Abstract
This paper analyzes the dynamic impact of discretionary government consumption purchases on private demand. Using a panel of 132 countries from 1960 to 2008, we find that while discretionary changes in government consumption lead to crowding-in effects in the short run, crowding-out effects take over in the medium run. In addition, we also find that both short-term crowding-in and medium-term crowding out effects are amplified once we control for periods of crisis.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
For example, Reinhart and Rogoff (2008, 2009a, b) find that banking crises lead to sharp declines in tax revenues, as well as to significant increases in government spending and, at the end of these episodes, economic growth recovers very slowly. Laeven and Valencia (2008) estimate that the net fiscal costs associated with systemic banking are substantial. Furceri and Zdzienicka (2010) find that banking crises are followed by a medium-term increase in the government gross debt-to-GDP ratio of about 37 percentage points.
See Furceri and Sousa (2011) for a review of the literature of crowding-in and crowding-out effects.
Similarly to Fatás and Mihov (2012), we consider government consumption rather than total government spending, because the former is readily comparable across countries and is not being subject to frequent structural breaks or changes in definitions. In addition, as Ilzetki and Vegh (2008) point, for policy purposes, one should look at instruments (such as government consumption) rather than outcomes (such as government spending), as the latter cannot be controlled by policymakers. From an empirical point of view, the consideration of government spending (instead of government consumption) would also be more vulnerable to a lack of precision in the identification of three main characteristics of fiscal policy (responsiveness, persistence and discretion). The reason for this is that government spending includes transfers and debt service, and we also include the debt level among the set of control variables. Finally, data for government consumption is available for a larger number of countries and a longer time period. Having said that, we recognize the obvious caveat that government consumption only accounts for a part of total government expenditure.
Theoretical models suggest that the effect of government shocks on economic activity is different between transitory and permanent shocks. While it would be interesting to empirically analyze this issue, our estimation strategy is not suitable for this purpose.
Pagan (1984) argues that when (i) the predetermined variables that appear in the equation of interest are also included in the first-stage regression, (ii) only lagged values of the generated regressors appear as explanatory variables, and (iii) an instrumental variable estimation is used in the second-stage, valid statistical inference can be made with a small loss of efficiency.
Including lags allows for a delayed impact of discretionary measures on real activity avoids getting biased estimates for the coefficients associated to fiscal discretion in the second stage. In fact, the shock is a function of the dependent variable. Consequently, the inclusion of contemporaneous fiscal discretion in equations (2) to (4) - instead of its lags -, would imply that the coefficient associated with fiscal discretion would be the “sum” of its own explanatory power and its covariance with the dependent variable. Putting it differently, the coefficient would be biased and the shock could not be retrieved or properly identified. Indeed, while tackling the issue of endogeneity and simultaneity in the first-stage, the issue of identification in the second-stage still requires a careful treatment. This is less of a problem when we only add the lags of the shock to the second-stage regressions.
Our specifications include an auto-regressive term of order one (AR1) and a set of lags for the discretionary government consumption. Therefore, for horizons s = 0, …, 4, and, in particular, in the case of the growth equations, the IRFs can be expressed, respectively, as \( \frac{{\partial \varDelta {y_{i,t}}}}{{\partial {{\hat{v}}_{i,t}}}} = 0 \), \( \frac{{\partial \varDelta {y_{i,t + 1}}}}{{\partial {{\hat{v}}_{i,t}}}} = {\delta_1} \), \( \frac{{\partial \varDelta {y_{i,t + 2}}}}{{\partial {{\hat{v}}_{i,t}}}} = {\delta_1}\beta + {\delta_2} \), \( \frac{{\partial \varDelta {y_{i,t + 3}}}}{{\partial {{\hat{v}}_{i,t}}}} = {\delta_1}{\beta^2} + {\delta_2}\beta + {\delta_3} \) and \( \frac{{\partial \varDelta {y_{i,t + 4}}}}{{\partial {{\hat{v}}_{i,t}}}} = {\delta_1}{\beta^3} + {\delta_2}{\beta^2} + {\delta_3}\beta + {\delta_4} \). The expressions for the consumption and the investment growth equations are similar. They alternate between positive and negative values depending on the signs and magnitudes of the parameter estimates \( \beta \) and \( {\delta_j} \). However, the stationary of the AR part (\( \left| \beta \right| < 1 \)) guarantees that responses coverge towards zero, although not necessarily in a monotonic way (Hamilton 1994).
The impulse-response functions are consistent with specifications (2)-(4). In this case, unless we impose some kind of factorization, the response of GDP, consumption and investment to the discretionary fiscal spending component cannot be assessed. In our framework, this can be achieved by including only the lags of the shock in the set of explanatory variables of the second-stage regressions. Although we do not estimate a (Bayesian) Vector Auto-Regressive or Maximum Likelihood framework, the underlying mechanism is similar. In addition, if the discretionary component of government spending is thought as a predictive variable and we assess its economic content over different time horizons, then our second-stage framework can be described as a set of forecasting regressions. In this context, predictors and predicted variables need to be evaluated at different moments in time, not contemporaneously.
