To summarize, fiscal procyclicality amplifies the effect of commodity price shocks on the business cycle in EMDEs. In the sample period examined, <mark>fiscal policy in the average EMDE commodity exporter is estimated to have increased the effect of a commodity price shock on output by more than one-fifth. T</mark> he results indicate that in EMDE commodity exporters fiscal policy has tended to amplify the business cycle, whereas in advanced-economy commodity exporters fiscal policy has tended to dampen it.

# **IV. Fiscal policy volatility**

# **IV.1 Estimating fiscal policy volatility**

The framework used to estimate fiscal policy volatility is based on the approach in Fatás and Mihov (2013) and Arroyo Marioli, Fatás, and Vasishtha (2023) , which involves estimating a fiscal policy reaction function of the following form: F F P (2) Where “ _Fiscal Policy_ ” is a variable that captures the stance of fiscal policy. Four alternative measures of tt tt tt tt PPF FF P FFee = αα + ββ CCFFPPrrPPmmF AAFFrrFFAAFFrree + γγ CCPPr FFPP + εε Where “ _Fiscal Policy_ ” is a variable that captures the stance of fiscal policy. Four alternative measures of fiscal policy are used: primary expenditures (which exclude net interest payments), revenues, government consumption, and the primary budget balance (which excludes net interest). The first three variables are expressed in real (inflation-adjusted) terms and measured as log differences. The primary budget balance is expressed as the annual change of its ratio to GDP. “ _Economic Activity_ ” denotes the cyclical stance of the economy and is represented by annual GDP growth. The alternatives—the output gap and the unemployment rate—are more difficult to construct or measure accurately for diverse economies.<sup>19</sup> summarizes the cyclical behavior of fiscal policy and indicates whether fiscal policy is countercyclical or procyclical. It is composed of both automatic stabilizers and the discretionary response of governments to economic fluctuations. ββ<sup>20</sup> The residual , captures changes in fiscal policy that are unrelated to the business cycle or any of the control variables. These decisions can be the result of political decisions (such as changes in tax rates or spending associated with the political cycle) or errors in policy (such as , εε mismeasurement of the output gap). The uncertainty associated with the residual can be seen as generating excessive volatility in GDP and, possibly, reduced long-term growth. Following Fatás and Mihov (2013), the volatility of fiscal policy is measured as the standard deviation of the residual in the fiscal policy reaction function ( ). εε Annual data are used for the 1990–2021 period for 184 countries, including 148 EMDEs and 36 advanced ii σσ Annual data are used for the 1990–2021 period for 184 countries, including 148 EMDEs and 36 advanced economies. The choice of the sample period is based on data availability. Of these 184 countries, 94 are commodity exporters and the remainder as commodity importers. Among commodity exporters, only five are advanced economies. Among commodity importers, 31 are advanced economies and 59 are EMDEs.

# **IV.2 Basic features of fiscal policy volatility**

The following stylized facts emerge from a comparison of the measures of fiscal policy volatility for EMDEs and advanced economies. First, over the past three decades, the volatilities of primary expenditures, government consumption, and revenues were all significantly higher in EMDEs than in advanced

> 19 HP-filtered GDP levels are also used as a measure of economic activity to check the robustness of the results. The results using this alternative measure are consistent with the baseline results.

> 20 The specification has potential endogeneity issues since fiscal policy could affect economic activity contemporaneously. While the literature has acknowledged these issues, it has made use of OLS in many instances because of the lack of an obvious instrument (for example, Aghion, Hemous and Kharroubi 2014; Alesina, Campante and Tabellini 2008; and Lane 2003). Studies that have explored a set of instruments to test the robustness of the results presented in these earlier papers find similar results (for example, Fatás and Mihov 2013). Given this, and for the sake of simplicity, the analysis in this paper makes use of OLS.

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