Time series analysis of a predator–prey system: Application of VAR and generalized impulse response function

2007 ◽  
Vol 60 (3) ◽  
pp. 605-612 ◽  
Author(s):  
Bradley T. Ewing ◽  
Kent Riggs ◽  
Keith L. Ewing
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Impulse Response ◽  
Response Function ◽  
System Application ◽  
Impulse Response Function ◽  
Predator Prey ◽  
Series Analysis ◽  
Prey System

scholarly journals Metapopulation dynamics of a persisting predator–prey system in the laboratory: time series analysis

1997 ◽  
Vol 21 (6/7) ◽  
pp. 415-430 ◽  
Author(s):  
Arne Janssen ◽  
Erik van Gool ◽  
Robert Lingeman ◽  
Josep Jacas ◽  
Gerrit van de Klashorst
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Metapopulation Dynamics ◽  
Predator Prey ◽  
Series Analysis ◽  
Prey System ◽  
Laboratory Time

Time series analysis of wind speed using VAR and the generalized impulse response technique

2007 ◽  
Vol 95 (3) ◽  
pp. 209-219 ◽  
Author(s):  
Bradley T. Ewing ◽  
Jamie Brown Kruse ◽  
John L. Schroeder ◽  
Douglas A. Smith
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Time Series Analysis ◽  
Impulse Response ◽  
Series Analysis

Hilbert Transformation Impulse Response

2014 ◽  
Vol 19 (4) ◽  
pp. 27-35
Author(s):  
Mariusz Sulima
Keyword(s):  
Time Series ◽  
Impulse Response ◽  
Response Function ◽  
Signal To Noise Ratio ◽  
Impulse Response Function ◽  
Equation System ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Signal To Noise ◽  
Input Time

Abstract This work presents a new DHT impulse response function based on the proposed nonlinear equation system obtained as a result of combining the DHT and IDHT equation systems. In the case of input time series with selected characteristics, the DHT results obtained using this impulse response function are characterised by a higher accuracy compared to the DHT results obtained based on the convolution using other known DHT impulse response functions. The results are also characterised by a higher accuracy than the DHT results obtained using the popular indirect DHT method based on discrete Fourier transform (DFT). Analysis of these example time series with selected characteristics was performed based on the signal-to-noise ratio.

scholarly journals A Study On The Productivity Of Koreas Industrial Sector With IT Technology Capital And R&D Stocks Variation

2011 ◽  
Vol 1 (10) ◽  
Author(s):  
Chuhwan Park ◽  
Tae-Woong Park ◽  
Byoung-Moo Heo
Keyword(s):  
Time Series ◽  
Granger Causality ◽  
Impulse Response ◽  
Response Function ◽  
Function Analysis ◽  
Impulse Response Function ◽  
Industrial Sector ◽  
Response Analysis ◽  
Industrial Growth ◽  
Time Periods

This paper examines the effects of IT technology capital and R&D stocks variation on the growth of Koreas industries with time series approaches. In detail, we analyze the Granger causality and impulse response analysis among the Koreas industrial growth, IT technology capital, and R&D stocks. When it comes to this research conclusion, we know that IT technology capital and R&D stocks shocks affect the growth of Koreas industrial sector. However, the revere effect is ambiguous in each industrial sector. Also, the impulse response function analysis shows that the effect of IT technology capital and R&D stocks fluctuation in each industrial sector is presented with different time periods.

scholarly journals Exploring river–aquifer interactions and hydrological system response using baseflow separation, impulse response modelling and time series analysis in three temperate lowland catchments

2021 ◽  
Author(s):  
Min Lu ◽  
Bart Rogiers ◽  
Koen Beerten ◽  
Matej Gedeon ◽  
Marijke Huysmans
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Impulse Response ◽  
Groundwater Level ◽  
System Response ◽  
Hydrograph Separation ◽  
Series Analysis ◽  
Baseflow Separation ◽  
Hydrological System ◽  
Response Modelling

