This paper m a product of the Poverty and Human Resources Division, Policy Research Department -- is part of a larger effort in the department to monitor progress in reducing poverty in the world. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Andrea Ramirez, room N8-036, telephone 202-458-5734, fax 202-522-1153, Internet address mravallion@worldbank.org. December 1996. (36 pages) The Policy Research Working Paper Series disseminates the findings of work in prowess to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the author. They do not necessarily represent the view of the World Bank, its Executive Directors, or the countries bey represent

This paper develops a regression limit theory for nonstationary panel data with large numbers of cross section Ž n. and time series Ž T. observations. The limit theory allows for both sequential limits, wherein T� � followed by n��, and joint limits where T, n�� simultaneously; and the relationship between these multidimensional limits is explored. The panel structures considered allow for no time series cointegration, heterogeneous cointegration, homogeneous cointegration, and near-homogeneous cointegration. The paper explores the existence of long-run average relations between integrated panel vectors when there is no individual time series cointegration and when there is heterogeneous cointegration. These relations are parameterized in terms of the matrix regression coefficient of the long-run average covariance matrix. In the case of homogeneous and near homogeneous cointegrating panels, a panel fully modified regression estimator is developed and studied. The limit theory enables us to test hypotheses about the long run average parameters both within and between subgroups of the full population.

Organizations enter alliances with each other to access critical resources, but they rely on information from the network of prior alliances to determine with whom to cooperate. These new alliances modify the existing network, prompting an endogenous dynamic between organizational action and network structure that drives the emergence of interorganizational networks. Testing these ideas on alliances formed in three industries over nine years, the authors show that the probability of a new alliance between specific organizations increases with their interdependence, but also with their prior mutual alliances, common third parties, and joint centrality in the alliance network. The differentiation of the emerging network structure, however, mitigates the effect of interdependence and enhances the effect of joint centrality on new alliance formation. 3

We present several Markov chain Monte Carlo simulation methods that have been widely used in recent years in econometrics and statistics. Among these is the Gibbs sampler, which has been of particular interest to econometricians. Although the paper summarizes some of the relevant theoretical literature, its emphasis is on the presentation and explanation of applications to important models that are studied in econometrics. We include a discussion of some implementation issues, the use of the methods in connection with the EM algorithm, and how the methods can be helpful in model specification questions. Many of the applications of these methods are of particular interest to Bayesians, but we also point out ways in which frequentist statisticians may find the techniques useful.

We examine the relationship between income growth and saving using both cross-country and household data. At the aggregate level, we find that growth Granger causes saving, but saving does not Granger cause growth. Using household data, we find that households with predictably higher income growth save more than households with predictably low growth. We argue that standard permanent income models of consumption cannot explain these findings, but, a model of consumption with habit formation may. The positive effect of growth on saving implies that previous estimates of the effect of saving on growth may be overstated.

JEL No. C10 The major contributions of twentieth century econometrics to knowledge were the definition of causal parameters when agents are constrained by resources and markets and causes are interrelated, the analysis of what is required to recover causal parameters from data (the identification problem), and clarification of the role of causal parameters in policy evaluation and in forecasting the effects of policies never previously experienced. This paper summarizes the development of those ideas by the Cowles Commission, the response to their work by structural econometricians and VAR econometricians, and the response to structural and VAR econometrics by calibrators, advocates of natural and social experiments, and by nonparametric econometricians and statisticians.

In this paper, we study the asymptotic distributions for least-squares (OLS), fully modi ed (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic distribution of the OLS estimator is shown to have a non-zero mean. Monte Carlo results examine the sampling behavior of the proposed estimators and show that (1) the OLS estimator has a non-negligible bias in nite samples, (2) the FM estimator does not improve over the OLS estimator in general, and (3) the DOLS out-performs both the OLS and FM estimators.

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We examine whether sharp debt increases through leveraged buyouts and recapitalizations interact with market structure to influence plant closing and investment decisions of recapitalizing firms and their rivals. We take into account the fact that recapitalizations and investment decisions are both endogenous and may be simultaneously influenced by the same exogenous events. Following their recapitalizations, firms in industries with high concentration are more likely to close plants and less likely to invest. Rival firms are less likely to close plants and more likely to invest when the market share of leveraged firms is higher. We are grateful to David Denis, Owen Lamont, Peter MacKay, Vojislav Maksimovic,

We study the long-run relationship between nominal exchange rates and monetary fundamentals in a quarterly panel of 18 countries extending from 1973.1 to 1997.1. Our analysis is centered on two issues. First, we test whether exchange rates are cointegrated with long-run determinants predicted by economic theory. These results generally support the hypothesis of cointegration. The second issue is to re-examine the ability for monetary fundamentals to forecast future exchange rate returns. Panel regression estimates and forecasts con¯rm that this forecasting power is signi¯cant. 1