Appendix A: Small Open Economy Model and Business Cycle Accounting
To perform the accounting exercise of the Swedish fiscal consolidation episode we first log-linearize the equilibrium condition of the model. We then rely on the Kalman Filter algorithm for the implementation of the business cycle account exercise. The variables used for the accounting exercise are: (i) the unemployment rate; (ii) the detrended GDP; (iii) Government consumption-to-GDP ratio; (iv) consumption-to-GDP ratio; (v) investment-to-GDP ratio; (vi) government primary balance-to-GDP ratio; (vii) Consumption tax; (viii) labor income tax; (ix) capital income tax; (x) detrended total factor productivity. From these variables we infer the underlying shocks affecting the economy from 1992 to 2000 by applying the Kalman filter algorithm.
The equilibrium conditions of the model require five additional shocks in order to avoid the problem of stochastic singularity: (i) job destruction rate shock; (ii) government transfer shock; (iii) investment shock; (iv) foreign interest rate shock; and (v) preference shock. These additional shocks are grouped in other demand shocks and allow us to identify the model and to obtain the historical decomposition of the observable variables. The model’s equilibrium conditions are the following:
Labor market tightness:
Definition of unemployment rate:
Evolution of total employment:
Exogenous evolution of the job destruction rate:
Evolution of the capital stock:
where λi,t is an investment shock that follows an AR(1) process:
The Tobin’s Q for the investment demand:
The marginal benefit of household of having one additional member working:
where βt = βexp(λd,t)/exp(λd,t−1) and λd,t is an intertemporal disturbance that follows an AR(1) process:
Households’ Euler equation for capital:
Households’ Euler equation for government bonds:
Households’ Euler equation for foreign bonds:
is the foreign interest rate that follows an AR(1) process:
where at is a technology shock that evolves according to an AR(1) process:
Rental rate of capital:
The fraction of recruiters satisies the optimality condition:
The marginal beneit of having one additional worker for the firms is given by:
Government primary balance:
Evolution of government consumption:
Evolution of consumption taxes:
Evolution of capital income taxes:
Evolution of labor income taxes:
Evolution of lump-sum transfers:
Government budget constraint:
The target wage rate,
, is determined by:
Effective wage rate:
Balance of payments condition for the economy as a whole:
Definition of net exports:
The balance growth path is characterized by a annual growth rate equal to γg, so Γt = (1 + γg)t.
An equilibrium for the detrended variables is defined as follows. Define
Defining a vector of observable variables as
where OBS are the corresponding steady state values of the observable variables. H′ is matrix of zeros and ones to make the mapping between observable variables and their respective variable in X.
Using annual data from 1992 to 2000 we apply the methodology of business cycle accounting developed by Chari et al. (2007). This implies that for the observable variables we use the Kalman Filter over the state-space system defined by (52) and (53) (see Hamilton, 1994). The Kalman filter provides a smoothed inference of εt, which allows us to decompose the sources of business cycle fluctuations during the fiscal consolidation episode. In addition, we set ρDES = 0.84 and ρR* = 0.79 for the persistence of the job destruction rate and foreign interest rate, which the point estimate of the autoregressive coefficient for these variables in Sweden. We also set ρtr = 0.50 for the exogenous government transfer shock. The standard deviation of shocks are σa = 0.016, αg = 0.016, σDES = 0.25, στc = 0.01, στk = 0.012, στn = 0.015, σtr = 0.015, ρR* = 0.014, which are consistent with the standard error of the residuals of fitting an autoregressive process of order one for each of these variable. We also set ρi = 0.84, ρd = 0.48, σi = 0.03, and σd = 0.03 based on the estimates from Adolfson et al. (2007).
Appendix B: Effective Tax Rates
The data used for calculating the tax rates comes from the European Commission macroeconomic database AMECO (available at http://ec.europa.eu/economy_finance/db_indicators/ameco/) and OECD.Stat Extracts (available at http://stats.oecd.org/). The data from OECD provides the tax revenues, while the data from AMECO determines the tax base. The ratio of both components defines the effective tax rate. Next, we describe the series used from each database and then show the formulas used to calculate the tax rates based on the work of Mendoza et al. (1994).
Data from AMECO is the following:
C: Nominal Private Consumption.
G: Nominal Government Consumption.
GW: Compensation of Employees, General Government.
OSPUE: Gross operating surplus and mixed income, Households and NPISH.
PEI: Net property income, Households and NPISH.
W: Gross wages and salaries, Households.
OS: Net operating surplus: Total Economy.
Data from the OECD database with their respective codes are:
5110: General taxes.
5121: Excise taxes.
1100: Income, profit and capital gains taxes of individuals.
2000: Social security contributions.
3000: Payroll taxes.
2200: Social security contributions of employers.
1200: Income, profit, and capital gains taxes of corporations.
4100: Recurrent taxes on immovable property.
4400: Taxes on financial and capital transactions.
Using these series we follow the methodology of Mendoza et al. (1994) to calculate the effective tax rates. We focus on the tax rates on consumption, labor, and capital. As an auxiliary variable, we calculate the personal income tax. A fraction of the income tax is allocated to the labor tax while the rest is assigned to the capital tax. Based on the data the methodology of Mendoza et al. (1994) we use the following formulas for the effective tax rates:
Personal income tax:
Labor income tax:
Capital income tax:
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Mr. Lama is a Senior Economist in the IMF Research Department and Mr. Medina is a professor of economics at Universidad Adolfo Ibañez. We thank Petya Koeva Brooks, James Daniel, Helge Berger, Gustavo Adler, Lars Svensson, Romain Duval, and participants at the Jobs and Growth seminar at the IMF and the Macroeconomic Modeling Workshop at Banca d’Italia. All errors are our own.
