Appendix: Data Sources
The data used in this paper consisted of quarterly series for the stock of base money, the nominal exchange rate, an index of industrial production, the consumer price index, and an index of a representative nominal wage for each of Argentina, Brazil, and Israel. The data for the monetary base, the nominal exchange rate, industrial production, and the consumer price index were taken from International Financial Statistics. The relevant series were, respectively: Reserve Money (line 14), the period-average exchange rate at market rates expressed as units of domestic currency per U.S. dollar (line rf), Industrial Production (line 66), and Consumer Prices (line 64). Wage data for Israel were also taken from IFS (Wages: Daily Earnings, line 65). The wage data for Argentina were quarterly averages of monthly wages for all manufacturing workers, taken from various issues of Indicadores de Coyuntura, published by FIEL (Fundacion de Investigaciones Economicas Latino-americanas). Finally, the wage series for Brazil consisted of quarterly averages of monthly wages for production workers in manufacturing, taken from Conjuntura Economica (Getulio Vargas Foundation).
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Bruno, M., and S. Fischer (1986), “The Inflationary Process in Israel: Shocks and Accommodation,” in The Israeli Economy, Yoram Ben-Porath (ed.), Cambridge, Harvard University Press, pp. 347–71.
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Leiderman, L. (1984), “On the Monetary-Macro Dynamics of Colombia and Mexico,” Journal of Development Economics (January-February), pp. 183–201.
Liviatan, N. (1986), “Inflation and Stabilization in Israel-Conceptual Issues and Interpretation of Developments,” (IMF, WP/86/10).
Liviatan, N. and S. Piterman, “Accelerating Inflation and Balance of Payments Crises, 1973-1984,” in The Israeli Economy, Yoram Ben-Porath (ed.), Cambridge, Harvard University Press, pp. 320–346.
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Van Wijnbergen, S., and R. Anand (1987), “Fiscal Deficits, Inflation, and the Financing of Government Expenditure in Turkey 1980–1986,” mimeo, World Bank.
Williamson, J. (ed.) (1985), Inflation and Indexation: Argentina, Brazil, and Israel, Washington DC, Institute for International Economics.
I would like to thank Nissan Liviatan, Mohsin Khan, and Miguel Kiguel for their comments on an earlier draft, without implicating them for any remaining errors.
Vector autoregressions have also been employed to examine money and output dynamics in developing countries (Colombia and Mexico) by Leiderman (1984).
See, for example, Bruno and Fischer (1985). More recently, Marshall and Morande (1987) have constructed a structural model of inflation for Brazil which includes precisely these variables.
An exception to the “data availability” rule was made for Argentina, where 1976:2 was dropped since a strong case can be made that this observation belongs to a different policy regime. The stabilization that followed the military overthrow of Isabel Peron had not been completed as of the second quarter of 1976.
The proportion of the forecast error variance of variable i which is contributed by variable j over an N-period horizon is an intuitively appealing way of summarizing the relative importance of j in causing movements in i over the sample period. The reason is that the contribution of j will depend both on the estimated coefficients of the first N innovations of j in the moving average representation for i and on the estimated variance of j. Thus j will make a relatively large contribution to the forecast error variance of i if a one-unit change in j has a relatively large effect on future values of i and/or if j has exhibited relatively pronounced variability over the sample period (see Sims (1980)).
Note that since the moving average representatioin is of infinite order, historical decomposition under this procedure always requires the choice of some base period T from which innovations can be computed.