Mohammad Hashem Pesaran

LONG-RUN STRUCTURAL MODELLING

The paper develops a general framework for identification, estimation, and hypothesis testing in cointegrated systems when the cointegrating coefficients are subject to (possibly) non-linear and cross-equation restrictions, obtained from economic theory or other relevant a priori information. It provides a proof of the consistency of the quasi maximum likelihood estimators (QMLE), establishes the relative rates of convergence of the QMLE of the short-run and the long-run parameters, and derives their asymptotic distributions; thus generalizing the results already available in the literature for the linear case. The paper also develops tests of the over-identifying (possibly) non-linear restrictions on the cointegrating vectors. The estimation and hypothesis testing procedures are applied to an Almost Ideal Demand System estimated on U.K. quarterly observations. Unlike many other studies of consumer demand this application does not treat relative prices and real per capita expenditures as exogenously given.

Persistence of Shocks and Their

This paper develops a multisectoral framework for the measurement of persistence of shocks to sectoral and aggregate output, and provides a decomposition of the contribution of shocks from different sources to the overall persistence measure. The framework is applied to U.K. output data, distinguishing four types of macroeconomic shocks: innovations in money supply growth, stock returns, exchange rates, and oil prices. Among the macro shocks, exchange-rate shocks have the largest persistence effects on aggregate output, through their effects on manufacturing sectors. The contribution of the identified macro shocks to total persistence was small, however, compared to that of sector-specific shocks. Copyright 1992 by Royal Economic Society.

Testing for Aggregation Bias in Linear Models

This paper discusses alternative methods of testing for aggregation bias and proposes direct tests of the discrepancy of the macroparameters from the average of the corresponding microparameters, and derives tests of aggregation bias in the general case where the parameters of interest may possibly be nonlinear functions of the microparameters. The paper also develops a Durbin-Hausman type misspecification test of the disaggregate model. These tests are then applied to disaggregate and aggregate specifications of employment functions for the U.K. economy disaggregated by forty industries. Copyright 1990 by Royal Economic Society.