scholarly journals An Analysis of Network Structure in Mazda’s Yokokai using the DEC Spatial Model

2021 ◽  
Vol 15 ◽  
pp. 74-78
Author(s):  
T. Ito ◽  
S. Tagawa ◽  
S. Matsuno ◽  
Y. Uchida ◽  
Rajiv Mehta ◽  
...  
Keyword(s):  
Time Series ◽  
Spatial Model ◽  
Euclidean Distance ◽  
Time Series Data ◽  
Three Dimensional ◽  
Series Data ◽  
Future Research ◽  
Cross Sectional ◽  
Corporate Group ◽  
The Relationship

By examining networks is possible to understand the nature of inter-firm relationships among organizational entities in any given corporate group, such as Toyota’s, Nissan’s or Mazda’s Keiretsu. Recently, a new three-dimensional spatial model has been developed that allows organizational scholars to ascertain the structure of a corporate group, the position of the individual firms, and the determinants of the firm performance. This new spatial paradigm –called the DEC spatial model– composed of degree, effective size and capacity that assessed the relationship between Euclidean distance and sales. Although it advances our understanding of networks, the bulk of the research is based on cross-sectional data, it is not possible ascertain the real nature of the relationship between the distance and sales. Instead, the analysis of networks requires using time series data as all the corporate members of a network are ongoing- concerns. To augment our understanding of the nature of inter-firms networks, the interrelationship between distance and sales is examined using time series data drawn from Mazda’s Yokokai in 1986, 2004 and 2005. More specifically, in this paper the data on transactions were collected and used to calculate the Euclidean distance using the DEC spatial model. The position and its determinants of all individual firms are identified and the trend of structure changes is discussed. Based on the findings of offered and avenues of future research are suggested.

scholarly journals An Analysis of Using Time-Series Current and Deferred Income Tax Expense to Forecast Income Taxes Paid

2015 ◽  
Vol 31 (3) ◽  
pp. 1015 ◽  
Author(s):  
Brock Murdoch ◽  
Paul Krause ◽  
Paul Guy
Keyword(s):  
Time Series ◽  
Income Tax ◽  
Prediction Accuracy ◽  
Time Series Data ◽  
Series Data ◽  
Future Research ◽  
Cross Sectional ◽  
Tax Payments ◽  
One Year ◽  
Tax Expense

Prior research, using cross-sectional data, concluded that interperiod income tax allocation is useful in forecasting income tax payments (Murdoch, Costa, & Krause, 1994 and Cheung, Krishnan, & Min, 1997). Both these articles suggested that future research should focus on investigating whether time-series data are also useful in forecasting income tax payments. This paper uses time-series data from 235 Compustat firms over a 20-year period to evaluate whether income tax expense is useful in forecasting one-, two-, and three-year ahead income tax payments. We conclude that firms predictions are more accurate for shorter forecast horizons. Additionally, we determine that deferred income tax expense enhances the ability of current income tax expense to predict future tax payments for approximately 40% of firms across all three forecast horizons. Furthermore, we find that the prediction accuracy of a firms one-year ahead forecasts is significantly related to the prediction accuracy of its two- and three-year ahead forecasts.

An easy way to create duration variables in binary cross-sectional time-series data

2020 ◽  
Vol 20 (4) ◽  
pp. 916-930
Author(s):  
Andrew Q. Philips
Keyword(s):  
Time Series ◽  
Missing Data ◽  
Time Series Data ◽  
Series Data ◽  
Duration Dependence ◽  
Cross Sectional ◽  
Common Solution ◽  
The Common

In cross-sectional time-series data with a dichotomous dependent variable, failing to account for duration dependence when it exists can lead to faulty inferences. A common solution is to include duration dummies, polynomials, or splines to proxy for duration dependence. Because creating these is not easy for the common practitioner, I introduce a new command, mkduration, that is a straightforward way to generate a duration variable for binary cross-sectional time-series data in Stata. mkduration can handle various forms of missing data and allows the duration variable to easily be turned into common parametric and nonparametric approximations.

scholarly journals PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA CURAH HUJAN EMPAT KABUPATEN DI PROVINSI JAWA TENGAH

2019 ◽  
Vol 8 (4) ◽  
pp. 418-427
Author(s):  
Eko Siswanto ◽  
Hasbi Yasin ◽  
Sudarno Sudarno
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Space Time ◽  
Series Data ◽  
Inverse Distance Weighted ◽  
Modeling And Forecasting ◽  
Distance Weighted ◽  
The Relationship ◽  
Inverse Distance

In many applications, several time series data are recorded simultaneously at a number of locations. Time series data from nearby locations often to be related by spatial and time. This data is called spatial time series data. Generalized Space Time Autoregressive (GSTAR) model is one of space time models used to modeling and forecasting spatial time series data. This study applied GTSAR model to modeling volume of rainfall four locations in Jepara Regency, Kudus Regency, Pati Regency, and Grobogan Regency. Based on the smallest RMSE mean of forecasting result, the best model chosen by this study is GSTAR (11)-I(1)12 with the inverse distance weighted. Based on GSTAR(11)-I(1)12 with the inverse distance weighted, the relationship between the location shown on rainfall Pati Regency influenced by the rainfall in other regencies. Keywords: GSTAR, RMSE, Rainfall

Influence of Inclination Angle on Intermittent Two Phase Flows

2016 ◽  
Author(s):  
Josep Escrig Escrig ◽  
Buddhika Hewakandamby ◽  
Georgios Dimitrakis ◽  
Barry Azzopardi
Keyword(s):  
Time Series ◽  
Void Fraction ◽  
Time Series Data ◽  
Silicone Oil ◽  
Wire Mesh ◽  
Series Data ◽  
Intermittent Flow ◽  
Two Phase ◽  
Cross Sectional ◽  
Inclined Pipes

