Policy Uncertainty and the Economy

KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

AUGUST 2016

AMERICAN ENTERPRISE INSTITUTE Policy Uncertainty and the Economy

KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

AUGUST 2016

The American Enterprise Institute (AEI) is a nonpartisan, nonprofit, 501(c)(3) educational organization and does not take institutional posi- tions on any issues. The views expressed here are those of the author(s). Table of Contents

I. INTRODUCTION...... 1

II. THE EARLY LITERATURE...... 2

III. MODERN THEORY...... 7

IV. A NEW EMPIRICAL APPROACH: UNCERTAINTY INDICES...... 13

V. TAX POLICY AND UNCERTAINTY: NEW APPROACHES...... 18

VI. IN SEARCH OF AN ESCAPE FROM ENDOGENEITY...... 22

VII. PUZZLES IN THE ELECTION CYCLE LITERATURE...... 23

VIII. CONCLUSION...... 28

ABOUT THE AUTHORS...... 29

REFERENCES...... 30

I. Introduction

ncertainty has remained a concept central to the identification issues that have belied empirical Ueconomics for almost as long as the field has attempts to assess the causal impact of uncertainty. existed. The literature has exploded in recent years, None of the attempts to overcome these issues, we as breakthroughs in modeling and measurement have argue, seems to have been successful to date. allowed researchers to identify both the theoreti- Sixth, we examine the literature that examines the cal impacts of heightened uncertainty under varying relationships between elections and uncertainty, eco- assumptions, and the likely empirical manifestations nomic activity and financial markets. Many empirical of these impacts. This paper provides a review of the papers fail to distinguish between countries in which latest developments in this literature and provides the timing of an election is well known in advance new evidence of the impact of uncertainty on eco- (e.g., the United States) and those in which the tim- nomic activity. ing of an election is endogenously determined (e.g., We proceed in a number of steps. First, we situ- the UK or Israel). Those that do, however, nonethe- ate the modern literature on policy uncertainty in less find significant effects of elections even in coun- the history of economic thought, as past quanda- tries in which the timing of an election is well known ries and debates in the field presage many of those to market participants far in advance. We explore in that continue. Second, we review the contemporary detail the relationship between elections and uncer- theory-focused literature. Though the literature has tainty, and provide new evidence relating elections developed a number of models, the lack of congru- to financial variables and the probability of reces- ity between theory and empirical calibration seems sion. The implications of rising political polariza- to remain an area for future work in the field to fill. tion, we argue, most parsimoniously explain both the Third, we review the indices that have been con- election-based literature’s existing puzzles and the structed in attempts to quantify uncertainty and new results we present. facilitate its empirical study. The differences among In aggregate, this review and the new results various indices developed to date reflect conceptual we present suggest the existence of at least three fault lines concerning what constitutes “uncertainty” remaining gaps that stand to be filled in this liter- that have existed in the field since the 1920s. ature: (1) the robust matching of well-specified Fourth, in a testament to the possibilities now theoretical models to empirical regularities; (2) offered by the development of indices of uncer- the development of causal identification strate- tainty, we analyze the relationship between statutory gies for overcoming endogeneity concerns; and (3) changes to the tax code and uncertainty. We find that given the possible prominence of political effects “endogenous” tax changes decrease economic policy in mediating the relationship between uncertainty uncertainty, while a certain species of “exogenous” and economic activity, a renewed focus on political tax changes increases economic policy uncertainty. mechanisms as both effects and causes of economic Fifth, we examine recent attempts to overcome policy uncertainty.

1 II. The Early Literature

A. An Intuitive Example the introduction of a random new tax then causes the price of his output to fluctuate between lower price

t may, at a glance, seem rational to invest in any P1 and higher price P2, given an upward-sloping sup- Iproject with expected cash flows that generate ply curve, the gain generated in the producer’s “good” a positive net present value. It may also be intuitive state with price P2 exceeds the loss in the producer’s to think that policy uncertainty can discourage eco- “bad” state with price P1. This can be seen in Figure 1, nomic activity in general and investment in particular. wherein the area of good state area A exceeds the area Contrary to this intuition, however, a strand of earlier of bad state area B. literature (e.g., Hartman 1972 and Abel 1983) demon- To the extent that producers can increase the strated that uncertainty can increase investment in quantity of goods produced as price increases, there- certain cases. fore, uncertainty can increase profits and average The intuition for this result serves as an important investment as well. anchor for an understanding of the possible channels A key feature of this simple example is the abil- through which uncertainty can influence economic ity of the producer to costlessly adjust his output up activity and the challenges facing modelers. Imagine and down. Beginning with Arrow (1968), Bernanke a producer who starts out selling goods at price P0. If (1983), and Pindyck (1988), however, economists have

Figure 1. Effect of a Random New Tax

PPP

P2 A

P0 B

Q1 Q0 Q2 Q

Source: Authors’ calculations.

2 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

generated more general models that assume adjust- it is rational to make the investment today. But it is, in ment to be costly or to have large fixed costs. When fact, still optimal to delay and postpone that decision adjustment is costly and returns are uncertain, then until tomorrow: the decision to delay allows one to a firm may experience regret for the choices it made. avert the $100 expenditure on the cost of the furnace This regret is a crucial element in modern models that in the event the price of gas rises and the operation find negative effects of uncertainty. of the furnace is no longer economically rational. As To illustrate, suppose, as in Auerbach and Hassett the Table 1 shows, if the probability of the gas price (2002), that a firm accustomed to powering its oper- rising is 0.5, then this delay until tomorrow increases ations with a coal furnace is considering the purchase the expected profit generated by the purchase from of a new, more energy-efficient gas-powered furnace. $100 to $150, an increase of $50. The $50 increase in This new furnace costs $100 today, but it has an uncer- expected value comes from avoiding the $100 loss tain return tomorrow because the future price of the if the 50 percent probability scenario of a gas price gas required to operate the gas-powered furnace is increase comes to fruition. uncertain. If the price of gas stays the same, the oper- Thus, because the firm can avoid the possible ation of the furnace stands to generate $400 in profit. loss of $100 if a bad state materializes and the price However, if there is bad news tomorrow, and the price of gas increases, it is better for the firm to delay the of gas increases, then the furnace will generate no new investment. revenue and therefore a $100 loss due to the $100 out- It is worth noting that the rationality of delay lay required to purchase it. depends on the irreversibility of the investment. Were If the probability of either outcome for the price of the firm able to sell the gas furnace for its full cost in gas is 0.5, ignoring discounting, then the expected net the event the price of gas rises, then the scenario in present value of purchasing the machine is: which the firm lost $100 as the price of gas rose would never materialize, because the firm would simply sell (0.5 x $400) + (0.5 x $0) – $100 = $100 the machine for $100 and break even in spite of the increase in the gas price. However, it seems unlikely Due to the positive expected value of the furnace’s that many investments are reversible. There are two future cash flows, it may be tempting to conclude that main reasons for this:

Table 1: Investing Today Versus Waiting Until Tomorrow

Today Tomorrow Tomorrow If good news If bad news Expected (Probability = 0.5) (Probability = 0.5) return

Scenario 1: The expected profit if you buy a new gas-powered furnace that costs $100 today, even though it has an uncertain return tomorrow. Pay $100 Earn $400 Earn nothing/eat loss $100

Scenario 2: Expected profit if you wait and decide whether to purchase the furnace tomorrow, when you already know whether the price of gas has increased. Pay nothing Earn $400 – $100 = $300 Earn nothing/no loss $150

Source: Authors’ calculations.

3 POLICY UNCERTAINTY AND THE ECONOMY

1. Many pieces of capital are customized and recessions. This creates a natural downward bias in therefore, once installed, have little or no value estimates of the effects of investment tax credits, as to any other firm or individual. For example, they will by the very nature of this process appear to attic insulation cannot be removed and resold co-vary with declines in investment. if energy prices decline (see Hassett and Met- To resolve this econometric issue, the literature calf 1994). turned toward cross-sectional variation and expec- tations of future tax policy changes. This strategy 2. If economic conditions render the operation exploited the fact that experience of major tax reforms of capital equipment economically unviable arguably offers periods in which there is exogenous for one firm, it seems unlikely that the opera- cross-sectional variation in the user cost of capi- tion of that same capital equipment would be tal or tax-adjusted value of q. Auerbach and Hassett economically viable for another firm. Though (1991) and Cummins, Hassett, and Hubbard (1994, the price of equipment may fall to reflect new 1995, 1996) demonstrate that major tax reforms are economic conditions, if economic conditions also associated with significant firm- andasset-level are such that the marginal cost of equipment’s variation in key tax parameters (such as the effective operation exceeds the marginal benefit for one rate of the investment tax credit and the present value firm, it seems unlikely that economic condi- of depreciation allowances). Hence, tax variables are tions would be such as to render it econom- likely to be a good instrument for the user cost or q ically viable for another firm to first pay the during tax reforms: variation across assets within a fixed cost of the equipment and then the mar- given year is large, as is within-asset variation over ginal costs of operation. time. The treatment of different assets relative to one another also changes over time. Contrary to those in Hence, in the real world, there is a gain to wait- the previous literature, estimates using this source ing in the presence of uncertainty if the investment of plausibly exogenous variation produced very large expenditure in question entails sunk costs. estimates of the impact of tax policy on investment, bridging part of the previous gulf between theoretical B. Situating the Modern Literature and empirical results. A debate about if and when uncertainty’s effects Many of the issues confronting the contemporary lit- increased or decreased investment, a debate that erature on policy uncertainty have long histories in would prove influential, emerged around this time. the literature. In contrast to the models that demonstrated that Building on the work of Tobin (1969) and Hayashi uncertainty can have salutary effects by inducing (1982) in modeling tax policy in terms of both future firms to shift expenditures to the “good” state when and present values, early papers found a priori the- they do not know how long it will last, Pindyck (1988) oretical reasons for uncertainty about tax policy to demonstrated that uncertainty can have a depress- influence investment by incentivizing firms to pull ing effect on investment if the investment is irrevers- capital expenditures from the future to the present ible. Hassett and Metcalf (1999), however, offered a (e.g., Auerbach and Hines 1988). But they failed to qualification to that conclusion. In place of the geo- find empirical corroboration (see Auerbach and Has- metric Brownian motion (GBM) processes then used sett 1992 for a discussion of these estimates). The to model tax policy uncertainty, Hassett and Met- identification issue at the root of the problem seems calf (1999) modeled tax policy as a Poisson jump clear in hindsight: as documented in Cummins, Has- process, a contribution that built upon the earlier sett, and Hubbard (1994), Congress tends to enact replacement of the GBM process with an alternative investment tax credits during recessions. Business mean-reverting process in Metcalf and Hassett (1995). investment tends, due to market forces, to fall during A GBM process is a continuous random walk capable

