Download Debt Consolidation and Financial Stability, with I. Angeloni, R

Debt Consolidation and Financial Stability
Ignazio Angeloni
European Central Bank and BRUEGEL
Ester Faia
Goethe University Frankfurt, Kiel IfW and CEPREMAP
Roland Winkler
Goethe University Frankfurt
November 2010.
Abstract
We compare three alternative public debt consolidation policies (respectively based on expenditure cuts, labour tax or consumption tax increases) in their effects on key macro variables
and on bank stability. Labor tax-based policies attain a rapid debt adjustment and low intertemporal debt costs, but at the expense of higher oscillations in bank leverage and risk. Expenditure
based and consumption tax-based strategies perform rather similary from one another, though
the second entails a somewhat higher output cost in the short to medium term.
Keywords: debt consolidation, financial stability, bank runs.
1
1
Introduction
The focus of this paper is the impact of public debt consolidation on financial stability. The analysis
of the effects of fiscal policy, a constantly active area of research, has received new attention recently
in the context of the financial crisis. Two different perspectives have been taken. On one side, a
lively debate has developed on the size of fiscal multipliers. Some economists, including some
close to the US administration, have argued that fiscal multipliers are large, hence suggesting an
active use of fiscal policy to stimulate aggregate demand. Others have provided evidence suggesting
much smaller or even negligible effects of fiscal policy1 . On the other side, concern in international
policy circles have grown over the effects the crisis will have over the medium-long term on public
debt accumulation in advanced economies. Discussions have focused mainly on the conditions for
maintaining long term fiscal solvency, and on the timing, modalities and effects of debt consolidation
programs2 . The very extensive theoretical and empirical literature on the effects of fiscal policy on
the macroeconomy provides a natural background for all these discussions, but unfortunately the
conclusions of this literature are very ambiguous3 .
In this paper we look at debt consolidation from a different angle, that of its effects on the
stability of the banking sector. Debt consolidation and financial stability are linked in a variety
of mutually interacting ways. It is evident that risks to financial stability, to the extent that they
require sizeable public financial resources to guarantee or recapitalize ailing banks, can have a
powerful fiscal impact: many examples, most recently and dramatically that of Ireland, illustrate
the point. But financial stability (or lack thereof) impacts on fiscal outcomes also indirectly,
through its effect on credit flows, aggregate demand, and eventually public budgets. Conversely,
debt consolidation strategies limit the resources available to support the banking sector, and, in
a longer run, affect the environment in which banks operate through their effects on growth and
inflation. Given the complexity of these links, we find it useful to approach the issue using a macro
model enriched by explicit banking and fiscal sectors. Our model, described in some detail in the
1
See Romer and Bernstein [14]; Cogan et al. [4]; Cwik and Wieland [5], Uhlig [17]; and Christiano, Eichenbaum
and Rebelo [3].
2
See in particular a stream of papers produced by the IMF staff, including Freedman et al [9] and IMF [11].
3
In his comprehensive 2004 VAR study of the effects of expenditure and tax shocks on inflation and output in the
main OECD countries, Perotti [13] notes at the outset that: ”While most economists would agree that a 10 percent
increase in the money supply will lead to some increase in prices after a while, perfectly reasonable economists can
and do disagree even on the basic qualitative effects of fiscal policy”.
2
next section, is the one presented in Angeloni and Faia [1], which introduces a banking sector a’ la
Diamond and Rajan ([7], [8]) into an otherwise standard DSGE model with nominal rigidities. We
extend the model with calibrated rules for public expenditures and receipts, divided into labour
and consumption taxes, and equations for interest payments and debt dynamics. The government
uses tax receipts and debt to finance public expenditures and to recapitalize risky banks.
With this model we conduct a thought experiment in two steps. First, we subject the model
to a set of shocks that proxy the impact of the financial crisis on the euro area economy in 20072009, including the immediate policy responses in terms of monetary and fiscal accommodation
as well as bank support. Second, we consider three alternative scenarios of fiscal consolidation:
the first based on expenditures reduction, the second on higher labour taxes, the third on higher
consumption taxes. In all three cases, we assume the objective is to return to the initial level of
the debt to output ratio within 10 years. We then compare the effects of these alternatives on the
main macro variables and two key fiscal variables and on the riskiness of the banking system. To
compare alternative banking outcomes, we assume that the steady state level of risk is optimal, so
that lower variability around, or faster convergence to, the steady state are desirable.
