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Template-Type: ReDIF-Paper 1.0
Title: A Monte Carlo Study of Growth Regressions
Classification-JEL: O4; O5
Author-Name: William R. Hauk
Author-Name: Romain Wacziarg
Author-Person: pwa67
Note: TWP EFG
Number: 0296
Creation-Date: 2004-01
Order-URL: http://www.nber.org/papers/t0296
File-URL: http://www.nber.org/papers/t0296.pdf
File-Format: application/pdf
Abstract: Using Monte Carlo simulations, this paper evaluates the bias properties of common estimators used in growth regressions derived from the Solow model. We explicitly allow for measurement error in the right-hand side variables, as well as country-specific effects that are correlated with the regressors. Our results suggest that using an OLS estimator applied to a single cross-section of variables averaged over time (the between estimator) performs best in terms of the extent of bias on each of the estimated coefficients. The fixed-effects estimator and the Arellano-Bond estimator greatly overstate the speed of convergence under a wide variety of assumptions concerning the type and extent of measurement error, while between understates it somewhat. Finally, fixed effects and Arellano-Bond bias towards zero the slope estimates on the human and physical capital accumulation variables.
Handle: RePEc:nbr:nberte:0296
Template-Type: ReDIF-Paper 1.0
Title: On the Relationship Between Determinate and MSV Solutions in Linear RE Models
Classification-JEL: C6
Author-Name: Bennett McCallum
Note: TWP
Number: 0297
Creation-Date: 2004-07
Order-URL: http://www.nber.org/papers/t0297
File-URL: http://www.nber.org/papers/t0297.pdf
File-Format: application/pdf
Publication-Status: published as McCallum, Bennett T. "On The Relationship Between Determinate And CSV Solutions In Linear Re Models," Economics Letters, 2004, v84(1,Jul), 55-60.
Abstract: This paper considers the possibility that, in linear rational expectations (RE) models, all determinate (uniquely non-explosive) solutions coincide with the minimum state variable (MSV) solution, which is unique by construction. In univariate specifications of the form y(t) = AE(t)y(t+1) + Cy(t-1) + u(t) that result holds: if a RE solution is unique and non-explosive, then it is the same as the MSV solution. Also, this result holds for multivariate versions if the A and C matrices commute and a certain regularity condition holds. More generally, however, there are models of this form that possess unique non-explosive solutions that differ from their MSV solutions. Examples are provided and a strategy for easily constructing others is outlined.
Handle: RePEc:nbr:nberte:0297
Template-Type: ReDIF-Paper 1.0
Title: The Use of Predictive Regressions at Alternative Horizons in Finance and Economics
Classification-JEL: C12; C22
Author-Name: Nelson C. Mark
Author-Person: pma186
Author-Name: Donggyu Sul
Author-Person: psu42
Note: TWP
Number: 0298
Creation-Date: 2004-08
Order-URL: http://www.nber.org/papers/t0298
File-URL: http://www.nber.org/papers/t0298.pdf
File-Format: application/pdf
Abstract: When a k period future return is regressed on a current variable such as the log dividend yield, the marginal significance level of the t-test that the return is unpredictable typically increases over some range of future return horizons, k. Local asymptotic power analysis shows that the power of the long-horizon predictive regression test dominates that of the short-horizon test over a nontrivial region of the admissible parameter space. In practice, small sample OLS bias, which differs under the null and the alternative, can distort the size and reduce the power gains of long-horizon tests. To overcome these problems, we suggest a moving block recursive Jackknife estimator of the predictive regression slope coefficient and test statistics that is appropriate under both the null and the alternative. The methods are applied to testing whether future stock returns are predictable. Consistent evidence in favor of return predictability shows up at the 5 year horizon.
Handle: RePEc:nbr:nberte:0298
Template-Type: ReDIF-Paper 1.0
Title: Optimal Invariant Similar Tests for Instrumental Variables Regression
Classification-JEL: C12; C30
Author-Name: Donald W.K. Andrews
Author-Person: pan30
Author-Name: Marcelo Moreira
Author-Person: pmo72
Author-Name: James H. Stock
Author-Person: pst148
Note: TWP
Number: 0299
Creation-Date: 2004-08
Order-URL: http://www.nber.org/papers/t0299
File-URL: http://www.nber.org/papers/t0299.pdf
File-Format: application/pdf
Publication-Status: published as Andrews, Donald W. K., Marcelo J. Moreira and James H. Stock. "Optimal Two-Sided Invariant Similar Tests For Instrumental Variables Regression," Econometrica, 2006, v74(3,May), 715-752.
