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We thank Tam Bayoumi, Peter Clark, Hali Edison, Ken Kletzer, David Robinson, and participants of a seminar in the IMF research department for comments on this draft, Ben Sutton for able research assistance, and Marlene George for assistance with the preparation of this paper.
To be precise, Campillo and Miron (1997) include government debt/GDP ratio at a base year in their regressions, but no time series on deficits or any other fiscal variable. Click (1998) regresses government spending to GDP on a measure of seignorage and finds that government spending is not a determinant of cross-country differences in seignorage.
For the purpose of this paper, the following countries are defined as emerging markets: Argentina, Brazil, Chile, China, Colombia, Egypt, Hungary, India, Indonesia, Israel, Korea, Malaysia, Mexico, Morocco, Pakistan, Peru, Philippines, South Africa, Thailand, Turkey, Uruguay, Venezuela, and Zimbabwe. This sample excludes three countries usually classified as emerging markets (Czech Republic, Poland, and Russia) due to data limitations. At the same time, it includes two countries (Morocco and Zimbabwe) which have lower nominal GDP than other countries typically classified as emerging markets, in an effort to broaden geographical coverage.
For a discussion of these feedback effects, see Dornbusch, Sturzenegger, and Wolf (1990). Specifically, the literature has highlighted six mechanisms through which inflation may affect the ratio of fiscal deficit to GDP: (i) lags in tax collection, which reduce the real value of the latter as inflation rises (the “Tanzi effect”); (ii) lower tax compliance as inflation rises (reflecting, inter alia, diminished credibility in public institutions); (iii) the burden of taxation rises, partly because households move into higher tax brackets in a progressive and less than perfectly indexed tax system; (iv) time lags between budgeted and actual government disbursements help reduce the real value of public spending; (v) the real value of the public debt may be eroded by inflation under imperfect indexation, but real interest payments may actually rise if real interest rates increase due to bondholders’ demand for higher risk premia; (vi) average public sector wages tend to decline even if indexed, provided that their adjustment intervals remain unchanged as inflation rises. As some of these effects clearly offset each other, it is often difficult to predict the net effect of inflation on the deficit.
See, for instance, Cagan (1956) and Dornbusch, Sturzenegger, and Wolf (1990) for specifications wherein the ratio of fiscal deficit to GDP is directly related to inflation without featuring the inflation tax base as a scaling variable. Two studies that include the ratio of narrow money to GDP in regressions relating fiscal deficits to inflation are Rodrik (1991) and Metin(1998).
Some studies have attempt to capture this non-linearity by measuring inflation as log (1+π) and regressing it on the nominal fiscal deficit scaled by nominal GDP. The advantage of the specification used in this paper is that such non-linearities are explicitly derived from a model with microfoundations and shown to be related to factors pertaining to the demand for money and domestic financial development.
See Banerjee, Dolado, Galbraith, and Hendry (1993) for an useful survey of ARDL models. Pesaran and Shin (1998) discuss the use of ARDL model in the estimation of cointegrating relationships and show that it has desirable finite sample properties.
The MG estimator consists of estimating separate ARDL models for each country and obtaining the overall panel estimates as the arithmetic average of individual country coefficients. The MG estimator has been shown to produce consistent estimates of the average of the parameters in heterogeneous panels, but such estimates will be inefficient if slope homogeneity restrictions hold.
With regard to other explanatory variables we consider, such as world inflation and oil prices, the exogeneity assumption seems clearly warranted.
This was case for several countries in the sample. Regressing current values of (G – T)/M1 on its lags as well as on lagged inflation yielded R2’s below 0.5 in quite a few cases.
Observations for two countries (China and Hungary) only start from 1980 and a few others from the mid-1970s. So, the panel is unbalanced.
Long series on broader fiscal deficit measures comprising local governments and including central bank losses proved impossible to obtain on a consistent basis for all countries. While the distinction is relatively unimportant for countries where the fiscal system is highly centralized (most Asian countries), level differences between central and general government deficits have been substantial in some cases (notably in Latin America). Yet, an inspection of data for some fiscally decentralized countries for which both measures are available indicates that they have tended to move together. Thus, we would not expect our results to change substantially if more comprehensive fiscal balance measures could be used.
In all regressions, the optimal lag structure (p,q) was chosen by the Schwartz Bayesian Criterion (SBC) and constrained to (p,q) ≤ 2 in order to conserve on degrees of freedom. Limiting the number of lags to at most two is a commonly used procedure for models involving a large number of parameters and estimated with annual data. In more than half of the countries, the SBC indicated that one lag of the dependent variable was enough.
This can be readily seen by substituting π ≈ ln(1 + π) and taking the derivative of (1), which yields:
For discussion of the channels through which these two variables can affect inflation trends in emerging markets, see International Monetary Fund (2001).
The other testable hypothesis derived from the time inconsistency theory and which has been examined in previous studies is that inflation tends to be lower in countries with more independent central banks (Cuckierman et al., 1992; de Haan and Kooi, 2000). However, the lack of time series on central bank independence measures for our sample of countries during the 1970–2000 period prevented us from testing its significance.
A recent study has found a positive correlation between openness and government size (Rodrik, 1998). It has been suggested that this positive correlation may reflect the use of government spending as an external risk-reducing device.
This belief has been qualified, however, by Fatás and Rose (2001) and more radically questioned by Tornell and Velasco (2000). The results of Table 6 have also to be cautioned by the difficulties in distinguishing between the regimes on the basis of a de facto v. de jure classification system. See Levy-Yeyati and Sturzenegger (2000).
Indeed one gets,