Realizar un cuadro comparativo entre los conceptos de enseñanza y
2.2 La organización social del aprendizaje.
2.2.2 El papel de la interacción profesor-alumno en el aprendizaje.
As discussed by Leeper (1991), Benhabib et al. (2001) and Woodford (2003), among oth- ers, there are potentially important interactions between the stance of monetary and fiscal policy. These papers have shown that when fiscal policy endogenously reacts (strongly enough) to debt, monetary policy must often satisfy the Taylor principle to ensure sta- ble debt dynamics.15 The literature has referred to this case as one of ‘passive’ fiscal policy and ‘active’ monetary policy. Alternatively, this fiscal stance is sometimes called ‘(locally) Ricardian’ following Woodford (2003). In the baseline model ψπ is estimated to be greater than one (with ψy close to zero), thus satisfying the Taylor principle. The coefficients determining the feedback to the fiscal policy instruments were all greater than required to satisfy the condition for passive fiscal policy.16
However, if fiscal policy were entirely unresponsive — ‘active’ or ‘non-Ricardian’ — monetary policy would need to be passive and violate the Taylor principle to ensure de- terminate debt dynamics. Consider a simple example of a debt-financed tax cut adopted from Davig and Leeper (2006). A debt-financed tax cut does not raise the present value of future taxes (given exogenous processes for the fiscal instruments). Households therefore perceive this as an increase in their lifetime wealth which, at initial prices and interest rates, raises the demand for goods. Monetary policy must not react too strongly (formally, it must violate the Taylor principle) because, as explained by Davig and Leeper (2006), three channels then act to satisfy the government’s intertemporal budget constraint (after imposing the transversality condition). First, passive monetary policy allows the money stock to to expand and clear the market, creating seignorage revenue. Second, surprise inflation revalues outstanding nominal debt. Third, lower real interest rates allow a higher level of debt to be serviced for a given stream of primary
15See Benhabib et al. (2001) for conditions under which, given a Ricardian (or ‘passive’) fiscal policy, active monetary policy still does not ensure determinate equilibrium dynamics.
16
Chapter 3 3.5 Model comparisons and robustness
Table 3.5: Model comparisons
Parameter Baseline No D.A. Exogenous policy Flexible prices
σ 2.2 2.2 1.1 2.7 (1.5,2.9) (1.5,2.9) (0.7,1.4) (2.0,3.4) κ (1.3,2.4)1.9 (1.5,2.7)2.1 (0.9,1.9)1.4 (2.3,3.8)3.1 µ (0.3,0.5)0.4 (0.3,0.5)0.4 (0.5,0.7)0.6 (0.04,0.2)0.14 φ00k 5.2 5.2 5.1 5.1 (4.7,5.6) (4.8,5.6) (4.7,5.5) (4.7,5.5) δ2 0.008 0.01 0.01 0.006 (0.002,0.01) (0.003,0.02) (0.004,0.02) (0.002,0.01) (5.3,6.1)5.7 (5.1,6.0)5.6 (5.3,6.1)5.7 (5.3,6.1)5.7 γyk (1.2,2.6)1.9 (2.2,3.4)2.8 - (1.0,2.6)1.8 γn y 0.5 0.3 - 0.8 (0.2,0.9) (0,0.5) (0.4,1.2) γyg (0.003,0.1)0.06 (0.003,0.1)0.06 - (0.003,0.1)0.07 γbk (0.21,0.48)0.35 (0.1,0.4)0.25 - (0.41,0.68)0.55 γbn (0.02,0.1)0.06 (0.02,0.1)0.07 - (0.009,0.06)0.03 γbg (0.04,0.2)0.1 (0.04,0.2)0.1 - (0.03,0.17)0.1 γgn (-0.02,0.1)0.05 (-0.03,0.1)0.04 - (-0.06,0.08)0.01 γk g -0.005 0.01 - 0.01 (-0.08,0.07) (-0.06,0.08) (-0.07,0.08) θN (0.05,0.07)0.06 (0.07,0.09)0.08 (0.06,0.09)0.07 (0.05,0.07)0.06 ψπ (1.5,1.8)1.7 (1.5,1.9)1.7 (0.995,1.0)0.999 (1.6,2.0)1.8 ψy (-0.02,0.02)-0.003 (-0.02,0.02)0.001 - (-0.04,0.006)-0.02 ψR 0.62 0.67 0.62 0.46 (0.56,0.67) (0.62,0.71) (0.57,0.68) (0.37,0.55) η (0.52,0.60)0.56 (0.59,0.66)0.62 (0.86,0.90)0.88 -
Log data density 0 -44 -69 -112
Chapter 3 3.6 Conclusion
surpluses. This active fiscal-passive monetary policy case is often referred to as the Fiscal Theory of the Price Level.
To consider this possibility, column four of table (3.5) presents the results from a model where fiscal instruments do not respond endogenously (equivalent to the case where the γ terms are set to zero). Fiscal policy is therefore described by exogenous processes, which are still related to the Romer–Romer shocks to make the model comparable. ψπ is estimated to be less than one, which satisfies the condition for passive monetary policy (although ψπ is not restricted to be less than one).