4 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

of generating values that approach infinity over time. probability of entering either one of the two possi- By contrast, a Poisson jump process features discrete ble states approaches 50 percent. “jumps” that arrive unpredictably, and can be mod- This progression involved models that allowed for eled to include jumps between only a few pivotal precise parameterization of uncertainty as a charac- values. Statutory tax rates, at least in the developed teristic of a well-specified random variable. The lit- world, tend to change discretely and remain between erature has also modeled an alternative in which 0 and 1. Modeling tax policy through a GBM process economic agents function without such information. therefore seemed less preferable than modeling tax Whether to distinguish, or not distinguish, between policy as a Poisson jump. parametric uncertainty (“risk” in colloquial English) The distinction between geometric Brownian and Knightian uncertainty (“uncertainty” in collo- motion and a stationary Poisson jprocess emphasized quial English) represents another enduring fault line in Hassett and Metcalf (1999) has a large impact on between authors in the literature. An increase in para- their results. While increasing uncertainty raises hur- metric uncertainty would occur if, say, the number of dle rates and slows investment if modeled via GBM, rounds in a gambler’s game of iterated coin toss were if modeled by a Poisson jump process, investment to increase from two to eight. The number of possible increases in the current period. This is because the outcomes would increase from 4 to 256, and the risk, Poisson jump process better simulates a situation in in any single bet, of betting on the wrong permutation which firms are more likely to find themselves where therefore would increase. But the number of possible they are both in a “high” investment tax credit (ITC) outcomes would remain finite and accurately calcula- state and nervous about the prospect of that “high” ble according to a well-known formula. By contrast, ITC state switching off, a situation that induces them imagine a different gambler drawing white or black to accelerate investment into the current “high” ITC marbles from an urn, managed by a genie who tells period. Contrary to the intuition that the irrevers- the gambler that the urn contains equal portions of ibility of investment necessarily entails a decline in white and black marbles. Suppose the genie manag- investment whenever uncertainty increases, then, the ing the urn, however, then tells the gambler that he modeling of tax changes through the Poisson jump could no longer profferany information about the rather than GBM process demonstrates the intu- ratio of white to black marbles in the urn. Though ition for when and how uncertainty can also increase the rational estimate for the probability of drawing investment even in the presence of irreversibility. a white or black marble remains 50 percent (assum- Hassett and Metcalf (1999) also delineate con- ing the marbles are replaced), this would create an ditions for distinguishing the effects of variation increase in “Knightian uncertainty” for the gambler. in policy uncertainty from variation in other eco- In contrast to the coin-flipping gambler, who can sim- nomic variables drawing on the important semi- ply change the equation he uses to describe the pro- nal contribution of Rothschild and Stiglitz (1976). cess that generates the outcomes, the marble-drawing First, the effect of uncertainty should vary as the gambler has transitioned to a state in which he pos- spread between the two states of the investment sesses no knowledge even of the distribution of possi- increases, even as the average of those two states ble distributions of marbles inside the urn.1 Whereas remains the same. This notion of an increase in the coin-flipper experiences an increase only in a “mean-preserving spread” as constitutive of an increase in uncertainty offers both an intuitive con- 1 Ellsberg (1961) presents evidence that individuals have an ceptualization and a metric that can be calibrated aversion to the type of uncertainty the marble-drawing gambler empirically. Second, as noted in Theil (1967), as the experienced a heightened level of, “ambiguity-aversion,” dis- probability between states approached 50 percent, tinct from aversion to risk of the sort experienced by a coin-toss- ing gambler. See Zeckhauser (2006) for an elaboration of the uncertainty increases, since agents have less infor- concept in the context of the “unknown and unknowable,” the mation about future states of the world when the conceptual basis of which he also attributes to Knight (1921).

5 POLICY UNCERTAINTY AND THE ECONOMY

parametric uncertainty, then, the gambler experi- sense in which I am using the term is that in which ences an increase only in Knightian uncertainty. This the prospect of a European war is uncertain, or the significance of the qualitative distinction between price of copper and the rate of interest twenty years these two kinds of uncertainty, made in 1921 pub- hence . . . [about] these matters there is no scien- lications by both John Maynard Keynes (Treatise on tific basis on which to form any calculable probabil- Probability) and Frank Knight (Risk, Uncertainty, and ity whatever. We simply do not know. Nevertheless, Profit), remains a point of disagreement among econ- the necessity for action and for decision compels us omists that continues to permeate articles on policy as practical men to do our best to overlook this awk- uncertainty in leading economics journals.2 As Keynes ward fact and to behave exactly as we should if we elaborated in a 1937 article in the Quarterly Journal of had behind us a good Benthamite calculation of a Economics, then as now a leading economics journal, series of prospective advantages and disadvantages, in response to criticism from Jacob Viner, a promi- each multiplied by its appropriate probability, wait- nent contemporary economist of his: ing to be summed. (Keynes 1937, 213–214)

By, “uncertain” knowledge, let me explain, I do not Nonetheless, in spite of its age, the relevance to the mean merely to distinguish what is known for cer- distinction between what Keynes refers to as “uncertain from what is only probable. The game of rou- tainty” versus “what is only probable” remains an lette is not subject, in this sense, to uncertainty . . . unsettled debate. Rather than impose one definition [even] the weather is only moderately uncertain. The throughout the paper, we will refer to papers in the terms their authors have chosen, making note of how they conceptualize uncertainty if it seems especially 2 See, in particular, the later discussions of Fernandez- relevant to contextualizing the topic at hand. Villaverde, of Jurado, Ludvigson, and Ng (2015).

6 III. Modern Theory

n more recent years, in tandem with the rise of the net exports through the business cycle. The key link Ivoluminous empirical literature on uncertainty to aggregate fluctuations, however, is heightened even reviewed later in the paper, a modern theoretical lit- with this correction. erature on the effects of uncertainty has also arisen. Turning from small open economies to the expe- One of the more prominent theoretical contribu- rience of the post-WWII United States, and from real tions to this literature comes from dynamic general interest rates to fiscal policy, Fernández-Villaverde et stochastic equilibrium (DGSE) models developed to al. (2015) offer a DGSE model of shocks to the vari- explain aggregate fluctuations in output and invest- ance of fiscal policy. F-V et al. (2015) decompose fiscal ment through fluctuations to various proxies for policy into government spending, the labor tax rate, uncertainty. In one notable contribution, Fernández- the capital tax rate, and the consumption tax rate. Villaverde et al. (2011)—henceforth known as F-V et They then feed baseline parameter values calibrated al. (2011)—explore the effects of innovations to real to fit thepost-WWII United States experience into interest rate volatility in small open economies, a set- their model. Their estimates of the output effects of ting germane to understanding the potential effects shocks to the variance of fiscal policy are large and, as of monetary policy uncertainty. Well specified, the the authors note, qualitatively on par with their esti- DGSE model in F-V et al. (2011) relies crucially on the mates for the output effect of innovations to the fed- real interest rate as the central propagation mecha- eral funds rate. These effects, while significant, lead nism of the general equilibrium effects implied by to a number of additional questions. The definition its model. They find that shocks to real interest rate of “uncertainty” is synonymous with “risk” or “objec- volatility significantly impact the economy, with tive uncertainty,” a concept on par with parametric higher volatility reducing consumption, investment, uncertainty (F-V et al. 2015, 3335). This contrasts with and output. others in the literature (e.g., Jurado, Ludvigson, and A couple of cautions are applicable to this result, Ng 2015) who distinguish between forecastable and however. First, the paper draws on data from the his- unforecastable increases in variance, a conceptualiza- torical experience of four Latin American economies tion that plausibly comports with the way individuals (Argentina, Brazil, Ecuador, and Venezuela) during tend to experience uncertainty. a period that stretches from roughly the mid-1990s To calibrate their model to the historical experi- through the late 2000s, a fairly unique period that ence of the post-WWII United States, the authors also may not generalize to developed countries. Second, calculate average tax rates based on the standard pro- there are the qualifications noted by Born and Pfeifer cedures for doing so using National Income and Prod- (2014) in a comment published in the American Eco- uct Accounts (NIPA) data. However, as intimated in nomic Review, the original article’s final publication Kelly, Pastor, and Veronesi (forthcoming), variation in venue. Born and Pfeifer (2014) note that the model in average tax rates estimated according to this proce- the original F-V et al. (2011) paper is in need of recali- dure can arise from many sources besides fiscal pol- bration due to a time aggregation error in the original icy or its variance. The NIPA procedure divides the piece and that, once an additional error in the calcula- total burden of taxation on a given factor (e.g., labor) tion of net exports is also corrected, the recalibrated by the total share of economic activity attributable to models lose explanatory power over the fluctuation of that factor of production or expenditure (e.g., labor

7 POLICY UNCERTAINTY AND THE ECONOMY

income). Hence, an economic shock that, say, dis- (1999) framework, they do not have that same incen- tributes labor income from higher- to lower-income tive in the presence of a middle ITC state. After all, in individuals, in a country with a progressive tax sys- the middle of the three states, the ITC can increase in tem, could change the calculated average tax rate the future as well as decrease. This mutes the incen- and therefore appear as a fiscal policy shock—even tive to shift investment to the current time period in if there were no change in the tax code or any fiscal order to make investments when their after-tax cost policy of the government, and no uncertainty about is at its minimum possible value, since the middle the tax rules. More broadly, any underlying economic state of the ITC value, unlike the high state of the ITC shock that changes the average tax rate as calculated value, is not necessarily the lowest cost state. Simi- through the NIPA procedure would appear as a shock larly, by introducing the possibility that a high ITC to the variance of fiscal policy. This suggests that can shift down only to the medium state, compared the F-V (2015) may misidentify shocks to economic to a two-state model with only low and high ITC val- activity that are not mediated by any policy channel ues, the Altug, Demers, and Demers (2009) model as shocks to the variance of fiscalpolicy. The F-V et reduces the difference in after-tax costs between the al. (2015) procedure for identifying variance in fiscal high ITC state and its set of alternatives. Though this policy, therefore, may have only an orthogonal rela- three-state approach changes the possible effects of a tionship to the underlying policy changes of the sort it temporary ITC on the level of investment to include seems to purport to identify. Though the emphasis in the possibility of a negative net effect, the Altug, F-V et al. (2015) on fiscal volatility in a DGSE setting Demers, and Demers (2009) framework nonethe- is a novel contribution to the economics literature, it less reliably generates estimates of an increase in the nonetheless seems worth both clarifying its defini- volatility of investment. On this basis, the authors tion of uncertainty on the conceptual level as well as conclude that policymakers contemplating the use equivocating the identifying power of the NIPA-based of temporary ITCs may face a tradeoff between the procedure used to estimate shocks to fiscal policy. long-run level and the volatility of investment. Altug, Demers, and Demers (2009) extend the As the authors concede, however, Altug, Demers, Hassett and Metcalf (1999) two-state model to a and Demers (2009) do not incorporate general or three-state model framework that they argue bet- market equilibrium effects (521). And given that ITCs ter characterizes post-WWII United States tax pol- plausibly tend to be enacted as countercyclical poli- icy experience. In contrast to Hassett and Metcalf cies during economic slowdowns, the possibility that (1999), they find through numerical simulations that ITCs have aggregate effects in a general equilibrium heightened uncertainty regarding ITCs necessarily setting that cannot be inferred from the “myopic firm” increases only the variability of investment, and can setting cannot be dismissed out of hand. Nonetheless, even have negative directional effects on its level in the introduction of the three-state model remains a the long run. Crucial to these results is their intro- notable contribution to the large literature on policy duction of the third state—the state of a medium ITC uncertainty focused in particular on tax policy. value, in addition to states “no” ITC and “high” ITC in Pawlina and Kort (2005) extend the Hassett and Hassett and Metcalf (1999)—that introduces uncer- Metcalf (1999) model to allow the government to set tainty about both the direction and the magnitude its policy in response to a trigger of real economic of the change in the ITC as well as the uncertainty activity. Such a setting is reminiscent of the observed about the timing of the policy change. It is not hard behavior of ITC policy in the United States, wherein to get an intuition for how their modeling approach the government attempts to stimulate investment in a leads to different conclusions from those in Hassett recession (e.g., a slowdown in real economic activity). and Metcalf (1999). Whereas firms have incentives They find that the impact of the trigger value on the to increase investment anytime the ITC rises to the optimal investment rule is not monotonic: the thresh- higher of the two states in the Hassett and Metcalf old decreases with uncertainty at low levels of the

