisis on the stock markets of eight Asian‐Pacific countries. Using current data to capture postcrisis behavior of returns, multivariate cointegration analysis reveals that a cointegrating relationship exists among the markets that transcend the financial crisis. Both vector error correction (VEC) and Granger causality tests demonstrate the profound effect of financial crisis in Korea on the returns of other countries. Granger causality tests further reveal that the events surrounding the crisis in Thailand and Indonesia largely dictate their own short‐run returns behavior since the advent of the crisis. Compared to earlier period, the post‐crisis era also experiences a closer relationship among the index returns of Hong Kong, Korea, and Singapore and a heightened degree of convergence among the returns of Asian markets.

What caused the mid-2000s world commodity price “bubble” and the recent commodity price growth? Some have suggested that rapid global industrial growth over the past decade is the key driver of price growth. Others have argued that high commodity prices are a result of excessively loose monetary policy. The purpose of this paper is to extend the current research in this area by incorporating emerging economies, the BRIC (Brazil, Russia, India, and China) nations specifically, into global measures.

The paper uses a vector error correction (VEC) model and computes variance decomposition and impulse response functions (IRFs).

The empirical analysis suggest that the “demand channel” plays a large part in explaining commodity price growth whether BRIC countries are included or excluded from the analysis. However, excess liquidity may also play a part in explaining price growth. In addition, factoring in BRIC country data leads to the conclusion that unexpected movements in liquidity eventually explain more of the variation in commodity prices than unexpected demand shocks. This specific result is not caught in the sample that only incorporates advanced economies.

Despite the theory of Frankel (1986) and the findings of previous global vector autoregression (VAR)/VEC analyses, interest rates, especially shocks, have a minimal impact on consumer and commodity prices. Perhaps future studies should include an interest rate in their analysis that more closely reflects interest rates associated with information used by commodity consumers, producers, and investors. Some analyses such as Hua (1998) use the LIBOR rate, which is highly associated with developed financial markets in the advanced economies. Data quality and availability in the BRIC countries severely limited the length of the time period analyzed and the frequency of the data. Finding longer sample periods or higher frequency data can help to minimize bias in future research. In this paper, monetary aggregates and short-term interest rates were loosely connected to monetary policy. It would also be interesting to directly examine how special programs like quantitative easing influenced global liquidity.

The results of the IRFs and variance decompositions confirm some of the previous findings reported in Belke et al. (2010), Hua (1998), and Swaray (2008) that suggest that positive shocks to liquidity positively impact commodity prices. In particular, both samples suggest that this is a short-run impact that occurs after two quarters. However, in the sample that includes information about liquidity from BRIC countries, excess liquidity positively affects commodity prices after six and seven quarters as well. The insignificant results of Granger causality tests of the effect of monetary variables on commodity prices suggests that this relationship is limited to movements in liquidity that is unexpected by agents in the system. These “shocks” could be attributed to a number of factors including exogenous monetary policy changes such as the unprecedented responses by the Federal Reserve during and after the 2008 global financial crisis.

First, empirical research that claims to analyze relationships at a “global” level needs to account for the growing influence of emerging economies and not simply the advanced economies. Otherwise, results may be biased as they were when too much of the forecast error variance in commodity prices was attributed to shocks to output when it should have been attributed to shocks to excess liquidity. Second, those who criticize expansionary monetary policy in the advanced countries, especially by the Federal Reserve, for pushing up commodity prices should also direct their attention toward monetary authorities elsewhere, especially the BRIC countries, since information on excess liquidity from these countries adds to the influence that global excess liquidity has on commodity prices. Third, monetary policymakers in the advanced countries need to closely monitor liquidity in the BRIC countries, since the discrepancies between the ALL and ADV samples suggests that BRIC excess liquidity affects commodity prices in a way that cannot be captured by examining advanced country data alone.

No other paper in this area looked at the BRIC countries.

This paper aims to examine whether the Sharīʿah indices outperform the conventional indices as evident from Dhaka Stock Exchange (DSE). To achieve the objective, the study, first, assesses the risk adjusted returns of the Sharīʿah and conventional indices and compares the same between the two indices. Second, it examines the short-run and long-run associations between the two indices.

The DSEX Sharīʿah index and DSE broad index of the DSE are used as representatives of the Sharīʿah and conventional indices, respectively. The study uses monthly data for the period 2014–2018 and applies a number of techniques such as risk adjusted returns, Johansen’s cointegration test, vector error correction model, Granger causality test, forecast error variance decomposition and impulse response functions techniques.

The study reveals that albeit there is no significant difference in simple mean between the two indices, the Sharīʿah index outperforms its conventional counterpart based on the risk adjusted returns. The two indices are associated only in the long-run, while no causal relationship is spotted between them. The overall results show that the Sharīʿah index has dominance over the conventional index in Bangladesh.

The study could use more pairs of indices, including additional variables such as financial crisis and macroeconomic variables.

