885 research outputs found
Saving-Economic Growth Nexus In Nigeria, 1970-2007: Granger Causality And Co-Integration Analyses
No full textThe controversy surrounding the direction of causality between saving and economic growth motivated this study. The author employed the Granger-causality and co-integration techniques to analyze the relationship between saving and economic growth in Nigeria during the period 1970-2007. The Johansen co-integration test indicates that the variables (economic growth and saving) are co-integrated, and that a long-run equilibrium exists between them. In addition, the granger causality test reveals that causality runs from economic growth to saving, implying that economic growth precedes and granger causes saving. Thus, we reject the Solow’s hypothesis that saving precedes economic growth, and accept the Keynesian theory that t is economic growth that leads to higher saving. The author recommends that government and policy makers should employ policies that would accelerate economic growth so as to increase saving.economic growth, saving, granger causality, co-integration.
Statistical Inference for Local Granger Causality
No full textGranger causality has been employed to investigate causality relations between components of
stationary multiple time series. We generalize this concept by developing statistical inference
for local Granger causality for multivariate locally stationary processes. Our proposed local
Granger causality approach captures time-evolving causality relationships in nonstationary processes. The proposed local Granger causality is well represented in the frequency domain and
estimated based on the parametric time-varying spectral density matrix using the local Whittle
likelihood. Under regularity conditions, we demonstrate that the estimators converge to multivariate normal in distribution. Additionally, the test statistic for the local Granger causality is
shown to be asymptotically distributed as a quadratic form of a multivariate normal distribution. For practical demonstration, the proposed local Granger causality method uncovered new
functional connectivity relationships between channels in brain signals. Moreover, the method
was applicable to topological data analysis to identify structural changes in financial data.
Key words and phrases: Brain signals, Local Granger causality, Local Whittle likelihood, Multivariate locally stationary processes, Time-varying spectral density matrix, Topological data
analysisThe authors would like to thank the two anonymous referees for their constructive suggestions. This paper has benefited considerably from those comments. The first author gratefully acknowledge JSPS Grant-in-Aid for Young Scientists (B) 17K12652 and JSPS Grant-in-Aid for Scientific Research (C) 20K11719. The second author gratefully acknowledge JSPS Grant-in-Aid for Scientific Research (S) 18H05290 The third author gratefully acknowledge the KAUST Research Fund. The first two authors also would like to express their thanks to the Institute for Mathematical Science (IMS), Waseda University, for their support for this research
Preclinical evaluation of the effect of the combined use of the Ethicon Securestrap® Open Absorbable Strap Fixation Device and Ethicon Physiomesh™ Open Flexible Composite Mesh Device on surgeon stress during ventral hernia repair [Corrigendum]
No full textSutton N, MacDonald MH, Lombard J, et al. [Med Devices (Auckl)]. 2018;11:1–9. On page 1, the co-author’s name was incorrectly listed as Bodgan Ilie. His correct name should be Bogdan Ilie. Read the original articl
The distributional properties of shocks to a fractional I(d) process having a marginal exponential distribution
No full textThis paper establishes practical criteria for selecting amongst hypothetical data generating processes in cases where the series has long memory and exponential distribution which implies that the innovations have extremely fat tails. Keywords: long memory process, absolute returns. JEL classification: C2 Corresponding author: Department of Economics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0508, USA. Research for this paper was supported by NSF grant SBR-9708615. 1 Introduction It is now a well established empirical fact that the absolute returns from daily stock prices have temporal properties similar to fractionally integrated, or I(d), process, see for example Ding, Granger and Engle (1993), Granger and Ding (1996), Granger, Ding and Spear (1997) and Mills (1997). It has also been shown that these absolute returns, after removal of outliers greater than 4oe, which are about 7 values per thousand terms, have a marginal distribution that appear..
