Neil R. Ericsson

Distributions of Error Correction Tests for Cointegration

This paper provides cumulative distribution functions, densities, and finite sample critical values for the single-equation error correction statistic for testing cointegration. Graphs and response surfaces summarize extensive Monte Carlo simulations and highlight simple dependencies of the statistics quantiles on the number of variables in the error correction model, the choice of deterministic components, and the estimation sample size. The response surfaces provide a convenient way for calculating finite sample critical values at standard levels; and a computer program, freely available over the Internet, can be used to calculate both critical values and p-values. Three empirical examples illustrate these tools.

Modeling Inflation in Australia

This article develops an empirically constant, data-coherent, error-correction model for inflation in Australia. The level of consumer prices is a markup over domestic and import costs, with adjustments for dynamics and relative aggregate demand. We address issues of cointegration, general to specific modeling, dynamic specification, model evaluation and testing, parameter constancy, forecasting, and exogeneity. We also test this model against existing models of Australian prices: This model encompasses (but is not encompassed by) the existing models.

Exogeneity, cointegration, and economic policy analysis

This overview examines conditions for reliable economic policy analysis based on econometric models, focusing on the econometric concepts of exogeneity, cointegration, causality, and invariance. Weak, strong, and super exogeneity are discussed in general, and these concepts are then applied to the use of econometric models in policy analysis when the variables are cointegrated. Implications follow for model constancy, the Lucas critique, equation inversion, and impulse response analysis. A small money-demand model for the United Kingdom illustrates the main analytical points. This article then summarizes the other articles in this issues special section on exogeneity, cointegration, and economic policy analysis.

Empirical Modeling of Money Demand

This paper examines several central issues in the empirical modeling of money demand. These issues include economic theory, data measurement, parameter constancy, the opportunity cost of holding money, cointegration, model specification, exogeneity, and inferences for policy. Review of these issues at a general level is paralleled by discussion of specific empirical applications, including some new results on the demand for narrow money in the United Kingdom.

Cointegration, exogeneity, and policy analysis: An overview

This overview describes the concepts of cointegration and exogeneity, focusing on analytical structure, statistical inference, and implications for policy analysis. Examples help clarify the concepts. The remainder of the overview summarizes the articles in a special issue of the Journal of Policy Modeling entitled Cointegration, Exogeneity, and Policy Analysis.

General-to-specific modeling: an overview and selected bibliography

This paper discusses the econometric methodology of general-to-specific modeling, in which the modeler simplifies an initially general model that adequately characterizes the empirical evidence within his or her theoretical framework. Central aspects of this approach include the theory of reduction, dynamic specification, model selection procedures, model selection criteria, model comparison, encompassing, computer automation, and empirical implementation. This paper thus reviews the theory of reduction, summarizes the approach of general-to-specific modeling, and discusses the econometrics of model selection, noting that general-to-specific modeling is the practical embodiment of reduction. This paper then summarizes fifty-seven articles key to the development of general-to-specific modeling.

Broad Money Demand and Financial Liberalization in Greece

This paper develops a constant, data-coherent, equilibrium correction model for broad money demand (M3) in Greece over 1976-1994. The aggregate M3 was targeted until recently, and current monetary policy still uses such aggregates as guidelines. In spite of financial innovation, financial liberalization, and large fluctuations in the inflation rate, the estimated model is remarkably stable. Dynamics are important, with price and income elasticities being much smaller in the short run than in the long run. The model provides a better understanding of the portfolio consequences of financial innovation and the effects of monetary policy in Greece.

Dollarization in post-hyperinflationary Argentina

Abstract This paper analyzes the continued dollarization of the Argentine economy, which experienced a rapid decline in inflation following its hyperinflations of the 1980s. First, a measure of dollar currency circulating in Argentina is developed, thereby improving upon previous studies of dollarization and currency substitution that focused on dollar deposit holdings only. Second, cointegration analysis of peso money demand in Argentina finds a negative ‘ratchet effect’ from inflation. The reduction in peso money demand attributable to the ratchet mirrors the estimated stock of all dollar assets held domestically by Argentine residents, consistent with the hypothesis of irreversible dollarization.

Conditional and structural error correction models

Abstract A ‘structural’ error correction model (in Boswijks sense) is a representation of a conditional error correction model that satisfies certain restrictions. This paper examines the conditions under which such a structural error correction model exists and when the associated representation is of interest. To clarify the nature of such models, several analytical and empirical examples are considered, which violate those conditions. Structural error correction models are economically appealing, but their limitations imply that some care must be taken when applying them in practice.

Forecast uncertainty in economic modeling

This paper provides an introduction to forecast uncertainty in empirical economic modeling. Forecast uncertainty is defined, various measures of forecast uncertainty are examined, and some sources and consequences of forecast uncertainty are analyzed. Empirical illustrations with the U.S. trade balance, U.K. inflation and real national income, and the U.S./U.K. exchange rate help clarify the issues involved.