Financial distress, free cash flow, and interfirm payment network: Evidence from an agent‐based model

• Date: 01 October 2020
• DOI: http://doi.org/10.1002/ijfe.1769
• Author: Jenny P. Danna‐Buitrago,Rémi Stellian
• Published date: 01 October 2020

Received: 12 January 2018 Revised: 28 June 2019 Accepted: 13 September 2019

DOI: 10.1002/ijfe.1769

RESEARCH ARTICLE

Financial distress, free cash flow, and interfirm payment

network: Evidence from an agent-based model

Rémi Stellian1Jenny P. Danna-Buitrago2

1Faculty of Economics and Management,

Department of Business Administration,

Pontificia Universidad Javeriana, AK. 7

#40B-36, Bogotá, Colombia

2Globalization and Sustainable

Development Research Center,Los

Libertadores University Institute, Cra. 16

#63A-68, Bogotá, Colombia

Correspondence

Rémi Stellian, Faculty of Economics and

Management, Department of Business

Administration, Pontificia Universidad

Javeriana, AK. 7 #40B-36, Bogotá,

Colombia.

Email: rstellian@javeriana.edu.co

Funding information

Pontificia Universidad Javeriana,

Grant/AwardNumber: 6258

Abstract

This paper provides theoretical evidence about financial distress in the business

sector in relation to firms' targeted free cash flow (FCF). An agent-based model

of a pure market economy is designed so that a population of firms interact with

one another and with a bank. The model determines the interfirm payment net-

work arising from supplier–customer relationships on the basis of a random

graph with uniform attachment mechanisms. The interfirm payment network

shapes both the liquidity available to each firm and the debts firms incur to

finance these payments. Eventually,firms might not have sufficient liquidity to

meet their debt requirements, hence their financial distress. Firms that target

higher FCFs must reduce their payments to suppliers for the same amount of

payments they expect to receive from customers. This influences the interfirm

payment network and, therefore, firms' financial distress. On this basis, compu-

tational experiments introduce variations in FCFtarg ets. The lowestFCF targets

lead to the lowest levels of financial distress in the business sector. Our simpli-

fied case of interactions opens the way for further research that employs more

complex agent-based models.

KEYWORDS

agent-based computational economics, business sector, financial distress, free cash flow, interfirm

payment network, random graph

JEL CLASSIFICATION

C63, E40, G31

1INTRODUCTION

Financial distress occurs when an economic agent

defaults on some of its debt because of a lack of liquidity.

Since the pioneering works of Altman (1968) and Ohlson

(1980), a huge body of literature has provided analytical

insights for understanding or even predicting the finan-

cial distress of nonfinancial firms (hereafter “firms”).

The explaining/predictive factors of financial distress

stem from finance and accounting and include profit

margin, return on equity, working capital require-

ments, and liquidity ratios (Altman, 1968; Ohlson, 1980;

Acosta-González & Fernández-Rodríguez, 2013; Amen-

dola et al., 2015; Campbell et al., 2008; Fallahpour et al.,

2017; Hernandez Tinoco & Wilson, 2013; Li & Sun,

2013; Li et al., 2013; Sayari & Mugan, 2017; Spaliara &

Tsoukas, 2013; Sun et al., 2017). Firms' age and size are

also considered (Amendola et al., 2015; Ben Jabeur, 2017;

Bhattacharjee et al., 2009; El Kalak & Hudson, 2016; Her-

nandez Tinoco & Wilson, 2013; Spaliara & Tsoukas, 2013),

as are different types of efficiency, such as “technical,”

“global,” “super,” and “generic” efficiency, as suggested

by Li et al. (2017; see also Pušnik and Tajnikar, 2008);

deficiencies in financial management abilities (Thornhill

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2STELLIAN AND DANNA-BUITRAGO

& Amit, 2003; Tykvová & Borell, 2012); managerial traits

such as overconfidence, overoptimism, and the illusion

of control (Kallunki & Pyykko, 2012); human and social

capital (Wetter & Wennberg, 2009); organizational culture

(Laitinen & Suvas, 2016); state ownership (Bhattacharjee

& Han, 2014); institutional shareholders as board mem-

bers (Manzaneque et al., 2016); and income-increasing

manipulations (Lin et al., 2016).