Abstract. Lowland rivers and shallow aquifers are closely coupled and their interactions are crucial for maintaining healthy stream ecological functions. In order to explore river–aquifer interactions and lowland hydrological system in three Belgian catchments, we apply a combined approach of baseflow separation, impulse response modelling and time series analysis over a 30–year study period at catchment scale. Baseflow from hydrograph separation shows that the three catchments are groundwater-dominated. The recursive digital filter methods generate a smoother baseflow time series than the graphical methods, and yield more reliable results than the graphical ones. Impulse response modelling is applied with a two–step procedure. The first step where groundwater level response is modelled shows that groundwater level in shallow aquifers reacts fast to the system input, with most of the wells reaching their peak response during the first day. There is an overall trend of faster response time and higher response magnitude in the wet (October–March) than the dry (April–September) periods. The second step of baseflow response modelling shows that the system response is also fast and that simulated baseflow can capture some variations but not the peaks of the separated baseflow time series. The time series analysis indicates that components such as interflow and overland flow, contribute significantly to stream flow. They are somehow included as part of the separated baseflow, which is likely to be overestimated from hydrograph separation. The impulse response modelling approach from the groundwater flow perspective can be an optional method to estimate the baseflow, since it considers some level of the physical connection between river and aquifer in the subsurface. Further research is however recommended to improve the simulation, such as giving more weight to wells close to the river and adding more drainage dynamics to the model input.

Does Eurobond issuance influence FDI location? Evidence from sub-Saharan Africa

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lord Mensah ◽  
Eric B. Yiadom ◽  
Raymond Dziwornu
Keyword(s):  
Time Series ◽  
Causal Relationship ◽  
Granger Causality ◽  
Impulse Response ◽  
Response Function ◽  
Impulse Response Function ◽  
Var Model ◽  
Fdi Inflows ◽  
Content Type ◽  
Sub Saharan

PurposeDoes the issuance of Eurobonds carry enough information about favourable domestic conditions to warrant more FDI inflows? In this study, the authors investigate how FDI is responding to the rising levels of Eurobonds in sub-Saharan African (SSA).Design/methodology/approachThe study uses the system GMM model to set up a panel with all 17 SSA countries with Eurobonds. The dataset was transformed into time series, and the VAR model and Granger causality were used to diffuse the doubt of a possible bi-causal relationship between Eurobonds and FDI. Additionally, the authors use the impulse response function to test the behaviour of FDI to a one-time shock to Eurobonds.FindingsThe study reports that Eurobond levels matter in explaining FDI receipts. Specifically, the authors report that the issuance of Eurobonds leads to a favourable increase in FDI inflows. The authors transform our data into time series and use the VAR model and Granger causality test to diffuse the doubt of a possible bi-causal relationship between Eurobonds and FDI. The authors’ findings from this exercise suggest that two lag levels of Eurobond are a good predictor of future FDI flows. More also, the authors use the impulse response function to test the behaviour of FDI to a one-time shock to Eurobonds and report that a one-unit standard deviation shock to Eurobonds will cause FDI to swell up over at least 8 years.Research limitations/implicationsThe study is limited in scope due to data availability. Future studies may consider using countries across the globe that have issued Eurobond to retest the current research objectives.Practical implicationsThe study establishes grounds to suggest that the issuance of Eurobonds carry enough information to foreign investors in deciding on the location of FDI.Originality/valueThe study is uniquely opening a new frontier to the discussion on how one international capital can be used to bait other foreign capital. It also discusses signalling theory at the macro level.

scholarly journals PENGELUARAN PEMERINTAH DI MALUKU: ANALISIS VECTOR AUTOREGRESSIVE

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Jacobus Cliff Diky Rijoly
Keyword(s):  
Time Series ◽  
Impulse Response ◽  
Response Function ◽  
Autoregressive Model ◽  
Impulse Response Function ◽  
Variance Decomposition ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive

