Han-Ying Liang, Yu Shen and Qiying Wang
Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two…
Abstract
Joon Y. Park is one of the pioneers in developing nonlinear cointegrating regression. Since his initial work with Phillips (Park & Phillips, 2001) in the area, the past two decades have witnessed a surge of interest in modeling nonlinear nonstationarity in macroeconomic and financial time series, including parametric, nonparametric and semiparametric specifications of such models. These developments have provided a framework of econometric estimation and inference for a wide class of nonlinear, nonstationary relationships. In honor of Joon Y. Park, this chapter contributes to this area by exploring nonparametric estimation of functional-coefficient cointegrating regression models where the structural equation errors are serially dependent and the regressor is endogenous. The self-normalized local kernel and local linear estimators are shown to be asymptotic normal and to be pivotal upon an estimation of co-variances. Our new results improve those of Cai et al. (2009) and open up inference by conventional nonparametric method to a wide class of potentially nonlinear cointegrated relations.
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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.
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Jiti Gao and Maxwell King
This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is established and studied to deal with the parametric specification of the…
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This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is established and studied to deal with the parametric specification of the nonparametric autoregressive errors with either stationarity or nonstationarity. Such a test procedure can initially avoid misspecification through the need to parametrically specify the form of the errors. In other words, we estimate the form of the errors and test for stationarity or nonstationarity simultaneously. We establish asymptotic distributions of the proposed test. Both the setting and the results differ from earlier work on testing for unit roots in parametric time series regression. We provide both simulated and real-data examples to show that the proposed nonparametric unit root test works in practice.
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Ali F. Darrat and Anas H. Hamed
Contrary to the restrictive bivariate results of Saunders (1995), our findings from open‐economy multivariate models accord with the conventional IS/LM apparatus and decisively…
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Contrary to the restrictive bivariate results of Saunders (1995), our findings from open‐economy multivariate models accord with the conventional IS/LM apparatus and decisively support the use of fiscal policy as a key macrostablization tool in the U.S. economy. We provide theoretical explanations for our results and produce empirical evidence for their robustness.
This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends…
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This chapter develops an asymptotic theory for a general transformation model with a time trend, stationary regressors, and unit root nonstationary regressors. This model extends that of Han (1987) to incorporate time trend and nonstationary regressors. When the transformation is specified as an identity function, the model reduces to the conventional cointegrating regression, possibly with a time trend and other stationary regressors, which has been studied in Phillips and Durlauf (1986) and Park and Phillips (1988, 1989). The limiting distributions of the extremum estimator of the transformation parameter and the plug-in estimators of other model parameters are found to critically depend upon the transformation function and the order of the time trend. Simulations demonstrate that the estimators perform well in finite samples.
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Andrea Bennett, Paul L. Gronewoller, Department of Finance and Real Estate
Summarizes three explanations put forward in previous research for the deviation of closed‐end fund (CEF) share prices from their net asset values and tests the theories based on…
Abstract
Summarizes three explanations put forward in previous research for the deviation of closed‐end fund (CEF) share prices from their net asset values and tests the theories based on market sentiment (noise trading) and market segmentation (market frictions). Analyses 1991‐1997 data on 18 UK CEFs (13 investing in the UK and 5 in the USA) to explore the pattern of cointegration and error corrected Granger causality between the fund discounts and indices which proxy for UK and US investor sentiment. Discusses the results, which support both theories for UK CEFs and show some evidence of cointegration and information transmission. Briefly considers consistency with other research and the implications of the findings.
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Nii Ayi Armah and Norman R. Swanson
In this chapter we discuss model selection and predictive accuracy tests in the context of parameter and model uncertainty under recursive and rolling estimation schemes. We begin…
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In this chapter we discuss model selection and predictive accuracy tests in the context of parameter and model uncertainty under recursive and rolling estimation schemes. We begin by summarizing some recent theoretical findings, with particular emphasis on the construction of valid bootstrap procedures for calculating the impact of parameter estimation error. We then discuss the Corradi and Swanson (2002) (CS) test of (non)linear out-of-sample Granger causality. Thereafter, we carry out a series of Monte Carlo experiments examining the properties of the CS and a variety of other related predictive accuracy and model selection type tests. Finally, we present the results of an empirical investigation of the marginal predictive content of money for income, in the spirit of Stock and Watson (1989), Swanson (1998) and Amato and Swanson (2001).