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.

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.

scholarly journals ANALISIS PENGARUH BELANJA MODAL TERHADAP PERTUMBUHAN EKONOMI DAN KETIMPANGAN PENDAPATAN DI SUMATERA BARAT

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Yohana Pranita ◽  
Idris Idris
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Income Inequality ◽  
Regression Model ◽  
Capital Expenditure ◽  
Secondary Data ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Capital Expenditures ◽  
West Sumatra

Abstrak : This study aims to determine and analyze the effect of capital expenditureon economic growth and income inequality in West Sumatra. This research isdescriptive and inductive. The data used in this study is secondary data with datacollection using panel data obtained from BPS West Sumatra Province 2014-2018period with 19 regencies / cities in West Sumatra. This study analyzed using asimultaneous equation model (simultaneous equation regression model). The resultsof this study indicate that (1) Capital Expenditures have a significant effect onEconomic Growth in West Sumatra (2) Capital Expenditures have no significanteffect on Income Inequality in West Sumatra (3) Simultaneously Capital Expendituresand Economic Growth have a significant effect on Income Inequality in WestSumatra.Keyword : Capital Expenditure, Economic Growth, Income Inequality

Non-performing Loans and Moral Hazard in the Indian Banking Sector: A Threshold Panel Regression Approach

2020 ◽  
pp. 097215092092613
Author(s):  
Robin Thomas ◽  
Shailesh Singh Thakur
Keyword(s):  
Panel Data ◽  
Moral Hazard ◽  
Regression Model ◽  
Fixed Effects ◽  
Bank Lending ◽  
Empirical Literature ◽  
Data Set ◽  
Panel Data Regression ◽  
Data Regression ◽  
Indian Banks

This article attempts to examine the effect of non-performing assets (NPA) on behaviour of banks in India. The objectives of this article is to test if lending choices of Indian Banks demonstrate moral hazard and to test whether an increase in NPA ratio of banks raises riskier bank lending. We employ a threshold panel data regression model on a data set retrieved from the Reserve bank of India, which covered 45 commercial banks during the period 2009–2015, to test if lending choices of Indian banks demonstrate moral hazard. The results establish that the moral hazard hypothesis does not hold true for the given sample of India Banks, suggesting that an increase in the NPA ratio does not potentially increase riskier lending in sample banks. We find empirical evidence for the notion that ‘too-big-to-fail’ banks possibly have certain incentives to take higher risks and thus have higher NPA ratios. Graphical approach to NPA threshold explanation reveals presence of threshold; however, it could not be statistically established. Future implications of findings are evaluated. The study seminally adds to the empirical literature on use of fixed effects threshold panel data regression model in the context of Indian banks.

Demand for Services: Determinants of Tax Preparation Fees

1999 ◽  
Vol 21 (s-1) ◽  
pp. 1-23 ◽  
Author(s):  
Peter J. Frischmann ◽  
Edward W. Frees
Keyword(s):  
Panel Data ◽  
Regression Model ◽  
Income Tax ◽  
Opportunity Costs ◽  
Censored Regression ◽  
Data Set ◽  
Service Demand ◽  
Censored Regression Model ◽  
Time Savings ◽  
Tax Savings

We empirically investigate the demand for income tax preparation services by examining factors that affect both the choice and level of utilization of service. We identify the demand factors as the taxpayer's (1) opportunity costs, (2) estimated tax savings when using a preparer, and (3) historical uncertainty in tax liability. Our panel data set allows us to measure individual-specific uncertainty, a new measure in assessing determinants of tax service demand. Consistent with prior research, choice is measured by whether a taxpayer uses a professional paid preparer. The preparer's fee is the measure of utilization level. Fee information is heavily censored in part because fees only need to be disclosed when taxpayers itemize deductions and have miscellaneous itemized deductions above the 2 percent limit. We develop a partially censored regression model to accommodate the censoring. Similar to Cragg (1971), we decouple the choice and level of utilization models; findings indicate differences between these models. Generally, taxpayers choose paid preparers for time savings and uncertainty protection. Fees, however, reflect the purchase of time and tax savings, not uncertainty protection. These results suggest that pricing structures for professional tax preparation services could be adjusted to more closely reflect the services provided.

State Rainy Day Funds and Government General Fund Expenditures: Revisiting the Stabilization Effect

2019 ◽  
Vol 47 (3) ◽  
pp. 465-492 ◽  
Author(s):  
Wenchi Wei ◽  
Dwight V. Denison
Keyword(s):  
Panel Data ◽  
Empirical Analysis ◽  
State Government ◽  
Explanatory Variable ◽  
Data Set ◽  
General Fund ◽  
Economic Recessions ◽  
Rainy Day Funds ◽  
Stabilization Effect ◽  
The Empirical Analysis

This study explores the stabilization effect of state rainy day funds (RDFs) on government general fund expenditures (GFEs). We discuss and explicitly illustrate the concept of stabilization effect. Moreover, we utilize the current year’s actual RDF usage as the explanatory variable of interest rather than the previous year’s RDF balance, which most existing studies focus on. A panel data set of states for fiscal years 1998 to 2014 is used in the empirical analysis. Due to the pro-cyclicality of the defined GFE gap and the countercyclicality of RDF usage, their positive correlation revealed in the empirical results demonstrates that the actual RDF usage helps to stabilize state government GFEs in both economic recessions and expansions. We also verify that the previous year’s RDF balance, when interacted with RDF deposit and withdrawal rules, can influence government GFEs, thus demonstrating the importance of RDF rules.

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.

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.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

Sign in / Sign up

Export Citation Format

Share Document