Our main conclusion is that the adjustment strategy based on labour taxes is the one that
destabilizes the financial sector the most. The labour tax increase opens a wedge between gross
and net wages and alters, at the margin, the return from using labour vs capital in production. The
marginal cost of a unit of output increases, and in presence of price stickiness so does inflation and,
given our assumptions about monetary policy, the nominal rate of interest. Bank leverage and risk
decline before gradually returning to the steady state. Given our parameter values the deviation
from baseline values is quite large. The differences between the adjustment based on expenditure
cuts or consumption taxes is more nuanced. The consumption tax is contractionary on output, but
its effect on inflation is less pronounced. Inflation and interest rates oscillate moderately, and so
does bank risk. Expenditure cuts have a moderate effect on output and inflation. All in all, bank
risk remains closer to baseline in the case of expenditure cuts, though the difference here depends
crucially on uncertain parameter values.
After an overview of the model in section 2, section 3 describes our alternative debt consolidation policies and illustrates our results. Section 4 concludes.
3
2
The Baseline Model
There are four type of agents in this economy: households, financial intermediaries, final good
producers and capital producers. Households make consumption and working decisions and hold
demand deposit and bank capital. Banks have special skills in redeploying projects in case of
early liquidation. Uncertainty in projects outcomes injects risk in bank balance sheets. Banks
are financed with deposits and capital; bank managers optimize the bank capital structure by
maximizing the combined return of depositors and capitalists. Banks are exposed to runs, with
a probability that increases with their deposit ratio or leverage. The desired capital ratio is determined by trading-off balance sheet risk with the ability to obtain higher returns for outside
investors in ”good states” (no run), which increase with the share of deposits in the bank’s liability side. Finally, firms are monopolistic competitive producers who face quadratic adjustment
costs of changing prices. The government finance government expenditure and bank recapitalization
policy through a mix of debt, consumption and labour taxes.
2.1
Households
There is a continuum of risk averse identical households who consume, save and work. Households
save by lending funds to financial intermediaries, in the form of deposits and bank capital4 . Since
household are risk averse in terms of their consumption and working decisions, they behave as
standard consumption smoother, solving a dynamic optimization problem. We further assume that
their utility features a certain degree of habit persistence in consumption; such an assumption
serves the purpose of smoothing fluctuations in consumption in a way that is empirically more
realistic. Households wealth is made up of their wage income and the returns from investment in
deposits, net of consumption and labour taxes. Households maximization results in the following
4
To allow aggregation within a representative agent framework we follow Gertler and Karadi [10] and assume that
in every period a fraction γ of household members are bank capitalists and a fraction (1 − γ) are workers/depositors.
Hence households also own financial intermediaries. Bank capitalists remain engaged in their business activity next
period with a probability θ, which is independent of history. This finite survival scheme is needed to avoid that
bankers accumulate enough wealth to remove the funding constraint. A fraction (1− θ) of bank capitalists exit in
every period, and a corresponding fraction of workers become bank capitalists every period, so that the share of bank
capitalists, γ, remains constant over time. Workers earn wages and return them to the household; similarly bank
capitalists return their earnings to the households.
4
Euler condition:
c
)
ct = c1 ct−1 + c2 Et ct+1 − c3 (rt − Et πt+1 ) − c4 (τtc − Et τt+1
(1)
where ct is the percentage deviation of consumption from the steady state, rt is the percentage
deviation of the rate paid on deposits, πt+1 is the percentage deviation of inflation and τtc is the
percentage deviation in consumption taxes. The parameters are c1 = γ/(1 + γ), c2 = 1/(1 + γ),
c3 = (1 − γ)/((1 + γ)σ), and c4 = c3 τ c /(1 + τ c ). The labour supply decision reads as follows:
wt = w1 nt + w2 ct − w3 ct−1 + w4 τtc + w5 τtn
(2)
where wt is the percentage deviation of wages from the steady state, nt is the percentage deviation
in employment, and τtn is the percentage deviation in labour taxes. The rest is as follows: w1 =
N/(1 − N ), w2 = σ/(1 − γ), w3 = γw2 , w4 = τ c /(1 + τ c ), and w5 = τ n /(1 − τ n ).
