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Robert Kollmann is a Professor of Economics at University of Paris XII. This project was started during a visit to the IMF’s Research Department, whose hospitality is gratefully acknowledged. The author acknowledges comments made by workshop participants at CEPREMAP, EC ARE, INSEAD, LSE, the Universities of Birmingham Exeter, Kiel, Munich and Tilburg and at several research conferences, as well as by Martin Cerisola, Michael Devereux, Chris Erceg, Harald Hau, Philip Lane, Alessandro Prati, Partha Sen and Harald Uhlig.
Also, the price adjustment mechanism assumed by Obstfeld and Rogoff generates very simple dynamics: e.g., after a permanent money supply shock, the economy is predicted to adjust to its new long run equilibrium in a single period. The model in the present paper yields richer dynamics.
That model also cannot generate significant exchange rate volatility (no exchange rate overshooting in that model). Hau’s (1998) version of the Obstfeld-Rogoff framework that assumes nominal wage rigidities (wages that are set one period in advance), rather than price rigidities in goods markets, likewise predicts negative international transmission of money supply shocks.
The model here is an extension of the quantitative small open economy (SOE) model in Kollmann (1997) to a two-country world (because of the SOE assumption, that earlier model is not suited for studying the cross-country correlations that are the focus of the present paper). Quantitative (calibrated) dynamic-optimizing open economy models with sticky nominal prices have also recently been presented by Betts and Devereux (1997) [BD] and by Chari, Kehoe and McGrattan (1997) [CKM]. The paper here differs significantly from their work, i.a. by assuming incomplete international asset markets (see discussion below) and sticky wages, by considering a broader set of monetary policy rules and by examining model implications for a wider set. of variables (i.a., asset returns). The focus of CKM’s analysis is different from that of the paper here, although (as was brought to my attentions after the analysis here was completed) they too note that money supply shocks may generate positive cross-country correlations of output, when nominal rigidities are assumed. The BD model can likewise generate high cross-country correlations of output, when money supply shocks drive business cycles, but only when pricing to market (PTM) behavior by exporters is assumed (PTM is also postulated by CKM). Neither of these two models can capture the high cross-country correlations of interest rates that are seen in the data. The main results in the present paper do not hinge on PTM (empirical estimates of the incidence of PTM behavior vary widely, by country and industrial sector; see, e.g., Hooper and Marquez (1995) for references to the relevant literature). Also, the paper here shows that productivity shocks too generate substantial positive cross-country correlations of output, when nominal rigidities are assumed.
Labor enters linearly in the period utility function. Such a specification is widely used in the Real Business Cycle literature, as it seems best suited for capturing the observed volatility of hours worked (e.g., Hansen (1985)).
This assumption is standard in business cycle models with price rigidities (e.g., Mankiw (1997, ch.8)). Equation (17) implies that, up to a certainty equivalent approximation, the price
The household’s financial transactions are, thus, restricted to trade in bonds. This asset market structure is consistent with the well documented home-country bias in investors’ equity portfolios (e.g., French and Poterba (1991)). Kollmann (1995, 1996, 1998) compares models of the international economy in which bonds only are traded internationally (as assumed in the present paper) to models that also allow for international trade in state-contingent assets—it is found that, empirically, the former models capture key international business cycle stylized facts better.
N.B. When the wage rate is fully flexible (D=0), then (32), (33) imply
These estimates pertain to short-run (quarterly) money demand elasticities. Estimates of short-run elasticities are used to calibrate the model, because the focus of the present paper is on high frequency movements in interest rates, exchange rates and other macroeconomic variables (long-run elasticities of money demand with respect to the transactions proxy are generally higher than short-run elasticities—e.g., estimation results presented by McCallum (1989) suggest that the long run elasticity is approximately 0.50). Note also that (as is common in the literature) the money demand functions estimated by the authors cited above use GNP as a scale variable, and not consumption per se.
The key model predictions discussed below are not sensitive to the assumed steady state velocity (a unit velocity is roughly consistent with data on the Ml consumption velocity in the G7 countries; e.g., in the U.S. that velocity was 0.93 in 1994).
The main simulation results are robust to the choice of v. In order to solve the model for the aggregate price and quantity variables on which the discussions below focus, no specific value has to be assigned to the parameter r that determines the elasticity of substitution between different types of labor (the linearization of the model yields a system of equations in the aggregate variables that does not depend on r). N.B. The aggregate technology (2) implies that the elasticity of substitution between imported and domestic (intermediate) goods equals unity. That elasticity is in the range of estimated elasticities reported in the international trade literature (see Backus et al. (1995)).
Taylor and Hall (1997, p. 434) argue that wage adjustments for non-union workers occur typically once every year, in the U.S. (wage contracts of union workers are changed less frequently).
