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To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

This study aims to investigate whether changes in consumer interest rate, exchange rate and housing supply have permanent effects on housing inflation in Turkey.

For this purpose, data from 2010M01 to 2020M06 and changes in consumer interest rate, exchange rate, housing supply and housing inflation were used. Relationships between variables are analyzed first by the Granger causality tests and then the conditional frequency domain causality tests. The conditional frequency domain causality test specifically reveals the permanent causality between variables, whether there is a permanent effect.

According to the Granger causality test results, there are causality relationships from changes in the consumer interest rate and exchange rate to housing inflation. However, there is no causality relationship between housing supply and housing inflation. According to the conditional frequency domain causality test results, there is causality for the permanent and mid-term from changes in the consumer interest rate to housing inflation and causality for the mid-term and temporary from changes in the exchange rate to housing inflation. Additionally, it was found that there are causality relationships between changes in the consumer interest rate and changes in the exchange rate.

The first limit of the study is that only 2010M01-2020M06 months can be considered. Because the date that variables started common is 2010M01. Besides, there is a limit in the study in variables used. Many variables, both micro and macro, can be added to affect housing inflation.

Housing inflation is a remarkable issue in Turkey. There is an increase in the number of studies on the subject in recent years. For this reason, the study is trying to contribute by approaching the subject from a different angle. The most important contribution of the study is that it has not been investigated whether the determinants of housing inflation have permanent or temporary effects, which were not done in previous studies. In addition, the method used reveals how many months the effects of changes in exchange rates, consumer interest rates and housing supply on housing inflation last. Based on the findings obtained from the methods, important economic and political implications have been put forward in depth.

This study aims to examine the impact of some real variables such as real effective exchange rates, real mortgage rates, real money supply, real construction cost index and housing sales on the real housing prices.

This study uses a nonlinear autoregressive distributed lag (NARDL) model in the monthly period of 2010:1–2021:10.

The real effective exchange rate has a positive and symmetric effect. The decreasing effect of negative changes in real money supply on real housing prices is higher than the increasing effect of positive changes. Only positive changes in the real construction cost index have an increasing and statistically significant effect on real house prices, while only negative changes in housing sales have a small negative sign and a small increasing effect on housing prices. The fact that the positive and negative changes in real mortgage rates are negative and positive, respectively, indicates that both have a reducing effect on real housing prices.

This study suggests the first NARDL model that investigates the asymmetric effects on real housing prices instead of nominal housing prices for Turkey. In addition, the study is the first, to the best of the authors’ knowledge, to examine the effects of the five real variables on real housing prices.

The causal relationship between money and income (output) has been an important topic and has been extensively studied. However, those empirical studies are almost entirely on Granger-causality in the conditional mean. Compared to conditional mean, conditional quantiles give a broader picture of an economy in various scenarios. In this paper, we explore whether forecasting conditional quantiles of output growth can be improved using money growth information. We compare the check loss values of quantile forecasts of output growth with and without using past information on money growth, and assess the statistical significance of the loss-differentials. Using U.S. monthly series of real personal income or industrial production for income and output, and M1 or M2 for money, we find that out-of-sample quantile forecasting for output growth is significantly improved by accounting for past money growth information, particularly in tails of the output growth conditional distribution. On the other hand, money–income Granger-causality in the conditional mean is quite weak and unstable. These empirical findings in this paper have not been observed in the money–income literature. The new results of this paper have an important implication on monetary policy, because they imply that the effectiveness of monetary policy has been under-estimated by merely testing Granger-causality in conditional mean. Money does Granger-cause income more strongly than it has been known and therefore information on money growth can (and should) be more utilized in implementing monetary policy.

As a response to global population growth and increasing demand for food, farmers have been complementing traditional agriculture practices with vertical farming (VF) and indoor hydroponic systems. To facilitate the growth of the VF industry, this paper aims to identify business model elements and their configurations that lead to high firm performance.

The research goals were met by conducting literature reviews coupled with a fuzzy-set qualitative comparative analysis (fsQCA) on five business model elements, “superior” OR “strong” performance as two possible outcomes, and the top-ranked global VF growers listed in the Crunchbase Database.

From the fsQCA results, it was observed that several business model configurations lead to strong firm performance. Vertical farms growing in urban settings and having strong customer engagement platforms, coupled with a presence of business-to-business (B2B) sales channels, are more consistently associated with superior performance. These results imply that the decision configuration of location, along with customer engagement activity and sales activity are differentiating factors between good firm performance and superior firm performance in the case of vertical farms.

This paper contributes to expanding the knowledge of business model theory, business model configurations and VF management, providing specific guidelines for vertical farm owners and investors related to decision-making for higher firm performance, as well as positive environmental, social and economic impact.

The paper will concentrate on the Grounded Theory Methodology (GTM) from the point of view of the contemplative social sciences (CSS). It will analyze how the mind is engaged in the construction of concept and what the role is of the consciousness of the mind's work in creating a theory that is based on the analysis of empirical data. We will review the research and analytical methods that could be inspirations for Contemplative Grounded Theory (CGT): constructivist grounded theory, classic grounded theory, transformational grounded theory, sociological introspection, holistic ethnography, mindful inquiry and transformational phenomenology, and contemplative qualitative inquiry.

We can find in many classical books from grounded theory (GT) some seeds of contemplative thinking, and we can reconstruct them (Glaser and Strauss, 1967; Glaser, 1978; Strauss, 1987). We would like to develop the inspirations more and perhaps change the sense of GT after the contemplative turn. We would like to show the possibilities of using CGT in research and also its limitations. Some empirical examples from research and analysis will be given to show how contemplation could be used in GT.