2.2
Banks
There is in the economy a large number (Lt ) of uncorrelated investment projects. The project lasts
two periods and requires an initial investment. Each project’s size is normalized to unity (think
of one machine) and its price is Qt . The projects require funds, which are provided by the bank.
Banks have no internal funds but receive finance from two classes of agents: holders of demand
deposits and bank capitalists. Total bank loans (equal to the number of projects multiplied by
their unit price) are equal to the sum of deposits (Dt ) and bank capital, (BKt ). The aggregate
bank balance sheet reads as Qt Lt = Dt + BKt . In the aggregate the demand for loans equates the
aggregate capital invested in the economy: Qt Lt = Qt Kt .
The capital structure (deposit share, equal to one minus the capital share) is determined by
bank manager on behalf of the external financiers (depositors and bank capitalists). The manager’s
task is to find the capital structure that maximizes the combined expected return of depositors and
capitalists, in exchange for a fee. Demand deposits have to be served first and sequentially5 ,
hence they are subject to runs, on the other side bank capitalists are rewarded pro-quota after all
depositors are served.
5
This set of assets include asset backed securities and alike.
5
As in Angeloni and Faia [1], we assume that the return of each project for the bank is equal to
an expected value, RA,t , plus a random shock, for simplicity assumed to have a uniform density with
dispersion ht . We assume that the dispersion of project is return is time-varying: more specifically
we assume that it follows an AR(1) process. Therefore, the outcome of project j is RA,t + xj,t ,
where xj,t spans across the interval [−ht ; ht ] with probability
1
2ht .
Each project is financed by one
bank, which act as a relationship lender. By running the project the bank acquires special skills
by means of which it can extract some rent. Indeed if uninformed investors would finance directly
investment projects, they would be able to redeploy only a fraction 0 < λt < 1 of the project
returns. Such fraction, namely the liquidation value, is also subject to aggregate shocks and follows
an AR(1) process.
In equilibrium three situations might arise: 1. the realized return to the project is so low that
a run occurs with certainty: 2. the realized return to the project is high enough to prevent a run
only if the bank redeploys the funds invested in the project: 3. the realized return to the project
is high enough to prevent runs even in absence of bank intervention. By considering those three
events, the bank managers chooses the optimal debt to loan ration to maximize the expected return
to outside investors:
dt = −rt + d1 rA,t + d2 ht + d3 λt
(3)
where dt is the percentage deviation from the steady state in demand deposits and rA,t is the
percentage deviation in the return to investment. The parameters are determined as follows:
d1 = RA /(RA + h), d2 = h/(RA + h), d3 = λ/(2 − λ). The optimal deposit ratio depends positively
on h, λ and RA , and negatively on R. An increase of R reduces deposits because it increases the
probability of run: this effect rationalize the so called risk taking channel (see Borio and Zhu [2],
Lorenzoni [12]). Moreover, an increase in RA raises d as it raises the marginal return in the no-run
case. Finally, an increase in h, which captures the riskiness of investment projects, raises d: higher
dispersion of returns induces banks to take up more risk.
The counterpart of the deposit ratio is represented by the optimal demand for capital, which
in log-linear form reads as:
bkt = −d/(1 − d)dt + qt + kt−1 + ubk
t
(4)
where bkt is the percentage deviation from the steady state in bank capital, qt is the percentage
6
deviation in the price of capital and kt−1 is the percentage deviation in capital. The variable ubk
t
represents a random shock to bank capital. As can be seen from equation 4 an increase in the price
of capital increases the value of bank capital: this effect captures the balance sheet channel in our
model. In each period bank capitalists earn an expected return, which in log-linear form reads as
follows:
rtkt = r1 rA,t + r2 ht − r3 (rt + dt )
(5)
where r1 = 2RA /(RA + h − Rd), r2 = (h − RA + Rd)/(RA + h − Rd), r3 = 2Rd/(RA + h − Rd).