Granger causality and equilibrium business cycle theory
No full textPostwar U.S. data show that consumption growth "Granger-causes" output and investment growth, which is puzzling if technology is the driving force of the business cycle. The author asks whether general equilibrium models with information frictions and non-technology shocks can rationalize the observed causal relationships. His conclusion is they cannot.Business cycles
The Canadian underground and measured economies: Granger causality results
No full textUsing new time-series data for the size of the Canadian underground economy, the relationship between unreported and measured GDP in that country is examined. Granger causality tests are conducted, with a proper allowance for the non-stationarity of the data. It is found that there is clear evidence of such causality from measured GDP to 'hidden' output, but only very mild evidence of Granger causality in the reverse direction. This result supports similar evidence for New Zealand reported by the first author, and has several interesting policy implications.
The Canadian Underground and Measured Economies: Granger Causality Results
No full textUsing new time-series data for the size of the Canadian underground economy, the relationship between unreported and measured GDP in that country is examined. Granger causality tests are conducted, with a proper allowance for the non-stationarity of the data. It is found that there is clear evidence of such causality from measured GDP to hidden output, but only very mild evidence of Granger causality in the reverse direction. This result supports similar evidence for New Zealand reported by the first author, and has several interesting policy implications
The Canadian Underground and Measured Economies: Granger Causality Results
No full textUsing new time-series data for the size of the Canadian underground economy, we examine the relationship between unreported and measured GDP in that country. Granger causality tests are conducted, with a proper allowance for the non-stationarity of the data. We find that there is clear evidence of such causality from measured GDP to "hidden" output, but only very mild evidence of Granger causality in the reverse direction. This result supports similar evidence for New Zealand reported by the first author, and has several interesting policy implications.Hidden Economy, Underground Economy, Tax Avoidance, Tax Evasion, Causality
Exploring the Use of Granger Causality for the Identification of Chemical Exposure Based on Physiological Data
No full textWearable sensors offer new opportunities for the early detection and identification of toxic chemicals in situations where medical evaluation is not immediately possible. We previously found that continuously recorded physiology in guinea pigs can be used for early detection of exposure to an opioid (fentanyl) or a nerve agent (VX), as well as for differentiating between the two. Here, we investigated how exposure to these different chemicals affects the interactions between ECG and respiration parameters as determined by Granger causality (GC). Features reflecting such interactions may provide additional information and improve models differentiating between chemical agents. Traditional respiration and ECG features, as well as GC features, were extracted from data of 120 guinea pigs exposed to VX (n = 61) or fentanyl (n = 59). Data were divided in a training set (n = 99) and a test set (n = 21). Minimum Redundancy Maximum Relevance (mRMR) and Support Vector Machine (SVM) algorithms were used to, respectively, perform feature selection and train a model to discriminate between the two chemicals. We found that ECG and respiration parameters are Granger-related under healthy conditions, and that exposure to fentanyl and VX affected these relationships in different ways. SVM models discriminated between chemicals with accuracy of 95% or higher on the test set. GC features did not improve the classification compared to traditional features. Respiration features (i.e., peak inspiratory and expiratory flow) were the most important to discriminate between different chemical’s exposure. Our results indicate that it may be feasible to discriminate between chemical exposure when using traditional physiological respiration features from wearable sensors. Future research will examine whether GC features can contribute to robust detection and differentiation between chemicals when considering other factors, such as generalizing results across speciesSignal Processing System
Stock Market Informational Efficiency in Germany: Granger Causality between DAX and Selected Macroeconomic Indicators
No full textAbstractThis study analyzes relationship between macroeconomic indicators and stock market in Germany. Aim of this paper is to answer the question how stock market reflects economic conditions and if stock market is informational efficient. Toda-Yamamoto (1995) approach is used for testing Granger causality. Bivariate analysis is performed on monthly data from January 1999 to September 2015, and six macroeconomic indicators are examined: industrial production, inflation, money supply, interest rate, trade balance and exchange rate. Analysis applies unit root tests, testing for cointegration using the Johansen methodology and Wald test for linear restriction to check Granger causality
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