The severity of the economic recession after the 2008 financial crisis led governments across the world to adopt fiscal stimulus measures between 2008 and 2010. This and subsequent attempts to reverse budget deficits have been accompanied by a resurgence of economic research on the effectiveness of fiscal policy in influencing aggregate demand and GDP.
The New Keynesian models employed in analyses of fiscal policy in the post-2008 great depression have generated the consensus conclusion that when interest rates are at a zero lower bound, fiscal multipliers are significantly larger than in ‘normal’ periods (Blanchard and Leigh 2014; Christiano et al. 2011; Delong et al. 2012; Eggertsson 2009). A common mechanism yielding that conclusion is that, with the interest rate’s zero lower bound preventing the Central Bank from reducing the policy rate as a Taylor Rule would dictate in the recession, fiscal expansion raises inflation expectations. The resulting decrease in real rates stimulates aggregate investment and consumption.
We argue that this mechanism is not sufficient to explain the larger fiscal multipliers during the post-2008 crisis, for it does not capture financial sector dynamics, which are particularly important for analysing South Africa’s economic relations because of the financial sector’s size and level of development.
The novelty of our work is that we study the impacts of fiscal policy in a model which explicitly models financial flows and balance sheets in the economy. Specifically, we develop a small general equilibrium model that builds on Devarajan and Go (1998) and is stock and flow consistent in the tradition of Backus et al. (1980) and Godley and Lavoie (2007). Unlike the standard financial accelerator mechanism, our framework captures the interlinkages of all balance sheets in the economy. In addition, it links economic activity, asset price movements, bank capital, perceptions of risks in the financial sector, and lending spreads (the difference between the loan rate and the repo rate), thereby capturing some of the dynamics identified by Woodford (2010) and Borio and Zhu (2012).
We calibrate the model to South African data and assess the likely impact of fiscal expenditure on output after 2008. A defining feature of the South African economy is its well-developed financial sector. The 2016 Global Competitiveness Report ranks South Africa 12th in terms of its level of financial sector development. The South African rand is the 20th most-traded currency globally and the country has one of the highest market-capitalization-to-GDP ratios, with the Johannesburg Stock Exchange ranked 18th globally in terms of its market capitalization. South Africa’s deep and liquid financial markets facilitate funding for private and public institutions and have been integral to economic development in different periods. This indicates that analysis of fiscal policy in the South African context needs to consider interactions through both the financial sector and the real economy.
Our results indicate that the expenditure fiscal multiplier in South Africa was in the range of 2 to 3 in the period immediately after the 2008 financial crisis, given the negative output gap, the low government-debt-to-GDP ratio, the monetary policy stance, the health of the South African financial sector, and the large inflow of foreign savings into the economy. Our results differ significantly from those of recent studies on South Africa and studies looking at the size of fiscal multipliers in other emerging markets. The absence of Ricardian households in our framework, the lack of supply-side constraints, the unresponsiveness of monetary authorities to the closing but still negative output gap (similar to zero-bound interest rate conditions), and, most importantly, the presence of stock-and-flow-consistent financial sector dynamics amplify the impact of a fiscal stimulus.
In the model, the causal chain runs as follows. Higher fiscal expenditure increases aggregate demand, stimulating domestic economic activity in the presence of idle resources. Factor incomes increase, improving firms’ profitability and household income. This translates into higher deposits with banks. The supply of loans increases as there are more deposits with the financial sector. Following the mechanisms outlined by Borio and Zhu (2012) and Woodford (2010), the acceleration in economic activity reduces the probability of default and the perception of risk, and improves valuations and the net worth of the financial sector, leading to higher levels of intermediation and lower lending spreads. The decline in lending spreads stimulates economic activity further, creating a feedback loop which operates through the balance sheets of all agents, unlike the financial accelerator mechanism proposed by Bernanke et al. (1999). The effect depends on the inflows of foreign savings, which reduce the savings constraint facing the domestic economy and allow investment expenditure to accelerate. This result is in line with the theoretical model of Blanchard et al. (2016). In the absence of foreign savings, the higher multiplier is primarily driven by the higher levels of household consumption, as higher equity prices make it easier for the representative household to achieve its target level of wealth.
Our result relies on low debt agents or credit unconstraint agents—in this case government— expanding demand and fuelling a financial accelerator mechanism. The latter depends on the health of the financial sector. In a stock-and-flow-consistent framework, this implies that the
deterioration in the net worth of government is offset by an improvement in the net worth of other agents. In the South African context, the non-financial enterprise and foreign sectors have seen improvements in their net worth while the household and government sectors have recorded deteriorations in their net worth.
The rest of the paper proceeds as follows. In Section 2, we review the relevant literature. Section 3 provides an overview of the South African fiscal system and fiscal policy since the 2008 financial crisis. The model framework and the data are discussed in Sections 4 and 5, respectively. Section 6 presents the results and Section 7 concludes. Read more