In every period with a certain probability, (1 − θ) bank capitalists exit the market. The capitalists who continue operating reinvest their returns in next period bank capital, whose dynamics
is described by the following log-linear accumulation equation:
bkt = θbkt−1 + (1 − θ − bk1 )(rtkt + qt + kt ) + bk1 bkgt
(6)
where bkgt represents the bank recapitalization policy set by the government and bk1 = BKG/BK.
Since demand depositors can enact an early withdrawal, the likelihood of a run will give us a measure
of bank riskiness:
brt = br1 ht − br2 rA,t + br3 (rt + dt )
where br1 = (RA − Rd)/(h − RA + Rd), br2 = RA /(h − RA + Rd), br3 = Rd/(h − RA + Rd).
2.3
Producers
Producers are modeled, as it is standard in the literature, as monopolistic competitors who produce
different varieties and face quadratic adjustment costs of changing prices. Their production function
is a Cobb-Douglas, which in log-linear terms reads as:
yt = at + α(kt−1 + ut ) + (1 − α)nt
(7)
where yt is the percentage deviations of output from the steady state, at represents the productivity
shock, ut captures variable capital utilization (see next section), and α is the share of capital in
the production function. Firms’ dynamic optimization decision leads to the following expectation
augmented Phillips curve (in log-linear terms):
π = βEt πt+1 + κmct
7
(8)
with κ = (ε − 1)Y /ϑ, and to the following equations for labour and capital demand:
wt = mct + at + α(ut + kt−1 ) − αnt
(9)
zt = mct + at + (α − 1)(ut + kt−1 ) + (1 − α)nt
(10)
where is the percentage deviation of the marginal cost from the steady state and zt is the percentage
deviation of the rental rate of capital.
2.4
Capital Producers
A competitive sector of capital producers combines investment (expressed in the same composite
as the final good, hence with price Pt ) and existing capital stock to produce new capital goods,
according to the following law of motion (in log-linear terms):
kt = (1 − δ)kt−1 + δit
(11)
where it is the percentage deviation of investment from the steady state. We follow Smets and
Wouters (2003) in assuming variable utilization of capital and adjustment costs on investment.
Under this assumption capital produces’ optimization leads to the following optimal investment
schedule (in log-linear terms):
it = i1 it−1 + i2 Et it+1 + i3 qt
(12)
where i1 = RA /(1 + RA ), i2 = 1/(1 + RA ), and i3 = φI i1 , and to the following equation for the
price of capital:
q = q1 Et qt+1 + q2 Et zt+1 − Et (rA,t+1 − πt+1 )
(13)
where q1 = (1 − δ)/(1 − δ + z) and q2 = z/(1 − δ + z) and where zt+1 is set according to the variable
utilization equation ut = ψu zt .
2.5
Goods Market Clearing, Monetary and Fiscal Policy
Production in this economy is allocated to consumption, investment and government, gt :
y t = y1 c t + y 2 i t + y 3 g t + y 4 z t
(14)
where y1 = C/Y , y2 = I/Y , y3 = G/Y , y4 = ψu zK/Y . As in the aftermath of the crisis most
central banks had driven their interest rate close to the zero lower bound, we assume that the
8
nominal interest rate is set to zero for a certain number of periods, T , while it follows a standard
Taylor thereafter:
rt =
0
φ π π t + φ y yt
for t ≤ T
for t > T
(15)
The fiscal sector is characterized by the following policy rules. The first determines the share
of financing between taxes and debt, bt :
τtn + τtc = ψT (bt + τtn + τtc )
(16)
The second determines the share of financing between consumption and labour taxes:
τtn = ψτ (τtc + τtn )
(17)
The third is the evolution of government spending, which follows an AR(1) process, but also
responds to government debt as in Corsetti et al. (2009):
gt = ρg gt−1 − γB bt + εgt
(18)
The government budget constraint is given by:
bt = b1 bt−1 + b2 (rt−1 − πt ) + b3 gt + b4 bkgt − b5 (ct + τtc ) − b6 (τtn + wt + nt ) + b7 τt
(19)
where b1 = 1/β, b2 = b1 B/Y , b3 = y3 , b4 = BKG/Y , b5 = τ c y1 , b6 = τ n wN/Y , and b7 = τ /Y .
3
Debt Consolidation Strategies
Parameters values for our simulations are detailed in the table below. Most have been chosen following previous literature expect the values for the banking parameters which have been calibrated
based on micro data.
