Policy uncertainty and cash dynamics

• Published date: 01 June 2022
• Author: Daniel Tut
• Date: 01 June 2022
• DOI: http://doi.org/10.1111/jfir.12279

Received: 7 May 2021

|

Accepted: 23 March 2022

DOI: 10.1111/jfir.12279

ORIGINAL ARTICLE

Policy uncertainty and cash dynamics

Daniel Tut

Department of Finance, Ted Rogers School of

Management, Ryerson University, Toronto,

Canada

Correspondence

Daniel Tut, Department of Finance, Ted

Rogers School of Management, Ryerson

University, 55 Dundas St. W, Toronto, ON

2C3, Canada.

Email: dtut@ryerson.ca

Abstract

Why and when do firms deviate from target cash? And why

do we observe imperfect adjustment of cash? I postulate

and provide evidence that policy uncertainty induces

financing frictions and adjustment costs, which decelerate

the speed of adjustment (SOA) of cash toward target. I find

that the effects of policy uncertainty on SOA are higher for

firms that operate below target cash than for firms that

operate above target cash. The results suggest that under

policy uncertainty shocks, firms deviate from target cash as

the expected benefit of deviation is greater than the

expected value of approaching the target.

JEL CLASSIFICATION

G30, G31, G32

1|INTRODUCTION

Why do weobserve imperfect adjustment of cash?And what is the roleof adjustment costsin cash‐holdingsdecisions?

What are the sources of these adjustment costs?Although the literature(Dittmar & Duchin, 2011; Jiang & Lie, 2016)

has documented the slow speed of adjustment (SOA) of cash, there is very little empirical work on conditions under

which firms may optimally deviate from target cash. In this article, I exploit one potential condition and source of

adjustmentcosts, namely, policy‐related uncertainty. The goal of this article is to fill an importantgap in the literature

by establishing a consistentlink between uncertainty, SOA,and cash holdings. In theprocess I evaluate the jointeffects

of policy‐uncertainty‐induced adjustment costs and financing frictions on the SOA toward target cash.

Policy‐related uncertainty induces financing frictions. That is, uncertainty creates a wedge between the benefit

of current‐period liquid assets and costly external finance in future states. These financing frictions lead to an

increase in adjustment costs,

1

which invariably affect the frequency with which firms rebalance cash holdings.

J Financ Res. 2022;45:422–444.422

|

wileyonlinelibrary.com/journal/JFIR

© 2022 The Southern Finance Association and the Southwestern Finance Association.

1

See Baker et al. (2016), Pastor and Veronesi (2012,2013), and Gungoraydinoglu et al. (2017) for a discussion of the real effects of policy uncertainty.

Intuitively, I expect that policy‐uncertainty‐induced adjustment costs slow down the SOA of cash and that such

costs are higher for firms that operate below target cash than for firms that operate above target cash. Specifically,

because of costly external finance in future states, firms that operate below target cash have a strong incentive to

increase cash holdings. Firms that operate above target cash tend to reduce investment because of precautionary

delays. Consistent with this hypothesis, my results suggest there is an inverse relation between policy uncertainty

and SOA of cash. Additionally, as policy uncertainty heightens, firms that operate above target cash tend to

decelerate SOA whereas firms that operate below target cash tend to accelerate SOA.

In this study, I focus on the effects of policy uncertainty shocks on the SOA of cash toward target. I first

document that the SOA of cash is imperfect and then examine the effects of policy‐uncertainty‐induced financing

frictions and adjustment costs on SOA. To measure the SOA of cash, I follow the two‐stage procedure outlined in

Jiang and Lie (2016), Byoun (2008), Dittmar and Duchin (2011), and Flannery and Rangan (2006). In the first stage,

I estimate optimal cash as the predicted value of cash from the Bates et al. (2009) and Opler et al. (1999) models of

cash holdings. In the second stage, I estimate a fixed effect model and regress the change in cash holdings against

deviation of current cash holdings from optimal cash holdings. The coefficient of deviation from target cash in the

second‐stage regression is the estimated SOA of cash. A coefficient value of 1 indicates perfect adjustment toward

target and a coefficient value of less than 1 indicates imperfect adjustment toward target. For the overall sample,

I estimate that the SOA toward target cash is approximately 26%, which is consistent with the estimated values in

the extant literature. In terms of half‐lives—that is, the time it takes for the average firm to adjust one‐half the

distance to its optimal (target) cash—the SOA translates to about 2.3 years.

2

To measure uncertainty, I use the Baker et al. (2016) index as my proxy for political and regulatory uncertainty.

The index accounts for policy‐related uncertainty separate from general macroeconomics uncertainty. The first

component of the index takes into account the effects of news articles from the ten major newspapers in the

United States. For an article to be included in the index, it has to contain at least one word related to uncertainty, at

least one word related to policy and at least one word related to the economy. The second component takes into

account dispersion in analyst forecasts. And the third component takes into account the effects of tax provisions

that are set to expire in the immediate future. The overall index is then computed as the normalized average weight

of the three components. On average, the index is significantly correlated with periods during which I would expect

increase in economic and political debates such as 9/11, the great recession and the 2013 government shut down.

3

Higher values of the index are associated with an increase in cash holdings (Duong et al., 2017), a decline in

investment (Gulen & Ion, 2016), and an increase in adjustment costs and financing costs (Pastor & Veronesi, 2012,

2013). To measure the effect of policy uncertainty on SOA, I control for all determinants of cash holdings including

the uncertainty measure; this allows us to capture the marginal effect of policy uncertainty on SOA conditional on

observables.

4

I find that there is asymmetry in adjustment speeds; firms that tend to hold more cash tend to have a

higher SOA than firms that hold less cash. I also find that during periods of significant policy related uncertainty,

high cash holdings firms tend to decelerate SOA at a faster rate than low cash holdings firms. The first result

suggests that it is easier to disgorge cash than to raise it. The second result suggests that uncertainty induces

adjustment costs that increase financing constraints and increase opportunity cost(s) in future states.

I also examine how firms respond to policy uncertainty shocks when the deviation of actual cash holdings from

target cash is either positive or negative. Consistent with Dittmar and Duchin (2011), I find that firms with positive

deviationfrom target cash tendto have higher SOA than firmswith negative deviation.I find that as policyuncertainty

heightens, firms that operate below target cash holdings tend to accelerate SOA whereas firms that operate above

2

Consistent with the literature, in the subsample analyses, I find that on average the estimated SOA of cash is between 21% and 50% The wide range in

value of SOA reflects the susceptibility of subsample analyses to outlier effects, that SOA is heterogeneous in the cross‐section.

3

According to Baker et al. (2016, p. 1599), “The resulting, which shows clear spikes around the Gulf Wars, close presidential elections, the 9/11 terrorist attack,

the stimulus debate, the Lehman Brothers bankruptcy and TARP legislation in late 2008, the summer 2011 debt dispute ….”

4

I thank the referee for carefully outlining this argument.

POLICY UNCERTAINITY AND CASH DYNAMICS AND CASH DYNAMICS

|

423