The measurement of government consumption in the WDI database is comparable across countries and over time.
The IRFs computed from the basic and extended specifications tend to overlap.
The fact that the multiplier on GDP is less than one and that consumption and investment positively respond to fiscal shocks would imply that remaining components of GDP (non-discretionary government spending and trade balance) should follow. However, while this argument holds for a time-series analysis on a single country, it may not necessary hold in a panel framework. In fact, the results of the panel analysis have to be interpreted as average responses over the panel sample. Therefore, it could be still the case that the average response of the trade balance is positive, as it depends on the different contribution (weight) of domestic absorption and trade balance in each country.
See Furceri and Sousa (2011) for a review of the literature.
In this case, for horizons s = 0, …, 4, and, in particular, in the case of the growth equations, the IRFs can be expressed as \( \frac{{\partial \varDelta {y_{i,t}}}}{{\partial {{\hat{v}}_{i,t}}}} = 0 \), \( \frac{{\partial \varDelta {y_{i,t + 1}}}}{{\partial {{\hat{v}}_{i,t}}}} = \left( {{\delta_1} + {\phi_1}} \right) \), \( \frac{{\partial \varDelta {y_{i,t + 2}}}}{{\partial {{\hat{v}}_{i,t}}}} = \left( {{\delta_1} + {\phi_1}} \right)\beta + \left( {{\delta_2} + {\phi_2}} \right) \), \( \frac{{\partial \varDelta {y_{i,t + 3}}}}{{\partial {{\hat{v}}_{i,t}}}} = \left( {{\delta_1} + {\phi_1}} \right){\beta^2} + \left( {{\delta_2} + {\phi_2}} \right)\beta + \left( {{\delta_3} + {\phi_3}} \right) \) and \( \frac{{\partial \varDelta {y_{i,t + 4}}}}{{\partial {{\hat{v}}_{i,t}}}} = \left( {{\delta_1} + {\phi_1}} \right){\beta^3} + \left( {{\delta_2} + {\phi_2}} \right){\beta^2} + \left( {{\delta_3} + {\phi_3}} \right)\beta + \left( {{\delta_4} + {\phi_4}} \right) \), respectively. The expressions for the consumption and the investment growth equations are similar.
The baseline scenario presents the results obtained using equations (2)-(4), where we do not control for the effect of the crises (direct and via the interaction term).
References
Abbas SA, Belhocine N, ElGanainy A, Horton M (2010) A historical public debt database. International Monetary Fund, IMF Working Paper No. 245
Afonso A, Agnello L, Furceri D (2010) Fiscal policy responsiveness, persistence and discretion. Public Choice 145(3):503–530
Agnello L, Cimadomo J (2012) Discretionary fiscal policies over the cycle: new evidence based on the ESCB disaggregated approach. Int J Cent Bank, June issue
Alesina A, Ardagna S (2010) Large changes in fiscal policy: taxes versus spending. In: Brown, JR (ed) Tax Policy Econ 24:35–68
Alesina A, Ardagna S, Perotti R, Schiantarelli F (2002) Fiscal policy, profits, and investment. Am Econ Rev 92(3):571–589
Alesina A, Tabellini G, Campante FR (2008) Why is fiscal policy often procyclical? J Eur Econ Assoc 6(5):1006–1036
Ardagna S (2009) Financial markets’ behavior around episodes of large changes in the fiscal stance. Eur Econ Rev 53:37–55
Arellano M, Bond S (1991) Some tests of specification for panel data: monte Carlo evidence and an application to employment equations. Rev Econ Stud 58:277–297
Baldacci E, Kumar MS (2010) Fiscal deficits, public debt, and sovereign bond yields. International Monetary Fund, IMF Working Paper No. 184
Baldacci E, Gupta S, Mulas-Granados C (2009) How effective is fiscal policy response in systemic banking crises? International Monetary Fund, IMF Working Paper No. 160
Cerra V, Saxena S (2008) Growth dynamics: the myth of economic recovery. Am Econ Rev 98:439–457
Cerra V, Panizza U, Saxena S (2009) International evidence on recovery from recessions. International Monetary Fund, IMF Working Paper No. 183
Cimadomo J (2012) Fiscal policy in real time. Scand J Econ, forthcoming
Cimadomo J, Kirchner M, Hauptmeier S (2010) Transmission of government spending shocks in the euro area: time variation and driving forces. European Central Bank, ECB Working Paper No. 1219
Claessens CA, Klingebiel D, Laeven L (2004) Resolving systemic financial crises: policies and institutions. The World Bank, Policy Research Working Paper No. 3377
Coenen G, Erceg C, Freedman C, Furceri D, Kumhof M, Lalonde R, Laxton D, Lindé J, Mourougane A, Muir D, Mursula S, de Resende C, Roberts J, Roeger W, Snudden S, Trabandt M, in’t Veld J (2012) Effect of fiscal stimulus in structural models. Am Econ J: Macroecon 4(1):22–68
Fatás A, Mihov I (2003) The case for restricting fiscal policy discretion. Q J Econ 118:1419–1447
Fatás A, Mihov I (2006) The macroeconomics effects of fiscal rules in the US states. J Public Econ 90:101–117