– Insert Table 1 here –
We simulate the model assuming an initial crisis scenario, which is set up to mimic closely the
actual situation experienced during the 2007-2008 crisis. Starting from this scenario we evaluate
9
alternative strategies to return the debt to output ratio to its pre-crises level within 10 years6 . Our
baseline simulation incorporates two elements: a set of shocks to the financial system, reproducing
the initial factors that generated the crisis, and a number of policy interventions, representing
the supporting measures (monetary, fiscal and financial) adopted as an immediate response to the
financial turmoil. Our aim here is to model, in a stylized way and according with the model’s
specification, the main forces that drive the behavior of the macroeconomic variables after the
crisis but before the fiscal consolidation is initiated.
The set of shocks generating ”the crisis” includes three components: a persistent increase in
the riskiness of investment for banks; a persistent decrease in the early liquidation value of bank
investment; a destruction of bank capital.7 The immediate post-crisis stimulus policies include
monetary expansion, fiscal expansion and bank support measures. First, we assume that the short
term interest rate is brought down to zero for 12 quarters. The second policy assumption is that
fiscal policy adopts a proactive output stabilization stance, with public expenditures responding
to output and not to past debt, and taxes constituting only a small shares of expenditures financing.8 Finally, the third policy is a bank capital support policy. We assume that the government
intervenes to refinance the bank capital when their capital/asset ratio is below the steady state.9
The recapitalization increases the budget deficit and is financed by taxes or debt, according to the
above rules.
Subject to these shocks and these policy rules, the model produces profiles for output, inflation,
bank risk, the budget deficit and the debt to output ratio depicted in figure 1.
– Insert Figure 1 here
Note, first, the strong contractionary effect on output which drops around 5 percent before
recuperating. Inflation drops by about 5 percent relative to steady state, then quickly rises back.
6
The IMF staff has designed long term scenarios of fiscal consolidation for the advanced G20 countries (see [11]).
The scenarios are based on a target of returning to a debt to output ratio below 60 percent by 2030. They assume
that the exit process starts in 2011, when the debt ratio for the aggregate they consider, is projected to be above
80 percent. In their scenario, the debt level would return to this level around 2021, i.e 10 years after the fiscal exit
starts. Hence, our consolidation strategy is broadly consistent with these IMF normative scnarios.
7
bk
bk
bk
Formally: ht = 0.85ht−1 + εht , εh0 = 0.2222; λt = 0.85λt−1 + ελt , ελ0 = −0.2222; ubk
t = 0.95ut + εt , ε0 = 0.2.
8
Formally, the tax and spending rules are set in a ”passive” mode (γB = 0, ψT = 0.1), the tax split is calibrated to
reproduce the euro area average (ψτ = 2/3) and government spending increases by 5 percent of GDP (εg0 = 0.05Y ).
9
Formally: bkgt = 0.7dt .
10
The public debt ratio rises quickly in the first years, then rises more slowly; in the long run, it
returns very slowly back to baseline given the very weak debt adjusting stance incorporated in the
policy functions. The budget deficit, as a ratio to output, rises by more than 4 percent. In the
financial sector, bank riskiness rise, mainly reflecting the impact effect of bank capital destruction.
The same figure 1 shows the response profiles of the main macro variables under the following
hypotheses concerning debt consolidation: consolidation based on spending cuts (left column), on
increases in labour taxes (central column), or on increases in consumption taxes (right column).
We posit that the debt consolidation takes place 12 quarters after the initial shock. This lag is
based on the observation that, in most countries, a significant adjustment of public budget is not
expected to take place before three years after the peak of the financial turmoil (2011 vs. 2008).
All three strategies are calibrated so as to bring public debt back to baseline within 10 years. The
three strategies are plotted against the no-consolidation case.
To start with, consider a debt consolidation achieved through spending cuts. The decline in
public spending leads to a contraction of output, despite some crowding in of private consumption.
The fall of output and employment increases marginal product and, in equilibrium, real marginal
costs. Hence inflation rises on impact10 . Responding to the higher inflation profile, monetary policy
(which also exits the crisis mode at t = 13) increases real rates. The monetary restriction reduces
bank risk, in presence of a risk-taking channel of monetary policy. The short-medium term outcome
is (moderately) less output, a bit more inflation and higher nominal rates, a safer financial system
and, of course, less public spending and lower budget deficit and debt accumulation. In the long
term, the policy activism is rewarded by higher output beyond t = 30.
