Statistical analysis of cointegration vectors

This paper develops a new approach to the problem of testing the existence of a level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a univariate equilibrium correction mechanism. The asymptotic distributions of these statistics are non-standard under the null hypothesis that there exists no level relationship, irrespective of whether the regressors are I(0) or I(1). Two sets of asymptotic critical values are provided: one when all regressors are purely I(1) and the other if they are all purely I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into purely I(0), purely I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. It is shown that the proposed tests are consistent, and their asymptotic distribution under the null and suitably defined local alternatives are derived. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macroeconometric model. Copyright © 2001 John Wiley & Sons, Ltd.

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Bounds testing approaches to the analysis of level relationships

The estimation and testing of long-run relations in economic modeling are addressed. Starting with a vector autoregressive (VAR) model, the hypothesis of cointegration is formulated as the hypothesis of reduced rank of the long-run impact matrix. This is given in a simple parametric form that allows the application of the method of maximum likelihood and likelihood ratio tests. In this way, one can derive estimates and test statistics for the hypothesis of a given number of cointegration vectors, as well as estimates and tests for linear hypotheses about the cointegration vectors and their weights. The asymptotic inferences concerning the number of cointegrating vectors involve nonstandard distributions. Inference concerning linear restrictions on the cointegration vectors and their weights can be performed using the usual chi squared methods. In the case of linear restrictions on beta, a Wald test procedure is suggested. The proposed methods are illustrated by money demand data from the Danish and Finnish economies.

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Maximum likelihood estimation and inference on cointegration — with applications to the demand for money

Maximun likelihood estimation and inference on cointegration - With applications to the demand for money

Any series of observations ordered along a single dimension, such as time, may be thought of as a time series. The emphasis in time series analysis is on studying the dependence among observations at different points in time. What distinguishes time series analysis from general multivariate analysis is precisely the temporal order imposed on the observations. Many economic variables, such as GNP and its components, price indices, sales, and stock returns are observed over time. In addition to being interested in the contemporaneous relationships among such variables, we are often concerned with relationships between their current and past values, that is, relationships over time.

Time Series Analysis

Volumes 2A and 2B of The Handbook of Economic Growth summarize recent advances in theoretical and empirical work while offering new perspectives on a range of growth mechanisms, from the roles played by institutions and organizations to the ways factors beyond capital accumulation and technological change can affect growth. Written by research leaders, the chapters summarize and evaluate recent advances while explaining where further research might be profitable. With analyses that are provocative and controversial because they are so directly relevant to public policy and private decision-making, these two volumes uphold the standard for excellence in applied economics set by Volumes 1A and 1B (2005). It offers definitive theoretical and empirical scholarship about growth economics. It empowers readers to evaluate the work of other economists and to plan their own research projects. It demonstrates the value of empirical testing, with its implicit conclusion that our understanding of economic growth will help everyone make better decisions.

Handbook of Economic Growth

This paper provides some new evidence on the behaviour of cross-country growth rates. We reject the linear model commonly used to study cross-country growth behaviour in favour of a multiple regime alternative in which different economies obey different linear models when grouped according to initial conditions. Further, the marginal product of capital is shown to vary with the level of economic development. These results are consistent with growth models which exhibit multiple steady states. Our results call into question inferences that have been made in favour of the convergence hypothesis and further suggest that the explanatory power of the Solow growth model may be enhanced with a theory of aggregate production function differences.

https://www.jstor.org/stable/pdfplus/2285053.pdf

Multiple regimes and cross‐country growth behaviour

This paper provides an analysis of aggregate behavioural outcomes when individual utility exhibits social interaction effects. We study generalized logistic models of individual choice which incorporate terms reflecting the desire of individuals to conform to the behaviour of others in an environment of noncooperative decisionmaking. Laws of large numbers are generated in such environments. Multiplicity of equilibria in these models, which are equivalent to the existence of multiple self-consistent means for average choice behaviour, will exist when the social interactions exceed a particular threshold. Local stability of these multiple equilibria is also studied. The properties of the noncooperative economy are contrasted with the properties of an economy in which a social planner determines the set of individual choices. Finally, a likelihood function based on the theoretical model is given and conditions for the econometric identifiability of the model are established.

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Discrete Choice with Social Interactions

SUMMARY This paper proposes and tests new definitions of convergence and common trends for per capita output. We define convergence for a group of countries to mean that each country has identical long-run trends, either stochastic or deterministic, while common trends allow for proportionality of the stochastic elements. These definitions lead naturally to the use of cointegration techniques in testing. Using centurylong time series for 15 OECD economies, we reject convergence but find substantial evidence for common trends. Smaller samples of European countries also reject convergence but are driven by a lower number of common stochastic trends.

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Convergence in international output

We provide an overview of recent empirical research on patterns of cross-country growth. The new empirical regularities considered differ from earlier ones, e.g. the well-known Kaldor stylized facts. The new research no longer makes production function accounting a central part of the analysis. Instead, attention shifts more directly to questions like, Why do some countries grow faster than others? It is this changed focus that, in our view, has motivated going beyond the neoclassical growth model.

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Steven N. Durlauf

Papers

Handbook of Economic Growth

Multiple regimes and cross‐country growth behaviour

Discrete Choice with Social Interactions

Convergence in international output

The new empirics of economic growth