Intermittent gas and liquid two-phase flow was generated in a 6 m × 67 mm diameter pipe mounted rotatable frame (vertical up to −20°). Air and a 5 mPa s silicone oil at atmospheric pressure were studied. Gas superficial velocities between 0.17 and 2.9 m/s and liquid superficial velocities between 0.023 and 0.47 m/s were employed. These runs were repeated at 7 angles making a total of 420 runs. Cross sectional void fraction time series were measured over 60 seconds for each run using a Wire Mesh Sensor and a twin plane Electrical Capacitance Tomography. The void fraction time series data were analysed in order to extract average void fraction, structure velocities and structure frequencies. Results are presented to illustrate the effect of the angle as well as the phase superficial velocities affect the intermittent flows behaviour. Existing correlations suggested to predict average void fraction and gas structures velocity and frequency in slug flow have been compared with new experimental results for any intermittent flow including: slug, cap bubble and churn. Good agreements have been seen for the gas structure velocity and mean void fraction. On the other hand, no correlation was found to predict the gas structure frequency, especially in vertical and inclined pipes.

scholarly journals An Empirical Analysis of Energy Consumption, FDI and High Quality Development Based on Time Series Data of Zhejiang Province

2020 ◽  
Vol 17 (9) ◽  
pp. 3321
Author(s):  
Shaolong Zeng ◽  
Yiqun Liu ◽  
Junjie Ding ◽  
Danlu Xu
Keyword(s):  
Time Series ◽  
Economic Development ◽  
Energy Consumption ◽  
Open Economy ◽  
High Speed ◽  
Time Series Data ◽  
Rapid Development ◽  
Series Data ◽  
High Quality ◽  
The Relationship

This paper aims to identify the relationship among energy consumption, FDI, and economic development in China from 1993 to 2017, taking Zhejiang as an example. FDI is the main factor of the rapid development of Zhejiang’s open economy, which promotes the development of the economy, but also leads to the growth in energy consumption. Based on the time series data of energy consumption, FDI inflow, and GDP in Zhejiang from 1993 to 2017, we choose the vector auto-regression (VAR) model and try to identify the relationship among energy consumption, FDI, and economic development. The results indicate that there is a long-run equilibrium relationship among them. The FDI inflow promotes energy consumption, and the energy consumption promotes FDI inflow in turn. FDI promotes economic growth indirectly through energy consumption. Therefore, improving the quality of FDI and energy efficiency has become an inevitable choice to achieve the transition of Zhejiang’s economy from high speed growth to high quality growth.

scholarly journals Visibility Graph Power Geometric Aggregation Operator and Its Application in Water, Energy and Food Efficiency Evaluation

2020 ◽  
Vol 17 (11) ◽  
pp. 3891
Author(s):  
Lihua Liu ◽  
Jing Huang ◽  
Huimin Wang
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Coupling Efficiency ◽  
Aggregation Operator ◽  
Visibility Graph ◽  
Series Data ◽  
Efficiency Evaluation ◽  
Geometric Operator ◽  
The Relationship

In the real decision-making process, there are so many time series values that need to be aggregated. In this paper, a visibility graph power geometric (VGPG) aggregation operator is developed, which is based on the complex network and power geometric operator. Time series data are converted into a visibility graph. A visibility matrix is developed to denote the links among different time series values. A new support function based on the distance of two values are proposed to measure the support degree of each other when the two time series values have visibility. The VGPG operator considers not only the relationship but also the similarity degree between two values. Meanwhile, some properties of the VGPG operator are also investigated. Finally, a case study for water, energy, and food coupling efficiency evaluation in China is illustrated to show the effectiveness of the proposed operator. Comparative analysis with the existing research is also offered to show the advantages of the proposed method.

Influence of systemic banking crisis and currency crisis on the relationship of export and economic growth

2017 ◽  
Vol 10 (1) ◽  
pp. 82-110
Author(s):  
Syed Ali Raza ◽  
Mohd Zaini Abd Karim
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Financial Crises ◽  
Currency Crises ◽  
Time Series Data ◽  
Banking Crises ◽  
Series Data ◽  
Content Type ◽  
Relationship Of ◽  
The Relationship

Purpose This study aims to investigate the influence of systemic banking crises, currency crises and global financial crisis on the relationship between export and economic growth in China by using the annual time series data from the period of 1972 to 2014. Design/methodology/approach The Johansen and Jeuuselius’ cointegration, auto regressive distributed lag bound testing cointegration, Gregory and Hansen’s cointegration and pooled ordinary least square techniques with error correction model have been used. Findings Results indicate the positive and significant effect of export of goods and services on economic growth in both long and short run, whereas the negative influence of systemic banking crises and currency crises over economic growth is observed. It is also concluded that the impact of export of goods and service on economic growth becomes insignificant in the presence of systemic banking crises and currency crises. The currency crises effect the influence of export on economic growth to a higher extent compared to systemic banking crises. Surprisingly, the export in the period of global financial crises has a positive and significant influence over economic growth in China, which conclude that the global financial crises did not drastically affect the export-growth nexus. Originality/value This paper makes a unique contribution to the literature with reference to China, being a pioneering attempt to investigate the effects of systemic banking crises and currency crises on the relationship of export and economic growth by using long-time series data and applying more rigorous econometric techniques.

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