The purpose of this paper is to investigate the relationship between the energy consumption and the economic growth in the USA and in a sectoral level by using monthly data from January 1991 to May 2016.

While assessing the relationship at a country level, the authors also examine five sectors by using quantile causality.

The findings indicate the existence of a causality at the sectoral level in tails. More specifically, industrial and electric sectors cause the growth at the lower and higher levels. Residential, commercial and transportation sectors do not cause the growth in all levels. Total consumption causes the growth in the middle and low levels but not in the high level. Finally, the empirical evidence signifies an asymmetric relationship between the covariates.

The results imply that when the consumption deals conditions with fluctuation, it is likely to be affected by growth. In such a case, energy policies gear toward reducing or increasing energy intensity, improving energy efficiency, encouraging the use of alternative sources and investing in the development of technology.

The authors use, for the first time, the quantile causality for the case of energy consumption and economic growth. The quantile test is useful for a thorough comprehension of the causal relationship for this area. Compared to the OLS, which is used for the majority of causality tests, the quantile investigates the causality at the sectoral level in the tails.

The purpose of the present study is to directly examine the relationship between bilateral exchange rate and stock market index in a bivariate framework during the period of the floating exchange rate regime in Thailand.

The monthly data used in this study are the stock market index or stock prices from the Stock Exchange of Thailand, and the nominal bilateral exchange rate in terms of baht per US dollar from the Bank of Thailand. The period covers July 1997 to June 2010 with 156 observations. This is the period that the country switched from fixed to floating exchange rate regime. The stock market return is calculated by the percentage change of stock market index (or stock prices) while the exchange rate return is the percentage change of the nominal bilateral exchange rate. Three estimation methods are used to capture the interaction between stock and foreign exchange markets: bounds testing for cointegration, non‐causality test, and the two‐step approach with a bivariate GARCH model and Granger causality test.

The results of the present study show that bounds testing for cointegration does not detect the long‐run relationship between stock prices and exchange rate. In addition, the non‐causality test fails the diagnostic test for multivariate normality in the residuals of the estimated VAR model. However, the two‐step approach adequately detects the linkages between the stock and foreign exchange markets. It is found that there exists positive unidirectional causality running from stock market return to exchange rate return. The exchange rate risk causes stock return to fall as expected. Moreover, there are bidirectional causal relations between stock market risk and exchange rate risk, but in different directions.

Since a rising trend in the risk in the foreign exchange market causes stock return to fall, both domestic and foreign investors should be aware of the risk or uncertainty in the foreign exchange market because it can cause their portfolio return to fall. For policymakers, reducing exchange rate risk cannot be done without the associated costs from a rising risk in the stock market.

This study provides an evidence of volatility (or risk) spillovers in stock and foreign exchange markets. In addition, the risk in foreign exchange market that adversely affects return in the stock market is an expected phenomenon under the floating exchange rate regime.

The purpose of this paper is to explore the contribution made by the balanced scorecard (BSC) in regaining the practice relevance of management accounting research.

Using discourse analysis, the paper investigates the speech genre in use in main BSC texts.

The authors' analysis reveals that the BSC is defined in a way that can provide management with a type of general overarching model. However, the model lacks realistic scholarly characteristics and instead it exhibits characteristics of a myth speech genre. This is especially so in the presentation of the central concern with cause‐effect statements in the BSC.

The authors' analysis, therefore, suggests that methodological issues relating to the usage of cause and effect statements must be solved if research, such as that carried out in the BSC development, is to become more relevant to practice. To overcome this problem and regain research relevance, the paper recommends a more scholarly speech genre, giving more attention to various usages of inferential statements and specifically a pragmatic constructivist perspective for analyzing construct causalities.

The paper advocates a scholarly methodological basis as a requirement for accounting innovation to enable it to solve practice problems in a way that improves practice and hence increases relevance of research.

The purpose of this paper is to examine the linear and nonlinear relations between returns volatility and trading volume for the Indian currency futures market.

To examine the contemporaneous relation between returns volatility and volume, the author uses the generalized method of moment estimator. For the linear causal relation, the author makes use of Granger (1969) bivariate vector autoregression model. The author tests for nonlinear Granger causality between returns volatility and trading volume based on a modified version of the Baek and Brock (1992) nonparametric technique developed by Hiemstra and Jones (1994).

The results indicate a negative contemporaneous relation between returns volatility and trading volume; therefore, the mixture of distribution hypothesis is not supported. The results of both linear and nonlinear Granger causality between futures returns volatility and trading volume indicate a significant bidirectional relation between the two variables lending support to the sequential arrival of information hypothesis. The results are robust to divergence of opinions as proxied by open interest.

The findings of this paper are important for the participants in the market and regulators. The participants in the market require alternatives to diversify their risk. The significant causal relation between returns volatility and trading volume implies that trading volume helps predict the futures prices and should lead to creation of more reliable hedging strategies for investment purposes. Furthermore, it may interest the regulators who need to decide upon the appropriateness of their policies in the currency futures market.

To the best of the author’s knowledge, there is no study that investigates the forecast ability of trading volume to futures returns volatility in an emerging currency futures market. Given that currency futures market is one of the largest markets in the world, and Indian rupee has seen wide fluctuations in the recent years, it seems exciting to explore the price–volume relation in the Indian currency futures market.