8 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

trigger value, but increases at high levels. This work redistribution is relevant for understanding the rela- suggests that the government may be able to solve for tionship between tax rates and asset prices. Tax rev- the optimal level of policy uncertainty, which would enues redistributed to a representative agent (or set minimize any negative consequences. The possibility of agents), in principle, would not have any effect on that trial and error may drive a government to such consumption volatility according to the model and a policy of minimizing the effects of uncertainty, it therefore could not influence asset prices through would seem, adds another argument in favor of the consumption-based effects. Though replete with view that effects that are attributable purely to tax stylized assumptions, the model of the relationship policy uncertainty may be small. between taxes and asset prices in Sialm (2006) none- Sialm (2006) models how stochastic variation in theless thus offers intriguing implications for future tax rates influences the pricing of assets in a model research relating policy uncertainty to asset pricing. with zero-coupon bonds of varying maturities and Ulrich (2013) likewise focuses on the relationship stocks that pay dividends in perpetuity. The model between policy uncertainty and asset pricing. But he includes only a representative consumer and a gov- pivots to uncertainty about fiscal multipliers, pur- ernment, which can rebate a nonzero portion of tax porting to extract information about what he terms revenue generated through a consumption tax, its “Knightian uncertainty” about the effects of fiscal sole source of revenue. In spite of these abstractions policy from real and nominal yield curves. In the from the US historical experience, the model gener- model of Ulrich (2013), investors observe the set of ates thought-provoking implications. The first is that fiscal policies that the government can choose from. the relationship of the tax rate to the equity and term The government maximizes its own welfare, a func- premiums depends on the relationship between the tion of both its own welfare and the welfare of the growth rate and the tax rate. Stochastic tax rates will private sector, choosing a fiscal policy subject to the not have a distinct effect on the equity or term premi- constraints thus created by the existence of political ums to the extent that they are necessarily positively costs for the government. The investor faces uncer- correlated with the growth rate of dividends. On this tainty about which of the set of known possible fis- basis, Sialm (2006) generates the finding that, if a cal policies the government has chosen. Hence, there higher tax burden serves as a causal impediment to is, according to Ulrich (2013), a “policy premium” economic growth, and the correlation between taxes built into the United States Treasury yield curve. This and growth becomes negative, larger equity premi- policy premium exists, according to Ulrich (2013), ums result. The second is that, to the extent tax rev- because “recession hedge assets” such as govern- enue collected by the government is rebated to the ment bonds underperform when the government’s representative consumer, taxes will not increase the spending multiplier is positive. To avert a represen- equity premium through the “income effect” that tative agent shorting the bonds in equilibrium, then, would arise from increasing the variability of con- the bonds must feature compensation for this risk sumption over time through stochastic taxation. of underperformance in the presence of policy mul- Granted, a “representative consumer” may not neces- tipliers. With cross-sectional Survey of Professional sarily capture the tax-and-transfer dynamics of most Forecasters (SPF) estimates for fiscal spending as modern developed economies.3 An intriguing impli- a proxy for uncertainty, Ulrich (2013) matches his cation of this dynamic, though, is that the distinction model to real and nominal Treasury yield curves as between government consumption and government well data on the implied volatility of Treasury debt from options markets. The study finds what seem to be plausible estimates: the SPF-based proxy for pol- 3 The author addresses this point in the robustness section, icy uncertainty can explain 18 percent of the vari- but details of how he modeled the introduction of agents with ation in the implied volatility of options on 10-year heterogeneous wealth levels and a redistributive government are not presented. US Treasury bond futures contracts. However, the

9 POLICY UNCERTAINTY AND THE ECONOMY

model in Ulrich (2013) assumes that the issuance of present a model that treats public debt and tax rates new supply of Treasury debt has no net effect on the as endogenous. They find that the effects of a negative yield curve (a “no net supply” assumption). Yet, many productivity shock are amplified when one allows for studies have documented the impact of fluctuations feedback effects to public debt: a negative productiv- in the supply of Treasury debt on the yield curve (e.g., ity shock induces a countercyclical increase in govern- Laubach 2009). And the fiscal policy adopted by the ment spending, and the burgeoning public debt that government is a crucial determinant of the issuance results induces long-run tax hikes that decrease the of Treasury debt and, therefore, of the yield curve. future value of wages and profits. These effects offset The absence of any modeling of this effect suggests the short-term benefits of consumption stabilization that interpreting the empirical estimates interpreted offered by such a policy. Given the persistently high by Ulrich (2013) as corroborating the model may not levels of public debt present in the developed world, be as intuitive as it would seem at a glance. Granted, where countries tend to have automatic “stabilizers” constructing a model that incorporates both the that smooth consumption volatility during output “demand-side” effects of fiscal policy and the effects shocks, this distinction between the long-run costs of of new Treasury bond supply on the yield curve would increases in fiscal uncertainty and short-run decreases certainly be a tall order. But it is difficult to arrive at in consumption volatility is one that the literature on an intuitive interpretation of estimates generated by a optimal fiscal policy would seem well-advised to pur- model that assumes there is no effect of an increase in sue. More broadly, the implications of the possible the supply of Treasury bonds on the yield curve, given tradeoff between the consumption insurance value of the well-known existence of precisely such effects and countercyclical fiscal policy and the risk that the cost how correlated the supply of Treasury bonds would of this consumption insurance could decrease future necessarily be to fiscal policy parameters of precisely welfare through the high rates of taxation that would the sort that Ulrich (2013) attempts to learn about be needed to finance this consumption insurance— through his analysis of the yield curve. even in bad states of nature where pre-tax income Croce, Nguyen, and Schmid (2012), by contrast, would be decreasing—offers an interesting perspec- turn to effects of uncertainty about the future fis- tive to the public finance literature. cal trajectory of the government. Crucial to their Nishide and Nomi (2009), for their part, focus spe- approach is a distinction between the volatility of cifically on a context in which the timing of a poten- short-run consumption and agent uncertainty about tial policy change can be known with certainty, a the long-run trajectory of the future US fiscal posi- departure from traditional ITC modeling frameworks tion. While countercyclical fiscal policies reduce the (e.g., Hassett and Metcalf 1999) where the timing of volatility of consumption, according to their model, the withdrawal of the ITC is a key unknown variable. aversion to ambiguity about model misspecification Nishide and Nomi (2009) have in mind, by their own concerning the long-run government fiscal posi- admissions, the context of elections, a context that tion implied by the negative covariance between will be explored from an empirical perspective later productivity and government expenditures due in the paper. Extending the real options framework to the countercyclical nature of fiscal policy leads first developed in Bernanke (1983), they analogize these same policies to generate welfare losses. The between the position of a firm making an investment model demonstrates that as agents become more decision ahead of a possible “regime shift” and the uncertainty-averse, they behave more and more as if holder of an American-style option with an expiration the “worst-case” scenario of a negative productivity date on the date of regime change. Echoing the results or fiscal shock in fact materialized—a result consis- of Bernanke (1983), they find that immediately before tent with the “real options” corner of the uncertainty a stochastic regime change, it is optimal for firms to literature (e.g., Bernanke 1983). Though they include a act as if the worst possible outcome will occur. For “zero deficit” specification as their baseline, they also example, if one party is hostile to business, while

10 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

another is friendly, then as the election approaches, predictable (e.g., the date of election results or the optimal investors will choose to delay investments, date of a scheduled vote in Congress). This predict- setting their investment levels to that which would ability of the date of the key information disclosure be appropriate if the unfriendly political party were would seem to suggest that waiting to delay a deci- to win. From this perspective, firms contemplating sion would, in many cases, offer particular value on investments ahead of elections lose the option value the benefit side in a policy context. of delaying by exercising that option early. The inves- Pivoting to the cost side of the decision of whether tor, then, faces a tradeoff between acquiring the prof- to delay, economically, the level of the interest rate its that would accrue if an investment were made determines the opportunity cost of delaying the before the threshold event on the one hand, and, on investment. As interest rates decrease, the future the other, foregoing the option value of delaying until value of current profits decreases: if risk-free( ) inter- the threshold event passes. The analogy to an equity est rates are zero, the future value of $1 today is $1 in option highlights the key mechanism of irreversibil- one year, but the future value of $1 today is $1.10 in ity in mediating the effects of uncertainty. In the case year if interest rates are 10 percent. This decreases of a stock option, an individual who exercises the the opportunity cost of delaying any given project: if option before a threshold event that ex post generates $1 today will only be worth $1 in one year because an adverse outcome can still readily sell their stock interest rates are zero, in contrast to a world of 10 in any state of the world, albeit at a discounted value percent interest rates that makes $1 today worth in certain states. To the extent that a real investment $1.10 in a year, then the $.10 opportunity cost that is irreversible, however, it becomes less likely that its you incur in a world of 10 percent rates is absent in full value could be recaptured in the event an adverse a world of 0 percent rates, diminishing the cost of outcome is realized.4 delay. The opposite effect holds true when interest Chetty (2007) presents a model relating the real rates rise, increasing the opportunity cost of delaying options effect to interest rates that has implications investment into the future. for when one would expect the effects of policy On the other hand, Chetty (2007) notes that the uncertainty to be relative large versus relatively small. steep yield curve likely to be present in an exception- In Chetty (2007), a firm considering whether to ally low interest rate environment exerts an influ- undertake an investment now or later faces a tradeoff ence in the opposite direction. To the extent that the between the real options value of delay and the pres- yield curve approximates the expected future values ent value of the future profits that otherwise would of short-term interest rates, as the yield curve steep- have accrued during the time of the delay. ens, the expected future costs of capital grow larger Though the model in Chetty (2007) generalizes relative to its current cost. All else equal, therefore, a beyond the policy context, it emphasizes that the ben- steeper yield curves creates incentives to pull invest- efits of delay become larger when the “learning” that ment forward. occurs during the period is greatest, an emphasis that This perspective offers interesting implications for underscores the model’s salience to understanding its understanding the recent US experience and the role effects on policy uncertainty. The key element relat- of monetary policy in shaping it. The persistence of ing the model to the policy context is that the timing the extraordinarily low interest rates adopted by the of when one will learn information about the future Federal Reserve, diminished the opportunity cost of path of policy seems, in many cases, to be rather delaying investment in the presence of uncertainty. Meanwhile, political polarization in the United States continued to march upward—a development that, for 4 As elaborated in Chetty (2007), for this dynamic to hold, it is reasons to be explored later, likely exacerbates the necessary only that real investments be sellable for lower frac- effect of the uncertainty that arises from elections. In tions of their original purchase value than financial investments, not that they be impossible to sell at any price. a country with presidential elections every four years