However, the results in table (3.5) imply that the model with fiscal feedback is pre- ferred by the data in terms of the log data density. This suggests that, at least over the whole sample, fiscal policy is sufficiently responsive to debt to ensure determinate debt dynamics. This result is similar to findings by Traum and Yang (2010). These authors also estimate a DSGE model using Bayesian methods and examine whether the data prefer active monetary-passive fiscal policy or passive monetary-active fiscal policy. They also find that the data prefer the active monetary-passive fiscal policy specification, although their fiscal policy specification is not as rich as above.
The results presented here do not, of course, consider the possibility that there were specific periods in the sample of passive or active fiscal policy. Recent work by, for example, Davig and Leeper (2006, 2011) estimate regime-switching policy rules for the United States, highlighting that different combinations of passive and active monetary and fiscal policy existed at different points in the post-war period. The use of narrative data presents an interesting avenue for future research in this direction.
3.6
Conclusion
In this chapter I have estimated a DSGE model using Bayesian methods to help under- stand the importance of the endogenous feedback from key macroeconomic variables to fiscal policy instruments. The central innovation in this chapter has been to make use of new, direct measures of tax changes constructed using a ‘narrative’ approach. Other methods, such as previously estimated DSGE models and SVARs, assume that the true tax shocks are unobserved, attempting to identify these using structural assumptions and performing estimation using National Accounts measures of tax revenues.
I showed how the narrative tax shocks can be integrated into a relatively stan- dard medium-scale DSGE model. I then estimated the parameters in the model using likelihood-based Bayesian techniques for the United States. The central results of this paper are threefold. First I showed that, having made use of the narrative tax changes identified by Romer and Romer (2010), the feedback from debt to the fiscal instruments is reduced. My new estimates were also shown to be lower than comparable results by Leeper et al. (2010). This was particularly true for the response of spending to debt and, to a lesser extent, the response of capital taxes to debt.
Chapter 3 3.6 Conclusion
Second, I showed that the capital tax multiplier is significantly increased when the Romer–Romer data are used in estimation of the model. Furthermore, in general, the tax multipliers I obtain are higher than those estimated elsewhere in the literature. In addition, I showed that the estimated model implies that exogenous tax changes have a peak effect between estimates found by Romer and Romer (2010) and in the SVAR literature. The effect of a government spending shock is found to be similar to the results in Leeper et al. (2010) but lower than in Zubairy (2010). In Chapter 4 I consider the transmission mechanisms of government spending shocks in more detail.
Third, I showed that the data prefer the baseline specification to three other versions of the model. Versions of the model that exclude depreciation allowances and sticky prices produced parameter estimates that were, in many cases, similar but there was a deterioration in the estimated log data density. I also showed that the data appear to prefer the model which allows for endogenous feedback to fiscal policy instruments. An important corollary of this is that the fiscal instruments appear to react sufficiently strongly to debt in the baseline model to ensure that passive monetary policy was not needed to ensure stable debt dynamics. However, as discussed previously, work by Davig and Leeper (2006, 2011) suggests the existence of different active/passive regimes at different points in the post-war sample. Bringing narrative data to bear on these issues is a potentially exciting avenue for further research.
Narrative data provide a rich new source of information for estimating the macroe- conomic effects of fiscal policy. This chapter has shown that incorporating these new measures into the estimation of a medium-scale DSGE model has important implications for the estimated strength of feedback from debt and output to the fiscal instruments, as well as the implied fiscal multipliers in response to structural fiscal policy shocks. Making greater use of this new source of data provides interesting scope for future work.
Chapter 4
Government spending, wealth
effects and distortionary taxation
4.1
Introduction
The effectiveness of government spending in stimulating the economy became a central policy question during the 2008 financial crisis. Whilst proponents and critics argued about the mechanisms determining policy success, I noted in Chapter 3 that standard macroeconomic models can generate a wide range of theoretical predictions depending on the assumptions made about how the spending increase is financed1 and assumptions about how consumers respond to implied future tax increases.
In Chapter 3 I pursued a full-information approach, estimating a DSGE model using Bayesian methods. Although appealing as a method for identifying the endogenous feedback from variables such as output or debt, full-information methods impose a lot of structure on the data. As I discussed in Chapter 1, considerable faith must therefore be placed in the model.
In recent years, a debate has emerged as to whether DSGE models can adequately account for the empirical effects of structural shocks to government expenditure found elsewhere in the empirical literature. For example, particular attention has been paid to whether DSGE models can account for SVAR evidence that private consumption and real wages tend to rise following a structural shock to government spending; see, for example, Monacelli and Perotti (2009), Ravn et al. (2007) or Linnemann (2006).2
In this chapter I again construct and estimate a DSGE model for the United States. However, rather than assuming the model is a full description of the data generating process, I focus on the model’s ability to account for a particular aspect of the data: namely the effect of government spending shocks. I employ a minimum distance ap-
1
Also see, for example, Baxter and King (1993) or Alesina et al. (2002). 2
It should be noted that narrative identification approaches have tended to find a fall in private consumption. For a review of this evidence and a reconciliation with the SVAR results see Perotti (2007).
