Asymptotic and bootstrap tests for linearity in a TAR-GARCH(1,1) model with a unit root

This paper derives the limiting distribution of the Lagrange Multiplier (LM) test for threshold nonlinearity in a TAR model with GARCH errors when one of the regimes contains a unit root. It is shown that the asymptotic distribution is nonstandard and depends on nuisance parameters that capture the degree of conditional heteroskedasticity and non-Gaussian nature of the process. We propose a bootstrap procedure for approximating the exact finite-sample distribution of the test for linearity and establish its asymptotic validity.     

Testing For Threshold Nonlinearity in Short-Term Interest Rates

This article addresses some empirical problems in the term structureof interest rates using a threshold autoregressive frameworkwith GARCH errors. This framework provides a parsimonious representationof some stylized features of interest rate data and facilitatesstatistical inference in the presence of high persistence andconditional heteroskedasticity. We propose a bootstrap-basedLM test for linearity in the conditional mean and variance functions.The empirical results indicate a presence of threshold nonlinearitiesin the AR and GARCH representations of the conditional momentsof short-term rate. The explicit modeling of these nonlinearitiesappears to improve the stability properties of the process forspot rate. The article also reports that allowing for thresholdnonlinearities in conditional mean and variance leads to significantforecast improvements. The economic significance of these findingsis evaluated by the term structure implications of the estimatedTAR-GARCH model.     

A MOMENT‐MATCHING METHOD FOR APPROXIMATING VECTOR AUTOREGRESSIVE PROCESSES BY FINITE‐STATE MARKOV CHAINS

This paper proposes a moment‐matching method for approximating vector autoregressions by finite‐state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle. Copyright © 2013 John Wiley & Sons, Ltd.     

A Network Perspective on Stakeholder Management: Facilitating Entrepreneurs in the Discovery of Opportunities

The problem of opportunity discovery is at the heart of entrepreneurial activity. Cognitive limitations determine the search for and the analysis of information and, as a consequence, constrain the identification of opportunities. Moreover, typical personal characteristics – locus of control, need for independence and need for achievement – suggest that entrepreneurs will tend to take a central position in their stakeholder environments and thus fail to adapt to the complexity of stakeholder relationships in their entrepreneurial activity. We approach this problem by adopting a network perspective on stakeholder management. We propose a heuristic approach of stakeholder analysis, which requires two mappings of the entrepreneurial constituents. The first mapping focuses on current interactions between the entrepreneur and their stakeholders, while the second focuses on a specific issue and the stakeholders that constitute it. In effect, such a stakeholder analysis requires entrepreneurs to use the complexity of stakeholder relationships in order to go beyond their cognitive limitations and thus facilitate the discovery of new opportunities. As we will argue, this has clear implications for the ethics and activities of entrepreneurs.     

Evaluation of Nonconventional Projects: GIRR and GERR vs. MIRR

This article considers evaluation of nonconventional projects and projects with cash outflows occurring not only at the beginning of project. It has been proved that, being a monotonically increasing function of a discount or finance rate, the modified internal rate of return (MIRR) fails to characterize the rate of return of such projects. We showed how to eliminate the MIRR's dependence on a finance rate and proved that in this case the MIRR becomes the “equivalent rate of return” proposed by Solomon. The generalized internal rate of return (GIRR) and generalized external rate of return (GERR) indices based on the generalized net present value (GNPV) approach are considered as alternatives to the MIRR. Several nonconventional projects have been evaluated using the MIRR, GIRR, and GERR rules. In order to verify the estimates, we drew up a simple project balance sheet, which demonstrated correctness of the results based on the GIRR and GERR rules and errors inherent in the MIRR application.     

Chi-squared tests for evaluation and comparison of asset pricing models

This paper presents a general statistical framework for estimation, testing and comparison of asset pricing models using the unconstrained distance measure of Hansen and Jagannathan (1997). The limiting results cover both linear and nonlinear models that could be correctly specified or misspecified. We propose modified versions of the existing model selection tests and new pivotal specification and model comparison tests with improved finite-sample properties. In addition, we provide formal tests of multiple model comparison. The excellent size and power properties of the proposed tests are demonstrated using simulated data from linear and nonlinear asset pricing models.     

Olley and Pakes‐style Production Function Estimators with Firm Fixed Effects

We show that control function estimators (CFEs) of the firm production function, such as Olley–Pakes, may be biased when productivity evolves with a firm‐specific intercept, in which case the correctly specified control function will contain a firm‐specific term, omitted in the standard CFEs. We develop an estimator that is free from this bias by introducing firm fixed effects in the control function. Applying our estimator to the data, we find that it outperforms the existing CFEs in terms of capturing persistent unobserved heterogeneity in firm productivity. Our estimator involves minimal modification to the standard CFE procedures and can be easily implemented using common statistical software.