John Chao, Myungsup Kim and Donggyu Sul
This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition…
Abstract
This paper proposes a new class of estimators for the autoregressive coefficient of a dynamic panel data model with random individual effects and nonstationary initial condition. The new estimators we introduce are weighted averages of the well-known first difference (FD) GMM/IV estimator and the pooled ordinary least squares (POLS) estimator. The proposed procedure seeks to exploit the differing strengths of the FD GMM/IV estimator relative to the pooled OLS estimator. In particular, the latter is inconsistent in the stationary case but is consistent and asymptotically normal with a faster rate of convergence than the former when the underlying panel autoregressive process has a unit root. By averaging the two estimators in an appropriate way, we are able to construct a class of estimators which are consistent and asymptotically standard normal, when suitably standardized, in both the stationary and the unit root case. The results of our simulation study also show that our proposed estimator has favorable finite sample properties when compared to a number of existing estimators.
Details
Keywords
Yonghui Zhang and Qiankun Zhou
It is shown in the literature that the Arellano–Bond type generalized method of moments (GMM) of dynamic panel models is asymptotically biased (e.g., Hsiao & Zhang, 2015; Hsiao &…
Abstract
It is shown in the literature that the Arellano–Bond type generalized method of moments (GMM) of dynamic panel models is asymptotically biased (e.g., Hsiao & Zhang, 2015; Hsiao & Zhou, 2017). To correct the asymptotical bias of Arellano–Bond GMM, the authors suggest to use the jackknife instrumental variables estimation (JIVE) and also show that the JIVE of Arellano–Bond GMM is indeed asymptotically unbiased. Monte Carlo studies are conducted to compare the performance of the JIVE as well as Arellano–Bond GMM for linear dynamic panels. The authors demonstrate that the reliability of statistical inference depends critically on whether an estimator is asymptotically unbiased or not.
Details
Keywords
In this paper, we study a partially linear dynamic panel data model with fixed effects, where either exogenous or endogenous variables or both enter the linear part, and the…
Abstract
In this paper, we study a partially linear dynamic panel data model with fixed effects, where either exogenous or endogenous variables or both enter the linear part, and the lagged-dependent variable together with some other exogenous variables enter the nonparametric part. Two types of estimation methods are proposed for the first-differenced model. One is composed of a semiparametric GMM estimator for the finite-dimensional parameter θ and a local polynomial estimator for the infinite-dimensional parameter m based on the empirical solutions to Fredholm integral equations of the second kind, and the other is a sieve IV estimate of the parametric and nonparametric components jointly. We study the asymptotic properties for these two types of estimates when the number of individuals N tends to ∞ and the time period T is fixed. We also propose a specification test for the linearity of the nonparametric component based on a weighted square distance between the parametric estimate under the linear restriction and the semiparametric estimate under the alternative. Monte Carlo simulations suggest that the proposed estimators and tests perform well in finite samples. We apply the model to study the relationship between intellectual property right (IPR) protection and economic growth, and find that IPR has a non-linear positive effect on the economic growth rate.
Details
Keywords
This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time…
Abstract
This paper provides a selective survey of the panel macroeconometric techniques that focus on controlling the impact of “unobserved heterogeneity” across individuals and over time to obtain valid inference for “structures” that are common across individuals and over time. We consider issues of (i) estimating vector autoregressive models; (ii) testing of unit root or cointegration; (iii) statistical inference for dynamic simultaneous equations models; (iv) policy evaluation; and (v) aggregation and prediction.
Details
Keywords
Tarek Eldomiaty, Ola Attia, Wael Mostafa and Mina Kamal
The internal factors that influence the decision to change dividend growth rates include two competing models: the earnings and free cash flow models. As far as each of the…
Abstract
The internal factors that influence the decision to change dividend growth rates include two competing models: the earnings and free cash flow models. As far as each of the components of each model is considered, the informative and efficient dividend payout decisions require that managers have to focus on the significant component(s) only. This study examines the cointegration, significance, and explanatory power of those components empirically. The expected outcomes serve two objectives. First, on an academic level, it is interesting to examine the extent to which payout practices meet the premises of the earnings and free cash flow models. The latter considers dividends and financing decisions as two faces of the same coin. Second, on a professional level, the outcomes help focus the management’s efforts on the activities that can be performed when considering a change in dividend growth rates.
This study uses data for the firms listed in two indexes: Dow Jones Industrial Average (DJIA30) and NASDAQ100. The data cover quarterly periods from 30 June 1989 to 31 March 2011. The methodology includes (a) cointegration analysis in order to test for model specification and (b) classical regression in order to examine the explanatory power of the components of earnings and free cash flow models.