Fatás A, Mihov I (2012) Policy volatility, institutions and economic growth. Rev Econ Stat, forthcoming
Furceri D, Sousa RM (2011) The impact of government spending on the private sector: crowding-out versus crowding-in effects. Kyklos 64(4):516–533
Furceri D, Zdzienicka A (2010) The consequences of banking crises on public debt. OECD Economics Department Working Paper No. 801
Furceri D, Zdzienicka A (2011) The real effects of financial crises in the European transition economies. Econ Transit 17:1–25
Giavazzi F, Pagano M (1990) Can severe fiscal contractions be expansionary? Tales of two small European countries. In Blanchard O and Fischer S (eds) NBER Macroeconomics Annual, MIT Press, Cambridge, Massachusetts, pp 75–122
Hamilton J (1994) Time series analysis. Princeton University Press, Princeton, New Jersey
Hansen L (1982) Large sample properties of generalized method of moments estimators. Econometrica 50:1029–1054
Henry J, Hernandez de Cos P, Momigliano S (2008) The impact of government budgets on prices: evidence from macroeconometric models. J Policy Model 30(1):123–143
Hutchison M, Noy I, Wang L (2010) Fiscal and monetary policies and the cost of sudden stops. J Int Money Finance 29(6):973–987
Ilzetki E, Vegh CA (2008) Procyclical fiscal policy in developing countries: truth or fiction? National Bureau of Economic Research, NBER Working Paper No. 14191
International Monetary Fund (2009) From recession to recovery: how soon and how strong? world economic outlook, chapter 3. International Monetary Fund, Washington, DC
International Monetary Fund (2010) Will it hurt? macroeconomic effects of fiscal consolidation. Chapter 3 of the IMF’s october 2010 “world economic outlook. International Monetary Fund, Washington, DC
Kaminsky G, Reinhart C (1999) The twin crises: the causes of banking and balance of payment problems. Am Econ Rev 89(3):473–500
Laeven L, Valencia F (2008) Systemic banking crises: a new database. International Monetary Fund, IMF Working Paper No. 224
Organisation for Economic Co-Operation and Development (2009) Economic outlook, vol 86. Organisation for Economic Co-Operation and Development, Paris
Pagan A (1984) Econometric issues in the analysis of regressions with generated regressors. Int Econ Rev 25(1):221–247
Reinhart CM, Rogoff KS (2008) Banking crises: an equal opportunity menace. National Bureau of Economic Research, NBER Working Paper No. 14587
Reinhart CM, Rogoff KS (2009a) The aftermath of financial crises. Am Econ Rev 99(2):466–472
Reinhart CM, Rogoff KS (2009b) This time is different: a panoramic view of eight centuries of financial crises. Princeton University Press, Princeton, New Jersey
Reinhart CM, Rogoff KS (2011) From financial crash to debt crises. Am Econ Rev 101(5):1676–1706
Sousa RM (2010) Housing wealth, financial wealth, money demand and policy rule: evidence from the Euro area. North Am J Econ Finance 21:88–105
Sousa RM (2012) Wealth, asset portfolio, money demand and policy rule. Bulletin of Economic Research, forthcoming.
Acknowledgements
The authors wish to thank Paul Cashin, Jacopo Cimadomo, William Gavin, Padamja Khandelwal, Samah Mazarei, Apostolos Serletis, Carlo Sdralevich, George Tavlas, Lukas Vogel, the Open Economies Review guest editors, Georgios P. Kouretas and Athanasios Papadopoulos, and to participants to Banque De France and IMF-MCD seminars and to XVI Annual International Conference on Macroeconomic Analysis and International Finance. The opinions expressed herein are those of the authors and do not necessarily reflect those of the Banque de France, the IMF or its member countries.
Author information
Authors and Affiliations
Corresponding author
Additional information
The authors wish to thank Paul Cashin, Jacopo Cimadomo, William Gavin, Padamja Khandelwal, Samah Mazarei, Apostolos Serletis, Carlo Sdralevich, George Tavlas, Lukas Vogel, the Open Economies Review guest editors, Georgios P. Kouretas and Athanasios Papadopoulos, and to participants to Banque De France and IMF-MCD seminars and to XVI Annual International Conference on Macroeconomic Analysis and International Finance. The opinions expressed herein are those of the authors and do not necessarily reflect those of the Banque de France, the IMF or its member countries.
Appendix
Appendix
A. Crisis episodes
Rights and permissions
About this article
Cite this article
Agnello, L., Furceri, D. & Sousa, R.M. Discretionary Government Consumption, Private Domestic Demand, and Crisis Episodes. Open Econ Rev 24, 79–100 (2013). https://doi.org/10.1007/s11079-012-9256-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11079-012-9256-2