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This paper aims to examine the relationship between trade and economic growth using data of UAE economy for the period of 1974-2011.

The bounds testing is applied for testing the cointegration relationship between the variables. The rolling window approach has been used to analyze the stability of long run coefficients.

The empirical analysis shows the presence of cointegration between trade and economic growth. Furthermore, exports have positive, but imports have negative effect on economic growth. The rolling window approach confirms the stability of long-run estimates.

This paper provides new insights for policymakers to use trade as economic tool for sustainable economic development.

This paper makes a unique contribution to the literature with reference to UAE, being a pioneering attempt to investigate the relationship between trade and economic growth by using long time series data and applying more rigorous techniques like time varying rolling window analysis.

The purpose of this study is to construct a financial conditions index (FCI) for the South African economy to enable the gauging of financial conditions and to better understand the macro-financial linkages in the country. The global financial crisis that began in 2007-2008 demonstrated how severe the impact of financial markets’ stress on real economic activity can be. In the wake of the financial crisis, policy-makers and decision-makers across the world identified the critical need for a better understanding of financial conditions, and more importantly, their impact on the real economy.

The FCI is constructed using monthly data over the period 1966 to 2011, and is based on a set of 16 financial variables, which include variables that define the state of international financial markets, asset prices, interest rate spreads, stock market yields and volatility, bond market volatility and monetary aggregates. The authors explore different methodologies for constructing the FCI, including full sample and rolling-window principal components analysis. Furthermore, the authors investigate whether it is beneficial to purge the FCI of the real effects of inflation, economic growth and interest rates, and evaluate the performance of our constructed FCIs by comparing their ability to pick up turning points in the South African business cycle, and by running in-sample causality (forecast) tests.

The authors find that the estimated FCIs are good predictors of economic activity; with the rolling-window FCI being the “best” performing index. Causality tests indicate that this FCI is a good in-sample predictor of industrial production growth and the Treasury Bill rate, but a weak predictor of inflation.

The authors find that the resulting FCI can act as an “early warning system”. This, in turn, may serve to indicate that monetary policy should take broader financial conditions into account.

This study offers three main contributions to the existing literature on financial conditions in South Africa: the authors construct an FCI over a sample period that is three decades longer than existing indices, the FCI of this paper comprises a wider coverage of financial variables than others and the authors make use of rolling-window estimation techniques that allow them to account for parameter instability and to capture the real-time constraints faced by a policymaker.

This paper aims to test empirically the performance of different models in measuring VaR and ES in the presence of heavy tails in returns using historical data.

Daily returns of popular indices (S&P500, DAX, CAC, Nikkei, TSE, and FTSE) and currencies (US dollar vs Euro, Yen, Pound, and Canadian dollar) for over ten years are modeled with empirical (or historical), Gaussian, Generalized Pareto (peak over threshold (POT) technique of extreme value theory (EVT)) and Stable Paretian distribution (both symmetric and non‐symmetric). Experimentation on different factors that affect modeling, e.g. rolling window size and confidence level, has been conducted.

In estimating VaR, the results show that models that capture rare events can predict risk more accurately than non‐fat‐tailed models. For ES estimation, the historical model (as expected) and POT method are proved to give more accurate estimations. Gaussian model underestimates ES, while Stable Paretian framework overestimates ES.

Research findings are useful to investors and the way they perceive market risk, risk managers and the way they measure risk and calibrate their models, e.g. shortcomings of VaR, and regulators in central banks.

A comparative, thorough empirical study on a number of financial time series (currencies, indices) that aims to reveal the pros and cons of Gaussian versus fat‐tailed models and Stable Paretian versus EVT, in estimating two popular risk measures (VaR and ES), in the presence of extreme events. The effects of model assumptions on different parameters have also been studied in the paper.

The purpose of this paper is to investigate the causal link between foreign direct investment (FDI) and exports in China based on the knowledge capital model (KK model, Markusen, 2002).

The bootstrap Granger full-sample and sub-sample rolling window causality test is used to determine whether FDI can promote exports.