 Pada tahun 1999 pemerintah Indonesia mengimplementasikan peraturan mengenai otonomi daerah, dampak langsung dari implementasi ini adalah setiap provinsi harus mampu mengembangkan pembangunan ekonomi di daerahnya sendiri. Hal ini juga terjadi di Maluku, peningkatan APBD (Anggaran Pendapatan dan Belanja Daerah), yang seharusnya menjadi instrument peningkatan pertumbuahan ekonomi di Maluku. Tapi, faktanya Maluku masih menjadi daerah termiskin ke 4 di Indonesia dan memiliki tingkat pengangguran paling tinggi di Indonesia. Efektifitas realisasi anggaran di duga menjadi permasalahan utama. Sesuai dengan data BPS Maluku mayoritas dari pengeluaran pemerintah yang ada digunakan sebagai pengeluaran/ belanja rutin (83.4%) dan sisanya (29.68%) diganakan sebagai belanja/ pengeluaran Modal, yang seharusnya di gunakan untuk mendorong akselerasi pertumbuhan ekonomi.Penelitian ini menggunakan VAR (Vector Autoregressive) model, untuk mengukur efek daro pengeluaran pemerintah terhadap pertumbuhan ekonomi Maluku, data yang di gunakan dalam penelitian ini menggunakan data time series dari tahun 1997-2016 yang besumber dati BPS Maluku.Hasil penelitian menunjukan bahwa pengeluaran pemerintah di tentukan oleh berbagai variabel diantaranya variabel eksogen (Kebijakan Pemerintah Melalui Penerimaan Migas maupun Non-Migas) serta variabel endogen ( PDB dan Pembentukan Modal Tetap). Hasil lain yang menggunakan instrument Impulse Response Function dan Analisis Variance Decomposition seluruh variable dalam jangka pendek dan jangka Panjang memiliki pengaruh positif terhadap Pengeluaran Pemerintah di Maluku.

scholarly journals Structure Damage Identification Based on Regularized ARMA Time Series Model under Environmental Excitation

Vibration ◽  
2018 ◽  
Vol 1 (1) ◽  
pp. 138-156 ◽  
Author(s):  
Xuan Zhang ◽  
Dongsheng Li ◽  
Gangbing Song
Keyword(s):  
Time Series ◽  
Impulse Response ◽  
Response Function ◽  
Structural Damage ◽  
Damage Identification ◽  
National Laboratory ◽  
Impulse Response Function ◽  
Time Series Model ◽  
Vibration Response ◽  
Structural Vibration

In this paper, a non-modal parametric method to identify structural damage using a regularized autoregressive moving average time series model under environmental excitation is proposed in combination with the virtual impulse response function. This method can use the structural vibration response to determine the damage caused to the structure during environmental excitation. Firstly, the virtual impulse response function is obtained by using the structural vibration response. Then, a regularized ARMA time series model is used to fit the virtual impulse response function. Based on the change of auto-regression coefficients in the regularization model under different damage cases, the structural damage is identified. The authors derive the regularization equation of an ARMA time series model to solve the problems in a time series model and obtain the regularization coefficient. Finally, this method is applied to a three-degrees-of-freedom chain structure and a three-floor shear structure of the Los Alamos National Laboratory (LANL). The experimental results show that the method based on the regularized ARMA time series model under environmental excitation can effectively identify the structural damage, which is a reliable method for damage identification. The regularized ARMA time series model can accurately extract signal features and has invaluable application prospects in the field of structural health monitoring.

Crime control in Nigeria: how relevant is remittance inflow?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Folorunsho M. Ajide
Keyword(s):  
Time Series ◽  
Impulse Response ◽  
Response Function ◽  
Crime Rate ◽  
Crime Control ◽  
Impulse Response Function ◽  
Series Data ◽  
Content Type ◽  
Positive Shock ◽  
Toda And Yamamoto

Purpose This paper aims to draw on extant literature to ascertain the relevance of remittance receipts in improving the level of crime control in Nigeria. Design/methodology/approach The study uses time series data spanning for a period of 1986–2017. It adopts dynamic ordinary least square (DOLS), vector auto regression impulse response function, variance decomposition and Toda and Yamamoto causality approach to analyse the data. Findings The following findings are established: DOLS shows that remittance receipt has negative and significant impact on crime rate in Nigeria. The impulse response function indicates that a positive shock to the remittance inflows reduces the level of crime in Nigeria. Moreover, a positive shock to the crime rate decreases the remittance. This implies that both variables respond to each other. Toda and Yamamoto causality approach shows that there is unidirectional causality moving from remittance inflow to criminal activities in Nigeria. These results persist after considering other institutional variables. These findings support the previous evidences on remittances-crime nexus and as well support the opportunity cost theory of crime. Originality/value Apart from being the first study in African region that evaluates the relevance of remittances in crime control, it also analyses the dynamics between crime rate and remittance receipts using time series econometrics which makes the study to be unique. The study shows that remittances can be used as part of toolkits for controlling criminal activities in Nigeria.

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