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Template-Type: ReDIF-Paper 1.0
Title: Econometric Models for Count Data with an Application to the Patents-R&D Relationship
Author-Name: Jerry A. Hausman
Author-Name: Bronwyn H. Hall
Author-Name: Zvi Griliches
Note: PR
Number: 0017
Creation-Date: 1984-10
Order-URL: http://www.nber.org/papers/t0017
File-URL: http://www.nber.org/papers/t0017.pdf
File-Format: application/pdf
Publication-Status: published as Hausman, Jerry A., Bronwyn Hall, and Zvi Griliches. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship." Econometrica, Vol. 52, No. 4, pp.909-938, July 1984.
Abstract: This paper focuses on developing and adapting statistical models of counts (non-negative integers) in the context of panel data and using them to analyze the relationship between patents and R&D expenditures. The model used is an application and generalization of the Poisson distribution to allow for independent variables; persistent individual (fixed or random) effects, and "noise" or randomness in the Poisson probability function. We apply our models to a data set previously analyzed by Pakes and Griliches using observations on 128 firms for seven years, 1968-74. Our statistical results indicate clearly that to rationalize the data, we need both a disturbance in the conditional within dimension and a different one, with a different variance, in the marginal (between) dimension. Adding firm specific variables, log book value and a scientific industry dummy, removes most of the positive correlation between the individual firm propensity to patent and its R&D intensity. The other new finding is that there is an interactive negative trend in the patents - R&D relationship, that is, firms are getting less patents from their more recent R&D investments, implying a decline in the "effectiveness" or productivity of R&D.
Handle: RePEc:nbr:nberte:0017
Template-Type: ReDIF-Paper 1.0
Title: Saddlepoint Problems in Contifuous Time Rational Expectations Models: A General Method and Some Macroeconomic Ehamples
Author-Name: Willem H. Buiter
Note: ITI IFM
Number: 0020
Creation-Date: 1984-06
Order-URL: http://www.nber.org/papers/t0020
File-URL: http://www.nber.org/papers/t0020.pdf
File-Format: application/pdf
Publication-Status: published as Buiter, Willem H. "Saddlepoint Problems in Continuous Time Rational Expectations Modelq: A General Method and Rome Macroeconomic Examples." Econometriaa, Vod. 52, No. 3, (may 1984), pp. 665-680.
Abstract: The paper presents a general solution method for rational expectations models that can be represented by systems of. deterministic first order linear differential equations with constant coefficients. It is the continuous time adaptation of the method of Blanchard and Kahn. To obtain a unique solution there must be as many linearly independent boundary conditions as there are linearly independent state variables. Three slightly different versions of a well-known small open economy macroeconomic model were used to illustrate three fairly general ways of specifying the required boundary conditions. The first represents the standard case in which the number of stable characteristic roots equals the number of predetermined variables. The second represents the case where the number of stable roots exceeds the number of predetermined variables but equals the number of predetermined variables plus the number of "backward-looking" but non-predetermined variables whose discontinuities are linear functions of the discontinuities in the forward-looking variables. The third represents the case where the number of unstable roots is less than the number of forward-looking state variables. For the last case, boundary conditions are suggested that involve linear restrictions on the values of the state variables at a future date. The method of this paper permits the numerical solution of models with large numbers of state variables. Any combination of anticipated or unanticipated, current or future and permanent or transitory shocks can be analyzed.
Handle: RePEc:nbr:nberte:0020
Template-Type: ReDIF-Paper 1.0
Title: Estimating Autocorrelations in Fixed-Effects Models
Author-Name: Gary Solon
Note: LS
Number: 0032
Creation-Date: 1984-02
Order-URL: http://www.nber.org/papers/t0032
File-URL: http://www.nber.org/papers/t0032.pdf
File-Format: application/pdf
Abstract: This paper discusses the estimation of serial correlation in fixed effects models for longitudinal data. Like time series data, longitudinal data often contain serially correlated error terms, but the autocorrelation estimators commonly used for time series, which are consistent as the length of the time series goes to infinity, are not consistent for a short time series as the size of the cross-section goes to infinity. This form of inconsistency is of particular concern because a short time series of a large cross-section is the typical case in longitudinal data. This paper extends Nickell's method of correcting for the inconsistency of autocorrelation estimators by generalizing to higher than first-order autocorrelations and to error processes other than first-order autoregressions. The paper also presents statistical tables that facilitate the identification and estimation of autocorrelation processes in both the generalized Nickell method and an alternative method due to MaCurdy. Finally, the paper uses Monte Carlo methods to explore the finite-sample properties of both methods.