The full-sample causality test indicates no causal relationship from FDI to exports. However, considering structural changes of exports and FDI, the authors’ find that the full-sample test is not reliable. Instead, the authors use the rolling window causality test to revisit the dynamic causal relationship, and the results present significant effects from FDI on exports, mostly around periods in which the proportion of FDI from Hong Kong, Macao and Taiwan is increasing. Specifically, positive impacts of FDI on exports are stronger than the negative impacts in China.

The findings in this study suggest a significant time-varying nature of the correlation between FDI and exports. The promotion effect of FDI to exports is proved by the rolling window approach; it thus supports the KK model that divides FDI into lateral FDI and vertical FDI and proves that the constitution of FDI is critical to the relationship between FDI and exports.

China has been facing adjustment of its economic structure in recent years, and in this situation, increasing the proportion of FDI that can bring advanced production function is critical for the industrial structural adjustment.

This paper uses the bootstrap rolling window causality test to investigate the time-varying nature of the causality between FDI and exports, considering structural changes for the first time. The authors further deepen the previous research and draw a more realistic conclusion.

The study is intended to find out the relationship between housing prices and the inflow of foreign capital in Pakistan. There is a shortage of housing units due to rising population and rural–urban migration since its inception; on the other hand, there is also a lack of housing finances. The urban sprawl has created the demand for housing units, but the supply of housing has not been increased up to the required level, the major reason is a deficiency of housing finances.

The analysis was carried out from 1973 to 2018, on an annual, quarterly and monthly basis; the structural changes are captured by the Zivot–Andrews unit root test. Gregory–Hansen test is used for cointegration, the combined cointegration also validates the results. In addition, the rolling window is used to capture timely changes between data sets. Finally, wavelet analysis is used to prove volatility.

The rising prices of housing in the country is alarming; Pakistan is a developing country, and it is facing many problems along with a housing shortage. The domestic sources of housing finances are inadequate, so foreign funds are welcomed. The rolling window regression proves that domestic factors along with the foreign capital inflow affect housing prices positively, and the wavelet analysis finds out that foreign direct investment is more volatile than workers’ remittances in financing the housing market.

This is a pioneering study to find out the impact of foreign capital inflows on the housing prices in the economy of Pakistan. The inadequacy of housing finances from domestic sources attracted foreign funds financing this sector. This study has used new techniques like rolling window and wavelet transformation, such techniques have not been used before.

The purpose of this paper is to investigate the impact of changes in credit stock on real and financial indicators in Turkey with a focus on conditional and time-varying dynamics.

In addition to lag-augmented vector autoregression (LA-VAR) based time-varying Granger causality tests, threshold models and a research setting that identifies high/low states of credit growth based on 24-month moving averages are used to explore regime-dependent behavior. For investigating the asymmetric dynamics, the authors use a methodology that identifies good/bad news in credit growth based on 24-month moving averages and standard deviations.

Results strongly suggest that the impact of changes in credit stock induces conditional responses. Moreover, we find evidence for asymmetric responses. In the case of Turkey, efforts to spur growth through credit produce a strong negative byproduct, a depreciation in the exchange rate. The authors also find that changes in credit stock have become more relevant for uncertainties in inflation and exchange rate expectations, particularly in the era after mid-2018 in which credit growth volatility has increased noticeably.

This study provides a comprehensive analysis of time-varying and conditional responses to a change in credit stock in a major emerging economy. Using a moving threshold based only on the available information in the analysis of state-dependency represents a new approach.

The purpose of this paper is to report on a sequential three-stage analysis of inflation persistence using monthly data from 11 inflation targeting (IT) countries and, for comparison, the USA, a non-IT country with a history of credible monetary policy.

First, the authors estimate inflation persistence in a rolling-window fractional-integration setting using the semiparametric estimator suggested by Phillips (2007). Second, the authors use tests for unknown structural breaks as a means to identify effects of the regime switch and the global financial crisis on inflation persistence. The authors use the sequences of estimated persistence measures from the first stage as dependent variables in the Bai and Perron (2003) structural break tests. Finally, the authors reapply the Phillips (2007) estimator to the subsamples defined by the breaks.