See Section III. and Appendix I for a discussion of the data. Standard Augmented Dickey-Fuller unit root fail to reject the hypothesis that log U.S. and G6 money supplies follow unit root processes and Phillips and Ouliaris (1990) cointegration tests suggest that these series are not cointegrated. This implies that the series can be modeled as VAR in first differences (see Campbell and Perron (1991, p. 170). The order of the VAR was chosen, based on the Akaike information criterion.
To simplify the discussion of the results, a symmetric shock process is assumed (the assumed autocorrelation of the money growth rate, 0.30, corresponds roughly to the mean of the diagonal elements of the autocorrelation matrix in Table 1; the standard deviations of the innovations in (44) are set at the mean value of the standard deviations of U.S. and’ G6 money supply innovations). N.B. as
The results here confirm previous studies that show that, in business cycle models without nominal rigidities, the predicted variability of exchange rates and stock returns tends to be much too low, when compared to the data, and that irrespective of whether money supply shocks and/or productivity shocks are assumed (see, e.g., Marshall (1992), Canova and De Nicolo’ (1995), Schlagenhauf and Wrase (1995)).
The response of a given variable zt is shown as (zt -z)/z, where z is the value of that variable in the unshocked steady state. In contrast, responses of interest rates and equity returns are shown as differences from that steady state (e.g., rt -r, where r is the steady state interest rate).
The prediction that a positive money supply shock induces a rise in domestic output, a fall in the domestic interest rate and an exchange rate depreciation is consistent with recent empirical evidence on the effect of money supply shocks (e.g., Eichenbaum and Evans (1995), Grilli and Roubini (1996)).
Conditions (29) and (30) imply that, up to a certainty equivalent approximation, Uncovered Interest Parity holds, in equilibrium:
Up to a certainty equivalent approximation, equations (28) and (30) imply that the date t nominal interest rate
Thorbecke (1997) documents empirically that unanticipated expansionary monetary policy shocks induce a significant rise in equity returns, on impact. The transitory nature of the predicted rise in stock returns is consistent with estimated responses of stock returns to money supply shocks that are reported by Marshall (1992, p. 1335).
Consider an intermediate good producer in country i that is “allowed”, at date t, to reset its export price, in terms of the currency of its foreign customers. Let
when the model with PTM is simultaneously subjected to money supply and to technology shocks, the predicted standard deviation of the nominal exchange rate and the cross-country correlations of the interest rate and of investment are 3.84%, 0.23 and 0.26, respectively, compared to 3.29%, 0.57 and 0.56 in the baseline model. The working paper version of this paper considers a case in which only exporters located in one of the two countries use PTM; predictions in that case change less, compared to the baseline model (the standard deviation of the nominal exchange rate and the cross-country correlations of the interest rate and investment are 3.55%, 0.47 and 0.43, respectively, in that case).
The above discussion of the baseline nominal rigidities model has focused on two mechanisms that induce positive transmission of a country 1 money supply increase to country 2 output (rise in country 1 absorption that raises demand for country 2 goods; fall in the country 2 interest rate induced by reduction in the country 2 price level) and one negative transmission effect (negative substitution effect due to the depreciation of the country 1 currency). When PTM is assumed, the second of these positive international transmission channels is weakened considerably (as the country 2 interest rate is hardly affected by the money supply shock). However, the negative international transmission effect is likewise weakened, compared to the baseline structure (under PTM, the assumed stickiness of prices, in the buyers’ currencies, dampens the short run effect of movements in the nominal exchange rate on the relative price between domestic and foreign intermediate goods faced by the buyers of these goods). The net result is that PTM does not affect the response of country 2 output to a country 1 money supply shock (as can be seen by comparing Panel (b) in Figures 1 and 3), which explains why the predicted cross-country correlation of output is hardly affected by PTM, as discussed above.
E.g., when only wages are sticky, then the predicted cross-country correlations of output, the nominal interest rate and the nominal equity return are 0.29, 0.13 and 0.37, respectively, when money supply and technology shocks are used simultaneously (see Column (4), Table 4), compared to 0.42, 0.57 and 0.45, in the baseline structure, while the predicted standard deviations of output and the nominal exchange rate drop to 1.93%. and 2.73%,, respectively, from 2.65%. and 3.29% in the baseline case.
Table 2 reports estimates of reaction functions in which
Assume that an autonomous positive money supply shock occurs m country 1, say. That shock raises the country 1 price level, and it reduces the price level in country 2, as discussed above. When f1 <0, this induces a rise in the country 2 money supply (it also implies that the country 1 money stock rises less than in the baseline case). Hence, the cross-country correlation of money rises, compared to the baseline case, which helps to understand why the cross-country correlations of real economic activity and of returns rise, as well.
Assume that a positive autonomous money supply shift occurs in country 1; such a shock induces a depreciation of the country 1 currency, which raises the country 2 money supply, when h2 =-0.10—hence, the cross-country correlation of money increases (to 0.38, from 0.20 in the baseline model), which helps to understand why output and the other variables considered in Table 5 are likewise more closely correlated across the two countries.