Using an action-based database, Guajardo et al. (2011) find that fiscal consolidations have negative effects on GDP and employment in the short-run.
The banking crisis that occurred during 1992-93 also contributed to the widening of the fiscal deficits. Floden (2013) estimates that the fiscal costs associated with the banking crisis were around 4 percent of GDP. In this paper we take as given the initial conditions in 1992 and do not model the banking crisis. We focus our analysis on the recovery period when the fiscal consolidation and structural reforms take place.
Although the unemployment rate declined to 5.6 percent by the year 2000, it was still higher than the pre-crisis level of 1.7 percent. Since the unemployment rate remained close to 6 percent during the following decade, it seems plausible to assume that an unemployment rate of 5–6 percent became the new long term equilibrium for the Swedish economy.
In order to implement the business cycle accounting methodology we add additional shocks, so the model predictions fully reproduce the macroeconomic data during the sample period 1992-2000. These additional shocks, labeled other demand shocks, play a minor role in explaining business cycle fluctuations during the sample period.
It is important to note that in 1981 Sweden experienced a real exchange rate depreciation comparable to the one occurred in 1992 (23 percent) with a limited impact on output growth and the trade balance. The limited effect could be attributed to the fact that the depreciation was temporary and occurred in a period characterized by high wage inflation and stagnant productivity growth, factors that prevented a sustained reduction in unit labor costs.
See Devries et al. (2011) for a detailed description of the consolidation measures during this episode.
For a discussion on the impact of the fiscal framework on the improvements in public finances see Floden (2013).
While the Mackinsey Global Institute (2006) emphasizes the role of deregulation in driving productivity gains, Pilat et al. (2002) provide evidence that the expansion of the information and communications technology sector also was responsible for broader productivity gains experienced during the 1990s in Sweden. Both views can be reconciled considering that deregulation and trade liberalization provided the incentives for the adoption of new technologies that lead to sustained productivity gains.
Barkbu et al. (2012) estimate that structural reforms increased labor productivity by 15 percentage points, about half of the 31 percent increase in productivity that occurred between 1990 and 2000. If labor productivity had followed the pre-crisis trend during the 1990s, it would have increased by just 11 percent (far lower than the observed increase of 31 percent). The gap between the observed productivity gains and the pre-crisis trend, 20 percent, could be interpreted as an upper bound estimate of the effects of structural reforms.
Each of the labor organizations (LP, TCO, SACO) groups represented several labor unions.
Blanchard et al. (2013) argue that the best approach to contain wage inflation is through a national wage agreement among social partners. Alternatively, the adoption of a flexible wage-setting process can contribute to set wages consistent with firm-level productivity. In Sweden both approaches were implemented during the 1990s in order to improve competitiveness.
Notice that β = (1 + γg)/(1 + r).
The baseline calibration ψ = 1 generates a fiscal spending multiplier of 0.5. This fiscal multiplier is consistent with the estimates for a small open economy like Sweden. See IMF Fiscal Monitor (2012).
To avoid the problem of stochastic singularity the number of shocks should be greater or equal to the number of observable variables. The implementation of the business cycle accounting decomposition is explained in appendix A.
The business cycle accounting methodology is akin to a historical decomposition of time series models, where the model predictions fit perfectly the data when all shocks are taken into account.
In the next section we relax the assumption of real wage rigidity and evaluate the implications of productivity gains on the trade balance and the unemployment rate.
Calmfors (2012a) mentions that high output growth derived from structural reforms was necessary for the successful implementation of the fiscal consolidation in Sweden.
In each of the simulations presented in this section we take as given the shocks estimated in the baseline business cycle accounting exercise and add one additional feature to each scenario.
We also conducted a robustness check by simulating the model with ψ = 2.4 which is consistent with a fiscal multiplier of 1. In that experiment the fiscal consolidation has a larger negative impact on GDP and the unemployment rate, but a limited effect on the fiscal balance.
The inertia parameter χw = 0.85 is consistent with an elasticity of real wages to total factor productivity of 0.3. This elasticity was estimated for the period 1960-1990, before the fiscal consolidation and the implementation of wage restraint policies. We use the following specification wt = ρwt−1 + ϕtfpt + εt, where wt and tfpt denote the logarithm of real wages and TFP and ϕ is the elasticity of real wages to TFP. The data was obtained from the AMECO database published by the European Commission. For the sample 1960-1990 we obtain the following coefficients wt = 0.84wt−1 + 0.34tfpt with R2 = 0.99.
This is akin to the mechanism of Giavazzi and Pagano (1990) of an “expansionary fiscal consolidation”. These authors analyze episodes in Ireland and Denmark, countries that experienced a reduction in interest rates and a consumption boom in the aftermath of a fiscal consolidation.
Flodén (2012) argued that the Swedish economic recovery during the 1990s was driven, in part, by a robust external demand. In this section we evaluate the importance of external demand in influencing the path of fiscal consolidation. We consider a counterfactual scenario where the terms of trade fall by the same magnitude as the one observed during the Great Recession (2009-2012) and analyze the implications for the fiscal consolidation.
In this scenario fluctuations in the terms of trade afect the value of domestic production in the rest of the world ptyt.