INTANGIBLE DETERMINANTS OF MARKET VALUE IN THE NEW ECONOMY: A DYNAMIC PANEL DATA ANALYSIS OF THE INDIAN SOFTWARE INDUSTRY

2009 ◽  
Vol 54 (03) ◽  
pp. 379-398 ◽  
Author(s):  
SUPRIYO DE
Keyword(s):  
Panel Data ◽  
Intangible Assets ◽  
Software Industry ◽  
Generalized Method Of Moments ◽  
Market Value ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Market Values ◽  
Software Firms ◽  
The Impact

Intangible assets like human capital and organization capital have driven the success of India's software industry. This article analyzes the impact of intangible assets on the market value of Indian software firms using a dynamic panel data model. Measures of tangible and intangible assets are constructed using firm-level panel data. The estimation technique uses system generalized method of moments (GMM) and minimum distance estimation (MDE). This methodology accounts for unobserved firm heterogeneity, endogenous explanatory variables and persistent variables. The results conclusively show that intangible assets have a significant impact on market values of Indian software firms.

scholarly journals Human Development Convergence and the Impact of Funds Transfer to Regions: A Dynamic Panel Data Approach

2020 ◽  
Vol 7 (12) ◽  
pp. 593-604
Author(s):  
Rah Adi Fahmi GINANJAR ◽  
Vadilla Mutia ZAHARA ◽  
Stannia Cahaya SUCI ◽  
Indra SUHENDRA
Keyword(s):  
Panel Data ◽  
Human Development ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
The Impact

scholarly journals Service Export Sensitivity to Internet Adoption: Evidence From Dynamic Panel Data Analysis

2020 ◽  
Vol 11 (6) ◽  
pp. 259
Author(s):  
Walid Chatti ◽  
Haitham Khoj
Keyword(s):  
Developing Countries ◽  
Panel Data ◽  
Panel Data Analysis ◽  
Developed Countries ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Internet Adoption ◽  
The Impact ◽  
Dynamic Panel Data Analysis ◽  
Service Export

This study aims to examine the causal linkages relating service exports to internet penetration for 116 countries over the period 2000-2017. Taking into account a wide panel of countries, we apply 2-Step GMM methodology for dynamic panel data models. The results show a bi-directional causality relating service exports to internet adoption for developed countries. For the global panel and developing countries, we find those same results attest a positive relationship between the internet adoption and service exports, but in the opposite way; the impact is very low and not significant. Regarding developing countries, despite the fact that internet positively affects service exports, it is considered less efficient than in developed countries.

scholarly journals The Role of Urbanization Rate in the Relationship between Air Pollution and Health Expenditures: A Dynamic Panel Data Approach

2015 ◽  
Vol 53 ◽  
pp. 68-72 ◽  
Author(s):  
Maryam Fattahi
Keyword(s):  
Air Pollution ◽  
Generalized Method Of Moments ◽  
Health Expenditures ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Public And Private ◽  
Urbanization Rate ◽  
The Impact ◽  
The Relationship

One of the available challenges in areas of health economics is identification of the effective factors on health expenditures. Air pollution plays important role in the public and private health expenditure but most studies have ignored the role of this category in explanation of health expenditures. On the other hand, the impact of air pollution on health expenditures is influenced by several factors. This study intends to investigate the effect of air pollution on public and private health expenditures and to identify the urbanization rate factor affecting the relationship between air pollution and public and private health expenditures. Scope of the present study is developing countries over period of 1995-2011. We used a dynamic panel and Generalized Method of Moments method. The empirical results indicate that air pollution has positive and significant effect on public and private health expenditures. Also, the results imply that urbanization rate affecting the relationship between air pollution and health expenditures that urbanization rate plays a reinforcing role.

scholarly journals Bias correction methods for dynamic panel data models with fixed effects

2017 ◽  
Vol 6 (2) ◽  
pp. 58
Author(s):  
Mohamed Abonazel
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Estimation Methods ◽  
Time Dimension ◽  
Dynamic Panel ◽  
Cross Sectional ◽  
Cross Sectional Dimension ◽  
Ls Estimator

This paper considers the estimation methods for dynamic panel data (DPD) models with fixed effects, which suggested in econometric literature, such as least squares (LS) and generalized method of moments (GMM). These methods obtain biased estimators for DPD models. The LS estimator is inconsistent when the time dimension (T) is short regardless of the cross-sectional dimension (N). Although consistent estimates can be obtained by GMM procedures, the inconsistent LS estimator has a relatively low variance and hence can lead to an estimator with lower root mean square error after the bias is removed. Therefore, we discuss in this paper the different methods to correct the bias of LS and GMM estimations. The analytical expressions for the asymptotic biases of the LS and GMM estimators have been presented for large N and finite T. Finally; we display new estimators that presented by Youssef and Abonazel [40] as more efficient estimators than the conventional estimators.