Explaining/predictive factors also identify with macroe-

conomic variables: for example, gross product, monetary

aggregates, and the openness rate (Salman et al., 2011);

aggregate corporate profits, the producer price index, and

averagestock market returns (Zhang et al., 2013); global oil

demand and supply conditions, the housing price index,

and the trade deficit (Bagliano & Morana, 2014); the retail

price index (Hernandez Tinoco & Wilson, 2013); and so

on (see also De Socio & Michelangeli, 2017; Liu, 2009). In

addition, firms' financial distress has been studied in rela-

tion to macroeconomic instability, as measured by shocks

in aggregate production, price levels, interest rates, and

exchange rates

(Bhattacharjee & Han, 2014; Bhattacharjee et al., 2009;

2009; Bruneau et al., 2012; Hunter & Isachenkova, 2006).

Market conditions, such as competition and prices, are

also considered (Lian, 2017; Madrid-Guijarroa et al., 2011;

Pušnik & Tajnikar, 2008). More recently, a growing lit-

erature explores firms' financial distress in relation to

production networks (input–output structure) and trade

credit networks among firms (Assenza et al., 2015; Delli

Gatti et al., 2003; Battiston et al., 2007; Hua et al., 2011;

Lian, 2017) as well as the broader credit network that also

involves banks (Battiston et al., 2012; Delli Gatti et al.,

2006; Li & Sui, 2016; Raberto et al., 2012; Riccetti et al.,

2013; 2016).

This paper is a new contribution to the existing lit-

erature on firms' financial distress. The starting point

of our investigation is the linkage between firms' finan-

cial distress and the interfirm payment network,thatis,

the system in which firms are interconnected through

payments to one another. On the one hand, these pay-

ments most notably arise from supplier–customer rela-

tionships and result in the circulation of liquidity among

firms. On the other hand, firms must finance part of

these payments by incurring debt. However, a core fea-

ture of contemporary economies is the decentralization

of economic decisions (Hahn, 1981). This means there

is a lack of a coordination process, for the whole busi-

ness sector, that ensures that the interfirm payment net-

work shapes the circulation of liquidity in such a way

that each firm has sufficient liquidity to meet its debt

requirements.

As a result, the interfirm payment network influences

firms' financial distress, and factors that influence this net-

work might also influence firms' financial distress. In this

paper, we propose to study one of these factors: firms'

free cash flow (FCF) targets. FCF is the firm's operat-

ing cash flow net of investments; that is, the payments

firms receive from customers (sales) minus the payments

made to suppliers for the purchase of inputs and assets,

including fixed assets (investments),minus taxes1(Brealey

et al., 2011). FCF represents liquidity available for divi-

dend payments, stock repurchases, debt repayment, and

new investments2(Park & Jang, 2013). The firm that

targets a higher FCF must pay less to suppliers for the

same amount of payments the firm expects to receive

from customers. Therefore, the firm requires less financial

resources for its operations. This limits the firm's indebt-

edness and ultimately helps it avoid financial distress.

However,lower payments to suppliers imply that suppliers

receive less liquidity, which weakens the suppliers' ability

to repay their own debts. Consequently,suppliers are more

likely to encounter financial distress (everything else being

equal). In addition, if a financially distressed supplier goes

bankrupt to settle its financial obligations, it will no longer

be the customer of other firms, which therefore might also

be left with less liquidity, enter financial distress, and go

bankrupt. Eventually,this gives rise to a chain reaction, in

which some firms' financial distress leads other firms to

finding themselves in the same situation (Hua et al., 2011;

Lian, 2017).

To gain a clearer picture of the influence of FCF tar-

gets on financial distress in the business sector through

the interfirm payment network, this paper elaborates an

agent-based model (Epstein, 1999; LeBaron & Tesfatsion,

2008; Tesfatsion, 2003). The model conceptualizes a pure

market economy, in which 100 firms interact with one

another and with a single bank:

1. As the model is run, firms pay one another.

2. Firms might request bank credit to finance their pay-

ments. Once each firm obtains liquidity through the

interfirm payment network, it is possible to assess

whether firms are able to repay their debts or whether

they enter financial distress.

3. The model is run several times, using different FCF

targets. This modifies the way firms pay one another

and enables us to analyse the extent of financial dis-

tress in the business sector, depending on the FCF

targets.

The agent-based model provides preliminary evidence

about firms' financial distress in relation to FCF and the

interfirm payment network. This paper is intended to be

a call for similar investigations that use more complex

agent-based models to gradually increase our understand-

ing of this subject.

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