Contemporaneous-threshold smooth transition GARCH models

This paper proposes a contemporaneous-threshold smooth transition GARCH (or C-STGARCH)model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization tosecond conditional moments of the contemporaneous smooth transition threshold autoregressive model of Dueker et al. (2007) in which the regime weights depend on the ex ante probability that a contemporaneous latent regime-specific variable exceeds a threshold value. A key feature of the C-STGARCH model is that its transition function depends on all the parameters of the model as well as on the data. The structural properties of the model are investigated, in addition to the finite-sample properties of the maximum likelihood estimator of its parameters. An application to U.S. stock returns illustrates the practical usefulness of the C-STGARCH model

Monetary Policy Rules and Directions of Causality: a Test for the Euro Area

Using a VAR model in first differences with quarterly data for the euro zone, the study aims to ascertain whether decisions on monetary policy can be interpreted in terms of a “monetary policy rule” with specific reference to the so-called nominal GDP targeting rule (Hall and Mankiw, 1994; McCallum, 1988; Woodford, 2012). The results obtained indicate a causal relation proceeding from deviation between the growth rates of nominal gross domestic product (GDP) and target GDP to variation in the three-month market interest rate. The same analyses do not, however, appear to confirm the existence of a significant inverse causal relation from variation in the market interest rate to deviation between the nominal and target GDP growth rates. Similar results were obtained on replacing the market interest rate with the European Central Bank refinancing interest rate. This confirmation of only one of the two directions of causality does not support an interpretation of monetary policy based on the nominal GDP targeting rule and gives rise to doubt in more general terms as to the applicability of the Taylor rule and all the conventional rules of monetary policy to the case in question. The results appear instead to be more in line with other possible approaches, such as those based on post Keynesian analyses of monetary theory and policy and more specifically the so-called solvency rule (Brancaccio and Fontana, 2013, 2015). These lines of research challenge the simplistic argument that the scope of monetary policy consists in the stabilization of inflation, real GDP, or nominal income around a “natural equilibrium” level. Rather, they suggest that central banks actually follow a more complex purpose, which is the political regulation of the financial system with particular reference to the relations between creditors and debtors and the related solvency of economic units

Contemporaneous threshold autoregressive models: Estimation, testing and forecasting

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta [1998. Modelling economic relationships with smooth transition regressions. In: Ullah, A., Giles, D.E.A. (Eds.), Handbook of Applied Economic Statistics. Marcel Dekker, New York, pp. 507–552.], in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well suited to rational expectations applications (and pricing exercises), in that it does not require the initial regimes to be predetermined. We investigate the properties of the model and evaluate its finite-sample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen [1992. The likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP. Journal of Applied Econometrics 7, S61–S82.] procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed

The term structure of interest rates and the Mexican economy

Can the yield spread, which has been found to predict with surprising accuracy the movement of key macroeconomic variables of developed countries, also predict such variables for a developing country experiencing economic turmoil? This article presents empirical results that suggest significant forecasting ability for the yield spread for segments of the Mexican economy during the 1995-1997 period of economic volatility. The actual and predicted variable changes sometimes conflict with those experienced by developed countries in part because of the unusually close relationship between the Mexican Treasury and the Banco de México. Consequently, analysts and policy officials may exploit the forecast potential of the yield spread, but only in the context of evolving institutional considerations. Copyright 2000 Western Economic Association International.

CAN LEADING BUSINESS CYCLE INDICATORS PREDICT THE DIRECTION OF THE SOUTH AFRICAN COMMERCIAL SHARE PRICE INDEX?

Leading indicators are a popular way to predict turning points in the business cycle. However, since the lead time of these indicators differ, those with a longer lead could potentially also be used to predict turning points in other leading indicators. This paper empirically explores the viability of using leading indicators to predict the turning points of an index of commercial shares on the JSE Securities Exchange. Although share prices are leading the business cycle, other leading indicators that lead the business cycle by a longer period should lead share prices and, therefore, could potentially be useful in predicting the direction of share price movements. Copyright 2005 Economic Society of South Africa.

Common genetic variation indicates separate causes for periventricular and deep white matter hyperintensities

BACKGROUND AND PURPOSE: Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genomewide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. METHODS: Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. RESULTS: In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genomewide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. CONCLUSIONS: Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.Nicola J. Armstrong, Karen A. Mather, Muralidharan Sargurupremraj, Maria J. Knol, Rainer Malik, Claudia L. Satizabal ... et al