scholarly journals An Asymptotic F Test for Uncorrelatedness in the Presence of Time Series Dependence

2020 ◽  
Vol 41 (4) ◽  
pp. 536-550 ◽  
Author(s):  
Xuexin Wang ◽  
Yixiao Sun
Keyword(s):  
Time Series ◽  
F Test ◽  
Series Dependence

Time series dependence and spectral analysis

2022 ◽  
pp. 261-299
Author(s):  
Dag Tjøstheim ◽  
Håkon Otneim ◽  
Bård Støve
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Series Dependence

Correcting for Cross-Sectional and Time-Series Dependence in Accounting Research

2010 ◽  
Vol 85 (2) ◽  
pp. 483-512 ◽  
Author(s):  
Ian D. Gow ◽  
Gaizka Ormazabal ◽  
Daniel J. Taylor
Keyword(s):  
Time Series ◽  
Equity Capital ◽  
Cost Of Debt ◽  
Test Statistics ◽  
Cost Of Equity Capital ◽  
Cost Of Equity ◽  
Cross Sectional ◽  
Accounting Research ◽  
The Cost ◽  
Series Dependence

ABSTRACT: We review and evaluate the methods commonly used in the accounting literature to correct for cross-sectional and time-series dependence. While much of the accounting literature studies settings in which variables are cross-sectionally and serially correlated, we find that the extant methods are not robust to both forms of dependence. Contrary to claims in the literature, we find that the Z2 statistic and Newey-West corrected Fama-MacBeth standard errors do not correct for both cross-sectional and time-series dependence. We show that extant methods produce misspecified test statistics in common accounting research settings, and that correcting for both forms of dependence substantially alters inferences reported in the literature. Specifically, several findings in the implied cost of equity capital literature, the cost of debt literature, and the conservatism literature appear not to be robust to the use of well-specified test statistics.

scholarly journals Pengaruh inflasi, investasi asing langsung dan pengeluaran pemerintah terhadap pertumbuhan ekonomi Indonesia

2018 ◽  
Vol 13 (2) ◽  
pp. 95-104
Author(s):  
Riris Prantika Putri ◽  
Heriberta Heriberta ◽  
Emilia Emilia
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Foreign Direct Investment ◽  
Direct Investment ◽  
Government Expenditure ◽  
Secondary Data ◽  
T Test ◽  
F Test ◽  
Independent Variables ◽  
Average Development

This study aims to analyze the development of inflation, foreign direct investment (FDI) and government expenditure to economic growth in Indonesia also to identify and analyze the effect of inflation, FDI and government expenditure to economic growth in Indonesia. The data used is secondary data in the form of time series. Based on the data obtained, the average development of economic growth in Indonesia during the period 2000-2017 was 5.29%. Based on the F test the independent variables tend to influence the dependent variable. In the t-test is known that inflation does not affect the economic growth in Indonesia, while FDI and government expenditure has a positive and significant impact on economic growth in Indonesia. The R2 value is 0,594602, amounting to 59.46% means that economic growth is affected by inflation, FDI and government expenditure, 40.54% influenced by other factors that were not included in this study

scholarly journals ANALISIS PENGARUH INFLASI, INVESTASI DAN PERTUMBUHAN EKONOMI TERHADAP PENGANGGURAN DI INDONESIA PERIODE TAHUN 2002 - 2015

2017 ◽  
Author(s):  
Seminar Nasional Multidisiplin Ilmu 2017 ◽  
Siti Delvi Jarniati
Keyword(s):  
Time Series ◽  
Least Squares ◽  
F Test

Penelitian ini bertujuan untuk mengetahui seberapa besar pengaruh inflasi, investasi, dan pertumbuhan ekonomi terhadap pengangguran di Indonesia. Jenis data dalam penelitian ini adalah data sekunder. Data yang digunakan merupakan data runtun waktu (time series) dari tahun 2002 – 2015. Penelitian ini menggunakan metode analisis regresi berganda, uji t, f-test dan koefisien determinasi dengan metode LS- Least Squares (LS and ARMA) menggunakan program eviews 6. Hasil penelitian menunjukkan bahwa inflasi, investasi dan pertumbuhan ekonomi berpengaruh berpengaruh terhadap pengangguran di Indonesia

scholarly journals Accounting for Autocorrelation in Detecting Mean Shifts in Climate Data Series Using the Penalized Maximal t or F Test