11 POLICY UNCERTAINTY AND THE ECONOMY

and midterm elections every two, this creates an envi- cost of delaying investment until the later time peri- ronment where the “learning” value of delay is large ods, when market participants expected the interest and the opportunity cost of delay is relatively low, an rates to rise. environment likely to exacerbate the negative effects Granted, interest rates and the shape of the yield of uncertainty. To the extent that the yield curve curve exert effects on economic activity through remained relatively flat during this time, this would many channels other than their effect on the oppor- only add yet another headwind stemming from the tunity cost of delaying investment ahead of a thresh- perceived low opportunity cost of delay indicated by old event, such as an election. Nonetheless, given the such a curve. Ironically, then, the steepening of the concurrent upward rise in political polarization expe- yield curve that began with the “Taper Tantrum” and rienced in the United States, the perspective in Chetty the specter of interest rate rises (but no implemented (2007) offers a thought-provoking perspective on the Fed funds rate increases) would have generated a tail- channels through which monetary policy and tax pol- wind to economic activity to the extent that it con- icy uncertainty shaped the US experience during the tributed to the perception of a higher opportunity Great Recession and its aftermath.

12 IV. A New Empirical Approach: Uncertainty Indices

s the theoretical literature on policy uncertainty papers. They also offer a separate specification that A has blossomed, so has the empirical literature. spans 1900 through the present and incorporates six Elemental to the development of this literature has leading US newspapers. They find very large and per- been the construction of new indices. These mea- sistent negative effects of uncertainty on economic sures of uncertainty, though imperfect, have enabled activity. As attested by the voluminous citations to empirical analysis of the causes and effects of policy the paper in the literature (over 500 according to uncertainty. Google Scholar), many of them empirical studies, the The most prominent index in this literature comes BBD (2015) has become a cornerstone of the recent from Baker, Bloom, and Davis (2015).5 The index resurgence in empirical work. is based on the frequency of the appearance of lan- Meanwhile, the creation of other indices of eco- guage on economic policy uncertainty (EPU) in major nomic uncertainty as distinct from EPU suggests newspapers. In order for a given article to be classi- the possibility of disentangling fluctuations in EPU fied as discussing EPU in the BBD (2015) framework, merely attributable to general economic uncertainty language for each of the three specified economic, (EU) from those that are not. This would allow policy, and uncertainty categories must be present. researchers to overcome a criticism of the literature The article must meet thresholds for economic con- analyzing the effects of EPU: that much of the vari- tent, policy content, and uncertainty content: each of ation in economic activity attributed to fluctuations the three is necessary but not sufficient for an article in EPU in fact derives from fluctuations in EU, which to be encoded with an EPU = 1 value and classified as then in turn influences economic activity. That is, pertaining to economic policy uncertainty in the BBD if bad states of nature both generate uncertainty (2015) framework. The index measures the presence about the future trajectory of economic activity and of EPU content as a fraction of a newspaper’s overall increase pressure on policymakers to act, then an content, standardizes the measure to the newspaper apparent increase in EPU may in fact be an artifact level, and then averages across standardized values. of a parallel increase in EU. If there are indices that This procedure sidesteps many issues that would measure EU but not EPU, however, then the diver- otherwise arise from using, say, raw counts of the gence between the BBD (2015) EPU index and those frequency of EPU articles in news media. In the pre- indices offers the possibility of understanding when ferred specification of BBD, which spans 1985 through variation in EPU is—and is not—due to variation the present, they incorporate 10 leading US news- in EU. Perhaps the most notable index that measures EU 5 Though this is the most recent version of the seminal Baker, as distinct from EPU comes from Jurado, Ludvigson, Bloom, and Davis (2015) paper, predecessors of the paper have and Ng (2015)—henceforth known as JLN (2015). existed in various forms for a number of years. The index has Even aside from their operationalization of the defi- gone through several permutations during those years, and the nition to construct an index, of note is the distinc- iteration described is that which is featured in their most recent paper. tion they draw between their conceptualization of

13 POLICY UNCERTAINTY AND THE ECONOMY

uncertainty and the conceptualization of uncertainty uncertainty, JLN (2015) aggregate an index from 132 adopted by many in the literature. Framing their individual economic variables. definition as a contrast to those that rely on proxies Yet another uncertainty index based on forecast such as the implied volatility of the stock market or error comes from Rossi and Sekhposyan (2015)— text-based analyses that may have only an orthogonal henceforth known as RS (2015). RS (2015) adopt relationship to latent underlying economic processes, the same conceptual definition of uncertainty as the they articulate: level of unpredictability about future economic conditions adopted in JNV (2015). In contrast to JLN We start from the premise that what matters for eco- (2015), however, RS (2015) based their measure of nomic decision making is not whether particular eco- forecast error on observable forecasts from the Sur- nomic indicators have become more or less variable vey of Professional Forecasters rather than a diffusion or disperse per se, but rather whether the economy index and measure forecast error on the “uncondi- has become more or less predictable; that is, less or tional likelihood” of drawing a given forecast error more uncertain (1178). from the distribution of realized forecast errors for four-quarter-ahead GDP growth between the fourth This definition puts the conceptualization of quarter of 1968 and the first quarter of 2014. Whereas uncertainty JLN (2015) squarely in line with that of JLN (2015) focuses on the expected forecast error Keynes (1937). JLN (2015) make a novel contribution conditional upon prevailing economic conditions, by constructing a metric that attempts to empirically RS (2015) do not condition their measure of forecast measure the extent to which this kind of uncertainty error on prevailing economic conditions. For instance, exists in the world. suppose a 5 percent realized forecast error for GDP is To operationalize this notion of uncertainty for in the 99th percentile of realized forecast errors in the empirical analysis, JLN (2015) employ a diffusion relevant SPF sample. Even if it were not possible to index that captures the expected value of realized know, at the time the forecast was made, that real- forecast error. The index in JLN (2015) addresses the ized forecast error were likely to be large (e.g., it was fact that it is more difficult to have accurate infor- just before the onset of the financial crisis), unlike in mation about the future state of the world in certain the JLN (2015) framework, the RS (2015) index would states of the world than in others. JLN (2015) achieves still be at its peak value.6 this by measuring the expected value of the difference To illustrate the covariance among these three between the realized value of a future economic vari- indices, Figure 2 plots them as well as their average able and its current forecasted value. The JLN (2015) at the quarterly frequency between 1968 and 2011. As index, in other words, captures how much you can one can see, though the data appear to evince a gen- today expect your best forecast for the future state of eral covariance, the correlations are not necessarily the world to diverge from how the future unfolds. For as strong as one may anticipate and exhibit periods instance, suppose the price of the S&P 500 collapsed. of conspicuous divergence. Figure 2 shows that there This plunge in the stock market would likely increase were two distinct episodes between Q4 1968 and Q4 the expected spread between realized future values 2011 for which the average of the index values rose for economic variables and today’s forecast. Such an above 1.65 standard deviations above its series mean.7 event would, therefore, increase uncertainty in the JLN (2015) framework: the expected gap between the 6 It is worth noting that Shoag and Veuger (2013) construct on a novel index of uncertainty at the cross-sectional level, which future state of the world and today’s expectation of opens up the possibility of using cross-sectional as well as tem- that state of the world has widened. JLN (2015) have poral variation. versions of the index with regard to an h-month- 7 The calculations were done as follows: For each individual ahead horizon with values for h months ahead of both series, the value of the index was standardized to zero based on 3 and 12. To construct an index of macroeconomic the series values from Q4 1968 to Q4 2011. To aggregate the

14 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

Figure 2. Indexing the Indices

from the Series Mean –1 Standard Deviations Away –2

–3 1970 1975 1980 1985 1990 1995 2000 2005 2010

Average Value Across Indices BBD (Text-Based) JLN (Conditional Forecast Error) RS (Unconditional Forecast Error)

Source: Authors’ calculations.

One corresponds roughly to the “Volcker disinfla- The relationships among the different indices can tion” and the associated double-dip recession in the be seen with perhaps more clarity in the correlation early 1980s. Evincing a series of dips of its own, the matrix featured in Table 2. index average exceeded +1.65 standard deviations in Q2 1980, Q1 1981, Q2 1981, Q3 1981, and Q1 1982. The Table 2. Index Correlation Matrix second corresponds with the financial crisis and the associated output contraction, exceeding +1.65 stan- BBD JLN RS dard deviations in Q1 2008, Q3 2008, Q4 2008, and BBD 1 0.27 –0.02 Q1 2009. JLN 0.27 1 0.30 RS –0.02 0.30 1 indices, the individual standardized series values for each quarter in the timeframe were averaged together. That series average Source: Authors’ calculations. of standardized values was then standardized to zero based on the values of that series. Statistically, this follows the procedure The RS index, as can be seen, has a flat to nega- outlined in BBD (2015) in the construction of their newspaper index. Q4 1968 to Q4 2011 was the least restrictive range of dates tive correlation with the BBD index, while the other for which it is possible to perform this calculation based on the two pairs of correlations are approximately or slightly data available in the data supplement of RS (2015), the source of below 0.3. The lack of any correlation between the the JNV (2015) and RS (2015) index values. Data were then BBD economic policy index and the RS economic merged with the “historical index” described in BBD (2015), as uncertainty index suggests that they are picking the preferred 1985–2015 specification of the index in BBD (2015) up almost entirely different signals. This –0.02 cor- dates back only until 1985 and therefore would have limited the sample length significantly. relation would be puzzling to the extent that latent

15 POLICY UNCERTAINTY AND THE ECONOMY

Figure 3. Uncertainty: The Dance of Economics and Ideology

5 5

4 4

3 3

2 2

1 1

0 0

–1 –1

–2 –2 as a Percent of GDP

Difference Between the Series –3. –3.