Do energy efficiency building codes help minimize the efficiency gap in the U.S.? A dynamic panel data approach

2020 ◽  
pp. 0958305X2094388
Author(s):  
Bishwa S Koirala ◽  
Alok K Bohara
Keyword(s):  
Energy Efficiency ◽  
Panel Data ◽  
Data Model ◽  
Unobserved Heterogeneity ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Residential Sector ◽  
Energy Efficiency Policy ◽  
Efficiency Gap

This study estimates the effects of energy efficiency policy in the residential sector using panel data of 48 contiguous states starting from 1970 to 2017. To avoid any unobserved heterogeneity and facilitate efficiency in estimation, this study employs a Dynamic Panel Data model with a two-step Generalized Method of Moments technique. The results suggest that energy efficiency policy for the residential sector has saved about 8.6 percent in energy consumption, which is about 22 percent of the total stated saving, leaving an energy efficiency gap of 1.5771 quadrillion Btu. Consistent with previous estimations, this study finds that theoretical saving amounts overestimate energy efficiency output and overinflate the increase in potential energy efficiency by about 32 percent. Since energy efficiency policy has failed to achieve the stated amount of saving in the residential sector, households have no incentive to adopt the energy efficiency policy, which has created an unusual gap in energy efficiency.

The Impact of Chinese Exports on Brazilian and Mexican Exports: A Model Using Dynamic Panel Data

2019 ◽  
pp. 1-17
Author(s):  
Luciane Franke ◽  
Marcos Tadeu Caputi Lélis ◽  
Alexsandro Marian Carvalho ◽  
José Roberto Iglesias
Keyword(s):  
Panel Data ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
The Impact

Estimating Dynamic Panel Data Models in Political Science

2002 ◽  
Vol 10 (1) ◽  
pp. 25-48 ◽  
Author(s):  
Gregory Wawro
Keyword(s):  
Panel Data ◽  
Political Science ◽  
Dynamic Models ◽  
Party Identification ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Panel Data Models ◽  
Dynamic Panel ◽  
Cross Sectional ◽  
Moments Estimators

Panel data are a very valuable resource for finding empirical solutions to political science puzzles. Yet numerous published studies in political science that use panel data to estimate models with dynamics have failed to take into account important estimation issues, which calls into question the inferences we can make from these analyses. The failure to account explicitly for unobserved individual effects in dynamic panel data induces bias and inconsistency in cross-sectional estimators. The purpose of this paper is to review dynamic panel data estimators that eliminate these problems. I first show how the problems with cross-sectional estimators arise in dynamic models for panel data. I then show how to correct for these problems using generalized method of moments estimators. Finally, I demonstrate the usefulness of these methods with replications of analyses in the debate over the dynamics of party identification.

scholarly journals The Effect of COVID-19 Pandemic on Corporate Dividend Policy in Indonesia: The Static and Dynamic Panel Data Approaches

Economies ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Georgina Maria Tinungki ◽  
Robiyanto Robiyanto ◽  
Powell Gian Hartono
Keyword(s):  
Panel Data ◽  
Dynamic Model ◽  
Method Of Moments ◽  
Capital Market ◽  
Dividend Policy ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Positive Signal ◽  
Dynamic Panel ◽  
The Capital Market

This research examines the effect of the crisis due to the COVID-19 pandemic on dividend policy in Indonesia. The purposive sampling method was used to collect data from corporates listed on the IDX from 2014 to 2020 and analyzed using static and dynamic panel data approaches. The fixed-effect models (FEM) were selected for the static panel data regression. Meanwhile, the first difference-generalized method of moments (FD-GMM) and system-generalized method of moments (SYS-GMM) were used for determine the robustness of the estimated dynamic panel data. The results showed that the crisis due to the pandemic led to higher dividend distribution on SYS-GMM. Furthermore, companies maintained the dividend level as a positive signal for investors which lifted the sluggish trade condition in the capital market. Profitability and previous year dividends positively affect dividend policy robustly. Furthermore, the results showed that age affects dividend policy on FD-GMM. Financial leverage has a robust effect, and firm size has an effect on FD-GMM in different directions, while investment opportunity does not affect dividend policy. Statistically, the FEM selected that violates the best linear unbiased estimation was proven to form parameters that were not much different from the estimates produced by the dynamic model, both from the coefficient of influence direction and significance, and the omitted variable bias occurs as evidenced in the robust test with dynamic model was solved. This research is also used as a reference for considering investors’ investment decisions in the new normal condition. Therefore, dividend policy can be considered as a positive signal to investors with the ability to stock trading activities in the capital market.

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