scholarly journals Financialization of Enterprise Assets and R&D Investment

2021 ◽  
Vol 235 ◽  
pp. 01037
Author(s):  
Yang Xu
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Threshold Effect ◽  
Nonlinear Relationship ◽  
Real Economy ◽  
Promotion Effect ◽  
Effect Model ◽  
Effect Regression ◽  
The Relationship ◽  
D Investment

This paper selects the panel data of 260 listed companies in China’s GEM from 2013 to 2017, and uses a fixed effect regression model to verify and analyze the overall impact of asset financialization of small and medium-sized entrepreneurial companies on R&D investment. The results show that the two are positively related overall. In addition, from the perspective of the shareholding structure, the threshold effect model is used to explore how the direction and extent of the effect of asset financialization on corporate R&D investment dynamically change. It is concluded that these will have a nonlinear relationship with the change in the shareholding structure. Only by optimizing the shareholding structure and adjusting the shareholding ratios of major shareholders and management to an appropriate range can the optimal promotion effect of asset financialization on enterprise R&D investment be achieved, and the harmonious development of the relationship between finance and real economy can be promoted.

The threshold effect of firm size on technological innovation: examination of panel data from China

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xiaoxue Zhou ◽  
Yu Li ◽  
Yao Zhang
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Technological Innovation ◽  
Firm Size ◽  
Manufacturing Sector ◽  
Threshold Effect ◽  
Nonlinear Relationship ◽  
Threshold Regression ◽  
Content Type ◽  
Threshold Regression Model

PurposeThe purpose of this paper is to explore the threshold effect of firm size on technological innovation using panel data from 2007 to 2012 for listed enterprises in China's manufacturing sector.Design/methodology/approachConsidering the aim of research question is to examine the nonlinear relationship, this paper utilizes the threshold regression proposed by Hansen's (2000).FindingsBased on a threshold regression model using panel data from 2007 to 2012 for listed enterprises in China's manufacturing sector, we find a series of new results. This nonlinear relationship is under the restrictions and impacts of various factors, such as industry characteristics and government subsidies. The results suggest that the threshold regression model well explains the complicated nonlinear relationship and transition process, and it can also shed light on management practice and policy.Originality/valueThere are categorical arguments regarding why firm size is not as effective as before in explaining the monotonic principle of industrial innovation, especially for establishing an effective industrial policy in a particular situation. One of the important reasons is that we have begun to adopt a new perspective from the nonlinear view on the relationship between firm size and industrial innovation. In this study, we have examined the threshold effect of firm size on industrial technological innovation, which is the most representative nonlinear relationship.

scholarly journals The efect of size on the relationship between control structure and voluntary disclosure in Brazilian companies

2020 ◽  
Vol 21 (55) ◽  
pp. 21-38
Author(s):  
Vagner Naysinger Machado ◽  
Igor Bernardi Sonza
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Voluntary Disclosure ◽  
Control Structure ◽  
Threshold Effect ◽  
Disclosure Policy ◽  
Panel Data Regression ◽  
Data Regression ◽  
Private Control ◽  
The Relationship

This study aims to analyze the influence of size on the relationship between the control structure on the voluntary disclosure policy of the listed companies in B3. To achieve this goal, we created a dependent variable, called "voluntary disclosure level", which corresponds to 38 indicators of information collected manually from the companies' statements and websites. Afterwards, we estimated a balanced panel data regression model with a threshold effect for size in order to identify the relationship between the variables. The results indicated that smaller companies, with a more concentrated control structure, tended to present a higher level of voluntary disclosure. However, for larger companies, the greater the concentration of the control structure, the less evidence of this information. These inferences lead to believe that the largest Brazilian corporations, with more concentrated control, may not be interested in disclosing voluntary information because most of their shareholders enjoy private control benefits.

scholarly journals Analisis Faktor-Faktor yang Mempengaruhi Jumlah Penduduk di Kota Semarang Menggunakan Metode Regresi Data Panel

2019 ◽  
Vol 12 (2) ◽  
pp. 36-41
Author(s):  
Prizka rismawati Arum
Keyword(s):  
Panel Data ◽  
Random Effect ◽  
Geographical Area ◽  
Random Effect Model ◽  
Factors Affecting ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Relationship ◽  
Number Of Births