–4 –4 Absolute Value of the Shift in Tax Liability

–5 –5 1970 1975 1980 1985 1990 1995 2000 2005 2010 2013

BBD-JLN Index Spread (Based on Series Standardized to 1 over the Sample Period) Absolute Value of the Shift in Tax Liability as a Percent of GDP

Source: Authors’ calculations.

underlying economic uncertainty drove both EU and code adopted due to the ideological preferences of EPU—if both the BBD and RS indices successfully incumbent presidents rather than as an endogenous extracted signals about the latent underlying factors response to economic conditions (e.g., a tax cut they purport to detect. Meanwhile, the JLN index to decrease the debt burden of future generations overlaps with the BBD index and the RS index to rather than to respond to a recession). Suppose that roughly the same magnitudes. The covariation of the one definition of policy uncertainty is uncertainty BBD and JLN indices, then, would seem like a more that arises from the discretionary conduct of poli- natural point of investigation to seeing when EPU cymakers and that whether to pursue ideologically may be driven by EU and when it may be driven by motivated tax changes is a discretionary choice made other factors. by policymakers. One way to attempt to observe Figure 3 plots the spread between the z-scores of whether ideologically motivated tax increases gen- the BBD and JLN indices, henceforth known as the erate observational consequences in the data would BBD-JLN spread. Given the nature of the two indi- be to examine whether ideologically motivated tax ces, the BBD-JLN spread represents a measure of changes correlate with increases in the spread of the the extent to which EPU that cannot be explained BBD index of EPU over the JLN index of general EU. by EU. Figure 3 also plots a measure of “ideolog- Though imperfect, especially during the tumultu- ically driven” tax changes constructed in Romer ous reign of the Volcker Fed between Q4 1979 and and Romer (2010). The Romer and Romer (2010) Q3 1987, the Romer and Romer (2010) measure of variable captures changes to the US federal tax ideological tax changes seems in Figure 3 to comport

16 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

broadly with what one would expect to observe whereas surging EU drove the spike in EPU during if ideologically motivated tax changes had some the Great Recession (which ended in Q2 2009), the explanatory power for some fraction of the variation persistently high EPU observed in its aftermath can- in economic policy uncertainty that is not attribut- not be attributed to EU. This pattern in the data sug- able to economic uncertainty. Granted, what Romer gests that the many studies examining EPU in the and Romer (2010) classify as ideologically motivated Great Recession and its aftermath would do well to changes are certainly more infrequent than local disaggregate the direct effects of the Great Reces- maxima in BBD-JLN spread. However, it seems likely sion from its aftermath.8 that successfully passed-and-legislated ideologi- Second, there is a visible trend upward over time. cal tax changes are the culmination of a long period To quantify: the BBD-JLN spread was positive during of attempts to pass those changes and that many only 16.3 percent of quarters from 1968 through 1983, attempted ideological tax changes do not show up and a striking 72.3 percent of all quarters from 1984 in the data because they are never successful. Hence through 2011. This would be consistent with the sec- the ideologically motivated tax changes that appear ond of the two explanations for the post-1960 upward in the Romer and Romer (2010) data may be likely drift in the BBD EPU index suggested by Baker et to close in time to other attempts to pass ideolog- al. (2014). While the first stresses the heightened ically motivated tax changes that do not appear in role of government in economic activity, the second the data because they never resulted in successful attributes the upward drift of the index to growing passage. But even such unsuccessful attempts would political polarization and its implications, The first seem likely to nonetheless cause an increase in the hypothesis would seem likely to manifest through the BBD-JLN spread. From this perspective, the poten- economic variables of the sort analyzed in JNV (2015) tial explanatory power of ideologically motivated tax and therefore in the JNV (2015) index, which would changes on variation in the BBD-JLN spread in Fig- have a dampening effect on the BBD-JLN spread. ure 3 becomes more acute. Political polarization, by contrast, would seem more Figure 3 suggests two notable observations. First, likely to manifest through a higher BBD index without the BBD-JLN spread was negative between Q1 2005 a corresponding increase in the JLN index. Hence, the and Q4 2009. This suggests that there was greater upward trend in the BBD-JLN spread supports the sec- economic uncertainty than economic policy uncer- ond notion: that political polarization offers the more tainty per se during this time period. Perhaps, then, plausible of the two explanations of the drift upward economic uncertainty was greater in magnitude than in levels of EPU as measured by the BBD (2015) index, economic policy uncertainty as the US credit boom observable in the United States since about 1960. that preceded the financial crisis reached its peak and as the United States began to experience the 8 This also suggests that, while economic factors may play a first-order economic consequences of the financial causal role in the initiation of a financial crisis, the political crisis that followed in 2008 and 2009 (with excep- effects of the initial crisis in the years following its onset may tion to the one slightly positive value in Q1 2008). offer a separate channel through which financial crises cause The BBD-JLN spread, however, turned positive in unusually distinct contractions in economic activity. Funke, Schularick, and Trebesch (2015) document these political Q1 2010 and reached its peak value for the duration effects, and we explore this possibility in a later section of of the entire series in Q3 2011. This suggests that the paper.

17 V. Tax Policy and Uncertainty: New Approaches

he emergence of the BBD (2015) indices and the records meticulously documented in Romer and Tthe Romer and Romer (2010) narrative account Romer (2009).9 of post-WWII tax changes affords the opportunity As Table 3 shows, when the Romer and Romer for the empirical investigation of the relationship (2009) series is disaggregated to the monthly level, between tax policy and uncertainty. Such an investiga- there is a significant relationship between endoge- tion reveals that there is a statistically significant rela- nous tax changes and the BBD EPU measure. There tionship between tax policy as documented in Romer is, however, no such relationship with regard to exog- and Romer (2010) and uncertainty as expressed in the enous tax changes. BBD (2015) index, though perhaps not a relationship of the sort that many would find intuitive. Table 3. The Effect of Tax Changes on the BBD We investigated this relationship through stan- EPU Index dard ordinary least squares (OLS) regressions. Months before Romer and Romer (2010) distinguish between both tax change Endogenous Exogenous endogenous and exogenous tax policy changes, as well as between tax changes they classify as endoge- 0 –20.13** 3.42 nous because they are intended to respond to a “cur- (8.44) (7.56) rent or planned change in government” spending and 1 –17.38** 7.12 those they classify as endogenous because they are (8.45) (7.55) intended to serve the purpose of “offsetting other influences on economic activity.” Likewise, within 2 –12.22 9.56 the category of exogenous tax changes, they distin- (8.46) (7.55) guish between those that are intended to “[increase] 3 –12.64 –2.56 long-run growth” and those intended to “[reduce] an (8.47) (7.56) inherited budget deficit.” * = significance at 10% level, ** = significance at 5% level Aggregated at the quarterly level, as it is in the Source: Authors’ calculations. original Romer and Romer (2010) publication, there is no statistically significant relationship between the Romer and Romer (2010) measures of tax changes The inclusion of the estimated impacts of the tax and the BBD EPU index measure. But aggregating for change in the first, second, and third months before longer periods can hamper identification by increas- the change has two important interpretations. First, ing noise-to-signal ratios. To overcome this, we used these variables can be interpreted as indications of the Romer and Romer (2009) detailed narrative his- the effects of expected effects, since tax legislation tory of tax changes that serves as the basis for the tax changes analyzed in Romer and Romer (2010) to con- 9 Romer and Romer (2009) is the companion background struct a monthly data series of tax shocks, based on paper to Romer and Romer (2010).

18 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

Table 4. Decomposing the Effects of Tax Changes on EPU

Endogenous Exogenous

Months before Counteract Counteract Future Long-run legislated tax Δgov. Spending other influence generations growth change (n = 20) (n = 10) (n = 14) (n = 23)

0 –24.56** –3.16873 22.20* –9.02 (9.58) (13.52) (11.43) (8.99)

1 –21.63** –0.90 23.78** –4.30 (9.59) (13.52) (11.42) (8.99)

2 –21.50** 11.78 28.16** –3.63 (9.59) (13.51) (11.41) (8.99)

3 –22.73** 4.88 10.68 –13.66 (9.59) (13.52) (11.45) (8.98)

* = significance at 10% level, ** = significance at 5% level Source: Authors’ calculations.

seems likely to have been discussed in the months trending downward in point estimate until the month leading up to the one in which they were signed of its enactment.10 These results would seem con- into law. Second, these variables can be interpreted sistent with what one would expect to observe if as placebo regressions that test whether the effect there were uncertainty about whether Congress and attributed to the tax change can be attributed to the the executive branch could reach bargains on issues economic environment in which that change was that, such as tax revenue increases to decrease a likely to occur. As would be expected, these “placebo” long-run debt burden, may be economically benefi- regressions suggest that any attempt to estimate the cial in the long run but politically costly in the short effects of what Romer and Romer (2010) identify as run. And if one imagines that political actors have endogenous tax regressions would likely be detecting only limited quantities of “political capital” to spend effects attributable to the economic environment, as on a given issue with economic consequences in the the endogenous tax cuts show a significant effect in long run, such as the long-run debt burden, then the the “placebo” month before they occurred. arrival of attempts by politicians to pass such legis- Distinguishing between subcategories within the lation in the short run raises substantial uncertainty exogenous and exogenous categories, as evinced by about the future trajectory of economic policy. After Table 4, reveals yet more significant patterns between all, if the attempt to pass legislation fails, then future tax policy and uncertainty. deficit-reducing tax reforms would seem to become In aggregate, the data suggest that political mech- less likely. Given that information about crucial leg- anisms may play a prominent role in mediating the islative bargaining constraints would likely begin to effects of policy uncertainty. On the exogenous side, the effects of an exogenous tax cut performed in the interest of decreasing the 10 Note that the data encode a series of Social Security reform acts of the early 1970s as meeting all four of these categories, but debt burden of significant generations is largest and the results do not change depending on whether or not these are statistically significant two months before its passage, included.