If we compare the impulse responses of a labour tax-based and a spending-based strategy, we
find that the tax-based strategy reduces output more strongly in the short run. Labour taxes produce a leftward shift in the labour supply curve that raises marginal costs sharply, hence inflation.
Monetary policy reacts with a significant increase in interest rates leading to a sharp drop in bank
risk which now undershoots its desired baseline value. Relative to the spending strategy, the labour
tax-based one obtains a more front-loaded debt reduction at the cost of a larger output loss. There
10
The rise in inflation is mild, however, and highly dependent on preferences parameters. This uncertain effect
matches the empirical evidence of Perotti [13], which is particularly ambiguous concerning the effect of public expenditure changes on inflation.
11
is also a significant loss in terms of inflation stabilization. If we compare a the labour tax-based to
the consumption tax-based strategy, we see that the consumption tax allows to overcome some of
the drawbacks of the labour tax. The overshooting of inflation is significantly reduced. The sharp
monetary contraction is avoided, and thus also the sharp deviation of bank risk from the desired
baseline value.
Complementing the visual inspection, we calculate root sums of discounted squared deviations
of output, inflation, bank risk and debt cost from the no-consolidation case, separately for the first
20 quarters (representing the performance of the three alternative policies in the short to medium
run) and for the whole infinite time horizon (long run). These calculations are reported in table 2.
– Insert Table 2 here –
Note, first, that there are significant improvements in the output and debt cost columns
in the section ”all quarters”. This means that all consolidation strategies, regardless of their
characteristics, improve markedly over the no-consolidation case in terms of long term output and
costs of debt performance. In terms of bank riskiness and inflation, the advantage is more mixed
but we see that the expenditure based and the consumption tax based strategies are beneficial or
at last neutral in terms of all our criteria relative to the indefinite continuation of the post-crisis
policy course.
By comparing the performance of the different strategies in table 2, we see that the spendingbased strategy does not produce significant changes relative to no-consolidation in the short to
medium run. In the long run, however, it improves the performance in terms of all criteria under
consideration. By contrast, a labour tax-based strategy generates a significant loss in terms of
bank risk and inflation at short horizons. The labour tax-based strategy actually leads to a loss
of 12 and 32 percent for bank risk and inflation relative to the no-consolidation scenario. In the
longer run such losses are mitigated, but there is still an under-performance in terms of inflation
and bank risk. The consumption tax-based strategy outperforms the labour-tax based one in terms
of bank risk and inflation but at the cost of a significant output loss in the short run. Notice that
the tax-based strategies do better in terms of a reduction in the costs of debt, because they entail
a more front-loaded consolidation of public debt.
12
4
Conclusions
To our knowledge, there are no other papers so far that have attempted an evaluation of the effects
of fiscal consolidation on bank and financial stability along lines similar to ours. Our attempt is
in many respects a very preliminary one, and as such should be refined and extended in a number
of ways. First, the alternative policy options we considered are rather sketchy and chosen mainly
for expository purposes: more realistic policy strategies could easily be constructed. Second, as
we have noted and as confirmed by the empirical evidence, certain key linkages (like for example
the effect of public expenditures on inflation) are highly depended on arbitrary parameter assumptions, yet critical in shaping the effect of fiscal changes on the banking sector. The way forward
here would probably be to characterize more carefully the mapping between parameter values and
macroeconomic outcomes. Finally, and obviously, our results are model dependent; their robustness
to alternative modelling choices should be ascertained before drawing any firm policy conclusions.
References
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Banks”. Mimeo.
[2] Borio, Claudio and Haibin Zhu, 2008. “Capital regulation, risk-taking and monetary policy: a
missing link in the transmission mechanism?”. BIS Working Papers No. 268.
[3] Christiano, Lawrence, Eichenbaum, Martin and Sergio Rebelo, 2009. “When is the government
spending multiplier large?”. NBER Working Paper 15394.
