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Appendix: Derivation of External Liability Equation
We thank seminar participants at the Central Bank of Brazil and the IMF, as well as Marcos Chamon, Marcello Estevão, and Sophocles Mavroeidis for comments on an earlier draft. The usual caveats apply.
Even though the literature on the relative performance of IT regimes in EMs is now sizeable (see, e.g., Loayza and Soto, 2002; Fraga, Goldfajn, and Minella, 2004; Miskin and Schmidt-Hebbel, 2007), model-based studies on the monetary transmission in these economies remain scarce. A notable exception has been the case of Chile. See Cespedes and Soto (2005) and the various references therein.
Other EMs that subsequently adopted IT are: South Africa and Thailand in 2000; Korea, Hungary and Mexico in 2001; and Peru and the Philippines in 2002. Chile first introduced annual targets for inflation in 1991, but a full-fledged IT framework has been in place only since 1999 after the relaxation of capital controls and elimination of exchange rate bands.
Technically the SVAR is an SVARX system due to the presence of exogenous foreign variables.
By domestic absorption (N) we mean the sum of expenditures on consumption, investment and government purchases, so by definition GDP will be equal to N plus exports minus imports.
The need for the latter often reflects the fact that there are permanent stochastic components that need to be removed to induce stationarity in the measured gap. Later we will provide a discussion of such transformations in detail, but even if there were no permanent components in the data, it is often the case for emerging-market economies that the equilibrium values to which the system will be adjusting are shifting over time in response to structural changes in the economy. Consequently, care should be taken when constructing these gaps, and any assessments of the resulting measures should rely on institutional knowledge of the economy being studied. This knowledge can be quite informative, not only of the presence of structural changes (such as those in the transition from high to low inflation regimes and across monetary policy frameworks as in Brazil between 1998 and 1999), but also of how sensible one’s estimation results appear to be. A striking example in the empirical macro literature of the problems arising from ignoring country-specific features in broad cross-country regressions pertains to the identification of the long-run effects of fiscal deficits on inflation; although solidly backed by theory, these effects are not easily discernable without properly taking into account country--group specific features in the estimation strategy. See Catão and Terrones (2005).
As discussed in the next section, we will augment this canonical specification to include the role of domestic interest spreads - a wedge which arises in models with deposit- and credit-in-advance constraints (see, e.g., Edwards and Végh, 1997). Since the domestic interest spread is itself a function of the policy interest rate as well as of a measure of the supply side of bank credit, this baseline specification for absorption will remain unchanged except for the addition of an extra term using an “excess credit” measure.
To the extent that target inflation is fully credible and thus becomes a true measure of expected inflation, then the interest rate variable in this regression is the theoretically relevant measure of the real interest rate in the Fisherian sense. This is consistent with econometric results reported in section VII.
Another rationale for this specification arises when the central bank seeks to prevent or minimize excessive appreciation of the currency for external competitiveness reasons. Avoiding large appreciations in the disinflation process has been, for instance, a well-known feature of the Chilean experience under IT. This has been reiterated recently by Chile’s central bank governor who in a public statement on October 17, 2007 indicated that the central bank reserves itself the right to intervene in the exchange rate market if the real exchange rate exhibits an “important misalignment” (sic) with respect to fundamentals. See http://ttda.today.reuters.com/news/Article.aspx?type=business News&StoryID=2007-10-18T1780731Z_01_N18424725
The specific way in which Edwards and Végh (1997) model bank technology yields a relationship between the lending and deposit spreads (measured relative to the base interest rate) and the credit to deposit ratio. But since deposit-in-advance constraints imply that deposits are proportional to expenditure, this directly translates into a functional relationship between bank spreads and the credit to expenditure ratio.
Allowing for the presence of an autonomous component in the “excess credit” variable that is not directly related to the interest rate seems particularly appropriate in the case of Brazil. Indeed, the existence of a large development bank (BNDES), which accounts for up to one quarter of domestic credit, and whose lending policies and rates arguably respond to other incentives can result in some lending rates significantly below market rates.
Even though the “dollarization” of private sector liabilities in Brazil is not nearly as extensive as in many other EMs, it is far from negligible. Starting from negligible amounts in the early 1990s, foreign currency denominated debt rose to 36% of total corporate debt in 1999, reaching 40% in 2002 (Bonomo, Martins, and Pinto, 2004, Table A.2). Using a large panel of firm-level data, Bonomo and others (2004) also find that balance sheet effects of currency movements have significant effects on credit demand and investment.
As discussed further below, we have experimented with both SVAR(1) and SVAR(2) models, but opted for an SVAR(1) specification. With larger samples it might be desirable to work with a higher-order VAR.
If the debt equation is also estimated, this would add an extra seven so treating it as an identity saves a number of parameters.
In our case
Adding the GNE gap to the credit equation gives a coefficient of 0.38 with a t-ratio of 1.03. While yielding the right sign, this lowers the t-ratio on the real interest rate variable to 1.2 suggesting strong multicollinearity between the variables. This is consistent with the evidence that absorption is itself a function of the interest rate and lagged excess credit so the GNE gap is spanned once those two variables are already present in the equation. For the purpose of illustrating our point, we dropped the GNE gap from the above single equation estimates but do include it in the VAR.
See the discussion by Eichenbaum (1994) on the difficulties faced by empirical work in the identification of a credit channel effects in the US, for which longer and better data and more disaggregated empirical evidence are available.
We have also experimented with extending the estimation period backwards to 1998Q2, i.e, after Brazilian inflation declined to single digit levels in 1997 and before the 1999Q1 devaluation and debt crisis. Both the coefficients on the output gap and inflation were significantly lower than after 1999Q2. This again reinforces the view that there was significant structural change in the monetary transmission process in Brazil before and after IT.
See Mishkin (2004) for a survey of these views and Masson, Savastano, and Sharma (1997) for an early prediction of the inadequacies of an IT framework in EMs.
Such a growing response of inflation to monetary tightening with lower output costs is also consistent with the experience of the US since the early 1990s, when (despite the lack of a formal IT framework) monetary policy became increasingly geared toward price stability. It has been argued that the credibility gains derived from such an implicit inflation targeting translated in subsequently lower sacrifice ratios (Goodfriend, 2005).