19 POLICY UNCERTAINTY AND THE ECONOMY

emerge within a few months of the legislation’s pas- between countercyclical tax legislation and EPU. If sage, the surge in uncertainty beginning two months government spending pushes growth toward its nor- before the passage of deficit-reducing legislation mal levels even in the absence of government action, seems intuitive. and is large in magnitude relative to any expected The finding of no significance for tax cuts asso- discretionary stimulus, then it seems plausible to ciated with an ideological desire for higher long-run suppose that the passage of a discretionary counter- growth rates may reflect the asymmetry between cyclical stimulus through legislation would have a the political popularity of tax hikes and tax cuts. If relatively muted effect on the state of the economy.11 tax cuts are politically more popular than tax hikes, Alternatively, it is possible that the passage of coun- it seems likely that any future tax increases would tercyclical legislation during business cycle troughs be advertised as a campaign issue. Conditional upon is expected to occur and therefore has nil impact on a given election outcome, then, the passage of a tax EPU when it occurs, as it would in such a case present cut may be more predictable than the passage of a tax little new information about the current and future hike, as voters would seem less likely to have infor- path of policy. mation about a possible tax hike than a possible The significant and negative effect of legislation tax decrease. In fact, Auerbach and Hassett (2006) concerning endogenous tax changes enacted to coun- demonstrate that the US stock market priced in the teract changes in government spending on EPU, how- implications of 2003 Dividend Tax Cuts, classified in ever, suggests that legislative action to offset the effect Romer and Romer (2009) as motivated by an ideolog- of other changes in government spending may con- ical desire to increase long-run growth, as the proba- tain information about the current and future path bility of a Bush victory fluctuated in betting markets. of economic policy. This may reflect the concern that Due to this political asymmetry and the asymmetry in the political constraints would preclude legislation to the incentives it creates for politicians to divulge this offset, say, the effect of expiring legislation, render- information while campaigning, then, it would seem ing the inability of policymakers to act a source of to make sense that the announcement of a legislative uncertainty as political gridlock results in fiscal policy intention to increase taxes would constitute more taking on an unpredictable path. In a legislative sys- a surprise than an announcement to decrease taxes tem as institutionally prone to gridlock as the United and therefore have more an association between EPU States Congress, it would not be hard to imagine this than would an announcement to decrease taxes. state of inaction becoming acutely contractionary as On the endogenous side, the results again finger the expiration of legislation, without any countervail- political mechanisms. Legislation passed to counter- ing legislation, could result in a sustained decrease in act a business cycle downturn would tend to fall into government spending desired by only a minority of the “to counteract other influence [besides a current Congress.12 Hence, the release of information about or future change in government spending] on eco- the presence of the political resolve to pass legislation nomic activity” category, in which there are no signif- to counteract other changes in government spend- icant results. This finding of no effect contrasts with ing may present valuable information that decreases the plausible intuition that the passage of countercy- uncertainty about the future of economic policy. clical legislation may decrease economic uncertainty As with the case of the exogenous tax hikes to by pushing growth rates back toward trend levels when bad states of nature emerge (e.g., by generating 11 It is worth noting that the Romer and Romer (2010) sample ends at the end of 2007 and does not have data on the impact of a mean-reverting effect). The existence of “automatic the American Recovery and Reinvestment Act, the large discre- stabilizers” that increase government spending with- tionary package enacted in response to the Great Recession. out any government action as economic conditions 12 The “pivot points”-based model of legislative gridlock in deteriorate constitutes one plausible explanation McCarty, Pool, and Rosenthal (2015) provides a formal frame- for the possible absence of a significant association work that seems consistent with this intuition.

20 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

decrease the debt burden on future generations, then, Assessing the relationship between specific items of the mechanism between the associations of EPU with legislation, such as tax changes, and EPU remains an tax changes endogenous to other changes in govern- intriguing area to be explored in future research. ment spending seems likely to be political in nature.

21 VI. In Search of an Escape from Endogeneity

ever far from its long history of identification to be difficult to dismiss out of hand. It therefore Nissues, the literature has long recognized that stands to reason that the financial crisis in the United pervasive endogeneity issues beguile attempts to States may have caused both a decline in corporate discern the effects of uncertainty (e.g., Rodrik 1991). investment through channels unmediated by politi- However, the literature has not yet successfully over- cal polarization (e.g., credit market disruptions) and, come these limitations. through separate causal channels, an increase in polit- A notable attempt at isolating the causal effect of ical polarization.14 economic policy uncertainty comes from the instru- This suggests that the instrumental variable identi- mental variable strategy in Gulen and Ion (2015). fication strategy in Gulen and Ion (2015) suffers from They choose a common metric of political polariza- a simultaneous determination problem: the instru- tion based on legislative behavior, a DW-NOMINATE ment (political polarization) and the outcome of score, as their instrument for policy uncertainty. interest (corporate investment) are simultaneously However, given that the experience of the US finan- determined by an omitted variable (an output con- cial crisis and its aftermath figures prominently in traction attributable to financial distress). As a result, their sample period, the recent research of Funke, the validity of their instrumental variable strategy Schularick, and Trebesch (2015) on 140 years of finan- appears to be undermined. cial crises in 20 advanced economies undermines BBD (2015) likewise attempt to isolate the effect their identification strategy.13 Funke, Schularick, of EPU by introducing a text-based measure of EU as and Trebesch (2015) demonstrate that financial cri- a control for the influence of EU on EPU. However, ses have substantial effects on political polarization the results generated by the core regression specifica- that are distinct from the effects of nonfinancial out- tions in BBD (2015) do not leave one persuaded that put contractions. The estimated magnitude of these EPU has an effect on economic activity distinct from effects are large: on average, what the authors call any effect due to EU. Specifically, in Table 2 of BBD “extreme right-wing parties” gain up to 30 percent (2015), four regressions obtain statistically signifi- more of the popular vote during the five years follow- cant results for both EU and EPU. But the coefficients ing a financial crisis. Though the partisan hue of the for EU and EPU, while statistically significant, obtain increase in political polarization since 1960 remains opposite signs. These results, then, appear more as an up for debate, this characterization of the post-WWII empirical puzzle to be solved than as a solution to the United States seems at least sufficiently plausible identification the methodology purports to overcome.

13 It is worth noting that the findings of Funke, Schularick, and 14 The surge in the BBD-JLN spread in the years following the Trebesch (2015) use a substantially larger sample than, but have Great Recession, visible in Figure 3, also becomes interesting results consistent with, those of Mian, Sufi, and Trebbi (2012). from this perspective.

22 VII. Puzzles in the Election Cycle Literature

nother source of policy uncertainty stems from One such possible explanation emerges if one Athe uncertainty generated by national elections. considers that increases in polarization could be There is a voluminous literature that documents the considered “second-order shocks” (e.g., shocks to effects of political election cycles on financial markets. the variance rather than the level) that increase the However, to the extent that the timing of elections are variance but preserve the mean of the cross sec- known, the influence of these cycles presents a puzzle tion of securities market returns. The influence of as to what the shock causing the perturbations of asset election outcomes on the distribution of US stock prices could plausibly be. market returns, after all, is well documented in the The rich literature documents that public secu- literature. A key set of findings comes from the novel rity markets exhibit higher volatility in close prox- identification strategy for measuring firm-level imity to US elections. The timing of presidential and exposure to fluctuations in government spending gubernatorial elections is known well in advance. If based on Bureau of Economic Analysis input-output markets are efficient, therefore, market participants data in Belo, Gala, and Li (2013). Consistent with ex will have factored in the timing of future elections, ante intuition, they find that firms with more (less) and their occurrence should have no influence on exposure to government programs significantly out- pricing activity. Yet, Li and Born (2006) find that perform under Democratic (Republican) presiden- US equity markets become more volatile as pres- cies. If higher political polarization implies that the idential elections approach. In a pivot to the state expected value of government spending is higher level, Gao and Qi (2012) find that municipal bonds during Democratic presidential regimes but lower floated by state governments immediately before an during Republican presidential regimes, then this election pay a premium of six to eight basis points suggests that the share of the variation in the cross due to this electoral proximity. It may be tempting section of US stock market returns explained by to suppose that election timing may influence the the party of the incumbent president will be higher pricing of financial assets through the influence on when political polarization is higher. Note, however, real economic activity documented by the likes of that an increase in polarization would seem likely to Jens (2013), who estimates that gubernatorial elec- have no effect on the mean of the expected return on tions reduce state-level investment by between the stock market as a whole even as it increased the 5 percent and 15 percent. But real economic effects variance of stock market returns (i.e., it would be a that are themselves the predictable consequences “mean-preserving spread”). of the occurrence of an election should be priced in Put differently, to the extent that higher political by rational market participants. This would seem to polarization increases the magnitude of the fluctua- suggest either that there are systematic violations of tions of government spending as the party of the pres- the efficient market hypothesis or that the effects of idential incumbent fluctuates, the secular increase in elections on asset prices are mediated through fac- political polarization observed since 1960 would be tors other than their mere occurrence. expected to increase the cross-sectional variation in

23 POLICY UNCERTAINTY AND THE ECONOMY

stock returns. If the shocks to markets from recent this type of first-order shock would not be present in US elections have been “polarization shocks” wherein political systems, such as the United States, with reg- the revealed platforms of the candidates are more ularly scheduled elections. extreme than had been anticipated, then this would Many studies, however, do not distinguish between constitute a second-order shock to stock market electoral systems where elections occur according to returns that would explain the finding of increased a fixed schedule and those where the occurrence of stock market volatility documented in Li and Born an election is a function of prevailing political con- (2006). Granted, given that it seems likely that inves- ditions. For instance, Bialkowski, Gottschalk, and tors would expect a higher level of expected return in Wisniweski (2008) analyze a panel of 130 elections exchange for tolerating a higher variance, the perpet- in 27 OECD countries between 1983 and 2004. This ual difficulty of disentangling first- fromsecond-order sample includes countries in which national elections shocks here seems particularly acute. But to the occur at regularly defined intervals (e.g., the United extent that the effects of uncertainty on asset prices States) and in which the timing of national elections manifest through a widening of the cross-sectional remains subject to the political circumstances of the dispersion of returns attributable to political polar- given moment (e.g., Israel). The analysis of 129 elec- ization, the shock would seem to be second-order tions across 33 countries in Pantzalis, Stangeland, and (e.g., to the variance), and the apparent first-order Turtle (2000) between 1974 and 1995 likewise aggre- shock to the level of returns would be epiphenomenal gates countries with both regularly scheduled national (i.e., a phenomenon that emerges as the by-product of elections and those in which the timing of elections a more-direct effect). can constitute a surprise. These studies, then, cannot In governmental systems where the timing of elec- differentiate between effects arising from the “shock” tions occurs due to political conditions (e.g., a vote of of the elections occurrence and shocks arising from no confidence in the legislature), however, the height- the content of any information revealed during the ened volatility and discounted prices in the lead-up to course of the elections occurrence (e.g., candidates an election is easier to understand. Many studies have committing to extreme policies). This constitutes a associated the occurrence of elections with declines in shortcoming that obscures evidence that could plausi- real investment activity. In addition to the Jens (2013) bly help to discriminate among the many mechanisms state-level study, consistent with the irreversibility of through which elections could generate uncertainty investment playing a crucial role in lifting the effects effects that influence economic activity. The litera- of uncertainty sired by elections on economic activity, ture would do well to address this distinction, if only Julio and Yook (2013) find that flows ofcross-border through the inclusion of dummy variables that cap- foreign direct investment, but not portfolio flows, are ture electoral dynamics in regression specifications. sensitive to proximity to the timing of foreign elec- Another perspective comes from the study of the tions. Hence, it is only logical that countries with pricing of equity index options around national elec- political systems where the timing of an election is tions and global summits by Kelly, Pastor, and Vero- itself a variable (e.g., Israel) have elections that influ- nesi (forthcoming). They find that “near the money” ence the pricing of financial assets. But these are options that straddle national elections or global first-order shocks to the level of the expected returns summits are more expensive than options that are on securities rather than the second-order shocks otherwise more or less identical. Consistent with that the literature on uncertainty focuses on. After the implications of the theoretical models that moti- all, if the occurrence of an election will depress real vate their empirical analysis, they find that this pre- economic activity by increasing uncertainty, then an mium increases either when economic conditions effect of an unexpected election would be to reduce are bad or when the data leading up to the election expected future levels of real economic activity and indicate a close election. These results seem to have therefore the expected rates of return on assets. But an intuitive explanation: equity index options offer