Residents are all people who live in the geographical area of Indonesia for six months or more and or those who have been domiciled for less than six months but aim to settle. Population growth is caused by two components, namely: fertility and mortality. To find out how big the relationship between the  population and the number of births and deaths in each sub-district of Semarang, must observed in several specific time periods and places at once. So in this study, the panel data regression method was used. In panel data regression testing, the results show that the panel data regression model formed to determine the factors that influence the level of population is the random effect model. In this model all assumptions are fulfilled. Significant factors affecting population are number of births. Births and deaths affect the population of 99.95% and the remaining 0.05% is influenced by other factors not examined Penduduk adalah semua orang yang berdomisili di wilayah geografis Indonesia selama enam bulan atau lebih dan atau mereka yang berdomisili kurang dari enam bulan tetapi bertujuan menetap. Pertumbuhan penduduk diakibatkan oleh dua komponen yaitu: fertilitas dan mortalitas. Untuk mengetahui seberapa besar keterkaitan antara jumlah penduduk dengan jumlah kelahiran dan kematian di setiap kecamataan Kota Semarang, harus diamati dalam beberapa periode waktu tertentu dan beberapa tempat secara bersamaan. Sehingga dalam penelitian ini digunakan metode regresi data panel. Dalam pengujian regresi data panel, didapatkan hasil bahwa Model regresi data panel yang terbentuk untuk mengetahui faktor-faktor yang mempengaruhi tingkat jumlah penduduk adalah model random Effect. Pada model tersebut semua asumsi terpenuhi. Faktor yang signifikan mempengaruhi jumlah penduduk adalah jumlah kelahiran. Kelahiran dan kematian mempengaruhi jumlah penduduk sebesar 99.95% dan sisanya sebesar 0.05% dipengaruhi oleh faktor- faktor lain yang tidak di teliti.    

scholarly journals Analisis Regresi Panel pada Pemodelan Tingkat Kematian Bayi di Provinsi Sulawesi Selatan

2020 ◽  
Vol 2 (2) ◽  
pp. 115
Author(s):  
Syafruddin Side ◽  
S. Sukarna ◽  
Raihana Nurfitrah
Keyword(s):  
Panel Data ◽  
Infant Mortality ◽  
Regression Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Least Square ◽  
Dummy Variable ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression

Penelitian ini membahas mengenai estimasi parameter model regresi data panel pada pemodelan tingkat kematian bayi di Provinsi Sulawesi Selatan dari tahun 2014 sampai dengan 2015. Data yang digunakan adalah data sekunder dari Dinas Kesehatan Provinsi Sulawesi Selatan yang berupa jumlah kematian bayi, berat bayi lahir rendah, persalinan yang ditolong oleh tenaga kesehatan, penduduk miskin, bayi yang diberi ASI ekslusif dan rumah tangga berperilaku bersih sehat di seluruh Kabupaten/Kota di Provinsi Sulawesi Selatan tahun 2014-2016. Analisis data dilakukan dengan menggunakan penghitungan manual dan dengan menggunakan software EViews 9. Pembahasan dimulai dari melakukan estimasi parameter model regresi data panel, menentukan model regresi data panel terbaik, , menguji asumsi model regresi data panel, pengujian signifikansi parameter dan interpretasi model regresi. Dalam penelitian ini diperoleh kesimpulan yaitu estimasi model regresi data panel terbaik dengan pendekatan fixed effect model.Kata kunci:Regresi Data Panel, Kematian Bayi, Fixed Effect Model, Least Square Dummy Variable. This research discusses about parameter estimation of panel data regression model of infant mortality level modelling in South Sulawesi from 2014 to 2015. The data used were secondary data from Dinas Kesehatan Provinsi Sulawesi Selatan in the form of number of infant mortality, low weight of infant, childbirth rescued by health workers, poor population, infants who were given exclusive breast milk and household that behaves well in the whole district/town in South Sulawesi year 2014-2016. Data analysis was performed using the calculation manually and by using EViews 9 software. The discussion started from doing parameter estimation of panel data regression model, determining the best panel data regression model, testing the assumption of panel data regression model, testing the signification of parameter and interpretation of regression model. Conclusion of this research are the estimation of regression model is the best panel data regression model with fixed effects model approach.Keywords:Panel Data Regression, Infant Mortality, Fixed Effect Model, Least Square Dummy Variable.

scholarly journals Liquidity Risk and Bank Performance: An Empirical Test for Tunisian Banks

2017 ◽  
Vol 7 (1) ◽  
pp. 46 ◽  
Author(s):  
Abdelaziz Hakimi ◽  
Khemais Zaghdoudi
Keyword(s):  
Panel Data ◽  
Financial Crisis ◽  
Credit Risk ◽  
Empirical Test ◽  
Random Effect ◽  
Liquidity Risk ◽  
Bank Performance ◽  
International Financial Crisis ◽  
Effect Regression ◽  
The Relationship

An important part of banking literature was interested in the relationship between credit risk and bank performance. However, only few studies investigated the association between liquidity risk and bank performance. The aim of this paper is to study the effect of liquidity risk on the Tunisian bank performance. To this end, we used a sample of 10 Tunisian banks over the period 1990-2013. By applying panel data method, precisely random effect regression, results show that liquidity risk decreases significantly Tunisian bank performance. Also, findings indicate that international financial crisis and inflation act negatively and significantly on bank performance.

