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.

Panel Kink Threshold Regression Model with a Covariate-Dependent Threshold

2020 ◽  
Author(s):  
Lixiong Yang ◽  
Chunli Zhang ◽  
Chingnun Lee ◽  
I-Po Chen
Keyword(s):  
Monte Carlo ◽  
Panel Data ◽  
Regression Model ◽  
Threshold Effect ◽  
Test Statistics ◽  
Threshold Regression ◽  
Finite Sample ◽  
Data Framework ◽  
Threshold Estimators ◽  
Threshold Regression Model

Abstract This paper extends the kink threshold regression (KTR) model with a constant threshold in Hansen (2017) to a panel data framework with a covariate-dependent threshold, where the threshold is modeled as a function of informative covariates. We suggest an estimator based on the within-group transformation, and propose test statistics for kink threshold effect and threshold constancy. We establish the asymptotic joint normality of the slope and threshold estimators, and derive the limiting distributions of the test statistics. Our asymptotical results show that the inclusion of a covariate-dependent threshold does not affect the asymptotic joint normality of the slope and threshold estimates in the kink threshold regression model. Monte Carlo simulations show that the finite sample proprieties of the proposed estimator and test statistics are generally satisfactory.

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.

Research on interval optimization of the proportion of female executives based on panel threshold model

2017 ◽  
Vol 30 (7) ◽  
pp. 1081-1092
Author(s):  
Xing Wang ◽  
Xuefeng Shao
Keyword(s):  
Regression Model ◽  
Market Value ◽  
Threshold Effect ◽  
Enterprise Management ◽  
Female Executives ◽  
Management Performance ◽  
Content Type ◽  
Optimal Interval ◽  
Threshold Regression Model ◽  
Panel Threshold Regression

Purpose This paper aims to seek the optimal proportion of female executives in corporate management teams, and to analyze the threshold effect of the proportion of female executives on the enterprise market value and enterprise management performance by using a panel threshold regression model. The purpose of this paper is to obtain the optimal interval, during which female executives exert positive effects on enterprise market value and enterprise management performance. Design/methodology/approach Based on the data of listed companies in SSE from 2003 to 2012, this paper conducts theoretical and empirical analysis by using a panel threshold regression model. Findings This paper proves that the proportion of female executives has a threshold effect on the enterprise market value and enterprise management performance. The results show that the proportion of female executives has an optimal interval. In other words, during the 53.8-68.4 percent interval, the proportion of female executives exerts the least negative effect on the enterprise market value and the most positive effect on the enterprise management performance. Originality/value In this paper, the non-linear relationship between female executives, enterprise market value and enterprise management performance has been verified, and the optimization interval of the female executives’ proportion has been figured out as well.

scholarly journals An investigation on impacts of structural changes in stocks’ past returns on financial analysts’ earnings forecasting rationality

2019 ◽  
Vol 3 (2) ◽  
pp. 188-202
Author(s):  
Zhixin Kang
Keyword(s):  
Regression Model ◽  
Structural Breaks ◽  
Structural Changes ◽  
Financial Analysts ◽  
Earnings Forecasts ◽  
Threshold Regression ◽  
Content Type ◽  
Time Period ◽  
Earnings Forecasting ◽  
Threshold Regression Model

Purpose The purpose of this paper is to test whether financial analysts’ rationality in making stocks’ earnings forecasts is homogenous or not across different information regimes in stocks’ past returns. Design/methodology/approach By treating stocks’ past returns as the information variable in this study, the authors employ a threshold regression model to capture and test threshold effects of stocks’ past returns on financial analysts’ rationality in making earnings forecasts in different information regimes. Findings The results show that three significant structural breaks and four respective information regimes are identified in stocks’ past returns in the threshold regression model. Across the four different information regimes, financial analysts react to stocks’ past returns quite differently when making one-quarter ahead earnings forecasts. Furthermore, the authors find that financial analysts are only rational in a certain information regime of stocks’ past returns depending on a certain return-window such as one-quarter, two-quarter or four-quarter time period. Originality/value This study is different from those in the existing literature by arguing that there could exist heterogeneity in financial analysts’ rationality in making earnings forecasts when using stocks’ past returns information. The finding that financial analysts react to stocks’ past returns differently in the different information regimes of past returns adds value to the research on financial analysts’ rationality.