Four countries (Canada, Iceland, Mexico, and South Korea) experience a structural break in inflation persistence that coincide with the implementation of the IT regime, and three IT countries (Sweden, Switzerland, and the UK), as well as the USA experience a structural break in inflation persistence that coincides with the global financial crisis.

The authors find that in most cases the estimates of inflation persistence switch from mean-reversion nonstationarity to mean-reversion stationarity.

Monetary policy implications differ between pre- and post-global financial crisis.

Global financial crisis affected the persistence of inflation rates.

First paper to consider the effect of the global financial crisis on inflation persistence.

The observed diagnostic symptoms are often characterized by local fluctuations of their values. Hence, instead of direct observation of symptoms it is worth observing their grey models and research similarity between life curves, which can enable to guess the nature of wear. The purpose of this paper is to find useful measures of similarity of diagnostics symptoms modeled by GM(1,1).

Measures of similarity may be used to determine the character of wear of the diagnosed object by way of comparison with known examples, which have previously been obtained and identified. A methodology for creation of such comparisons based on pre-smoothing by means of a GM(1,1) model with rolling window has been proposed. The process of smoothing enables to eliminate local fluctuations of a symptom. Their existence makes it difficult to compare symptoms. Application of a rolling window enables in turn to map the symptom properly, which may be difficult in the case of relatively short period of accelerated wear and changes of symptom values. To compare the life curves it is also necessary to normalize the life curves, so that they are represented by the same number of measurements (compression or extension of the measure of operation).

The paper concerns the similarity measures for symptom life curves obtained during vibration monitoring of fan mills working at a heat and power station. Similarity measures of symptoms were proposed and applied to the acquired data from the machines.

The method of symptom modeling and life curve comparing can be used to discover type of wear of the machine and eventually estimation of the remaining useful life.

The proposed method is very important for development of condition monitoring.

The purpose of this paper is to construct a financial development index (FDI) for the Indian economy and also examine the relationship between FDI and economic growth.

Augment Dickey Fuller, Phillips Perron and Ng Perron unit root tests are employed in order to determine the level of integration. The long‐ and short‐run dynamics are obtained by using auto‐regressive distributed lag approach to cointegration and rolling window approach to estimate coefficient of each observation.

The results indicate that long‐run relationship is presented among the economic growth, FDI, real‐interest rate (RIR), labor force and capital. But FDI negatively associated with economic growth in the case of long‐ and short‐run and RIR also negatively determine the economic growth only in the long run. The rolling regression result confirms that FDI negatively associated to growth in the years of 1978, 1979, 1984‐1987, 1990, 1996‐2000, 2004 and 2005 and RIR is impede economic growth in the years of 1978, 1979, 1986, 1988‐1997, 2001, 2002, 2006 and 2008.

The paper constructs an FDI for the Indian economy by using the four indicators of financial development. The findings are useful for India's policy makers in order to maintain the parallel expansion of financial development and economic growth.

The purpose of this study is to investigate the impact of foreign capital inflows and economic growth on stock market capitalization in Pakistan by using the annual time series data from the period of 1976 to 2011.

The autoregressive distributed lag bound testing cointegration approach, the error correction model and the rolling window estimation procedures have been performed to analyze the long run, short run and behavior of coefficients, respectively.

Results indicate that foreign direct investment (FDI), workers’ remittances and economic growth have significant positive relationship with the stock market capitalization in long run as well as in short run. Results of the dynamic ordinary least square and the fully modified ordinary least square suggest that the initial results of long-run coefficients are robust. Results of variance decomposition test show the bidirectional causal relationship of FDI and economic growth with stock market capitalization. However, unidirectional causal relationship is found in between workers’ remittances and stock market capitalization.

It is suggested that in Pakistan, investors can make their investment decisions through keeping an eye on the direction of the considered foreign capital inflows and economic growth.

This paper makes a unique contribution to the literature with reference to Pakistan, being a pioneering attempt to investigate the effects of foreign capital inflows and economic growth on stock market by using long time series data and applying more rigorous techniques.