scholarly journals Import of Russian regions under conditions of COVID-19

2021 ◽  
pp. 87-93
Author(s):  
S. S. Krasnykh
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Russian Federation ◽  
Economic Consequences ◽  
Steady Increase ◽  
Russian Regions ◽  
Coronavirus Infection ◽  
The Russian Federation ◽  
The Relationship ◽  
Infection Spread

The article examines the import activities of the subjects of the Russian Federation in the context of the coronavirus infection spread, analyses the import dynamics for 2019–2021, and constructs a regression model of panel data confirming the relationship between imports and the number of COVID-19 cases. It has been found that the number of cases of COVID-19 is directly impact on the import. Import volumes, in value terms, for the period 2019–2021, show a steady increase, which can be explained by an increase in mortality in the Russia, socio-economic consequences associated with the spread of COVID-19, and anticovidal sanitary and epidemiological restrictions.

An Empirical Analysis of Asymmetry and Threshold Effect of Intergovernmental Grants in India: A Panel Data Analysis

2018 ◽  
Vol 21 (2) ◽  
pp. 458-472 ◽  
Author(s):  
Asharani Samal
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
State Government ◽  
Capital Expenditure ◽  
Threshold Effect ◽  
Threshold Regression ◽  
Flypaper Effect ◽  
Intergovernmental Grants ◽  
Data Set ◽  
Reform Period

The present study empirically examines the effect of intergovernmental grants on the expenditure of state government in India. Using a panel data set during 1980–1981 to 2009–2010, the flypaper effect was found in the case of total and revenue expenditure and also an evidence of an asymmetric effect to change (increase or decrease) in grant variable for entire sample period. Again, to understand the flypaper and asymmetry effect in the pre- and post-reform period, this study uses the data from 1980–1981 to 1989–1990 as a pre-reform period and 1991–1992 to 2009–2010 as a post-reform period. The results of the panel regression model and two-stage least squares (2SLS) method show that there is an absence of flypaper effect except capital expenditure in the pre-reform period, whereas there exists an evidence of flypaper effect except capital expenditure in the post-reform period. Similarly, the responses of all the expenditure accounts are found to be asymmetric except capital expenditure. Further, in order to find the non-linear effect, this study employs Hansen (1999) threshold regression model to measure the threshold effect of intergovernmental grants on total expenditure of state government. The threshold regression results indicate that lower-income state grants have a stronger flypaper effect than middle- and higher-income states.

scholarly journals PENENTUAN KARAKTERISTIK PARIWISATA DAN MODEL JUMLAH WISATAWAN UNTUK KABUPATEN/KOTA DI PROVINSI ACEH

2016 ◽  
Vol 16 (1) ◽  
pp. 43-50
Author(s):  
Nurhasanah Nurhasanah ◽  
Nany Salwa ◽  
Nelva Amelia
Keyword(s):  
Panel Data ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Regional Government ◽  
Tourist Attractions ◽  
Tourist Destinations ◽  
Effect Model ◽  
Panel Data Regression ◽  
Data Regression ◽  
The Relationship

Tourism is one of the primary sectors that is expected to increase the regional government income. Therefore there is a need to observe the factors that affect the successfulness of tourism factors and products offered. Tourism products can be tourist destinations, where the characteristics of that particular destination can affect the decisions made by the tourist to return the place again. The characteristics of tourism in Aceh can be analyzed by using biplot analysis. Meanwhile, the effects of tourism characteristics on the number of tourists in Aceh from the year 2008 until 2013 is analyzed using panel data regression analysis that is approached by Fixed Effext Model (FEM). Based on the biplot graph, the cities that are superior in their number of all tourism products are Sabang and Banda Aceh. Cities other than these two cities tend to have a lower number of their tourism products. The biplot graph can explain the relationship between the variables of tourism products by 83.8%. Based on the model of fixed effect panel data, Aceh tourism products that affect the number of tourists in Aceh is the number of accommodations, restaurants, and tourist attractions. Fixed effect model explain correlation between the variables of tourism products to the number of tourists in Aceh by 78.8%.

scholarly journals Environmental regulation, Industrial structure upgrading and Economic growth in Beijing Tianjin Hebei region

2021 ◽  
Vol 235 ◽  
pp. 02021
Author(s):  
Menglu Li
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Panel Data ◽  
Environmental Regulation ◽  
Industrial Structure ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
The Relationship ◽  
Industrial Structure Upgrading

This paper selects the panel data of 13 cities in Beijing Tianjin Hebei region from 2008 to 2016, and uses the fixed effect model to study the relationship between environmental regulation, industrial structure upgrading and economic growth in Beijing Tianjin Hebei region. The results show that: strengthening environmental regulation can promote the upgrading of industrial structure in Beijing Tianjin Hebei region by reducing the emission of pollutants; the upgrading of industrial structure is conducive to promoting the economic development of Beijing Tianjin Hebei region.

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