Fiscal sustainability in India: evidence from Markov switching and threshold regression models

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vaseem Akram ◽  
Badri Narayan Rath
Keyword(s):  
Regression Model ◽  
Public Debt ◽  
Markov Switching ◽  
Fiscal Sustainability ◽  
Optimum Level ◽  
Fiscal Deficit ◽  
Threshold Regression ◽  
Content Type ◽  
Sustainability Issue ◽  
Threshold Regression Model

PurposeThe purpose of this study is to examine the fiscal sustainability issue by dividing the fiscal deficit into high and low regimes using the quarterly data from 1997: Q1 to 2013: Q3. Further, we obtain the optimum level of public debt at which fiscal sustainability can be achieved.Design/methodology/approachThis study uses the Markov Switching-Vector Error Correction Model (MS-VECM) for examining fiscal sustainability and threshold regression model to obtain the optimum level of debt.FindingsThe results derived from MS-VECM reveal the evidence in favor of fiscal sustainability during low fiscal deficit periods. Similarly, using a threshold regression model, the optimum public debt as a percentage to GDP seems to be around 21 per cent on a quarterly basis, beyond this level, public debt hurts economic growth.Practical implicationsFrom the policy front, the government of India should cut down the fiscal deficit only if debt reaches beyond a threshold level.Originality/valueNoting that the vast literature has focused on examining the fiscal sustainability in India, the novelty of this study is to examine the fiscal sustainability by considering high and low deficits regimes using a non-linear approach.

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.

Firms and export performance: does size matter?

2020 ◽  
Vol 47 (5) ◽  
pp. 985-999
Author(s):  
Van T.C. Ha ◽  
Mark J. Holmes ◽  
Trang M. Le
Keyword(s):  
Firm Size ◽  
Design Methodology ◽  
Positive Relationship ◽  
Manufacturing Sector ◽  
Export Performance ◽  
Nonlinear Relationship ◽  
Content Type ◽  
Regression Approach ◽  
Size Matter ◽  
The Relationship

PurposeThe purpose of this paper is to examine the relationship between export performance and firm size.Design/methodology/approachAnalysing a large sample of firms in the Vietnamese manufacturing sector, the authors employ a quantile regression approach to asses whether or not the relationship between exporting and firm size is dependent upon the extent of exporting that firms already undertake.FindingsThe authors find that increased firm size leads to higher export volumes. However, in sharp contrast to literature that largely focuses on considering a linear relationship between these two variables, the authors further find that the positive relationship becomes weaker as the extent of exporting activity increases.Originality/valueIn contrast to the earlier literature, a key novelty of the approach is that the authors obtain new insights in terms of establishing a nonlinear relationship between firm size and export performance in the case of Vietnamese manufacturing.

Determinants of being acquired in Indian manufacturing sector: a panel data analysis

2016 ◽  
Vol 8 (4) ◽  
pp. 246-263 ◽  
Author(s):  
Mohd Irfan ◽  
Sarani Saha ◽  
Sanjay Kumar Singh
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Unobserved Heterogeneity ◽  
Manufacturing Sector ◽  
Panel Data Analysis ◽  
Essential Requirement ◽  
Content Type ◽  
Advertising Intensity ◽  
Increase In Productivity ◽  
Indian Manufacturing Sector

Purpose The purpose of this study is to examine the firms’ determinants of being acquired in Indian manufacturing sector. There is evidence of relationship between likelihood of being acquired and several firm specific characteristics such as age, size, research and development (R&D), advertising intensity, productivity, leverage, profitability, intangible assets and financial constraints. However, little is known about the association between these characteristics and likelihood of acquisition in Indian manufacturing sector. Design/methodology/approach The sample is a panel of 2,189 Indian manufacturing firms spanning almost 10 years (1998-2007). Random effects logistic (REL) regression model is adopted to control the firm specific unobserved heterogeneity in the sample. This is an essential requirement for providing accurate and effective determinants of being acquired. Findings Empirical results reveal that the determinants of being acquired in Indian manufacturing sector are age, size, R&D intensity, advertising intensity, productivity and leverage. The findings indicate that increase in firms’ age, size, R&D intensity and advertising intensity increases the likelihood of being acquired. However, increase in productivity and leverage decreases the likelihood of being acquired. Research limitations/implications Findings of this study may be useful for potential targets to arrive at more thoughtful assessment of their attractiveness and, accordingly, promote their acquisition as a more efficient mode of exit. Originality/value The paper contributes some empirical evidence on the determinants of being acquired in Indian manufacturing sector by using panel data and REL regression model.

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