Chapter 4 4.1 Introduction
proach, matching the impulse response functions from the model to those obtained from a SVAR, identified using the method of Blanchard and Perotti (2002). Results from the estimated model can then be compared with the SVAR evidence to evaluate the model’s performance.
This chapter is particularly concerned with the endogenous response of tax rates to government spending shocks and the strength of the so-called ‘wealth effect’ on labour supply — both of which crucially affect the predictions of standard macroeconomic mod- els. The estimated model is shown to match key aspects of the empirical evidence with a realistic set of tax instruments and transmission channels.
For all their complexity, many standard models of fiscal policy often rely on a very simple fiscal policy instrument, the lump sum tax, to finance an expenditure shock. This includes state of the art policy models such as that of Smets and Wouters (2007) and recent papers, for example by Cogan et al. (2010), who analyse the size of fiscal multipliers in the U.S.
However, the lump sum tax assumption is far from innocuous. Lump sum tax-finance implies a ‘wealth’ effect as (expected) income falls. Consumption falls but, assuming leisure and consumption are normal goods, labour supply and consequently output rise. This allows the neoclassical model, and others based on it, to match empirical evidence that GDP increases following a discretionary government spending stimulus.
There are, however, several issues with this mechanism. Firstly, the output rise relies both on the strength of the wealth effect and the lack of distortions associated with the instrument. Consider using a labour income tax instead. The labour supply decision is now distorted, producing strong negative substitution effects. Generally this substitution effect dominates, lowering labour supply and output. Secondly, even if the wealth effect channel can explain the output response, it generates consumption and the real wage responses that are at odds with the empirical Structural Vector Autoregression (SVAR) literature.3 Thirdly, there is the practical realism of the assumption. Lump sum taxes are rarely, if ever, used as primary instruments of tax policy. Chapter 2 and Romer and Romer (2010) illustrate that most tax actions in the U.K. and U.S. respectively were changes in distortionary taxes.4
Since there is no a priori reason to assume that a particular mix of tax instruments finances a spending increase, my first goal in this chapter is to estimate the endogenous response of tax rates for the United States and construct a New Keynesian model which replicates these.
The second goal is then to examine the strength of the wealth effect on labour supply itself. The wealth effect channel is still potentially important even after modelling and estimating the distortionary tax rules. This is because the government’s budget con-
3
Again, see Perotti (2007) for a review of this evidence. 4
This includes, for example, both tax changes to directly fund spending measures and tax changes to deal with a budget deficit.
Chapter 4 4.1 Introduction
straint must hold in each period. In several models (such as Burnside et al. (2004)), this is done using a lump sum tax. Furthermore, even if the budget constraint is satisfied by issuing debt, Ricardian equivalence with respect to lump sum taxes implies the same wealth effect on labour supply. It is therefore important to consider jointly the strength of the wealth effect on labour supply and the endogenous tax responses to the spending shock.
Following Monacelli and Perotti (2009), I use Jaimovich and Rebelo (2009) (JR) preferences which allow for a variable wealth effect on labour supply. Following Schmitt- Grohe and Uribe (2010) (who do not investigate fiscal policy issues), I estimate the size of this effect. As shown by Monacelli and Perotti, a useful feature of these preferences is that, when the wealth effect on labour supply is limited, consumption and the real wage can increase. This further motivates estimating the importance of the channel.
To evaluate the importance of other potential transmission mechanisms I include a range of more standard features such as sticky prices, variable capital utilisation and habits. I show that the estimated model can match the positive empirical response of key variables including output, consumption and the real wage, which is a challenge for many New Keynesian models. These results arise for a number of reasons. Firstly, the importance of the wealth effect on labour supply is small. Secondly, mechanisms such as sticky prices, variable capital utilisation, investment adjustment costs and habits all play an important role in matching the evidence. Thirdly, distortionary tax rates rise following the expenditure shock but their small magnitude crucially reduces the distortions involved. This explains why the positive output and consumption responses prevail.
The results in this chapter contribute, and are related, to several branches of the current literature. Firstly, I directly contribute to the literature which seeks to explain the empirical effects of discretionary shocks to government expenditure. As discussed above, much work has been focused on matching the sign of the consumption (and real wage) response.5 Few papers in this specific branch of the literature have considered distortionary taxes or included empirically realistic tax policy rules (Burnside et al. (2004) and Reis (2008) being two exceptions). To my knowledge, no papers have empirically evaluated the importance of the wealth effect channel as a transmission mechanism of fiscal policy.6
Secondly, by estimating tax policy rules, the results in this chapter have a relationship with the literature discussed in Chapter 3, and to which Chapter 3 contributes. Both Leeper et al. (2010) and Zubairy (2010) perform Bayesian estimation of DSGE models that include feedback to the tax rates from output and debt (but not spending). However,
5
Zubairy (2009), as I do, follows a minimum distance approach, estimating how well a ‘deep habits’ model of the form of Ravn et al. (2007) (with lump sum taxes) can explain a government spending shock.
6
Although, as noted above, Monacelli and Perotti (2009) do show how varying the strength of this effect has useful implications.