Term structure forecasting in affine framework with time-varying volatility

This study extends the affine Nelson–Siegel model by introducing the time-varying volatility component in the observation equation of yield curve, modeled as a standard EGARCH process. The model is illustrated in state-space framework and empirically compared to the standard affine and dynamic Nelson–Siegel model in terms of in-sample fit and out-of-sample forecast accuracy. The affine based extended model that accounts for time-varying volatility outpaces the other models for fitting the yield curve and produces relatively more accurate 6- and 12-month ahead forecasts, while the standard affine model comes with more precise forecasts for the very short forecast horizons. The study concludes that the standard and affine Nelson–Siegel models have higher forecasting capability than their counterpart EGARCH based models for the short forecast horizons, i.e., 1 month. The EGARCH based extended models have excellent performance for the medium and longer forecast horizons.     

Is There a Link Between Poverty and Food Security?

The study examines cointegration and causal relationship between FDI, terrorism and economic growth in Pakistan using quarterly frequencies for the period 1988–2010. For empirical analysis data is divided into two sub-periods i.e. pre 9/11 (1988–2001) and post 9/11 (2002–2010) periods. The results show that long run cointegration holds between FDI, terrorism and economic growth. Granger causality results indicate that there is bidirectional short and long run causality between economic growth and FDI for both sub-samples. These findings are supported by variance decomposition and impulse response analysis. The findings suggest applicability of modernization theory to explain FDI and economic growth relationship. The results also reveal that terrorism has a deteriorating impact on FDI.     

Dynamics of the term structure of interest rates and monetary policy: is monetary policy effective during zero interest rate policy?

The monetary policy targets the short rates; however, during zero interest rate policy (ZIRP), the short end of the yield curve cannot serve as a policy instrument. Relying on the joint yields-macro latent factors model, this study empirically examines the effect of monetary policy stances on term structure and the possible feedback effect on the real sector using the Japanese experience of ZIRP. The analysis indicates that it is the entire term structure that transmits the policy shocks to the real economy rather than the yield spread only. The monetary policy signals pass through the yield curve level and slope factors to stimulate the economic activity. The curvature factor, besides reflecting the cyclical fluctuations of the economy, acts as a leading indicator for future inflation. In addition, policy influence tends to be low as the short end becomes segmented toward medium/long-term of the yield curve. Furthermore, volatility in bond markets is found to be asymmetrically affected by positive and negative shocks and long end tends to be less sensitive to stochastic shocks than the short maturities. The expectation hypothesis of the term structure does not hold during the ZIRP period.     

Working Therapeutically with Indian Families within a New Zealand Context

This article aims to raise awareness amongst non‐Indian therapists working with Indian people by highlighting some of the important aspects of Indian culture within the New Zealand context. Although there is a great deal of diversity amongst Indians, there are some fundamental issues that would have relevance for most Indians. Specific issues relating to immigrant families are discussed, such as the sacrifices made by families in the hope of providing a better future for their children and the difficulties encountered by new migrants. The cultural clash for young people caught between parental expectations and peer pressure can often lead to significant family conflict. Some of the common pitfalls for non‐Indian therapists working with Indian people are outlined and suggestions made in relation to the process of therapy.     

Critical success factors of TQM: A select study of Indian organizations

In the context of TQM, it is essential that the organizations identify a few key critical success factors, which should be given special attention for ensuring successful implementation of TQM program. The concept of critical success factors (CSFs) and their use in supporting planning efforts was originated from the approach associated with the development and implementation of management information systems. This paper represents a review of the literature on CSFs and supported by various philosophies of TQM. Such factors are considered as conducive to the success of TQM implementation. Based on an exploratory study of Indian organizations engaged in manufacturing and services, CSFs have been identified.     

Generalized Nelson–Siegel term structure model: do the second slope and curvature factors improve the in-sample fit and out-of-sample forecasts?

The dynamic Nelson–Siegel (DNS) model and even the Svensson generalization of the model have trouble in fitting the short maturity yields and fail to grasp the characteristics of the Japanese government bonds yield curve, which is flat at the short end and has multiple inflection points. Therefore, a closely related generalized dynamic Nelson–Siegel (GDNS) model that has two slopes and curvatures is considered and compared empirically to the traditional DNS in terms of in-sample fit as well as out-of-sample forecasts. Furthermore, the GDNS with time-varying volatility component, modeled as standard EGARCH process, is also considered to evaluate its performance in relation to the GDNS. The GDNS model unanimously outperforms the DNS in terms of in-sample fit as well as out-of-sample forecasts. Moreover, the extended model that accounts for time-varying volatility outpace the other models for fitting the yield curve and produce relatively more accurate 6- and 12-month ahead forecasts, while the GDNS model comes with more precise forecasts for very short forecast horizons.