24 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

Figure 4. Policy Uncertainty and Asset Pricing Through the Election Cycle, January 1985–March 2015

30%

25%

20%

15%

10%

0% –24 –20 –16 –12 –8 –4 048121620

ar-Over-Year Change –5% Ye –10% (Rolling Three-Month Average) –15%

–20% Months Away from a Presidential Election Month

Economic Policy Uncertainty Index (from Baker, Bloom, and Davis) P/E Ratio of the S&P 500 Moody's Corporate BAA Debt, 10-Year Treasury Yield Spread

Source: Authors’ calculations. a form of portfolio insurance against the risks of investor in exchange for the claim on the firm’s earn- adverse election or summit outcomes, and the price ings that a share of its stock represents. A relatively of portfolio insurance rises when the period of cov- high P/E ratio serves as an indication that the firm can erage includes a national election or global sum- raise capital at a relatively low cost: When the P/E is mit. A further intriguing line of thought comes from higher, it means the market perceives the equity to be their finding that some of the options pricing effect less risky. The spread between the yield on Moody’s is attributable to an increase in the market pricing of BAA-rated debt and the 10-year Treasury yield is an “tail risk,” the risk of a substantial price decline. This alternative measure of the risk premium. It indicates would seem to suggest their findings dovetail with the how much market participants demand in exchange large macro-finance literature on rare disasters and for holding bonds that, according to Moody’s, come asset prices, perhaps the most voluminous of which with “moderate credit risk” and have “certain specu- addresses the equity risk premium (e.g., Barro 2006). lative characteristics.” A larger spread indicates that The link between political and policy uncertainty market participants are charging businesses more for is clearly an important area for future research. We buying their bonds instead of the “risk-free” bonds note here that the macro-level correlations in the data of the US government. Figure 4 plots these measures are highly suggestive. The price-to-earnings ratio of against the BBD measure of policy uncertainty. As the the S&P 500 measures the price a firm can charge an chart shows, stock valuations and debt spreads both

25 POLICY UNCERTAINTY AND THE ECONOMY

Figure 5. 12-Month-Ahead Odds of Recession Entrance

35.0% 35

30 29.4%

20 18.8%

15 14.3% Within the Next Year 10

Percent of Months with a Recession 5

0 December 1854–May 2016 January 1946–May 2016

Presidential Election Month Any Month

Source: Authors’ calculations.

respond adversely to the increases in uncertainty that month. And the magnitude of the ratio of the con- seem to come with the election cycle. ditional to the unconditional odds does not depend Meanwhile, as Figure 5 shows, the probability of on whether the sample is the full period spanning a recession occurring within the next 12 months is 1854 through May 2016 or limited to the post-WWII roughly twice as high in the US during the month of a United States. presidential election relative to other months. That is, The perspective from the frequency with which Figure 5 shows the probability of entering a recession recessions in the US follow presidential elections within 12 months after a presidential election month leaves a similar impression. In a country with a (e.g., between November of an election year and the four-year election cycle, 25 percent of all months are following October) and compares it with the same within 12 months of a presidential election. Under the set of odds for all months, which can be thought of null hypothesis that there is no relationship between as the placebo. From a Bayesian perspective, based on presidential elections and the onset of recessions, this analysis, a rational agent would multiply his prior one would therefore expect 25 percent of recessions “unconditional” estimate for the odds of a recession to be within 12 months of an election. Yet, as Figure occurring in the next 12 months by a factor of roughly 6 shows, 41.2 percent of recessions between Decem- two in order to ascertain the odds of a recession ber 1854 and May 2016 and 45.5 percent of recessions occurring in the next 12 months “conditional” upon between January 1946 and May 2016 began within 12 the knowledge that the current month is an election months of a presidential election.

26 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

Figure 6. Recession Starts Within 12 Months of a Presidential Election

50 45.5% 45 41.2% 40

30 25.0% 25.0% 25

of a Presidential Election Month 10

5 Percent of Recession Starts Within 12 Months 0 December 1854–May 2016 January 1946–May 2016

Observed Expected Under Null Hypothesis

Source: Authors’ calculations.

All in all, the literature on the effects of uncer- parsimonious explanation for the otherwise puzzling tainty and elections offers intriguing results but few results on the effects of election cycles on asset prices, theories that seem capable of synthesizing the results disentangling the causal channels at play seems likely documented in the literature as a whole. Though an to be a relevant area of research going forward. increase in political polarization seems like the most

27 VIII. Conclusion

learly, the literature on the economics of uncer- elections may be a much bigger factor than has been Ctainty has evolved in many different directions appreciated by the macroeconomic empirical litera- since the 1990s. The establishment of a synthesis of ture to date. Many questions remain, but the fact that these many different strands is certainly an ongoing the most pressing research questions are so precisely enterprise, but our descriptive data analysis presented focused is perhaps the best metric of progress. here suggests that the uncertainty associated with

28 About the Authors

Kevin A. Hassett is director of research for domestic Joseph W. Sullivan is a senior research associate in policy and State Farm James Q. Wilson Chair at the economic policy studies at the American Enterprise American Enterprise Institute. Institute.

29 References

Abel, Andrew B. 1983. “Optimal Investment Under Uncertainty.” American Economic Review 73 (1): 228–33. ———. 1990. “Consumption and Investment,” in Handbook of Monetary Economics, edited by Benjamin M. Fried- man and Frank H. Hahn. Vol. 2: 725–78. Amsterdam: North-Holland. Altug, Sumru, Fanny S. Demers, and Michel Demers. 2009. “The Investment Tax Credit and Irreversible Invest- ment.” Journal of Macroeconomics 31, no. 4 (December): 509–22. Alvarez, Luis H. R., Vesa Kanniainen, and Jan Södersten. 1998. “Tax Policy Uncertainty and Corporate Invest- ment: A Theory of Tax-Induced Investment Spurts.” Journal of Public Economics 69, no. 1: 17–48. Arrow, K. J. 1968. “Optimal Capital Policy and Irreversible Investment,” in Value, Capital, and Growth, edited by J. N. Wolfe, 1–20. Chicago: Aldine. Auerbach, Alan J. 1989. “Tax Reform and Adjustment Costs: The Impact on Investment and Market Value,” Inter- national Economic Review 30 (November): 939–62. Auerbach, A. J., and Kevin Hassett. 1991. “Recent U.S. Investment Behavior and the Tax Reform Act of 1986: A Disaggregate View,” Carnegie-Rochester Conference Series on Public Policy 35: 185–215. ———. 1992. “Tax Policy and Business Fixed Investment in the United States,” Journal of Public Economics 47 (March): 141–70. ———. 2002. “Fiscal Policy and Uncertainty.” International Finance 5, no. 2 (Summer): 229–49. ———. 2006. “Dividend Taxes and Firm Valuation: New Evidence.” American Economic Review 96, no. 2 (May): 119–23. Auerbach, Alan J., and James R. Hines Jr. 1988. “Investment Tax Incentives and Frequent Tax Reforms,” American Economic Review 78, no. 2 (May): 211–16. Baker, Scott R., Nicholas Bloom, Brandice Canes-Wrone, Steven J. Davis, and Jonathan Rodden. 2014. “Why Has US Policy Uncertainty Risen Since 1960?” American Economic Review 104, no. 5 (May): 56–60. Belo, Frederico, Vito D. Gala, and Jun Li. 2013. “Government Spending, Political Cycles, and the Cross Section of Stock Returns.” Journal of Financial Economics 107, no. 2 (February): 305–24. Bernanke, Ben S. 1983. “Irreversibility, Uncertainty, and Cyclical Investment, Quarterly Journal of Economics, 98: 85–106. ———. 2004. “The Great Moderation: Remarks by Governor Ben S. Bernanke at the Meetings of the Eastern Eco- nomic Association.” Washington, DC, February 20. Białkowski, Jędrzej, Katrin Gottschalk, and Tomasz Piotr Wisniewski. 2008. “Stock Market Volatility Around National Elections.” Journal of Banking & Finance 32, no. 9 (September): 1941–53. Bloom, Nicholas. 2009. “The Impact of Uncertainty Shocks.” Econometrica 77, no. 3 (May): 623–85. ———. 2014. “Fluctuations in Uncertainty.” Journal of Economic Perspectives 28, no. 2 (Spring): 153–76. Bloom, Nick, Stephen Bond, and John Van Reenen. 2007. “Uncertainty and Investment Dynamics.” Review of Eco- nomic Studies 74, no. 2 (April): 391–415. Boehm, Hjalmar, and Michael Funke. 2000. “Optimal Investment Strategies Under Demand and Tax Policy Uncertainty,” CESifo Working Paper, No. 31. Booth, James R., and Lena Chua Booth. 2003. “Is Presidential Cycle in Security Returns Merely a Reflection of Business Conditions?” Review of Financial Economics 12, no. 2: 131–59.

