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Economic growth before and after the fiscal stimulus of 2008–2009: the role of institutional quality and government size

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Abstract

Governments implemented fiscal stimulus packages to alleviate the global financial crisis of 2007–2009. Using annual data from 1996 to 2019, we investigate economic growth in a large sample of countries for pre-and post-Global Financial Crisis years. Our approach analyzes the interaction between institutional quality and government size (government expenditures as share of GDP), reinforced by threshold estimations. We document that economies react to government size depending on the quality of the institutions in question. First, fixed effects models indicate higher institutional quality has positive effects on growth, while government size—and its interactions with institutional quality—has negative effects. Second, the coefficients of government size on economic growth are negative with higher institutional quality and become larger in the post-Global Financial Crisis years. These combined results indicate that higher-quality institutions make economies less tolerant of rising government expenditures than lower-quality institutions. Our main findings support institutional quality as the channel through which fiscal policy has real effects. The evidence herein is robust to measures of institutional quality from different databases.

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Notes

  1. We refer to government size in this paper as G/Y: government expenditures (G) divided by GDP (gross domestic product, Y).

  2. Other studies address G/Y and factors such as trade and public sector quality. Rodrik (1998) handles the relative size of government influenced by the amount of trade openness, with recent evidence for Latin American economies provided by Vianna and Mollick (2018a) and Williams (2021) for a larger sample of countries. Lizardo and Mollick (2009) examine the effect of government consumption on economic growth in 23 Latin American countries over the years 1974–2003. Employing the “Armey Curve”, they show that the typical Latin American government is spending beyond the optimal point. Oto-Peralías and Romero-Ávila (2013) argue that public sector quality plays an important role in the link between government size and growth and show that the size of government negatively affects growth only when bureaucracy quality is weak. Divino et al. (2020) explore government size and the composition of public spending for the 27 Brazilian states using annual data from 2004 to 2010.

  3. In a previous version of this paper, institutional quality (INST) was calculated as an equally-weighted average of the six WGI measures: Control of Corruption, Government Effectiveness, Political Stability and Absence of Violence, Regulatory Quality, Rule of Law, and Voice and Accountability.

  4. We use the indicator from the World Bank national accounts data and OECD National Accounts data files (General government final consumption expenditure, % of GDP; code NE.CON.GOVT.ZS). There is another indicator from the IMF (Expense, % of GDP; code GC.XPN.TOTL.GD.ZS). While the former accounts for all government current expenditures for purchases of goods and services, the latter measures cash payments for operating activities of the government in providing goods and services.

  5. Other series, not displayed in Table 1, are as follows. A country’s real interest rate is its lending interest rate adjusted for inflation as measured by its GDP deflator. It shows the extent of monetary policy, towards more accommodation since the GFC: declining from 7.372% to 6.263% over the two subperiods. Infrastructure is proxied by the number of fixed telephone subscriptions per 100 people, and the average total population is also used.

  6. The Table reporting the matrix of correlation coefficients for the variables in the empirical model is available upon request.

  7. According to the executive summary of V-Dem (2021), the level of democracy enjoyed by the average global citizen in 2021 is down to 1989 levels. The last 30 years of democratic advances have been replaced with dictatorships on the rise, harboring 70% of the world population: 5.4 billion people, and signals of changing nature of autocratization.

  8. Seo and Shin (2016) estimate dynamic panel threshold models of firm investment depending on lagged investment, cash flows, Tobin’s q, and leverage. In their case, the transition variable can be either cash flows, Tobin’s q, or leverage. The results change across transition variables (and different thresholds) but the cash flow sensitivity of investment is stronger for cash-constrained, high-growth and high-leveraged firms.

  9. A previous version of this article also adopted, for completeness, an alternative specification in which G/Y is the threshold due to contributions of government size and growth reviewed earlier. For example, crowding-in happens when higher government spending leads to an increase in private sector investment. This occurs due to higher government spending leading to an increase in economic growth and therefore encouraging firms to invest once the growing economy brings more profitable investment opportunities. These results for G/Y as threshold variable are available upon request but are generally less conclusive. The threshold identified for G/Y is quite low, around 3% of GDP, and the results of institutional quality effects on RGDP growth are very mixed.

  10. It is possible to summarize some of the channels in Acemoglu et al., (2003, pp. 61–62) as follows. In institutionally weak societies, we should have: 1. Few constraints on rulers: following a change in the balance of political power, groups that gain politically may attempt to use their new power to redistribute assets and income to themselves (more economic turbulence); 2. Greater gains from coming to power, and correspondingly, greater losses from not controlling political power; 3. Economic cooperation may have to rely on ‘‘trust’’, shocks may make it impossible to sustain cooperation and lead to output collapses; 4. Contractual arrangements will be more imperfect, making certain economic relationships more susceptible to shocks; 5. Politicians may be forced to pursue unsustainable policies in order to satisfy various groups and remain in power and volatility may result when these policies are abandoned; and 6. Entrepreneurs may choose sectors/activities from which they can withdraw their capital more quickly, thus contributing to economic instability.

  11. The search for the threshold on institutions is set as follows when constructing a grid for estimating the threshold, reported as r in Tables 3 and 4 below. It is required to be a positive real number < 1. We use 0.2 for the trim_rate in xthenreg STATA command, which means that the start and end points of the grid are the 0.1 quantile and 0.9 of the observed measure of institutions. Doing so, this in practice ignores the extreme values of institutional quality.

  12. In the Arellano–Bond method, first differences of the regression equation are taken to eliminate the individual effects. Then, deeper lags of the dependent variable are used as instruments for differenced lags of the dependent variable (which are endogenous).

  13. Given that Seo and Shin (2016) post-estimation tests for dynamic threshold panel data are not currently available in Stata, we run “xtabond2” to obtain Arellano-Bond (AR2) test for second-order autocorrelation with a p-value of 0.148; and Hansen J-test of overidentifying restrictions with a p-value of 0.135. Further specifications and regression results are available upon request.

  14. Note that before the year 2000 EFW collected a single observation per country for 5-year periods.

  15. In a Table available upon request, with time trend varying with thresholds and endogenous G/Y, the coefficients under higher institutional quality are estimated statistically significant at − 11.55 for GE, − 22.19 for INST and − 9.616 for EFW and more mixed under lower institutional quality.

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Authors and Affiliations

  1. Department of Economics, The University of Texas Rio Grande Valley, 1201 West University Drive, Edinburg, TX, 78539-2999, USA

    Andre Varella Mollick

  2. National Treasury Attorney’s Office in the State of Santa Catarina, Federal Government of Brazil, Rua Arcipreste Paiva 107, Centro, Florianópolis, SC, 88010-530, Brazil

    Andre Coelho Vianna

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Mollick, A.V., Vianna, A.C. Economic growth before and after the fiscal stimulus of 2008–2009: the role of institutional quality and government size. Public Choice 198, 189–207 (2024). https://doi.org/10.1007/s11127-023-01121-5

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