Handle: RePEc:nbr:nberte:0032
Template-Type: ReDIF-Paper 1.0
Title: Consistent Estimation Using Data From More Than One Sample
Author-Name: William T. Dickens
Author-Name: Brian A. Ross
Note: LS
Number: 0033
Creation-Date: 1984-03
Order-URL: http://www.nber.org/papers/t0033
File-URL: http://www.nber.org/papers/t0033.pdf
File-Format: application/pdf
Abstract: This paper considers the estimation of linear models when group average data from more than one sample is used. Conditions under which OL8 coefficient estimates are consistent are identified. The standard OL8 covariance estimate is shown to be inconsistent and a consistent estimator is proposed. Finally, since the conditions under which OL8 is consistent are quite restrictive, several estimators which are consistent in many cases where OL8 is not are developed. The large sample distribution properties and an estimator for the asymptotic covariance matrix for the most general of these alternative estimators is also presented. One important application of these findings is to estimating compensating wage differences. Past authors, beginning with Thaler and Rosen (1976) have argued that finer classification schemes would reduce errors-in-variable bias. The analysis presented here suggests that the opposite is true if finer classification results in fewer observations per classification. This could explain why authors using the broader (industry) classification schemes have found larger compensating differences and suggests that these estimates may be closer to the true values.
Handle: RePEc:nbr:nberte:0033
Template-Type: ReDIF-Paper 1.0
Title: Policy evaluation and design for continuous time linear rational expectations models: some recent development
Author-Name: Willem H. Buiter
Note: ITI IFM
Number: 0034
Creation-Date: 1984-04
Order-URL: http://www.nber.org/papers/t0034
File-URL: http://www.nber.org/papers/t0034.pdf
File-Format: application/pdf
Publication-Status: published as Buiter, Willem (ed.) Macroeconomic theory and stabilization policy. Ann Arbor: University of Michigan Press, 1989.
Abstract: The paper surveys some recent developments in policy evaluation and design in continuous time linear rational expectations models. Much recent work in macroeconomics and open economy macroeconomics fits into this category. First the continuous time analogue is reviewed of the discrete time solution method of Blanchard and Kahn. Some problems associated with this solution method are then discussed, including non-uniqueness and zero roots. Optimal (but in general time-inconsistent) and time-consistent (but in general suboptimal) solutions are derived to the general linear-quadratic optimal control problem, based on work by Calvo, Driffill, Miller and Salmon and the author. A numerical example is solved, involving optimal and time-consistent anti-inflationary policy design in a contract model.
Handle: RePEc:nbr:nberte:0034
Template-Type: ReDIF-Paper 1.0
Title: Conditional Projection by Means of Kalman Filtering
Author-Name: Richard H. Clarida
Author-Name: Diane Coyle
Note: ME
Number: 0036
Creation-Date: 1984-05
Order-URL: http://www.nber.org/papers/t0036
File-URL: http://www.nber.org/papers/t0036.pdf
File-Format: application/pdf
Abstract: We establish that the recursive, state-space methods of Kalman filtering and smoothing can be used to implement the Doan, Litterman, and Sims (1983) approach to econometric forecast and policy evaluation. Compared with the methods outlined in Doan, Litterman, and Sims, the Kalman algorithms are more easily programmed and modified to incorporate different linear constraints, avoid cumbersome matrix inversions, and provide estimates of the full variance covariance matrix of the constrained projection errors which can be used directly, under standard normality assumptions, to test statistically the likelihood and internal consistency of the forecast under study.
Handle: RePEc:nbr:nberte:0036
Template-Type: ReDIF-Paper 1.0
Title: Errors in Variables in Panel Data
Author-Name: Zvi Griliches
Author-Name: Jerry A. Hausman
Note: LS
Number: 0037
Creation-Date: 1984-05
Order-URL: http://www.nber.org/papers/t0037
File-URL: http://www.nber.org/papers/t0037.pdf
File-Format: application/pdf
Publication-Status: published as Griliches, Zvi and Jerry A. Hausman. "Errors in Variables in Panel Data: A Note with an Example," Journal of Econometrics, Vol. 31, pp. 93-118, 1985.
Abstract: Panel data based on various longitudinal surveys have become ubiquitous in economics in recent years. Estimation using the analysis of covariance approach allows for control of various "individual effects" by estimation of the relevant relationships from the "within" dimension of the data. Quite often, however, the "within" results are unsatisfactory, "too low" and insignificant. Errors of measurement in the independent variables whose relative importance gets magnified in the within dimension are often blamed for this outcome. However, the standard errors-in-variables model has not been applied widely, partly because in the usual micro data context it requires extraneous information to identify the parameters of interest. In the panel data context a variety of errors-in-variables models may be identifiable and estimable without the use of external instruments. We develop this idea and illustrate its application in a relatively simple but not uninteresting case: the estimation of "labor demand" relationships, also known as the "short run increasing returns to scale" puzzle.
Handle: RePEc:nbr:nberte:0037
Template-Type: ReDIF-Paper 1.0
Title: Correcting for Truncation Bias Caused by a Latent Truncation Variable
Author-Name: David E. Bloom
Author-Name: Mark R. Killingsworth
Note: LS
Number: 0038
Creation-Date: 1984-06
Order-URL: http://www.nber.org/papers/t0038
File-URL: http://www.nber.org/papers/t0038.pdf
File-Format: application/pdf
Publication-Status: published as Bloom, David E. and Mark R. Killingsworth. "Correcting for Truncation Bias Caused by a Latent Truncation Variable." Journal of Econometrics, Vol. 27 , No. 1, January 1985, pp.131-135.