Abstract: This paper considers tests of the parameter on endogenous variables in an instrumental variables regression model. The focus is on determining tests that have certain optimal power properties. We start by considering a model with normally distributed errors and known error covariance matrix. We consider tests that are similar and satisfy a natural rotational invariance condition. We determine tests that maximize weighted average power (WAP) for arbitrary weight functions among invariant similar tests. Such tests include point optimal (PO) invariant similar tests. The results yield the power envelope for invariant similar tests. This allows one to assess and compare the power properties of existing tests, such as the Anderson-Rubin, Lagrange multiplier (LM), and conditional likelihood ratio (CLR) tests, and new optimal WAP and PO invariant similar tests. We find that the CLR test is quite close to being uniformly most powerful invariant among a class of two-sided tests. A new unconditional test, P*, also is found to have this property. For one-sided alternatives, no test achieves the invariant power envelope, but a new test. the one-sided CLR test. is found to be fairly close. The finite sample results of the paper are extended to the case of unknown error covariance matrix and possibly non-normal errors via weak instrument asymptotics. Strong instrument asymptotic results also are provided because we seek tests that perform well under both weak and
Handle: RePEc:nbr:nberte:0299
Template-Type: ReDIF-Paper 1.0
Title: Volatility Comovement: A Multifrequency Approach
Classification-JEL: C13; C32
Author-Name: Laurent E. Calvet
Author-Person: pca582
Author-Name: Adlai J. Fisher
Author-Person: pfi214
Author-Name: Samuel B. Thompson
Note: TWP
Number: 0300
Creation-Date: 2004-08
Order-URL: http://www.nber.org/papers/t0300
File-URL: http://www.nber.org/papers/t0300.pdf
File-Format: application/pdf
Publication-Status: published as Calvet, Laurent E., Adlai J. Fisher and Samuel B. Thompson. "Volatility Comovement: A Multifrequency Approach," Journal of Econometrics, 2006, v131(1-2,Mar-Apr), 179-215.
Abstract: We implement a multifrequency volatility decomposition of three exchange rates and show that components with similar durations are strongly correlated across series. This motivates a bivariate extension of the Markov-Switching Multifractal (MSM) introduced in Calvet and Fisher (2001, 2004). Bivariate MSM is a stochastic volatility model with a closed-form likelihood. Estimation can proceed by ML for state spaces of moderate size, and by simulated likelihood via a particle filter in high-dimensional cases. We estimate the model and confirm its main assumptions in likelihood ratio tests. Bivariate MSM compares favorably to a standard multivariate GARCH both in- and out-of-sample. We extend the model to multivariate settings with a potentially large number of assets by proposing a parsimonious multifrequency factor structure.
Handle: RePEc:nbr:nberte:0300
Template-Type: ReDIF-Paper 1.0
Title: Identification and Estimation of Discrete Games of Complete Information
Classification-JEL: L0; L2; C1; C7
Author-Name: Patrick Bajari
Author-Name: Han Hong
Author-Name: Stephen Ryan
Author-Person: pry32
Note: TWP
Number: 0301
Creation-Date: 2004-10
Order-URL: http://www.nber.org/papers/t0301
File-URL: http://www.nber.org/papers/t0301.pdf
File-Format: application/pdf
Abstract: We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation-based estimators for static, discrete games. With appropriate exclusion restrictions about how covariates enter into payoffs and influence equilibrium selection, the model is identified with only weak parametric assumptions. Monte Carlo evidence demonstrates that the estimator can perform well in moderately-sized samples. As an application, we study the strategic decision of firms in spatially-separated markets to establish a presence on the Internet.
Handle: RePEc:nbr:nberte:0301
Template-Type: ReDIF-Paper 1.0
Title: Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak
Classification-JEL: C12; C15; C30
Author-Name: Marcelo J. Moreira
Author-Person: pmo72
Author-Name: Jack R. Porter
Author-Name: Gustavo A. Suarez
Note: TWP
Number: 0302
Creation-Date: 2004-11
Order-URL: http://www.nber.org/papers/t0302
File-URL: http://www.nber.org/papers/t0302.pdf
File-Format: application/pdf
Abstract: It is well-known that size-adjustments based on Edgeworth expansions for the t-statistic perform poorly when instruments are weakly correlated with the endogenous explanatory variable. This paper shows, however, that the lack of Edgeworth expansions and bootstrap validity are not tied to the weak instrument framework, but instead depends on which test statistic is examined. In particular, Edgeworth expansions are valid for the score and conditional likelihood ratio approaches, even when the instruments are uncorrelated with the endogenous explanatory variable. Furthermore, there is a belief that the bootstrap method fails when instruments are weak, since it replaces parameters with inconsistent estimators. Contrary to this notion, we provide a theoretical proof that guarantees the validity of the bootstrap for the score test, as well as the validity of the conditional bootstrap for many conditional tests. Monte Carlo simulations show that the bootstrap actually decreases size distortions in both cases.
Handle: RePEc:nbr:nberte:0302
Template-Type: ReDIF-Paper 1.0
Title: Optimal Inference in Regression Models with Nearly Integrated Regressors
Classification-JEL: C12; C32
Author-Name: Michael Jansson
Author-Person: pja19
Author-Name: Marcelo J. Moreira
Author-Person: pmo72
Note: TWP
Number: 0303
Creation-Date: 2004-11
Order-URL: http://www.nber.org/papers/t0303
File-URL: http://www.nber.org/papers/t0303.pdf
File-Format: application/pdf
Abstract: This paper considers the problem of conducting inference on the regression coefficient in a bivariate regression model with a highly persistent regressor. Gaussian power envelopes are obtained for a class of testing procedures satisfying a conditionality restriction. In addition, the paper proposes feasible testing procedures that attain these Gaussian power envelopes whether or not the innovations of the regression model are normally distributed.
Handle: RePEc:nbr:nberte:0303