The study has important implications to investors, especially the religious Muslims and ethical ones, who are suggested to invest their funds in the Sharīʿah index without sacrificing returns, rather be monetarily more benefited. Moreover, the other investors can generate diversification benefits by adding both Sharīʿah and conventional indices in their portfolios in the short-run.

Unlike previous studies, this study endeavors to use a comprehensive methodology to conduct its analysis. Moreover, this is supposedly the first ever effort to conduct such a study in the context of Bangladesh.

This paper investigates the efficiency of the futures market for Brazilian live cattle to predict prices in the spot market of Argentinian steers. The lack of derivatives related to the beef market in the futures exchange in Argentina was the main factor behind the decision to analyse the efficiency of the Brazilian live cattle futures as a predictor of spot prices of Argentinian steers.

We opted to employ the efficient markets hypothesis to approach the question. The hypothesis that futures prices are non‐biased predictors of spot prices is considered to be a true proposition only if the efficient markets hypothesis is not rejected. In methodological terms, the efficiency of the futures market for Brazilian live cattle relative to the spot market of Argentinian steers was verified using the Johansen co‐integration test. A vector error correction model – which enables verification of the question of bias in the prediction of prices, was used to estimate the long‐term equilibrium between spot and futures prices.

The results provided no evidence of bias in the prediction of prices and found the predictive efficiency of the Brazilian live cattle futures market relative to the spot market of Argentinians steers to be approximately 80 per cent. Thus, the future prices of Brazilian live cattle can expressly assist participants in the Argentinian beef production chain to predict the spot prices of steers.

Esse trabalho verifica a eficiência do mercado futuro do boi gordo brasileiro em relação ao mercado a vista dos novilhos argentinos. A ausência de derivativos relacionados ao mercado da carne bovina em bolsa de futuros na Argentina foi o principal aspecto motivador da análise da eficiência do mercado futuro do boi gordo brasileiro como preditordos preços a vista dos novilhos argentinos.

Assim sendo, optou‐se por uma abordagem à luz da teoria da hipótese dos mercados eficientes. A hipótese de que os preços futuros são preditores não viesados dos preços a vista é tida como uma proposição verdadeira somente se a hipótese de eficiência de mercado não for rejeitada. No contexto metodológico, a eficiência do mercado futuro do boi gordo brasileiro em relação ao mercado a vista dos novilhos argentinos foi verificada a partir do teste de cointegração de Johansen, enquanto que o equilíbrio no longo prazo entre os preços a vista e futuros, que possibilita a verificação da questão do viés na predição dos preços, foi estimado por um modelo vetorial de correção de erro.

Os resultados evidenciaram o não viés na predição dos preços e a eficiência do mercado futuro do boi gordo brasileiro em relação ao mercado a vista dos novilhos argentinos de aproximadamente 80%. Logo, os preços futuros do boi gordo brasileiro podem auxiliar de maneira expressiva os agentes da cadeia produtiva da carne bovina argentina na predição dos preços a vista dos novilhos.

The purpose of this paper is to develop and empirically test the conditions that describe adjustment velocities to reach equilibrium under Cournot's duopoly model.

The paper uses a vector error correction (VEC) framework as the basis for determining and testing adjustment velocities using data about cellphone service in Colombia in the time period from 1995 to 2001.

Empirical evidence suggests the following: first of all, companies operating in the cellphone market behave as cournot's competitors and have constant marginal costs; secondly, cellphone companies operating in the eastern zone of Colombia are in long‐term equilibrium; and lastly, equilibrium adjustment velocities are statistically significant. As predicted by theory, in terms of welfare, the existence of equilibrium in Cournot's model implies that cellphone users in the eastern zone of Colombia enjoy a small consumer surplus.

Testing the microeconomic implications of the equilibrium dynamics of Cournot's model, using a VEC framework.

The key purpose of this paper is to examine the causality and long‐run relationship between CO2 emission and agricultural output for an agriculture‐dependent developing country, namely Bangladesh.

In order to attain the objective, this study has used long‐time series data and employed advanced econometric techniques of unit root test, nonlinear least square estimation, Vector Error Correction estimation and Granger causality test.

The empirical results of the study reveal that Bangladesh agricultural output is not a Granger causal for Bangladesh CO2 emission, but the country's CO2 emission is a Granger causal for its agricultural output. The results also reveal for Bangladesh that any disequilibrium between CO2 emissions and agricultural output could take approximately 17 years to converge to the long‐run equilibrium. The results further reveal that the adjustment rate for Bangladesh agricultural output is positive and quite fast at the rate of 69 percent a year. So any disequilibrium will be corrected mostly by the adjustment in Bangladesh agricultural output.

The current CO2 emission in Bangladesh is still below the equilibrium level, which is considered to be an advantage for the country, particularly its agriculture sector which will reasonably not face any stricter CO2 emissions controlling policies and regulations in the near future.

The originality of this study lies on the extent to which an agriculture‐dependent developing country such as Bangladesh does not have greater concern about the CO2 emission for now and the near future. The originality does also lie on the fact that no other study has yet examined this issue.