[4] Cogan, John F., Cwik, Tobias, Taylor, John B. and Volker Wieland, 2010. “New Keynesian
versus Old Keynesian Government Spending Multipliers.” Journal of Economic Dynamics and
Control 34, 281-295.
[5] Cwik, Tobias and Volker Wieland , 2009. “Keynesian government spending multipliers and
spillovers in the euro area.” Mimeo.
[6] Corsetti, Giancarlo, Andre Meier, and Gernot Müller, 2009. “Fiscal Stimulus with Spending
Reversals”. IMF Working Paper 09/106.
13
[7] Diamond, Douglas W. and Raghuram G. Rajan, 2000. “A Theory of Bank Capital”. Journal
of Finance 55, 2431–2465.
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Financial Fragility: A Theory of Banking”. Journal of Political Economy 109, 287–327.
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(2009). “Fiscal Stimulus to the Rescue: Short Run Benefits and Potential Long Run Costs of
Fiscal deficits”, IMF Working paper 09/255
[10] Gertler, Mark and Peter Karadi, 2009. “A Model of Unconventional Monetary Policy”. Mimeo,
NYU.
[11] International Monetary Fund, 2010. “Strategies for Fiscal Consolidation in the Post-Crisis
World”. Mimeo.
[12] Lorenzoni, Guido, 2008. “Inefficient Credit Booms”. Review of Economic Studies 75 809–833.
[13] Perotti, Roberto, 2004. “Estimating the Effects of Fiscal Policyin OECD Countries”, IGIER
Working paper 276.
[14] Romer, Christina and Jared Bernstein, 2009. “The job impact of the American recovery and
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[16] Trabandt, Mathias and Harald Uhlig, 2009. “How Far Are We from the Slippery Slope? The
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14
Table 1: Parameter values
Parameter
Description
Value
σ
γ
N
β
α
δ
ε/(ε − 1)
φI
ψu
ϑ
h
λ
θ
φp
φy
G/Y
τc
τn
Elasticity of consumption
Degree of habit formation
Steady state value of labour hours
Discount factor
Share of capital in production
Capital depreciation rate
Price mark-up
Capital adjustment cost
Capital utilization cost
Price stickiness parameter
Project return dispersion in steady state
Steady state liquidation value
Bank capitalist survival probability
Weight on inflation stabilisation
Weight on output stabilisation
Steady state share of government spending
Steady state consumption tax
Steady state labour tax
1.4
0.5
0.3
0.99
1/3
0.025
0.2
1/6
1/0.2
30
0.45
0.45
0.97
1.5
0.5/4
0.23
0.17
0.41
15
Table 2: Comparison of alternative debt consolidation strategies
Horizon
Criterion
Consolidation:
Spending
Labour tax
Consumption tax
20 quarters
Output
−7
−8
−12
Bank risk
All quarters
Inflation
Debt costs
Output
+3
+18
+15
+39
+50
+44
Gain/loss in percent
+4
−5
−12
−32
−2
0
Bank risk
Inflation
Gain/loss in percent
+7
+1
−9
−22
0
+10
Debt costs
+79
+85
+84
Notes: Gains (+) or losses (-), in percent, of the corresponding consolidation strategy in terms of the given criterion, relative to the no consolidation
scenario.
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OUTPUT
SPENDING
LABOUR TAX
2
2
0
0
0
−2
−2
−2
−4
−4
−4
−6
0
20
40
5
INFLATION
CONSUMPTION TAX
2
−6
0
20
40
10
0
20
40
0
20
40
0
20
40
0
20
40
0
20
40
5
5
0
−6
0
0
−5
BANK RISKINESS
−10
0
20
40
0
20
40
−10
4
3
2
2
2
1
0
1
0
−2
0
0
20
40
6
BUDGET DEFICIT
−10
3
−1
−4
0
20
40
5
4
−1
5
0
2
0
−5
0
−2
DEBT OUTPUT RATIO
−5
−5
0
20
40
−10
0
20
40
−5
40
40
40
30
30
30
20
20
20
10
10
10
0
0
20
40
0
0
20
40
0
Figure 1: Debt consolidation strategies. Solid lines with x-marks are baseline crisis simulations without
debt consolidation. Solid lines with circles are impulse responses under debt consolidation based on spending
cuts (left column), on labour tax increases (central column), on consumption tax increases (right column).
17