towards the goal of more predictable and credible fiscal policy, a number of countries have adopted constraints on their fiscal policies in the form of one or several types of fiscal rules that impose numerical limits on budgetary aggregates (see, for example, Kopits and Symansky (1998) and (2001), IMF (2012), as well as Wyplosz (2005) and (2012)). The imposition of such rules may spill over onto the country’s business cycles through several channels.

 Fiscal rules may limit the ability of the government to respond to business cycles shocks and smooth out their effects on the economy. This will tend to amplify macroeconomic volatility.  By imposing limits on fiscal policy, fiscal rules lower the stock of debt that the government may accumulate, as well as make fiscal policy more predictable, thus reducing the incidence of fiscal policy shocks on the economy. This channel will tend to reduce macroeconomic volatility.

Therefore, the net effect of fiscal rules adoption depends on which of the two channels dominates. We investigate this question empirically, by comparing the business cycles dynamics of fiscal rule adopters and non-adopters; as well as by controlling for the potential effects of fiscal rules presence when evaluating the effects of country size on its business cycles characteristics.

Lastly, we also control for commodity exporting status since commodity exporting countries are more prone to external shocks such as weather and terms of trade.

# **3. Data Description and Methodology**

# **Data**

A common feature of the studies discussed above is that they rely on relatively small samples of developing countries in their analysis. To a large extent, this is due to limited availability of quarterly data. This produces a trade-off between the country coverage of the analysis and the usage of quarterly versus annual data. Annual data for the key macroeconomic aggregates is available for almost all countries and thus allows for the broadest possible sample coverage. In fact, for most very small countries, which are of particular interest to us, quarterly data are not available at all, leaving us no choice but to use annual data. Moreover, many macroeconomic variables now have long time-series coverage at annual frequency going back to the 1960s, which gives us sufficiently long time series for reliable statistical inference. On top of that, annual data are available for a large spectrum of macroeconomic variables, which allows us to examine various dimensions of business cycle fluctuations.

Our data come from several sources. Most of the macroeconomic variables and variables reflecting country size (population, labor force, employment, geographic area, etc.) are taken from the _World Development Indicators_ (WDI) database of the World Bank. This data set covers the period of 1960-2014 at annual frequency. Most aggregate quantities that we use are measured in constant 2005 US dollars.<sup>10</sup> The data on most fiscal variables, such as government revenues, expenditures, and net lending/borrowing are from the International Monetary Fund’s _World Economic Outlook_ (WEO)

> 10 The business cycle moments remain unchanged when variables are measured in constant local currency units since the two denominations differ by a constant factor.

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