Abstract: We discuss estimation of the model Y[sub i] = X[sub i]b[sub y] + e[sub Yi] and T[sub i] =X[sub i]b[sub T] + e[sub Ti] when data on the continuous dependent variable Y and on the independent variables X are observed if the "truncation variable" T > 0 and when T is latent. This case is distinct from both (i) the "censored sample" case, in which Y data are available if T > 0, T is latent and X data are available for all observations, and (ii) the "observed truncation variable" case, in which both Y and X are observed if T > 0 and in which the actual value of T is observed whenever T > O. We derive a maximum-likelihood procedure for estimating this model and discuss identification and estimation.
Handle: RePEc:nbr:nberte:0038
Template-Type: ReDIF-Paper 1.0
Title: Data Problems in Econometrics
Author-Name: Zvi Griliches
Note: PR
Number: 0039
Creation-Date: 1984-07
Order-URL: http://www.nber.org/papers/t0039
File-URL: http://www.nber.org/papers/t0039.pdf
File-Format: application/pdf
Publication-Status: published as Griliches, Zvi. "Data Issues in Econometrics." Handbook of Econometrics , Vol. III, edited by Zvi Griliches and Michael D. Intriligator, North-Holland, 1986, chapter 21.
Abstract: This review of data problems in econometrics has been prepared for the Handbook of Econometrics (Vol. 3, Chap. 25, forthcoming). It starts with a review of the ambivalent relationship between data and econometricians, emphasizing the largely second-hand nature of economic data and the consequences that flow from the distance between econometricians as users of data and its producers. Section II describes the major types of economic data while Section III reviews some of the problems that arise in trying to use such data to estimate model parameters and to test economic theories. Section IV reviews the classical errors in variables model and its applicability to micro-data, especially panel data. Section V discusses missing data models and methods and illustrates them with an empirical example. Section VI focuses on the problem of estimating models in the absence of a full history, suggests a possible range of solutions, and provides again an empirical example: using a short panel to investigate the weights to be used in constructing a correct "capital" measure. The chapter closes (Section VII) with some final remarks on the existential problem of econometrics: life with imperfect data and inadequate theories.
Handle: RePEc:nbr:nberte:0039
Template-Type: ReDIF-Paper 1.0
Title: Rational Expectations Models with a Continuum of Convergent Solutions
Author-Name: Michael Mussa
Note: EFG
Number: 0041
Creation-Date: 1984-09
Order-URL: http://www.nber.org/papers/t0041
File-URL: http://www.nber.org/papers/t0041.pdf
File-Format: application/pdf
Abstract: This paper examines five examples of rational expectations models with a continuum of convergent solutions and demonstrates serious difficulties in the economic interpretation of these solutions. The five examples are (1) a model of optimal capital accumulation with a negative rate of time preference, (2) Taylor's (1977) linear rational expectations model of macroeconomic equilibrium; (3) Calvo's (1984) model of contract setting and price dynamics; (4) Obstfeld's (1984) equilibrium model of monetary dynamics with individual optimizing agents; and (5) Calvo's (1978) life-cycle model of savings and asset valuation. In every case, when these models yield a continuum of convergent infinite horizon solutions, these solutions fail to exhibit economically appropriate, forward looking dependence of the endogenous variables on the paths of the exogenous forcing variab1es--a difficulty that does not arise under the circumstances where these models yield unique convergent infinite horizon solutions. Further, the three models that have natural finite horizon versions, either lack finite horizon solutions or have solutions that do not converge to any of the infinite horizon solutions. Again, this difficulty arises only under the circumstances where these models have a continuum of infinite horizon solutions.
Handle: RePEc:nbr:nberte:0041
Template-Type: ReDIF-Paper 1.0
Title: New Econometric Techniques for Marcoeconomic Policy Evaluation
Author-Name: John B. Taylor
Author-Person: pta174
Note: EFG
Number: 0042
Creation-Date: 1984-11
Order-URL: http://www.nber.org/papers/t0042
File-URL: http://www.nber.org/papers/t0042.pdf
File-Format: application/pdf
Publication-Status: published as Taylor, John B. "New Econometric Approaches to Stabilization Policy in Stochastic Models of Macroeconomic Fluctuations," Handbook of Econometrics, Vol. III, ed by Z. Griliches and M.D. Intriligator, Elsivier Science Publishers, 1985.
Abstract: This paper is an expository review of recently developed techniques that are designed to evaluate macroeconomic policy using econometric models ; The exposition focuses on dynamic stochastic models with rational expectations and with discrete time. The method of undetermined coefficients is used to calculate the effects of anticipated, unanticipated, permanent, and temporary policy shocks; the same method is also used to calculate the effect of alternative policy rules on the stochastic equilibrium. This method provides a convenient unifying framework for comparing alternative solution methods for models with rational expectations. Estimation, testing and identification techniques are reviewed as well as recent methods for solving large nonlinear models.
Handle: RePEc:nbr:nberte:0042