Michael Binder

Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be consistent and asymptotically normally distributed irrespective of the unit root and cointegrating properties of the underlying PVAR model. The transformed likelihood framework is also used to derive unit root and cointegration tests in panels with short time dimension; these tests have the attractive feature that they are based on standard chi-square and normal distributed statistics. Examining Generalized Method of Moments (GMM) estimation as an alternative to our proposed ML estimator, it is shown that conventional GMM estimators based on standard orthogonality conditons break down if the underlying time series contain unit roots. Also, the implementation of extended GMM estimators making use of variants of homoskedasticity and stationarity restrictions as suggested in the literature in a univariate context is subject to difficulties. Monte Carlo evidence is adduced suggesting that the ML estimator and parameter hypothesis and cointegration tests based on it perform well in small sample; this is in marked contrast to the small sample performance of the GMM estimators.

Stochastic Growth Models and Their Econometric Implications

This article considers the consequences of explicitly allowing for stochastic technological progress and stochastic labor input in the discrete-time Solow-Swan and AK growth models. It shows that the capital-output ratio, but not output per capita, is ergodic irrespective of whether there is a unit root in technology, and thus is the more appropriate measure to use in the cross-sectional analysis of the growth process. Furthermore, the article derives the cross-sectional and time-series implications of the stochastic Solow-Swan model and contrasts these to those of its deterministic counterpart. Among these implications are that the mean of the capital-output ratio depends in a precise way not only on the saving rate and the growth rate of labor input, but also on the variance and higher-order cumulants of the capital-output ratio. Using the Summers-Heston data for seventy-two countries from 1960 to 1992, strong support is found for the predictions of the stochastic Solow-Swan model as compared to those of its deterministic counterpart (as well as those of the AK model), including a significant negative cross-sectional relationship between the mean and the variance of the capital-output ratio.

MULTIVARIATE LINEAR RATIONAL EXPECTATIONS MODELS

This paper considers the solution of multivariate linear rational expectations models. It is described how all possible classes of solutions (namely, the unique stable solution, multiple stable solutions, and the case where no stable solution exists) of such models can be characterized using the quadratic determinantal equation (QDE) method of Binder and Pesaran (1995, in M.H. Pesaran & M. Wickens [eds.], Handbook of Applied Econometrics: Macroeconomics , pp. 139–187. Oxford: Basil Blackwell). To this end, some further theoretical results regarding the QDE method expanding on previous work are presented. In addition, numerical techniques are discussed allowing reasonably fast determination of the dimension of the solution set of the model under consideration using the QDE method. The paper also proposes a new, fully recursive solution method for models involving lagged dependent variables and current and future expectations. This new method is entirely straightforward to implement, fast, and applicable also to high-dimensional problems possibly involving coefficient matrices with a high degree of singularity.

Life-cycle consumption under social interactions

Abstract In this paper we examine how social interactions affect consumption decisions at various levels of aggregation in a life-cycle economy made up of peer groups. For this purpose, we consider two analytically solvable life-cycle models, one under certainty equivalent behavior and one under prudence, and explicitly allow for three different forms of social interactions in peer groups, namely conformism, altruism, and jealousy. We show that whether social interactions have any effects on individuals’ optimal consumption decisions critically depends on intertemporal rather than static considerations. This is true regardless of whether individuals’ preferences are time separable or exhibit habit formation, and whether information within peer groups is homogeneous or disparate. It implies that analyzing the effects of social interactions in static rather than intertemporal settings is likely to be misleading. We also show that social interactions, when coupled with either habit formation or prudence, can significantly strengthen the effects of habit formation or prudence in the direction of resolving two well-known puzzles in the literature on the permanent income hypothesis, namely excess smoothness and excess sensitivity.

Decision Making in the Presence of Heterogeneous Information and Social Interactions

The authors consider the solution of multivariate linear rational expectations models in the presence of heterogeneous information and social interactions. To overcome the infinite regress in expectations problem that arises in the solution of these models, we assume that agents expectations about the decisions and expectations of other agents are based solely on public information. They show that the resulting solutions satisfy the key postulates of the rational expectations hypothesis, but can nevertheless exhibit dynamic properties quite different from those under homogeneous information. The authors illustrate this by analyzing a model of firms optimal factor demand decisions. In this model, the presence of information heterogeneity may accentuate the propagation effects of external shocks on firms factor demands. Copyright 1998 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

Solution of finite-horizon multivariate linear rational expectations models and sparse linear systems

This paper presents e

Solution of Nonlinear Rational Expectations Models with Applications toFinite-Horizon Life-Cycle Models of Consumption

cient methods for the solution of xnite-horizon multivariate linear rational expectations (MLRE) models, linking the solution of such models to the problem of solving sparse linear equation systems with a block-tridiagonal coe

Chapter 4 On the Relation Between Investment and Economic Growth: New Cross-Country Empirical Evidence

cient matrix structure. Two numerical schemes for the solution of this type of equation systems are discussed, and it is shown how these procedures can be adapted to e

On the Conditional Effects of IMF Program Participation on Output Growth

ciently solve nite-horizon MLRE models. As the two numerical schemes are fully recursive and only involve elementary matrix operations, they are also straightforward to implement. The numerical schemes are illustrated by applying them to a nite-horizon adjustment cost problem of expenditure shares under adding-up constraints, and to a nite-horizon linear-quadratic optimal control problem. ( 2000 Elsevier Science B.V. All rights reserved.

GAUSS and Matlab codes for Multivariate Rational Expectations Models and Macroeconometric Modelling: A Review and Some New Results

This paper considers the solution of nonlinear rationalexpectations models resulting from the optimality conditions of afinite-horizon intertemporal optimization problem satisfying Bellmansprinciple of optimality (and possibly involving inequality constraints). Abackward recursive procedure is used to characterize and solve thetime-varying optimal decision rules generally associated with these models.At each stage of these backward recursions, either an analytical ornumerical solution of the optimality conditions is required. When ananalytical solution is not possible, a minimum weighted residual approach isused. The solution technique is illustrated using a life-cycle model ofconsumption under labor income and interest rate uncertainties (and possiblyinvolving liquidity constraints). Approximate numerical solutions areprovided and compared with certainty-equivalent solutions and, whenpossible, with exact solutions.