2008 ◽  
Vol 47 (9) ◽  
pp. 2423-2444 ◽  
Author(s):  
Xiaolan L. Wang
Keyword(s):  
Time Series ◽  
Open Source Software ◽  
Empirical Approach ◽  
Data Series ◽  
Climate Data ◽  
F Test ◽  
First Order ◽  
Open Source Software Package ◽  
Testing Algorithm ◽  
New Algorithms

Abstract This study proposes an empirical approach to account for lag-1 autocorrelation in detecting mean shifts in time series of white or red (first-order autoregressive) Gaussian noise using the penalized maximal t test or the penalized maximal F test. This empirical approach is embedded in a stepwise testing algorithm, so that the new algorithms can be used to detect single or multiple changepoints in a time series. The detection power of the new algorithms is analyzed through Monte Carlo simulations. It has been shown that the new algorithms work very well and fast in detecting single or multiple changepoints. Examples of their application to real climate data series (surface pressure and wind speed) are presented. An open-source software package (in R and FORTRAN) for implementing the algorithms, along with a user manual, has been developed and made available online free of charge.

scholarly journals PENGARUH PERTUMBUHAN EKONOMI DAN TINGKAT INFLASI TERHADAP JUMLAH PENGANGGURAN DI PROVINSI ACEH

2017 ◽  
Author(s):  
Seminar Nasional Multidisiplin Ilmu 2017 ◽  
Hovonly Aprista Simbolon
Keyword(s):  
Time Series ◽  
F Test

Pengangguran di suatu daerah dapat dipengaruhi oleh beberapa faktor diantaranya pertumbuhan ekonomi dan tingkat inflasi. Penelitian ini bertujuan untuk mengetahui pengaruh pertumbuhan ekonomi dan tingkat inflasi terhadap jumlah pengangguran di Provinsi Aceh. Jenis data dalam penelitian ini adalah data sekunder berupa time series dari tahun 2000-2014. Data yang diperoleh dari Produk Domestik Bruto dan Laju Inflasi sebagai variabel independen dan Tingkat Pengangguran Terbuka (TPT) sebagai variabel dependen. Metode analisis yang digunakan dalam penelitian ini adalah analisis regresi berganda, uji-t, f-test dan koefisien determinasi. Hasil uji parsial menunjukkan bahwa Pertumbuhan Ekonomi dan tingkat inflasi memiliki pengaruh positif tidak signifikan terhadap Jumlah pengangguran di Provinsi Aceh. Semakin besar pertumbuhan ekonomi dan semakin rendah tingkat inflasi maka semakin kecil jumlah pengangguan di Provinsi Aceh. Karena itu pemerintah Provinsi Aceh dipandang perlu membuka kesempatan kerja bagi masyarakat guna meningkatkan pertumbuhan ekonomi.

scholarly journals Statistical Learning With Time Series Dependence: An Application to Scoring Sleep in Mice

2013 ◽  
Vol 108 (504) ◽  
pp. 1147-1162 ◽  
Author(s):  
Blakeley B. McShane ◽  
Shane T. Jensen ◽  
Allan I. Pack ◽  
Abraham J. Wyner
Keyword(s):  
Time Series ◽  
Statistical Learning ◽  
Series Dependence

scholarly journals ANALIZING FACTOR THAT AFFECTING IMPORT OF MAIZE IN INDONESIA ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI IMPOR JAGUNG DI INDONESIA

2019 ◽  
Vol 12 (2) ◽  
Author(s):  
Raditya Audayuda ◽  
Elpawati E ◽  
Iwan Aminudin
Keyword(s):  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Series Data ◽  
F Test ◽  
Maize Production ◽  
Us Dollar

The purpose of The study is to identify the factor that affecting import of maize in Indonesia, Ana to analyze The factor that affecting import of maize in Indonesia. The data used in The Study is Time series data from 1990 to 2014 sourced from BPS(Badan Pusat Statistik) and Kementrian Pertanian. The method used in The Study is linear regression analysis using SPSS 18 software. Statistics Test that used in this Study including R2 , F-test, and T-test.In this Study we can concluded that R2 test value is 0,703 that means 70,3% import of maize explained by variable that used in model, which is: maize production (produksi jagung), maize consumption (konsumsi jagung), maize domestic prize (harga jagung domestik), maize import prize (harga jagung impor), and Rupiah to US Dollar currency (Nilai tukar rupiah terhadap dollar Amerika), and remaining 29,7% remains explained by another variable that exclude by this model. After all The testing, results shows all variable in The model affecting maize import simultaneously, and partial Test shows maize production, maize consumption, maize domestic prize, and Rupiah to US Dollar currency partially affecting import of maize in Indonesia, and maize import prize variable didn’t affect import of maize in Indonesia.

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