30 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

Born, Benjamin, and Johannes Pfeifer. 2014. “Risk Matters: The Real Effects of Volatility Shocks: Comment.” American Economic Review, 104, no. 12 (December): 4231–39. Brogaard, Jonathan, and Andrew Detzel. 2015. “The Asset-Pricing Implications of Government Economic Policy Uncertainty.” Management Science 61, no. 1 (January): 3–18. Caballero, Ricardo J. 1999. “Aggregate Investment.” In Handbook of Macroeconomics, edited by John B. Taylor and Michael Woodford. Vol. 1: 813–62. (Amsterdam: North-Holland). Chetty, Raj. 2007. “Interest Rates, Irreversibility, and Backward-Bending Investment.” Review of Economic Studies 74, no. 1 (January): 67–91. Croce, Mariano M., Thien T. Nguyen, and Lukas Schmid. 2012. “The Market Price of Fiscal Uncertainty.” Journal of Monetary Economics 59, no. 5 (July): 401–16. Cummins, Jason, Kevin A. Hassett and R. Glenn Hubbard. 1994. “A Reconsideration of Investment Behavior Using Tax Reforms as Natural Experiments,” Brookings Papers on Economic Activity 2: 1–59. ———. 1995. “Have Tax Reforms Affected Investment?” InTax Policy and the Economy, edited by James M. Poterba. Vol. 9: 131–49. Cambridge: MIT Press. ———. 1996. “Tax Reforms and Investment: A Cross-Country Comparison,” Journal of Public Economics 62, nos. 1–2 (October): 237–73. Durnev, Art. 2010. “The Real Effects of Political Uncertainty: Elections and Investment Sensitivity to Stock Prices.” Paris December 2010 Finance Meeting EUROFIDAI-AFFI. http://papers.ssrn.com/sol3/papers. cfm?abstract_id=1695382. Ellsberg, Daniel. 1961. “Risk, Ambiguity, and the Savage Axioms.” Quarterly Journal of Economics 75, no. 4 (Novem- ber): 643–69. Ferguson, Thomas, and Hans-Joachim Voth. 2008. “Betting on Hitler—The Value of Political Connections in Nazi Germany.” Quarterly Journal of Economics 123, no. 1 (February): 101–37. Fernández-Villaverde, Jesus, Pablo Guerron-Quintana, Juan Rubio-Ramirez, and Martin Uribe. 2011. “Risk Mat- ters: The Real Effects of Volatility Shocks.” American Economic Review 101, no. 6 (October): 2530–61. Fernández-Villaverde, Jesus, Pablo Guerron-Quintana, Keith Keuster, and Juan Rubio-Ramirez. 2015. “Fiscal Vol- atility Shocks and Economic Activity.” American Economic Review 105, no. 11 (November): 3352–84. Funke, Manuel, Moritz Schularick, and Christoph Trebesch. 2015. “Going to Extremes: Politics After Financial Crises, 1870–2014,” Centre for Economic Policy Research, Discussion Paper No. 10884, October. Füss, Roland, and Michael M. Bechtel. 2008. “Partisan Politics and Stock Market Performance: The Effect of Expected Government Partisanship on Stock Returns in the 2002 German Federal Election.” Public Choice 135, nos. 3/4 (June): 131–50. Gao, Pengjie, and Yaxuan Qi. 2012. “Political Uncertainty and Public Financing Costs: Evidence from US Munic- ipal Bond Markets.” http://extranet.sioe.org/uploads/isnie2012/qi_gao.pdf. Geithner, Timothy. 2014. Stress Test: Reflections on Financial Crises. Random House: New York. Gemmill, Gordon. 1992. “Political Risk and Market Efficiency: Tests Based in British Stock and Options Markets in the 1987 Election.” Journal of Banking & Finance 16, no. 1 (January): 211–31. Gulen, Huseyin, and Mihai Ion. 2015. “Policy Uncertainty and Corporate Investment.” Review of Financial Studies (September 3). Hall, Robert E., and Dale W. Jorgenson. 1967. “Tax Policy and Investment Behavior,” American Economic Review 57 (June): 391–414. Hansen, Lars Peter. 2014. “Uncertainty Outside and Inside Economic Models.” National Bureau of Economic Research Working Paper 20394. http://www.nber.org/papers/w20394.pdf. Hartman, Richard. 1972. “The Effects of Price and Cost Uncertainty on Investment.” Journal of Economic Theory 5, no. 2 (October): 258–66.

31 POLICY UNCERTAINTY AND THE ECONOMY

Hassett, Kevin A., and Gilbert E. Metcalf. 1999. “Investment with Uncertain Tax Policy: Does Random Tax Policy Discourage Investment?” Economic Journal 109, no. 457 (July): 372–93. Hassett, Kevin A., and R. Glenn Hubbard. 2002. “Tax Policy and Business Investment.” In Handbook of Public Economics 2: 1293–343. Hayashi, F. 1982. “Tobin’s Marginal q and Average q: A Neoclassical Interpretation.” Econometrica 50, no. 1 (Jan- uary): 213–24. Jens, Candace. 2013. “Political Uncertainty and Investment: Causal Evidence from U.S. Gubernatorial Elections.” http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2176855. Jorgenson, Dale W. 1963. “Capital Theory and Investment Behavior.” American Economic Review. 53, no. 2 (May): 247–59. Julio, Brandon, and Youngsuk Yook. 2013. “Policy Uncertainty, Irreversibility, and Cross-Border Flows of Capi- tal.” http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2024612. ———. 2012. “Political Uncertainty and Corporate Investment Cycles.” Journal of Finance 67, no. 1 (February): 45–83. Jurado, Kyle, Sydney C. Ludvigson, and Serena Ng. “Measuring Uncertainty.” 2015. American Economic Review 105, no. 3 (March): 1177–216. Kang, Wensheng, Kiseok Lee, and Ronald A. Ratti. 2014. “Economic Policy Uncertainty and Firm-Level Invest- ment.” Journal of Macroeconomics 39, part A (March): 42–53. Kelly, Bryan, Lubos Pastor, and Pietro Veronesi. Forthcoming. “The Price of Political Uncertainty: Theory and Evidence from the Option Market.” Journal of Finance. Keynes, John Maynard. 1937. “The General Theory of Employment.” Quarterly Journal of Economics 51, no. 2 (Feb- ruary): 209–23. ———. 1921. A Treatise on Probability. London: Macmillan. Accessed through Project Gutenberg. http://www. gutenberg.org/files/32625/32625-pdf.pdf. Kim, Chansog Francis, Christos Pantzalis, and Jung Chul Park. 2012. “Political Geography and Stock Returns: The Value and Risk Implications of Proximity to Political Power.” Journal of Financial Economics 106, no. 1 (October): 196–228. Knight, Frank H. 1921. Risk, Uncertainty, and Profit. Boston: Hart, Schaffner & Marx; Houghton Mifflin Company. Laubach, Thomas. 2009. “New Evidence on the Interest Rate Effects of Budget Deficits and Debt.” Journal of the European Economic Association 7, no. 4 (June): 858–85. Li, Jinliang, and Jeffery A. Born. 2006. “Presidential Election Uncertainty and Common Stock Returns in the United States.” Journal of Financial Research 29, no. 4 (Winter): 609–22. Liu, Jun, Jun Pan, and Tan Wang. 2005. “An Equilibrium Model of Rare-Event Premia and Its Implication for Option Smirks.” Review of Financial Studies 18, no. 1 (Spring): 131–64. McCarty, Nolan, Keith T. Poole, and Howard Rosenthal. 2006. Polarized America: The Dance of Ideology and Unequal Riches. Vol. 5. Cambridge, MA: MIT Press. Metcalf, Gilbert E., and Kevin A. Hassett. 1995. “Investment Under Alternative Return Assumptions: Comparing Random Walks and Mean Reversion.” Journal of Economic Dynamics and Control 19, no. 8 (November): 1471–88. Mian, Atif R., Amir Sufi, and Francesco Trebbi. 2012. “Resolving Debt Overhang: Political Constraints in the Aftermath of Financial Crises.” National Bureau of Economic Research, Working Paper No. 17831. Niemann, Rainer. 2004. “Tax Rate Uncertainty, Investment Decisions, and Tax Neutrality.” International Tax and Public Finance 11, no. 3 (May): 265–81. Nishide, Katsumasa, and Ernesto Kazuhiro Nomi. 2009. “Regime Uncertainty and Optimal Investment Timing.” Journal of Economic Dynamics and Control 33, no. 10 (October): 1796–1807.

32 KEVIN A. HASSETT AND JOSEPH W. SULLIVAN

Pantzalis, Christos, David A. Stangeland, and Harry J. Turtle. 2000. “Political Elections and the Resolution of Uncertainty: The International Evidence.” Journal of Banking & Finance 24, no. 10 (October 1): 1575–604. Pastor, Lubos, and Pietro Veronesi. 2012. “Uncertainty About Government Policy and Stock Prices.” Journal of Finance 67, no. 4 (August): 1219–64. Pastor, Lubos, and Pietro Veronesi. 2013. “Political Uncertainty and Risk Premia.” Journal of Financial Economics 110, no. 3 (December): 520–45. Pawlina, Grzegorz, and Peter M. Kort. 2005. “Investment Under Uncertainty and Policy Change.” Journal of Eco- nomic Dynamics and Control 29, no. 7 (July): 1193–209. Pindyck, Robert S. 1988. “Irreversible Investment, Capacity Choice, and the Value of the Firm.” American Eco- nomic Review 78, no. 5 (December): 969–85. Rodrik, Dani. 1991. “Policy Uncertainty and Private Investment in Developing Countries.” Journal of Development Economics 36, no. 2 (January): 229–42. Romer, Christina D., and David H. Romer. 2009. “A Narrative Analysis of Postwar Tax Changes.” http://www.aea- web.org//articles.php?doi=10.1257/aer.100.3.763. ———. 2010. “The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks.” American Economic Review 100, no. 3 (June): 763–801. Rossi, Barbara, and Tatevik Sekhposyan. 2015. “Macroeconomic Uncertainty Indices Based on Nowcast and Fore- cast Error Distributions.” American Economic Review 105, no. 5 (May): 650–55. Rothschild, Michael, and Joseph Stiglitz. 1976. “Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information.” Quarterly Journal of Economics 90, no. 4 (November): 629–49. Santa-Clara, Pedro, and Rossen Valkanov. 2003. “The Presidential Puzzle: Political Cycles and the Stock Market.” Journal of Finance 58, no. 5 (October): 1841–72. Shoag, Daniel, and Stan Veuger. 2013. “Uncertainty and the Geography of the Great Recession.” AEI Economics Working Paper 2013-05. Sialm, Clemens. 2006. “Stochastic Taxation and Asset Pricing in Dynamic General Equilibrium.” Journal of Eco- nomic Dynamics and Control 30, no. 3: 511–40. Theil, Henri. 1967. Economics and Information Theory. Amsterdam: North Holland Press. Tobin, James. 1969. “A General Equilibrium Approach to Monetary Theory.” Journal of Money, Credit, and Banking 1, no. 1 (February):15–29. Ulrich, Maxim. 2013. “How Does the Bond Market Perceive Government Interventions?” Columbia Business School Research Paper No. 12/42. Zeckhauser, Richard. 2006. “Investing in the Unknown and Unknowable.” Capitalism and Society 1, no. 2 (August).