The results conclude that: (a) Dividends growth rates are cointegrated with the two models significantly; (b) Dividend growth rates are significantly and positively associated with growth in sales and cost of goods sold only. Accordingly, these are the two activities that firms’ management need to focus on when considering a decision to change dividend growth rates, (c) The components of the earnings and free cash flow models explain very little of the variations in dividends growth rates. The results are to be considered a call for further research on the external (market-level) determinants that explain the variations in dividends growth rates. Forthcoming research must separate the effects of firm-level and market-level in order to reach clear judgments on the determinants of dividends growth rates.
This study contributes to the related literature in terms of offering updated robust empirical evidence that the decision to change dividend growth rate is discretionary to a large extent. That is, dividend decisions do not match the propositions of the earnings and free cash flow models entirely. In addition, the results offer solid evidence that financing trends in the period 1989–2011 showed heavy dependence on debt financing compared to other related studies that showed heavy dependence on equity financing during the previous period 1974–1984.
Details
Keywords
Tarek Ibrahim Eldomiaty, Islam Azzam, Mohamed Bahaa El Din, Wael Mostafa and Zahraa Mohamed
The main objective of this study is to examine whether firms follow the financing hierarchy as suggested by the Pecking Order Theory (POT). The External Funds Needed (EFN) model…
Abstract
The main objective of this study is to examine whether firms follow the financing hierarchy as suggested by the Pecking Order Theory (POT). The External Funds Needed (EFN) model offers a financing hierarchy that can be used for examining the POT. As far as the EFN considers growth of sales as a driver for changing capital structure, it follows that shall firms plan for a sustainable growth of sales, a sustainable financing can be reached and maintained. This study uses data about the firms listed in two indexes: Dow Jones Industrial Average (DJIA30) and NASDAQ100. The data cover quarterly periods from June 30, 1999, to March 31, 2012. The methodology includes (a) cointegration analysis in order to test for model specification and (b) causality analysis in order to show the generic and mutual associations between the components of EFN. The results conclude that (a) in the majority of the cases, firms plan for an increase in growth sales but not necessarily to approach sustainable rate; (b) in cases of observed and sustainable growth of sales, firms reduce debt financing persistently; (c) firms use equity financing to finance sustainable growth of sales in the long run only, while in the short run, firms use internal financing, that is, retained earnings as a flexible source of financing; and (d) the EFN model is quite useful for examining the hierarchy of financing. This study contributes to the related literature in terms of utilizing the properties of the EFN model in order to examine the practical aspects of the POT. These practical considerations are extended to examine the use of the POT in cases of observed and sustainable growth rates. The findings contribute to the current literature that there is a need to offer an adjustment to the financing order suggested by the POT. Equity financing is the first source of financing current and sustainable growth of sales, followed by retained earnings, and debt financing is the last resort.
Details
Keywords
Alex Rockey, Lorna Gonzalez, Megan Eberhardt-Alstot and Margaret Merrill
Connectedness is essential for student success in online learning. By projecting themselves as real people through video, instructors support connectedness. In this chapter…
Abstract
Connectedness is essential for student success in online learning. By projecting themselves as real people through video, instructors support connectedness. In this chapter, researchers apply the theory of social presence (Garrison, Anderson, & Archer, 2000) to case studies from two public higher education institutions: a four-year university and a large research university. Analysis identifies video as a humanizing element of online courses. Findings suggest video could be used in a variety of ways (e.g., video lectures, synchronous office hours, weekly overview videos), and no single use of video was perceived to be more or less effective in developing social presence and humanizing the learning experience. However, participants especially perceived connectedness when video was used in a variety of ways. Students from the second case study validated a perception of connectedness to the instructor that faculty in our first case study hoped to achieve. However, one instructor’s perception of disconnect illustrates that video is just one of several pedagogical practices necessary to create a satisfying learning experience for both students and instructors. While video is not the only way to establish social presence, findings suggest video is an effective practice toward creating a humanized and connected online learning community.
Details
Keywords
The authors consider the quasi maximum likelihood (MLE) estimation of dynamic panel models with interactive effects based on the Ahn et al. (2001, 2013) quasi-differencing methods…
Abstract
The authors consider the quasi maximum likelihood (MLE) estimation of dynamic panel models with interactive effects based on the Ahn et al. (2001, 2013) quasi-differencing methods to remove the interactive effects. The authors show that the quasi-difference MLE (QDMLE) over time is inconsistent when